The DOI matches its Crossref record; 66 of the 72 references it cites were found in a registry or an index; none of the 42 sources its claims cite is checked for support yet.
Co-infections in people with COVID-19: a systematic review and meta-analysis.
Open accessAbstract
Objectives In previous influenza pandemics, bacterial co-infections have been a major cause of mortality. We aimed to evaluate the burden of co-infections in patients with COVID-19. Methods We systematically searched Embase, Medline, Cochrane Library, LILACS and CINAHL for eligible studies published from 1 January 2020 to 17 April 2020. We included patients of all ages, in all settings. The main outcome was the proportion of patients with a bacterial, fungal or viral co-infection. . Results Thirty studies including 3834 patients were included. Overall, 7% of hospitalised COVID-19 patients had a bacterial co-infection (95% CI 3-12%, n=2183, I2=92·2%). A higher proportion of ICU patients had bacterial co-infections than patients in mixed ward/ICU settings (14%, 95% CI 5-26, I2=74·7% versus 4%, 95% CI 1-9, I2= 91·7%). The commonest bacteria were Mycoplasma pneumonia, Pseudomonas aeruginosa and Haemophilus influenzae. The pooled proportion with a viral co-infection was 3% (95% CI 1-6, n=1014, I2=62·3%), with Respiratory Syncytial Virus and influenza A the commonest. Three studies reported fungal co-infections. Conclusions A low proportion of COVID-19 patients have a bacterial co-infection; less than in previous influenza pandemics. These findings do not support the routine use of antibiotics in the management of confirmed COVID-19 infection.
Overview
AI snapshot
Written from the paper’s full text.
TL;DR
This systematic review and meta-analysis found that bacterial co-infections were uncommon in hospitalised COVID-19 patients, with a pooled proportion of 7%, and viral co-infections in 3%. The authors conclude these findings do not support routine empirical antibiotics for confirmed COVID-19.
Key findings
- Among 30 studies and 3834 patients, the pooled proportion of laboratory-confirmed bacterial co-infection in hospitalised COVID-19 patients was 7% (95% CI 3–12%, n=2183, I²=92.2%).
- Bacterial co-infections were higher in ICU-only studies than in mixed ward/ICU studies: 14% (95% CI 5–26%, n=204, I²=74.7%) versus 4% (95% CI 1–9%, n=1979, I²=91.7%).
- The pooled proportion with viral co-infection was 3% (95% CI 1–6%, n=1014, I²=62.3%); RSV and influenza A were the commonest. The commonest bacteria were *Mycoplasma pneumoniae* (42% of 27 confirmed bacterial detections), *Pseudomonas aeruginosa* (12%), and *Haemophilus influenzae* (12%).
- Co-infected patients were more likely to die than non-co-infected patients (pooled OR 5.82, 95% CI 3.4–9.9, n=733, 4 studies, I²=85.4%).
Methods
- Systematic review and meta-analysis searching Embase, Medline, Cochrane Library, LILACS, and CINAHL from 1 January 2020 to 17 April 2020, with no language restriction; single case reports and studies with fewer than ten participants were excluded.
- Included 30 studies (29 observational studies and 1 RCT) with 3834 patients; most data were from adults, with three small paediatric-only studies (n=86), and 23 of 30 studies were from China.
- Pooled proportions were estimated using a random-effects model (DerSimonian Laird weights) with Freeman-Tukey double arcsine transformation, exact binomial 95% CIs, and heterogeneity assessed by I²; analyses used Stata 16.0.
Limitations
- Stated: more than three-quarters of included studies were from China early in the pandemic; most were case series with limited co-infection details, few data on timing of co-pathogen detection, and possible under-investigation of secondary infections.
- Stated: broad-spectrum antibiotic use may have reduced bacterial culture sensitivity and underestimated co-infections; some reported bacteria may have been colonisers rather than causative pathogens; healthcare-system differences may limit global representativeness, and most included patients were hospitalised.
- Stated: there was significant unexplained heterogeneity, especially for bacterial co-infections; many participants remained hospitalised at censor date, likely underestimating later secondary infections; publication bias was not assessed. Evident from the text: the pooled estimates rely heavily on observational case series with risk-of-bias concerns in selection and outcome ascertainment.
Model-written summary. Check it against the paper before relying on it.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
32 Own result · 28 Not checked yet · 13 Own interpretation · 8 No basis given · 5 Own method
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Thirty studies including 3834 patients were included.”
- Also stated in: § Results · plain
“Data on 3834 patients from 29 observational studies and one RCT were included”
- Also stated in: § Results · plain
“leaving 30 studies which were included in the analyses”
§ Co-infections in people with COVID-19: a systematic review and meta-analysis > Abstract > Results
plainn = 3,834- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
- Also stated in: § Results · plain
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Overall, 7% of hospitalised COVID-19 patients had a bacterial co-infection (95% CI 3-12%, n=2183, I2=92·2%).”
- Also stated in: § Results · plain
“For hospitalised COVID-19 patients, the overall pooled proportion of patients who had laboratory-confirmed bacterial co-infections was 7% (95% confidence intervals (CI) 3 to 12, n=2183, 18 studies, 19 datasets, I2 92·2%).”
- Also stated in: § Discussion · hedged
“Our meta-analysis indicated that overall 7% of hospitalised COVID-19 patients had a bacterial co-infection, increasing to 14% in studies that only included ICU patients.”
§ Co-infections in people with COVID-19: a systematic review and meta-analysis > Abstract > Results
plainn = 2,183- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
- Also stated in: § Results · plain
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“A higher proportion of ICU patients had bacterial co-infections than patients in mixed ward/ICU settings (14%, 95% CI 5-26, I2=74·7% versus 4%, 95% CI 1-9, I2= 91·7%).”
- Also stated in: § Results · plain
“Subgroup analysis of studies with separate data for ICU patients only showed that a greater proportion of them had bacterial co-infections than patients from mixed hospitalised/ICU studies (14% (95% CI 5-26), n=204, I2=74.7% versus 4% (95% CI 1-9), n=1979, I2 91·7% respectively, p=0·05)”
§ Co-infections in people with COVID-19: a systematic review and meta-analysis > Abstract > Results
plaincorrelationaln = 204- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
- Also stated in: § Results · plain
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The pooled proportion with a viral co-infection was 3% (95% CI 1-6, n=1014, I2=62·3%), with Respiratory Syncytial Virus and influenza A the commonest.”
- Also stated in: § Results · hedged
“From pooled analysis, an estimated 3% of patients had a confirmed viral co-infection (95% CI 1-6, n=1014, 16 studies, I2=62·3%).”
§ Co-infections in people with COVID-19: a systematic review and meta-analysis > Abstract > Results
plainn = 1,014- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
- Also stated in: § Results · hedged
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Other fungal co-infections from respiratory samples were Aspergillus flavus (2 patients), Aspergillus fumigatus and Candida glabrata (one patient each).”
§ Co-infections in people with COVID-19: a systematic review and meta-analysis > Results
plainn = 2- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Pooled analysis of crude odds ratios for death indicated that COVID-19 patients with a co-infection were more likely to die than patients who did not have a co-infection (pooled OR 5·82, 95% CI 3·4 – 9·9, n=733, 4 studies, I2=85·4%).”
§ Co-infections in people with COVID-19: a systematic review and meta-analysis > Results
hedgedcorrelationaln = 733- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Subgroup analysis did not show a significant difference in proportions between patients on ICU and the mixed hospitalised population (5% (95% CI 1-14, n=42, 2 studies) and 3% (95% CI 1-5%, n=972, 14 studies, I2=62·9%) respectively)”
§ Co-infections in people with COVID-19: a systematic review and meta-analysis > Results
plainn = 42- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Excluding three studies which only included paediatric patients resulted in a slight decrease in overall proportion of viral co-infected patients to 2% (95% CI 1-5%, n=886, 13 studies, I2=55·5%).”
§ Co-infections in people with COVID-19: a systematic review and meta-analysis > Results
plaindirectn = 886- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“For hospitalised patients, the overall proportion of co-infected patients was 12% (95% CI 2-29, n=991, 6 studies, I2=97·3%).”
§ Co-infections in people with COVID-19: a systematic review and meta-analysis > Results
plainn = 991- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
In the paper
“One study42, which included SARS-CoV-2 positive patients seen in outpatients and the emergency department reported viral co-infection in 23/115 patients (20%).”
§ Co-infections in people with COVID-19: a systematic review and meta-analysis > Results
What the sources say
- Not checked yetcites [42] Kim, 2020, Rates of Co-infection Between SARS-CoV-2 and Other Respiratory Pathogens, JAMA source
plainn = 115- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
- It may state two separate claims as one. 21
- Probably not a substantial claim. 24
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The commonest bacteria were Mycoplasma pneumonia, Pseudomonas aeruginosa and Haemophilus influenzae.”
- Also stated in: § Results · plain
“The most frequently detected bacterial pathogen was Mycoplasma pneumoniae (42% of 27 confirmed bacterial pathogen detections), followed by Pseudomonas aeruginosa (12%, including one patient with bacteraemia) and Haemophilus influenzae (12%).”
- Also stated in: § Discussion · plain
“the most commonly detected bacterial pathogen was M.pneumoniae, followed by P.aeruginosa, H.influenzae and K.pneumoniae.”
§ Co-infections in people with COVID-19: a systematic review and meta-analysis > Abstract > Results
plainn = 4- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
- Also stated in: § Results · plain
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“with Respiratory Syncytial Virus and influenza A the commonest.”
- Also stated in: § Results · plain
“respiratory syncytial virus (RSV) was the most prevalent respiratory virus (16·9% of detections), followed by influenza A (15·5%).”
§ Co-infections in people with COVID-19: a systematic review and meta-analysis > Abstract > Results
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
- Also stated in: § Results · plain
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Three studies reported fungal co-infections.”
§ Co-infections in people with COVID-19: a systematic review and meta-analysis > Abstract > Results
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
None of the sources cited for this claim have been checked yet.
In the paper
“Four fungal pathogens were identified from three studies.10 , 23 , 35 Candida albicans was isolated from the respiratory tract in five patients and urinary tract of a sixth.”
§ Co-infections in people with COVID-19: a systematic review and meta-analysis > Results
What the sources say
- Not checked yetcites [10] Wang, 2020, Clinical Features of 69 Cases with Coronavirus Disease 2019 in Wuhan, China, Clin Infect Dis
- Not checked yetcites [23] Chen, 2020, Epidemiological and clinical characteristics of 99 cases of 2019 novel coronavirus pneumonia in Wuhan, China: a descriptive study, Lancet source
- Not checked yetcites [35] Yang, 2020, Clinical course and outcomes of critically ill patients with SARS-CoV-2 pneumonia in Wuhan, China: a single-centered, retrospective, observational study, Lancet Respir Med source
plainn = 5- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Sensitivity analysis excluding one study which only included children did not significantly affect the overall proportion of patients with bacterial co-infection, nor did it decrease the heterogeneity (6% (95% CI 2-12), I2=92·4%), although the difference between ICU patients and a mixed hospital population failed to reach statistical significance (p=0·08).”
§ Co-infections in people with COVID-19: a systematic review and meta-analysis > Results
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“In a sensitivity analysis excluding this study, the proportion of co-infected patients fell to 7% (95% CI 2-12, n=652, I2=79·5%), similar to the proportion of patients with specific bacterial co-infections.”
§ Co-infections in people with COVID-19: a systematic review and meta-analysis > Results
plainn = 652- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
None of the sources cited for this claim have been checked yet.
In the paper
“One study reported that bacterial infection was a predictor of death in older patients based on univariate regression analysis (hazard ratio (HR) 7·01 (95% CI 3·65-13·5, p<001), but it was not a significant predictor on multivariate analysis (adjusted HR 1·52 (95% CI 0·71-3·24, p=0·28).”
§ Co-infections in people with COVID-19: a systematic review and meta-analysis > Results
plaincorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“There were no data in the remaining studies relating to the time from admission to detection of co-infection.”
§ Co-infections in people with COVID-19: a systematic review and meta-analysis > Results
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“In the missing outcome and selection of reported result domains there were some concerns due to lack of information on how secondary infections were ascertained and continued hospitalisation of some participants at the censor date.”
§ Co-infections in people with COVID-19: a systematic review and meta-analysis > Results
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Other bacteria detected were Enterobacter species (three patients), Acinetobacter baumannii and Chlamydia species (two patients each), and Enterococcus faecium, methicillin resistant Staphylococcus aureus (MRSA), and Serratia marscecens (one patient each)”
§ Co-infections in people with COVID-19: a systematic review and meta-analysis > Results
plainn = 3- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“We found only one report of MRSA and no cases of co-infection with S.pneumoniae nor S.pyogenes.”
§ Co-infections in people with COVID-19: a systematic review and meta-analysis > Discussion
plainSingle case- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Klebsiella pneumoniae was isolated from four patients, including a carbapenem resistant isolate from one patient with hospital-acquired pneumonia (HAP) and bacteraemia, and an extended spectrum beta lactamase positive isolate from another patient with HAP.”
§ Co-infections in people with COVID-19: a systematic review and meta-analysis > Results
plainn = 4- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
In the paper
“A highly resistant Acinetobacter baumannii was isolated in a further study.23”
§ Co-infections in people with COVID-19: a systematic review and meta-analysis > Discussion
What the sources say
- Not checked yetcites [23] Chen, 2020, Epidemiological and clinical characteristics of 99 cases of 2019 novel coronavirus pneumonia in Wuhan, China: a descriptive study, Lancet source
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“More than three-quarters of the studies we included were from China describing patients at the start of the pandemic.”
§ Co-infections in people with COVID-19: a systematic review and meta-analysis > Discussion
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“with little evidence of S.aureus, S.pneumoniae or S.pyogenes having a major role.”
§ Co-infections in people with COVID-19: a systematic review and meta-analysis > Discussion
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
- Rests on an assumption: The pooled proportion of bacterial co-infection is valid despite significant unexplained heterogeneity.
In the paper
“Although there were more than 3,800 patients included in this review, this is only a small representation of the total number of SARS-CoV-2 infections, which currently stands at around 3 million cases worldwide.65”
§ Co-infections in people with COVID-19: a systematic review and meta-analysis > Discussion
What the sources say
- Not checked yetcites [65] World Health Organization. Coronavirus disease 2019 (COVID-19) Situation Report – 99 Available from:https://www.who.int/docs/default-source/coronaviruse/situation-reports/20200428-sitrep-99-covid-19.pdf?sfvrsn=119fc381_2. Accessed 13 May 2020
plainn = 3,800- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“Two independent reviewers (LL and BL/VB) screened the abstracts of identified studies and reviewed the full texts of those which were potentially eligible, with disagreements resolved by consensus.”
§ Co-infections in people with COVID-19: a systematic review and meta-analysis > Methods > Search strategy and selection criteria
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
In the paper
“We conducted this systematic review meta-analysis in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines.15”
§ Co-infections in people with COVID-19: a systematic review and meta-analysis > Methods > Search strategy and selection criteria
What the sources say
- Not checked yetcites [15] Moher, 2009, Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement, BMJ source
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“Two reviewers (LL and BL/VB) independently extracted data from individual studies using a predefined template.”
§ Co-infections in people with COVID-19: a systematic review and meta-analysis > Methods > Data extraction and analysis
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
In the paper
“Furthermore, co-infection has been associated with more severe outcomes in pandemic and seasonal influenza.7”
§ Co-infections in people with COVID-19: a systematic review and meta-analysis > Introduction
What the sources say
- Not checked yetcites [7] Joseph, 2013, Bacterial and viral infections associated with influenza, Influenza Other Respir Viruses source
plaincorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
None of the sources cited for this claim have been checked yet.
In the paper
“there is evidence that co-infections do not occur in patients infected with MERS-CoV8 and occur rarely in patients infected with SARS-CoV-1.9”
§ Co-infections in people with COVID-19: a systematic review and meta-analysis > Introduction
What the sources say
- Not checked yetcites [8] Assiri, 2013, Epidemiological, demographic, and clinical characteristics of 47 cases of Middle East respiratory syndrome coronavirus disease from Saudi Arabia: a descriptive study, Lancet Infect Dis source
- Not checked yetcites [9] Zahariadis, 2006, Risk of ruling out severe acute respiratory syndrome by ruling in another diagnosis: variable incidence of atypical bacteria coinfection based on diagnostic assays, Can Resp J
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
None of the sources cited for this claim have been checked yet.
In the paper
“The bacteria most commonly associated with influenza infection have been reported to be those which commonly colonise the nasopharynx, such as Streptococcus pneumoniae, Staphylococcus aureus, and Streptococcus pyogenes, with secondary infection usually occurring in the first 6 days of influenza.43, 44, 45”
§ Co-infections in people with COVID-19: a systematic review and meta-analysis > Discussion
What the sources say
- Not checked yetcites [43] MacIntyre, 2018, The role of pneumonia and secondary bacterial infection in fatal and serious outcomes of pandemic influenza a(H1N1)pdm09, BMC Infect Dis source
- Not checked yetcites [44] Chertow, 2013, Bacterial coinfection in influenza: a grand rounds review, JAMA source
- Not checked yetcites [45] Klein, 2016, The frequency of influenza and bacterial coinfection: a systematic review and meta-analysis, Influenza Other Respir Viruses source
plaincorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
In the paper
“The study protocol is registered with the National Institute for Health Research international prospective register of systematic reviews (PROSPERO).18”
§ Co-infections in people with COVID-19: a systematic review and meta-analysis > Methods > Data extraction and analysis
What the sources say
- Not checked yetcites [18] Lansbury, 2020, Co-infections in people with COVID-19: a systematic review and meta-analysis, PROSPERO
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
In the paper
“For observational studies, we assessed the risk of bias in the domains of study group selection and ascertainment of co-infection using a modification of the Newcastle-Ottawa Scale.16”
§ Co-infections in people with COVID-19: a systematic review and meta-analysis > Methods > Data extraction and analysis
What the sources say
- Not checked yetcites [16] Wells G, Shea B, O'Connell D, Peterson J, V Welch, Losos M, et al. The Newcastle-Ottawa Scale (NOS) for assessing the quality of nonrandomised studies in meta-analysesAvailable from: http://www.ohri.ca/programs/clinical_epidemiology/oxford.asp. Accessed 13 May 2020
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“As we anticipated a high level of heterogeneity, an a priori decision was made not to abandon meta-analyses due to high heterogeneity.”
§ Co-infections in people with COVID-19: a systematic review and meta-analysis > Methods > Data extraction and analysis
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim.
In the paper
“This, on its own, is not a highly specific test and may result in overestimation of infections.48”
§ Co-infections in people with COVID-19: a systematic review and meta-analysis > Discussion
What the sources say
- Not checked yetcites [48] Sobieszczanska, 2014, Relevance of serology for Mycoplasma pneumoniae infection among children with persistent cough, Adv Clin Exp Med source
hedgedconditional- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
In the paper
“The Cochrane Risk of Bias Tool (version 2) was used to assess risk of bias in randomised controlled trials (RCTs).17”
§ Co-infections in people with COVID-19: a systematic review and meta-analysis > Methods > Data extraction and analysis
What the sources say
- Not checked yetcites [17] Sterne, 2019, RoB 2: a revised tool for assessing risk of bias in randomised trials, BMJ source
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
None of the sources cited for this claim have been checked yet.
In the paper
“at the time of writing there are an increasing number of reports from Europe of patients with probable or possible COVID-19 associated pulmonary aspergillosis.50, 51, 52, 53, 54”
§ Co-infections in people with COVID-19: a systematic review and meta-analysis > Discussion
What the sources say
- Not checked yetcites [50] Alanio A, Dellière S, Fodil S, Bretagne S, B.M. High Prevalence of Putative Invasive Pulmonary Aspergillosis in Critically Ill COVID-19 Patients (April 14, 2020) Available from: SRN:https://ssrn.com/abstract=3575581 or http://dx.doi.org/10.2139/ssrn.3575581. Accessed 13 May 2020 source
- Not checked yetcites [51] Blaize, 2020, Fatal Invasive Aspergillosis and Coronavirus Disease in an Immunocompetent Patient, Emerg Infect Dis source
- Not checked yetcites [52] Koehler, 2020, COVID-19 Associated Pulmonary Aspergillosis, Mycoses source
plaincorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
None of the sources cited for this claim have been checked yet.
In the paper
“Patients with acute respiratory distress syndrome caused by influenza have been reported to be at increased risk of invasive aspergillosis (IA), even in the absence of predisposing immunocompromising conditions.55 , 56”
§ Co-infections in people with COVID-19: a systematic review and meta-analysis > Discussion
What the sources say
- Not checked yetcites [55] Koehler, 2019, Intensive care management of influenza-associated pulmonary aspergillosis, Clin Microbiol Infect source
- Not checked yetcites [56] Schauwvlieghe, 2018, Invasive aspergillosis in patients admitted to the intensive care unit with severe influenza: a retrospective cohort study, Lancet Respir Med source
plaincorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“With the emergence of the COVID-19 pandemic during the winter months, it is unsurprising that studies in our review were also detecting viral co-infection in patients with COVID-19.”
§ Co-infections in people with COVID-19: a systematic review and meta-analysis > Discussion
plaincorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
None of the sources cited for this claim have been checked yet.
In the paper
“Detection of galactomannan (a polysaccharide antigen found primarily in the cells walls of Aspergillus species) from bronchoalveolar lavage fluid (BALF), has been shown to be a useful and rapid tool for identification of IA in both immunocompromised and immunocompetent patients.58, 59, 60, 61”
§ Co-infections in people with COVID-19: a systematic review and meta-analysis > Discussion
What the sources say
- Not checked yetcites [58] D'Haese, 2012, Detection of galactomannan in bronchoalveolar lavage fluid samples of patients at risk for invasive pulmonary aspergillosis: analytical and clinical validity, J Clin Microbiol source
- Not checked yetcites [59] Meersseman, 2008, Galactomannan in bronchoalveolar lavage fluid: a tool for diagnosing aspergillosis in intensive care unit patients, Am J Respir Crit Care Med source
- Not checked yetcites [60] Patterson, 2016, Practice Guidelines for the Diagnosis and Management of Aspergillosis: 2016 Update by the Infectious Diseases Society of America, Clin Infect Dis source
plaincorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“The strengths of our study include our use of a comprehensive search strategy to identify potentially eligible studies from multiple databases as well as handsearching relevant journals for recently published articles up to our search cut-off date.”
§ Co-infections in people with COVID-19: a systematic review and meta-analysis > Discussion
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
In the paper
“Influenza has been shown to have dual seasonality in China, with the incidence in northern China following a winter pattern typically seen in northern hemisphere countries, whereas in southern China the virus is prevalent throughout the year.64”
§ Co-infections in people with COVID-19: a systematic review and meta-analysis > Discussion
What the sources say
- Not checked yetcites [64] Shu, 2010, Dual seasonal patterns for influenza, China, Emerg Infect Dis source
boosted- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
In the paper
“the usefulness of standard publication bias tests for proportional meta-analyses has been questioned, with funnel plots and statistical tests potentially yielding misleading results.66”
§ Co-infections in people with COVID-19: a systematic review and meta-analysis > Discussion
What the sources say
- Not checked yetcites [66] Hunter, 2014, In meta-analyses of proportion studies, funnel plots were found to be an inaccurate method of assessing publication bias, J Clin Epidemiol source
hedgedconditional- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“This unexplained heterogeneity may be due to differences between studies in disease severity, patient comorbidities, treatment differences (such as corticosteroid administration), use of antibiotics prior to and during hospitalisation, or other unidentified covariates.”
§ Co-infections in people with COVID-19: a systematic review and meta-analysis > Discussion
hedgedconditional- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“It is possible that patients with a suspected secondary infection may not have had thorough microbiological investigations given the unprecedented circumstances and enormous strain on the hospital systems.”
§ Co-infections in people with COVID-19: a systematic review and meta-analysis > Discussion
hedgedconditional- Asserted: passes — The authors put it forward as true.
- Checkable: fails — It may be too vague to check against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. It may be too vague to check against evidence.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“We did not assess publication bias in this review”
§ Co-infections in people with COVID-19: a systematic review and meta-analysis > Discussion
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“some of the bacteria reported may have been merely colonising a normally non-sterile site rather than being causative agents of secondary infections”
§ Co-infections in people with COVID-19: a systematic review and meta-analysis > Discussion
hedged- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
The paper relies on this without support.
This is the first systematic review to evaluate the burden of co-infections in patients with confirmed SARS-CoV-2 infection.
“To our knowledge, our study is the first systematic review to evaluate the burden of co-infections in patients with confirmed SARS-CoV-2 infection.”
The paper relies on this without support.
The pooled proportion of bacterial co-infection is valid despite significant unexplained heterogeneity.
“There was significant heterogeneity among studies, particularly in the meta-analyses of bacterial co-infections which was not accounted for by age group or setting.”
The paper relies on this without support.
The previous influenza pandemic co-infection proportions are comparable to COVID-19.
“we found that the overall proportion of COVID-19 patients who have a bacterial coinfection is lower than in previous influenza pandemics”
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
In the citing paper
“Compared with patients in mixed wards/intensive care unit (ICU) settings, ICU patients have a higher proportion of bacterial infections (Lansbury et al., 2020).”
From Oral Microbiome and SARS-CoV-2: Beware of Lung Co-infection (2020) · cites this paper as Lansbury et al., 2020
In the citing paper
“In addition, bacterial co-infection occurred in 7% of hospitalized COVID-19 patients.”
From Oral Microbiome and SARS-CoV-2: Beware of Lung Co-infection (2020) · cites this paper as Lansbury et al., 2020
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
Each contradiction between two passages listed here was confirmed by an independent check.
Rated minor: it would not touch a result — a value no result rests on, a p-value that stays on the same side of the significance level, or a conflict that is clerical, resolved elsewhere in the paper, or outside its own findings.
In the paper
“Ruan41 | China | Retrospective database, Died vs discharged | 150 (68 deceased, 82 survivors) | Not specified | n/a | n/aa | 16·2%”
§ Co-infections in people with COVID-19: a systematic review and meta-analysis > Results
Reported 16.2 · recomputed 45.333333
Rated minor: it would not touch a result — a value no result rests on, a p-value that stays on the same side of the significance level, or a conflict that is clerical, resolved elsewhere in the paper, or outside its own findings.
In the paper
§ Co-infections in people with COVID-19: a systematic review and meta-analysis > Results
“only three small studies reporting data exclusively from children (n=86).13 , 31 , 39”
§ Co-infections in people with COVID-19: a systematic review and meta-analysis > Results
“Tagarro31 | Spain | Case series Hosp/non-hosp/PIC | 41 | Adult”
Citations
Cites
Preferred Reporting Items for Systematic Reviews and Meta-Analyses: the PRISMA statement
Moher, D., Liberati, A., Tetzlaff, J., Altman, D. G., & for the PRISMA Group (2009) · BMJ · doi:10.1136/bmj.b2535 · Cited by 83,823
Clinical features of patients infected with 2019 novel coronavirus in Wuhan, China
Huang, C., Wang, Y., Li, X., Ren, L., Zhao, J., Hu, Y., Zhang, L., Fan, G., Xu, J., Gu, X., et al. (2020) · The Lancet · doi:10.1016/s0140-6736(20)30183-5 · Cited by 48,884
Preferred reporting items for systematic reviews and meta-analyses: the PRISMA Statement.
(2009) · PubMed Central · Cited by 44,859
RoB 2: a revised tool for assessing risk of bias in randomised trials
Sterne, J. A. C., Savović, J., Page, M. J., Elbers, R. G., Blencowe, N. S., Boutron, I., Cates, C. J., Cheng, H.-Y., Corbett, M. S., Eldridge, S. M., et al. (2019) · BMJ · doi:10.1136/bmj.l4898 · Cited by 34,787
Clinical characteristics of coronavirus disease 2019 in China
Guan, W.-J., Ni, Z.-Y., Hu, Y., Liang, W.-H., Ou, C.-Q., He, J.-X., Liu, L., Shan, H., Lei, C.-L., Hui, D. S. C., et al. (2020) · New England Journal of Medicine · doi:10.1056/nejmoa2002032 · Cited by 30,246
A novel coronavirus from patients with pneumonia in China, 2019
Zhu, N., Zhang, D., Wang, W., Li, X., Yang, B., Song, J., Zhao, X., Huang, B., Shi, W., Lu, R., et al. (2020) · New England Journal of Medicine · doi:10.1056/nejmoa2001017 · Cited by 28,244
Zhou, F., Yu, T., Du, R., Fan, G., Liu, Y., Liu, Z., Xiang, J., Wang, Y., Song, B., Gu, X., et al. (2020) · The Lancet · doi:10.1016/s0140-6736(20)30566-3 · Cited by 27,263
Chen, N., Zhou, M., Dong, X., Qu, J., Gong, F., Han, Y., Qiu, Y., Wang, J., Liu, Y., Wei, Y., et al. (2020) · The Lancet · doi:10.1016/s0140-6736(20)30211-7 · Cited by 21,415
(2014) · Medical Entomology and Zoology · Cited by 17,633
Lu, R., Zhao, X., Li, J., Niu, P., Yang, B., Wu, H., Wang, W., Song, H., Huang, B., Zhu, N., et al. (2020) · The Lancet · doi:10.1016/s0140-6736(20)30251-8 · Cited by 11,907
Research works printed but not linked: 1
- Mo, 2020, Clinical characteristics of refractory COVID-19 pneumonia in Wuhan, China. Clin Infect Dis.
Cited by
Sorted by citations
Items 301–400 of 1,000
The potential role of Fluoroquinolones in the management of Covid-19 a rapid review
Damanhouri, Z. A., Alkreathy, H. M., Ali, A. S., & Karim, S. (2021) · Journal Of Advanced Pharmacy Education And Research · doi:10.51847/fe1ioiptwd · Cited by 28
Bertuzzi, A. F., Ciccarelli, M., Marrari, A., Gennaro, N., Dipasquale, A., Giordano, L., Cariboni, U., Quagliuolo, V., Alloisio, M., & Santoro, A. (2021) · British Journal of Cancer · doi:10.1038/s41416-021-01396-9 · Cited by 28
Coinfections with Respiratory Pathogens among COVID-19 Patients in Korea
Roh, K. H., Kim, Y. K., Kim, S., Kang, E.-R., Yang, Y.-J., Jung, S., Lee, S.-H., & Sung, N. (2021) · Canadian Journal of Infectious Diseases and Medical Microbiology · doi:10.1155/2021/6651045 · Cited by 28
COVID19 associated mucormycosis: Is GRP78 a possible link?
Gumashta, J., & Gumashta, R. (2021) · Journal of Infection and Public Health · doi:10.1016/j.jiph.2021.09.004 · Cited by 28
Lee, R., Cho, S., Lee, D., Ahn, H., Choi, H., Choi, S., Choi, J.-K., Choi, J., Kim, S. Y., Kim, Y. J., et al. (2022) · The Korean Journal of Internal Medicine · doi:10.3904/kjim.2022.069 · Cited by 28
Shah, M. M., Patel, K., Milucky, J., Taylor, C. A., Reingold, A. L., Armistead, I., Meek, J. I., Anderson, E. J., Weigel, A., Reeg, L., et al. (2023) · Influenza and Other Respiratory Viruses · doi:10.1111/irv.13107 · Cited by 28
Gajić, I., Jovićević, M., Popadić, V., Trudić, A., Kabić, J., Kekić, D., Ilic, A., Klašnja, S., Hadnadjev, M., Popadic, D. J., et al. (2023) · Journal of Hospital Infection · doi:10.1016/j.jhin.2023.04.013 · Cited by 28
Luštrek, M., Cesar, Z., Suljič, A., Kogoj, R., Knap, N., Virant, M. J., Uršič, T., Petrovec, M., Avšič‐Županc, T., & Korva, M. (2024) · Respiratory Research · doi:10.1186/s12931-024-02862-7 · Cited by 27
Pyoverdine Inhibitors and Gallium Nitrate Synergistically Affect Pseudomonas aeruginosa
Kang, D., Revtovich, A. V., Deyanov, A. E., & Kirienko, N. V. (2021) · mSphere · doi:10.1128/msphere.00401-21 · Cited by 27
Le, N. P. K., Herz, C., Gomes, J. V. D., Förster, N., Antoniadou, K., Mittermeier-Kleßinger, V. K., Mewis, I., Dawid, C., Ulrichs, C., & Lamy, E. (2021) · International Journal of Molecular Sciences · doi:10.3390/ijms22136766 · Cited by 27
Co-infections observed in SARS-CoV-2 positive patients using a rapid diagnostic test
Fontana, C., Favaro, M., Minelli, S., Bossa, M. C., & Altieri, A. (2021) · Scientific Reports · doi:10.1038/s41598-021-95772-3 · Cited by 27
Atypical bacterial co‐infections among patients with COVID‐19: A study from India
Chaudhry, R., Sreenath, K., Batra, P., Vinayaraj, E. V., Rathor, N., Saikiran, K. V. P., Aravindan, A., Singh, V., Brijwal, M., Soneja, M., et al. (2021) · Journal of Medical Virology · doi:10.1002/jmv.27324 · Cited by 27
Cohen, R., Finn, T., Babushkin, F., Geller, K., Alexander, H., Shapiro, M., Uda, M., Mostrchy, A. R., Amash, R., Shimoni, Z., et al. (2021) · Scandinavian Journal of Infectious Diseases · doi:10.1080/23744235.2021.1985732 · Cited by 27
Cooksey, G. L. S., Morales, C., Linde, L., Schildhauer, S., Guevara, H. F., Chan, E., Gibb, K., Wong, J., Lin, W., Bonin, B. J., et al. (2021) · Emerging infectious diseases · doi:10.3201/eid2801.211682 · Cited by 27
Influenza viruses and coronaviruses: Knowns, unknowns, and common research challenges
Terrier, O., Si‐Tahar, M., Ducatez, M., Chevalier, C., Pizzorno, A., Goffic, R. L., Crépin, T., Simon, G., & Naffakh, N. (2021) · PLoS Pathogens · doi:10.1371/journal.ppat.1010106 · Cited by 28
Jamnani, A. N., Montazeri, M., Mirzakhani, M., Moosazadeh, M., & Haghighi, M. (2022) · SN Comprehensive Clinical Medicine · doi:10.1007/s42399-021-01114-9 · Cited by 27
Pérez, Á. G. C., & Oluyori, D. A. (2022) · Mathematical Modelling and Numerical Simulation with Applications · doi:10.53391/mmnsa.2022.016 · Cited by 27
Soares, J. M., Guimarães, F. E. G., Yakovlev, V. V., Bagnato, V. S., & Blanco, K. C. (2022) · Scientific Reports · doi:10.1038/s41598-022-25546-y · Cited by 27
Saleem, Z., Haseeb, A., Godman, B., Batool, N., Altaf, U., Ahsan, U., Khan, F. U., Mustafa, Z. U., Nadeem, M. U., Farrukh, M. J., et al. (2022) · Antibiotics · doi:10.3390/antibiotics12010070 · Cited by 27
Iacovelli, A., Oliva, A., Siccardi, G., Tramontano, A., Pellegrino, D., Mastroianni, C. M., Venditti, M., & Palange, P. (2023) · BMC Pulmonary Medicine · doi:10.1186/s12890-023-02315-9 · Cited by 27
Flare of the silent pandemic in the era of the COVID-19 pandemic: Obstacles and opportunities
Rayan, R. Α. (2023) · World Journal of Clinical Cases · doi:10.12998/wjcc.v11.i6.1267 · Cited by 27
Cavallazzi, R., & Ramírez, J. A. (2024) · Infectious Disease Clinics of North America · doi:10.1016/j.idc.2023.12.010 · Cited by 26
Dejani, N. N., Elshabrawy, H. A., Filho, C. D. S. M. B., & de Sousa, D. P. (2021) · Biomolecules · doi:10.3390/biom11081254 · Cited by 26
Ming, D. K. Y., Myall, A., Hernandez, B., Weiße, A. Y., Peach, R. L., Barahona, M., Rawson, T. M., & Holmes, A. H. (2021) · BMC Infectious Diseases · doi:10.1186/s12879-021-06621-7 · Cited by 26
Nanopore metagenomic sequencing for detection and characterization of SARS-CoV-2 in clinical samples
Gauthier, N. P. G., Nelson, C., Bonsall, M. B., Locher, K., Charles, M., MacDonald, C., Krajden, M., Chorlton, S. D., & Manges, A. R. (2021) · PLoS ONE · doi:10.1371/journal.pone.0259712 · Cited by 26
Evans, M. E., Simbartl, L. A., Kralovic, S. M., Clifton, M., DeRoos, K., McCauley, B. P., Gauldin, N., Flarida, L., Gamage, S. D., Jones, M., et al. (2022) · Infection Control and Hospital Epidemiology · doi:10.1017/ice.2022.93 · Cited by 26
Alhumaid, S., Alabdulqader, M. A., Dossary, N. A., Alawi, Z. A., Alnaim, A. A., mutared, K. M. A., Noaim, K. I. A., Ghamdi, M. A. A., Albahrani, S. J., Alahmari, A. A., et al. (2022) · Tropical Medicine and Infectious Disease · doi:10.3390/tropicalmed7110380 · Cited by 26
Hospital Antibiotic Use during COVID-19 Pandemic in Italy
Perrella, A., Fortinguerra, F., Pierantozzi, A., Capoluongo, N., Carannante, N., Vecchio, A. L., Bernardi, F. F., Trotta, F., & Cangini, A. (2023) · Antibiotics · doi:10.3390/antibiotics12010168 · Cited by 26
Tan, L. V., Hong, N. T. T., Ngoc, N. M., Thanh, T. T., Lam, V. T., Nguyet, L. A., Nhu, L. N. T., Ny, N. T. H., Minh, N. N. Q., Man, D. N. H., et al. (2020) · Journal of Infection · doi:10.1016/j.jinf.2020.06.033 · Cited by 26
Staub, M., Beaulieu, R. M., Graves, J. A., & Nelson, G. E. (2020) · Infection Control and Hospital Epidemiology · doi:10.1017/ice.2020.1291 · Cited by 25
Antibiotic usage and stewardship in patients with COVID-19: too much antibiotic in uncharted waters?
Evans, T. J., Davidson, H., Low, J. M., Basarab, M., & Arnold, A. (2020) · Journal of Infection Prevention · doi:10.1177/1757177420976813 · Cited by 25
Pneumocystis jirovecii pneumonia in an immunocompetent patient recovered from COVID-19
Viceconte, G., Buonomo, A. R., Lanzardo, A., Pinchera, B., Zappulo, E., Scotto, R., Moriello, N. S., Vargas, M., Iacovazzo, C., Servillo, G., et al. (2021) · Scandinavian Journal of Infectious Diseases · doi:10.1080/23744235.2021.1890331 · Cited by 25
García-Posada, M., Aruachan-Vesga, S., Rojas, D. M., Humánez, K., Coll, H. A. S., Dajil, H. J. C., Faccini, Á., & Mattar, S., V (2021) · Journal of Infection and Public Health · doi:10.1016/j.jiph.2021.02.013 · Cited by 25
Timbrook, T. T., Hueth, K. D., & Ginocchio, C. C. (2021) · Diagnostic Microbiology and Infectious Disease · doi:10.1016/j.diagmicrobio.2021.115476 · Cited by 25
Nasa, P., Azoulay, É., Chakrabarti, A., Divatia, J. V., Jain, R., Rodrigues, C. S., Rosenthal, V., Alhazzani, W. A., Arabi, Y. M., Bakker, J., et al. (2021) · The Lancet Infectious Diseases · doi:10.1016/s1473-3099(21)00626-5 · Cited by 25
COVID-19-associated fungal infections in Iran: A systematic review
Nazari, T., Sadeghi, F., Izadi, A., Sameni, S., & Mahmoudi, S. (2022) · PLoS ONE · doi:10.1371/journal.pone.0271333 · Cited by 25
Rădulescu, P. M., Davitoiu, D. V., Băleanu, V. D., Pădureanu, V., Râmboiu, D. S., Şurlin, V., Bratiloveanu, T. C., Georgescu, E. F., Streba, C. T., Mercuţ, R., et al. (2022) · Diagnostics · doi:10.3390/diagnostics12123118 · Cited by 25
Selvam, R. M. E., Lim, I. H. Y., Lewis, J. C., Lim, C. H., Yap, M. K. K., & Tan, H. S. (2023) · Scientific Reports · doi:10.1038/s41598-023-34643-5 · Cited by 25
Ahmed, O. B., Asghar, A. H., Bamaga, M. A., Bahwerth, F. S., & Ibrahim, M. E. (2023) · PLoS ONE · doi:10.1371/journal.pone.0289359 · Cited by 25
Manohar, P., Loh, B., & Leptihn, S. (2020) · Infectious Microbes & Diseases · doi:10.1097/im9.0000000000000034 · Cited by 25
Almeida, S. C. G., de Lemos, A. P. S., Bierrenbach, A. L., de Moraes, J. C., & Brandileone, M. C. D. C. (2024) · Microorganisms · doi:10.3390/microorganisms12020401 · Cited by 24
Kubin, C. J., Loo, A. S., Cheng, J., Nelson, B. C., Mehta, M., Mazur, S., So, W., Calfee, D. P., Singh, H. K., Greendyke, W. G., et al. (2021) · American Journal of Health-System Pharmacy · doi:10.1093/ajhp/zxaa419 · Cited by 24
Macciò, U., Zinkernagel, A. S., Schuepbach, R. A., Probst‐Müller, E., Frontzek, K., Brugger, S. D., Hofmaenner, D. A., Moch, H., & Varga, Z. (2022) · Frontiers in Medicine · doi:10.3389/fmed.2022.778489 · Cited by 24
Managing antibiotic shortages: lessons from EAHP and ECDC surveys
Miljković, N., Polidori, P., & Kohl, S. (2022) · European Journal of Hospital Pharmacy · doi:10.1136/ejhpharm-2021-003110 · Cited by 24
Kudliński, B., Zgoła, D., Stolińska, M., Murkos, M., Kania, J., Nowak, P., Noga, A., Wojciech, M., Zaborniak, G., & Zembroń-Łacny, A. (2022) · Diagnostics · doi:10.3390/diagnostics12040859 · Cited by 24
Ghosh, A. K., Singh, R., Reddy, S., Singh, S., Rudramurthy, S. M., Kaur, H., Choudhary, H., & Chakrabarti, A. (2022) · Frontiers in Cellular and Infection Microbiology · doi:10.3389/fcimb.2022.953750 · Cited by 24
Mutua, J. M., Njeru, J. M., & Musyoki, A. M. (2022) · BMC Infectious Diseases · doi:10.1186/s12879-022-07885-3 · Cited by 27
Wu, H.-Y., Chang, P.-H., Huang, Y., Tsai, C.-S., Chen, K., Lin, I., Hsih, W.-H., Tsai, W.-L., Chen, J.-A., Yang, T.-L., et al. (2022) · Journal of Microbiology Immunology and Infection · doi:10.1016/j.jmii.2022.12.003 · Cited by 24
Garza–Ramos, U., Silva-Sánchez, J., López-Jácome, L. E., Hernández-Durán, M., Colín‐Castro, C. A., Sánchez-Pérez, A., Rodríguez-Santiago, J., Morfín‐Otero, R., Rodríguez-Noriega, E., Velázquez-Acosta, C., et al. (2023) · Microbial Drug Resistance · doi:10.1089/mdr.2022.0226 · Cited by 24
Vaz, E. S., Vassiliades, S. V., Giarolla, J., Polli, M. C., & Parise‐Filho, R. (2023) · European Journal of Clinical Pharmacology · doi:10.1007/s00228-023-03486-4 · Cited by 24
Francesco, M. A. D., Signorini, L., Piva, S., Pellizzeri, S., Fumarola, B., Corbellini, S., Piccinelli, G., Simonetti, F., Carta, V., Mangeri, L., et al. (2023) · Journal of Medical Virology · doi:10.1002/jmv.28892 · Cited by 24
Toribio-Avedillo, D., Gómez-Gómez, C., Sala‐Comorera, L., Galofré, B., & Muniesa, M. (2024) · The Science of The Total Environment · doi:10.1016/j.scitotenv.2024.170636 · Cited by 24
Pulia, M. S., Wolf, I., Schwei, R. J., Chen, D. J., Lepak, A. J., Schulz, L. T., & Safdar, N. (2020) · Infection Control and Hospital Epidemiology · doi:10.1017/ice.2020.1329 · Cited by 24
Myeloid phenotypes in severe COVID-19 predict secondary infection and mortality: a pilot study
Marais, C., Claude, C., Semaan, N., Charbel, R., Barreault, S., Travert, B., Piloquet, J., Demailly, Z., Morin, L., Merchaoui, Z., et al. (2021) · Annals of Intensive Care · doi:10.1186/s13613-021-00896-4 · Cited by 25
COVID-19 and invasive fungal coinfections: A case series at a Brazilian referral hospital
Martins, A. C., Psaltikidis, E. M., de Lima, T. C., Fagnani, R., Schreiber, A. Z., Conterno, L. D. O., Kamei, K., Watanabe, A., Trabasso, P., Resende, M. R., et al. (2021) · Journal de Mycologie Médicale · doi:10.1016/j.mycmed.2021.101175 · Cited by 23
Rapid antimicrobial susceptibility profiling using impedance spectroscopy
Swami, P., Verma, G., Holani, A., Kamaraju, S., Manchanda, V., Sritharan, V., & Gupta, S. (2021) · Biosensors and Bioelectronics · doi:10.1016/j.bios.2021.113876 · Cited by 23
Ali, W., Elsahn, A. F., Ting, D. S. J., Dua, H. S., & Mohammed, I. (2022) · Antibiotics · doi:10.3390/antibiotics11040475 · Cited by 23
Arumugam, S. N., Manohar, P., Sukumaran, S., Sadagopan, S., Loh, B., Leptihn, S., & Nachimuthu, R. (2022) · BMC Microbiology · doi:10.1186/s12866-022-02603-0 · Cited by 23
Yahya, R. O. (2022) · Healthcare · doi:10.3390/healthcare10122412 · Cited by 23
Mustafa, Z. U., Iqbal, S., Asif, H. R., Salman, M., Jabbar, S., Mallhi, T. H., Khan, Y. H., Sono, T. M., Schellack, N., Meyer, J. C., et al. (2023) · Antibiotics · doi:10.3390/antibiotics12030481 · Cited by 24
López-Herrero, R., Prada, L. S.-D., Tamayo-Velasco, Á., Lorenzo‐López, M., Gómez‐Pesquera, E., Sánchez-Quirós, B., de la Varga-Martínez, O., Gómez-Sánchez, E., Resino, S., Tamayo, E., et al. (2023) · European Journal of Public Health · doi:10.1093/eurpub/ckad060 · Cited by 23
Effective prognostic and clinical risk stratification in COVID‐19 using multimodality biomarkers
Liu, A., Hammond, R., Donnelly, P., Kaski, J. C., & Coates, A. R. M. (2023) · Journal of Internal Medicine · doi:10.1111/joim.13646 · Cited by 24
Yang, Y.-T., Zhong, X., Fahmi, A., Watts, S., Ashcroft, D. M., Massey, J., Fisher, L., MacKenna, B., Mehrkar, A., Bacon, S., et al. (2023) · Antimicrobial Resistance and Infection Control · doi:10.1186/s13756-023-01280-6 · Cited by 23
Nittayananta, W., Lerdsamran, H., Chutiwitoonchai, N., Promsong, A., Srichana, T., Netsomboon, K., Prasertsopon, J., & Kerdto, J. (2024) · Virology Journal · doi:10.1186/s12985-023-02282-x · Cited by 24
Malhotra, H., Bacchani, D., & Mamoria, V. P. (2021) · Indian Journal of Critical Care Medicine · doi:10.5005/jp-journals-10071-23781 · Cited by 24
Root-Bernstein, R. S. (2021) · Vaccines · doi:10.3390/vaccines9050474 · Cited by 23
Khan, S., Bond, S. E., Bakhit, M., Hasan, S. S., Sadeq, A. A., Conway, B. R., & Aldeyab, M. A. (2022) · Antibiotics · doi:10.3390/antibiotics11111600 · Cited by 23
Characterizing coinfection in children with COVID-19: A dual center retrospective analysis
Zhang, D. D., Acree, M. E., Ridgway, J. P., Shah, N. S., Hazra, A., Ravichandran, U., & Kumar, M. (2020) · Infection Control and Hospital Epidemiology · doi:10.1017/ice.2020.1221 · Cited by 22
Tellapragada, C., & Giske, C. G. (2021) · European Journal of Clinical Microbiology & Infectious Diseases · doi:10.1007/s10096-021-04194-6 · Cited by 22
Signorini, L., Moioli, G., Calza, S., Hauwermeiren, E. V., Lorenzotti, S., Fabro, G. D., Renisi, G., Lanza, P., Saccani, B., Zambolin, G., et al. (2021) · Critical Care Explorations · doi:10.1097/cce.0000000000000430 · Cited by 22
Leuven, J. T. V., Gonzalez, A. J., Ijezie, E. C., Wixom, A. Q., Clary, J. L., Naranjo, M. N., Ridenhour, B. J., Miller, C. R., & Miura, T. A. (2021) · mSphere · doi:10.1128/msphere.00479-21 · Cited by 24
COVID-19 and Co-infection in Children: The Indian Perspectives
Raychaudhuri, D., Sarkar, M., Roy, A., Roy, D., Datta, K., Sengupta, T., Hazra, A., & Mondal, R. K. (2021) · Journal of Tropical Pediatrics · doi:10.1093/tropej/fmab073 · Cited by 22
Faleye, T. O. C., Bowes, D. A., Driver, E. M., Adhikari, S., Adams, D., Varsani, A., Halden, R. U., & Scotch, M. (2021) · Viruses · doi:10.3390/v13091803 · Cited by 23
Boorgula, S. Y., Yelamanchili, S., Kottapalli, P., & Naga, M. D. (2022) · Journal of Laboratory Physicians · doi:10.1055/s-0041-1741438 · Cited by 22
Prevalence and Clinical Impact of Coinfection in Patients with Coronavirus Disease 2019 in Korea
Jeong, S., Lee, N., Park, Y., Kim, J., Jeon, K., Park, M.-J., & Song, W. (2022) · Viruses · doi:10.3390/v14020446 · Cited by 22
Co-infections in COVID-19 patients and correlation with mortality rate. Minireview
Fehér, Á., Szarvas, Z., Lehoczki, A., Fekete, M., & Fazekas‐Pongor, V. (2022) · Physiology International · doi:10.1556/2060.2022.00015 · Cited by 22
COVID-19 and C. auris: A Case-Control Study from a Tertiary Care Center in Lebanon
Allaw, F., Haddad, S. F., Habib, N., Moukarzel, P., Naji, N. S., Kanafani, Z. A., Ibrahim, A., Zahreddine, N. K., Spernovasilis, N. A., Poulakou, G., et al. (2022) · Microorganisms · doi:10.3390/microorganisms10051011 · Cited by 22
Hong, W., White, P. L., Backx, M., Gangneux, J., Reizine, F., Koehler, P. A., Bentvelsen, R. G., Cuestas, M. L., Fakhim, H., Jung, J. I., et al. (2022) · Clinical Imaging · doi:10.1016/j.clinimag.2022.07.003 · Cited by 22
SHEA statement on antibiotic stewardship in hospitals during public health emergencies
Barlam, T. F., Mohajer, M. A., Al‐Tawfiq, J. A., Auguste, A. J., Cunha, C. B., Forrest, G. N., Gross, A. E., Lee, R. A., Seo, S. K., Suh, K. N., et al. (2022) · Infection Control and Hospital Epidemiology · doi:10.1017/ice.2022.194 · Cited by 22
Jorge, G. P., Goes, I. C. R. D. S., & Gontijo, M. T. P. (2022) · Current Infectious Disease Reports · doi:10.1007/s11908-022-00788-z · Cited by 22
Shiralizadeh, S., Keramat, F., Hashemi, S. H., Majzoobi, M. M., Azimzadeh, M., Alikhani, M. S., Karami, P., Rahimi, Z., & Alikhani, M. Y. (2023) · BMC Microbiology · doi:10.1186/s12866-023-02825-w · Cited by 22
Ahmadi, T. S., Behrouz, B., & Gargari, S. L. M. (2024) · Scientific Reports · doi:10.1038/s41598-023-50859-x · Cited by 22
Duan, Y., Wang, J., Wang, S., Zhang, R., Hu, J., Li, W., & Chen, B. (2024) · European Journal of Clinical Microbiology & Infectious Diseases · doi:10.1007/s10096-024-04755-5 · Cited by 22
Ramos, B., Lourenço, A. B., Monteiro, S., Santos, R., & Cunha, M. V. (2024) · The Science of The Total Environment · doi:10.1016/j.scitotenv.2024.174272 · Cited by 23
de Buhr, N., & von Köckritz‐Blickwede, M. (2021) · mBio · doi:10.1128/mbio.03304-20 · Cited by 22
Marshall, N. C., Kariyawasam, R. M., Zelyas, N. J., Kanji, J. N., & Diggle, M. A. (2021) · Virology Journal · doi:10.1186/s12985-021-01545-9 · Cited by 22
High-value Laboratory Testing for Hospitalized COVID-19 Patients: A Review
Čiháková, D., Streiff, M. B., Menez, S. P., Chen, T. K., Gilotra, N. A., Michos, E. D., Marr, K. A., Karaba, A. H., Robinson, M. L., Blair, P. W., et al. (2021) · Future Virology · doi:10.2217/fvl-2020-0316 · Cited by 23
Promising Expectations for Pneumococcal Vaccination during COVID-19
Im, H., Ser, J., Sim, U., & Cho, H. (2021) · Vaccines · doi:10.3390/vaccines9121507 · Cited by 22
Asthmatic patients and COVID‐19: Different disease course?
Alberca, R. W., Yendo, T. M., Aoki, V., & Sato, M. N. (2021) · Allergy · doi:10.1111/all.14601 · Cited by 22
Thaden, J. T., & Maskarinec, S. A. (2020) · Clinical Microbiology and Infection · doi:10.1016/j.cmi.2020.09.002 · Cited by 21
Barrasa, H., Martín, A. H. S., Maynar, J., Rello, J., Torres, M. F., Aguirre-Quiñonero, A., & Canut, A. (2020) · Journal of Infection · doi:10.1016/j.jinf.2020.12.001 · Cited by 21
Posteraro, B., Angelis, G. D., Menchinelli, G., D’Inzeo, T., Fiori, B., Maio, F. D., Cortazzo, V., Sanguinetti, M., & Spanu, T. (2021) · Journal of Clinical Medicine · doi:10.3390/jcm10081752 · Cited by 21
Health care-associated infections in patients with COVID-19 pneumonia in COVID critical care areas
Marín‐Corral, J., Pascual-Guàrdia, S., Muñoz-Bermúdez, R., Salazar‐Degracia, A., Climent, C., Vilà-Vilardel, C., Acer, M., Picornell, M., Restrepo, M. I., Masclans, J. R., et al. (2021) · Medicina Intensiva · doi:10.1016/j.medin.2021.04.003 · Cited by 21
Henig, O., Kehat, O., Meijer, S. E., Chikly, A., Weiss‐Meilik, A., Egoz, E., Ben‐Ami, R., & Paran, Y. (2021) · Antibiotics · doi:10.3390/antibiotics10091056 · Cited by 22
Sahajpal, N., Mondal, A. K., Ananth, S., Njau, A. N., Jones, K., Ahluwalia, P. K., Oza, E., Ross, T. M., Kota, V. K., Kothandaraman, A., et al. (2022) · Scientific Reports · doi:10.1038/s41598-022-07152-0 · Cited by 21
van Charante, F., Wieme, A. D., Rigole, P., Canck, E. D., Ostyn, L., Grassi, L. C., Deforce, D. L. D., Crabbé, A., Vandamme, P. A. R., Joossens, M., et al. (2022) · Biofilm · doi:10.1016/j.bioflm.2022.100079 · Cited by 21
Pathophysiology of Methicillin-Resistant Staphylococcus aureus Superinfection in COVID-19 Patients
Gul, H., Mahmood, K., Gul, H., Tariq, M., Ain, Q. U., Hayat, A., & Rehman, M. U. (2022) · Pathophysiology · doi:10.3390/pathophysiology29030032 · Cited by 21
Kapoula, G. V., Vennou, K. E., & Bagos, P. G. (2022) · Diagnostics · doi:10.3390/diagnostics12123086 · Cited by 21
Hye, M. A., Biswas, M. A. H. A., Uddin, M. F., & Saifuddin, M. (2022) · Computational Mathematics and Modeling · doi:10.1007/s10598-023-09564-7 · Cited by 21
Miftode, I.-L., Leca, D. A., Miftode, R.-Ş., Roşu, F. M., Plesca, C. E., Loghin, I. I., Țimpău, A. S., Mitu, I., Mititiuc, I. L., Dorneanu, O., et al. (2023) · Antibiotics · doi:10.3390/antibiotics12020324 · Cited by 21
Metadata
- Authors
- Lansbury, L., Lim, B., Baskaran, V., & Lim, W. S.
- Affiliations
- University of Nottingham (GB)
- University of Cambridge (GB)
- Nottingham University Hospitals NHS Trust (GB)
- Corresponding author
- Lansbury, Louise
- Lim, Benjamin
- Baskaran, Vadsala
- Lim, Wei Shen
- Venue
- Journal of Infection
- Publisher
- Elsevier BV
- Published
- 2020-08
- Volume
- 81
- Issue
- 2
- Pages
- 266-275
- ISSN
- 0163-4453 (ISSN-L)
- PMC
- PMC7255350
- OpenAlex
- W3029242200
- Semantic Scholar
- 178ec3f24c4d80e4010688e584fffe519bccb407
- Cited by
- 1,619
- References
- 72
- Citations by year
- 2026: 67 · 2025: 88 · 2024: 170 · 2023: 304 · 2022: 393 · 2021: 463 · 2020: 132
- FWCI
- 15.26
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Journal of Infection (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Repository@Nottingham (University of Nottingham) (acceptedVersion, other-oa)
- Repository@Nottingham (University of Nottingham) (submittedVersion, cc-by-nc-nd)
- Funders
- National Institute for Health and Care Research
- Topics
- Health Sciences › Medicine › Infectious Diseases › COVID-19 Clinical Research Studies
- Health Sciences › Medicine › Epidemiology › Pneumonia and Respiratory Infections
- Health Sciences › Medicine › Epidemiology › Respiratory viral infections research
- Keywords
- COVID-19 pandemic, bacterial co-infection, viral coinfection, fungal co-infection, Mycoplasma pneumoniae pneumonia, Pseudomonas aeruginosa, Haemophilus influenzae, respiratory syncytial virus, influenza A virus, intensive care unit patients, antibiotic use, hospitalized patients
- MeSH terms
- Betacoronavirus, COVID-19, SARS-CoV-2, Bacterial Infections, Humans, Mycoses, Pneumonia, Viral, Virus Diseases, Coronavirus Infections, Pandemics, Coinfection
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
A language model drew the claims from the paper on 2026-10-09, under version 3 of the claim definition (model deepseek-v4.1-flash, prompt extract-v3).
A second model labelled each claim on 2026-10-09 (model jev-1.13-20260917, definition revision gold-guideline-v0.2).
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
