Prognostic Factors for 30-Day Mortality in Critically Ill Patients With Coronavirus Disease 2019: An Observational Cohort Study

Ferrando-Vivas, Paloma; Doidge, James; Thomas, Karen; Gould, Doug W.; Mouncey, Paul; Shankar-Hari, Manu; Young, J. Duncan; Rowan, Kathryn M.; Harrison, David A.

doi:10.1097/ccm.0000000000004740

Cited by 114COVID-19 Clinical Research StudiesSepsis Diagnosis and TreatmentRespiratory Support and Mechanisms

Prognostic Factors for 30-Day Mortality in Critically Ill Patients With Coronavirus Disease 2019: An Observational Cohort Study

Open access

Ferrando-Vivas, Paloma, Doidge, James, Thomas, Karen, Gould, Doug W., Mouncey, Paul, Shankar-Hari, Manu, Young, J. Duncan, Rowan, Kathryn M. +1 more·2021·Critical Care Medicine

DOI 10.1097/ccm.0000000000004740PMC PMC7737692

Open this paper in CoChat — free account

Abstract

OBJECTIVES: To identify characteristics that predict 30-day mortality among patients critically ill with coronavirus disease 2019 in England, Wales, and Northern Ireland. DESIGN: Observational cohort study. SETTING: A total of 258 adult critical care units. PATIENTS: A total of 10,362 patients with confirmed coronavirus disease 2019 with a start of critical care between March 1, 2020, and June 22, 2020, of whom 9,990 were eligible (excluding patients with a duration of critical care less than 24 hr or missing core variables). MEASUREMENTS AND MAIN RESULTS: The main outcome measure was time to death within 30 days of the start of critical care. Of 9,990 eligible patients (median age 60 yr, 70% male), 3,933 died within 30 days of the start of critical care. As of July 22, 2020, 189 patients were still receiving critical care and a further 446 were still in acute hospital. Data were missing for between 0.1% and 7.2% of patients across prognostic factors. We imputed missing data ten-fold, using fully conditional specification and continuous variables were modeled using restricted cubic splines. Associations between the candidate prognostic factors and time to death within 30 days of the start of critical care were determined after adjustment for multiple variables with Cox proportional hazards modeling. Significant associations were identified for age, ethnicity, deprivation, body mass index, prior dependency, immunocompromise, lowest systolic blood pressure, highest heart rate, highest respiratory rate, Pa o 2/F io 2 ratio (and interaction with mechanical ventilation), highest blood lactate concentration, highest serum urea, and lowest platelet count over the first 24 hours of critical care. Nonsignificant associations were found for sex, sedation, highest temperature, and lowest hemoglobin concentration. CONCLUSIONS: We identified patient characteristics that predict an increased likelihood of death within 30 days of the start of critical care for patients with coronavirus disease 2019. These findings may support development of a prediction model for benchmarking critical care providers.

Integrity signals

Registry

Crossref · 10.1097/ccm.0000000000004740

Cites

29 of 29 references verified0 citation errors · 0 not checkable

Statistics

Recomputing p-values needs the paper’s full text.

Claims the paper makes

We couldn’t retrieve this paper’s full text, so its claims and self-check weren’t run. The registry and citation checks still apply.

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?

30-day mortality is primarily determined by acute factors such as initial hemodynamic instability and multi-organ failure.
“This is likely because 30-day mortality is primarily determined by acute factors such as initial hemodynamic instability and multi-organ failure [29], whereas 90-day mortality is influenced by cumulative effects of EFI over time, particularly through its impact on nutritional status.”
From The impact of enteral feeding intolerance on the prognosis of patients with septic shock in South Korea (2025) · cites this paper as [29]

Clinical course and risk factors for mortality of adult inpatients with COVID-19 in Wuhan, China: a retrospective cohort study
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 · see citing works
Characteristics of and Important Lessons From the Coronavirus Disease 2019 (COVID-19) Outbreak in China: Summary of a Report of 72 314 Cases From the Chinese Center for Disease Control and Prevention
Wu, Z., & McGoogan, J. M. (2020) · JAMA · doi:10.1001/jama.2020.2648 · Cited by 17,016 · see citing works
Heat Shock Protein A12B Protects Vascular Endothelial Cells Against Sepsis-Induced Acute Lung Injury in Mice
Chen, Y., Wang, L., Kang, Q., Zhang, X., Yu, G., Wan, X., Wang, J., & Zhu, K. (2017) · Cellular Physiology and Biochemistry · doi:10.1159/000477308 · Cited by 10,730 · see citing works
Clinical course and outcomes of critically ill patients with SARS-CoV-2 pneumonia in Wuhan, China: a single-centered, retrospective, observational study
Yang, X., Yu, Y., Xu, J., Shu, H., Xia, J., Liu, H., Wu, Y., Zhang, L., Yu, Z., Fang, M., et al. (2020) · The Lancet Respiratory Medicine · doi:10.1016/s2213-2600(20)30079-5 · Cited by 10,066 · see citing works
Acute Respiratory Distress Syndrome
Ards Definition Task Force (2012) · JAMA · doi:10.1001/jama.2012.5669 · Cited by 8,806 · see citing works
Risk Factors Associated With Acute Respiratory Distress Syndrome and Death in Patients With Coronavirus Disease 2019 Pneumonia in Wuhan, China
Wu, C., Chen, X., Cai, Y., Xia, J., Zhou, X., Xu, S., Huang, H., Zhang, L., Zhou, X., Du, C., et al. (2020) · JAMA Internal Medicine · doi:10.1001/jamainternmed.2020.0994 · Cited by 8,249 · see citing works
Partial residuals for the proportional hazards regression model
SCHOENFELD, D. (1982) · Biometrika · doi:10.1093/biomet/69.1.239 · Cited by 3,111 · see citing works
Systematic review and critical appraisal of prediction models for diagnosis and prognosis of COVID-19 infection
Wynants, L., Van Calster, B., Bonten, M. M., Collins, G. S., Debray, T. P., De Vos, M., Haller, M. C., Heinze, G., Moons, K. G., Riley, R. D., et al. (2020) · doi:10.1101/2020.03.24.20041020 · Cited by 3,070 · see citing works
Factors associated with hospital admission and critical illness among 5279 people with coronavirus disease 2019 in New York City: prospective cohort study
Petrilli, C. M., Jones, S. A., Yang, J., Rajagopalan, H., O’Donnell, L., Chernyak, Y., Tobin, K. A., Cerfolio, R. J., François, F., & Horwitz, L. I. (2020) · BMJ · doi:10.1136/bmj.m1966 · Cited by 3,045 · see citing works
Calculating the sample size required for developing a clinical prediction model
Riley, R. D., Ensor, J., Snell, K. I. E., Harrell, F. E., Martin, G. P., Reitsma, J. B., Moons, K. G. M., Collins, G., & van Smeden, M. (2020) · BMJ · doi:10.1136/bmj.m441 · Cited by 2,917 · see citing works
Epidemiology, clinical course, and outcomes of critically ill adults with COVID-19 in New York City: a prospective cohort study
Cummings, M. J., Baldwin, M. R., Abrams, D. C., Jacobson, S. D., Meyer, B. J., Balough, E. M., Aaron, J. G., Claassen, J., Rabbani, L. E., Hastie, J. M., et al. (2020) · The Lancet · doi:10.1016/s0140-6736(20)31189-2 · Cited by 2,198 · see citing works
Lymphopenia predicts disease severity of COVID-19: a descriptive and predictive study
Tan, L., Wang, Q., Zhang, D., Jinya, D., Huang, Q., Wang, Q., Wang, Q., & Miao, H. (2020) · Signal Transduction and Targeted Therapy · doi:10.1038/s41392-020-0148-4 · Cited by 1,684 · see citing works
Risk Factors Associated With Mortality Among Patients With COVID-19 in Intensive Care Units in Lombardy, Italy
Grasselli, G., Greco, M., Zanella, A., Albano, G., Antonelli, M. M., Bellani, G., Bonanomi, E., Cabrini, L., Carlesso, E., Castelli, G. P., et al. (2020) · JAMA Internal Medicine · doi:10.1001/jamainternmed.2020.3539 · Cited by 1,608 · see citing works
Development and Validation of a Clinical Risk Score to Predict the Occurrence of Critical Illness in Hospitalized Patients With COVID-19
Liang, W., Liang, H., Ou, L., Chen, B., Chen, A., Li, C., Li, Y., Guan, W., Sang, L., Lu, J., et al. (2020) · JAMA Internal Medicine · doi:10.1001/jamainternmed.2020.2033 · Cited by 1,387 · see citing works
An interpretable mortality prediction model for COVID-19 patients
Li, Y., Zhang, H., Gonçalves, J. M., Xiao, Y., Wang, M., Guo, Y., Sun, C., Tang, X., Jing, L., Zhang, M., et al. (2020) · Nature Machine Intelligence · doi:10.1038/s42256-020-0180-7 · Cited by 1,304 · see citing works
Imputing missing covariate values for the Cox model
White, I., & Royston, P. (2009) · Statistics in Medicine · doi:10.1002/sim.3618 · Cited by 994 · see citing works
Prognosis Research Strategy (PROGRESS) 2: Prognostic Factor Research
Riley, R. D., Hayden, J. A., Steyerberg, E. W., Moons, K. G. M., Abrams, K., Kyzas, P. A., Malats, N., Briggs, A., Schroter, S., Altman, D. G., et al. (2013) · PLoS Medicine · doi:10.1371/journal.pmed.1001380 · Cited by 823 · see citing works
Illustrating bias due to conditioning on a collider
Cole, S. R., Platt, R. W., Schisterman, E. F., Chu, H., Westreich, D., Richardson, D., & Poole, C. (2010) · International Journal of Epidemiology · doi:10.1093/ije/dyp334 · Cited by 796 · see citing works
A Tool for Early Prediction of Severe Coronavirus Disease 2019 (COVID-19): A Multicenter Study Using the Risk Nomogram in Wuhan and Guangdong, China
Gong, J., Ou, J., Qiu, X., Jie, Y., Chen, Y., Yuan, L., Cao, J., Tan, M., Xu, W., Zheng, F., et al. (2020) · Clinical Infectious Diseases · doi:10.1093/cid/ciaa443 · Cited by 513 · see citing works
Multiple imputation of covariates by fully conditional specification: Accommodating the substantive model
Bartlett, J. W., Seaman, S. R., White, I. R., Carpenter, J. R., & Initiative, A. D. N. (2014) · Statistical Methods in Medical Research · doi:10.1177/0962280214521348 · Cited by 483 · see citing works
Trends in Mortality for Medicare Beneficiaries Treated in the Emergency Department From 2009 to 2016
Burke, L. G., Epstein, S. K., Burke, R. C., Orav, E. J., & Jha, A. K. (2019) · JAMA Internal Medicine · doi:10.1001/jamainternmed.2019.4866 · Cited by 382 · see citing works
Clinical course and predictors of 60-day mortality in 239 critically ill patients with COVID-19: a multicenter retrospective study from Wuhan, China
Xu, J., Yang, X., Yang, L., Zou, X., Wang, Y., Wu, Y., Zhou, T., Yuan, Y., Qi, H., Fu, S., et al. (2020) · Critical Care · doi:10.1186/s13054-020-03098-9 · Cited by 236 · see citing works
Trends in Intensive Care for Patients with COVID-19 in England, Wales, and Northern Ireland
Doidge, J., Gould, D. W., Ferrando-Vivas, P., Mouncey, P. R., Thomas, K., Shankar‐Hari, M., Harrison, D. A., & Rowan, K. (2020) · American Journal of Respiratory and Critical Care Medicine · doi:10.1164/rccm.202008-3212oc · Cited by 169 · see citing works
Self-citation
Development and External Validation of a Prognostic Multivariable Model on Admission for Hospitalized Patients with COVID-19Preprint
Xie, J., Hungerford, D., Chen, H., Abrams, S. T., Li, S., Wang, G., Wang, Y., Kang, H., Bonnett, L. J., Zheng, R., et al. (2020) · SSRN Electronic Journal · doi:10.1101/2020.03.28.20045997 · Cited by 157 · see citing works
Baseline characteristics and outcomes of patients with COVID-19 admitted to intensive care units in Vancouver, Canada: a case series
Mitra, A. R., Fergusson, N. A., Lloyd‐Smith, E., Wormsbecker, A., Foster, D., Karpov, A., Crowe, S., Haljan, G., Chittock, D. R., Kanji, H. D., et al. (2020) · Canadian Medical Association Journal · doi:10.1503/cmaj.200794 · Cited by 142 · see citing works
Deep learning for predicting COVID-19 malignant progression
Fang, C., Bai, S., Chen, Q., Zhou, Y., Xia, L., Qin, L., Gong, S., Xie, X., Zhou, C., Tu, D., et al. (2021) · Medical Image Analysis · doi:10.1016/j.media.2021.102096 · Cited by 139 · see citing works
ACP Risk Grade: A Simple Mortality Index for Patients with Confirmed or Suspected Severe Acute Respiratory Syndrome Coronavirus 2 Disease (COVID-19) During the Early Stage of Outbreak in Wuhan, ChinaPreprint
Lu, J., Hu, S., Fan, R., Liu, Z., Yin, X., Wang, Q., Lv, Q., Cai, Z., Li, H., Hu, Y., et al. (2020) · medRxiv · doi:10.1101/2020.02.20.20025510 · Cited by 122 · see citing works
Clinical phenotypes of critically ill COVID-19 patients
Azoulay, É., Zafrani, L., Mirouse, A., Lengliné, É., Darmon, M., & Chevret, S. (2020) · Intensive Care Medicine · doi:10.1007/s00134-020-06120-4 · Cited by 66 · see citing works
Untitled work
Harrell, F., Jr. (1996) · doi:10.1002/(sici)1097-0258(19960229)15:4

Flagged first, then by citations

5 of the 34 references couldn’t be matched to a known paper.

Sorted by citations

Diabetes, hypertension, body mass index, smoking and COVID-19-related mortality: a systematic review and meta-analysis of observational studies
Mahamat‐Saleh, Y., Fiolet, T., Rebeaud, M. E., Mulot, M., Guihur, A., Fatouhi, D. E., Laouali, N., Peiffer‐Smadja, N., Aune, D., & Severi, G. (2021) · BMJ Open · doi:10.1136/bmjopen-2021-052777 · Cited by 205 · see citing works
Coronavirus Disease 2019 as Cause of Viral Sepsis: A Systematic Review and Meta-Analysis*
Karakike, E., Giamarellos‐Bourboulis, E. J., Kyprianou, M., Fleischmann-Struzek, C., Pletz, M. W., Netea, M. G., Reinhart, K., & Kyriazopoulou, E. (2021) · Critical Care Medicine · doi:10.1097/ccm.0000000000005195 · Cited by 182 · see citing works
Addressing the post-acute sequelae of SARS-CoV-2 infection: a multidisciplinary model of care
Parker, A. M., Brigham, E. P., Connolly, B. A., McPeake, J. M., Agranovich, A. V., Kenes, M. T., Casey, K. S., Reynolds, C., Schmidt, K. F. R., Kim, S. Y., et al. (2021) · The Lancet Respiratory Medicine · doi:10.1016/s2213-2600(21)00385-4 · Cited by 169 · see citing works
Trends in Intensive Care for Patients with COVID-19 in England, Wales, and Northern Ireland
Doidge, J., Gould, D. W., Ferrando-Vivas, P., Mouncey, P. R., Thomas, K., Shankar‐Hari, M., Harrison, D. A., & Rowan, K. (2020) · American Journal of Respiratory and Critical Care Medicine · doi:10.1164/rccm.202008-3212oc · Cited by 169 · see citing works
Self-citation
Clinical characteristics and outcomes of invasively ventilated patients with COVID-19 in Argentina (SATICOVID): a prospective, multicentre cohort study
Estenssoro, E., Loudet, C., Ríos, F. G., Edul, V. S. K., Plotnikow, G. A., Andrian, M., Romero, I., Piezny, D., Bezzi, M., Mandich, V., et al. (2021) · The Lancet Respiratory Medicine · doi:10.1016/s2213-2600(21)00229-0 · Cited by 167 · see citing works
The impact of COVID-19 on the wellbeing of the UK nursing and midwifery workforce during the first pandemic wave: A longitudinal survey study
Couper, K., Murrells, T., Sanders, J., Anderson, J. E., Blake, H., Kelly, D. M., Kent, B., Maben, J., Rafferty, A. M., Taylor, R. M., et al. (2021) · International Journal of Nursing Studies · doi:10.1016/j.ijnurstu.2021.104155 · Cited by 120 · see citing works
Protective ventilation and outcomes of critically ill patients with COVID-19: a cohort study.
Ferreira, J. C., Ho, Y.-L., Besen, B. A. M. P., Malbouisson, L. M. S., Taniguchi, L. U., Mendes, P. V., Costa, E. L. V., Park, M., Daltro-Oliveira, R., Roepke, R. M. L., et al. (2021) · PubMed Central · doi:10.1186/s13613-021-00882-w · Cited by 113 · see citing works
Factors associated with mortality in patients with COVID‐19 admitted to intensive care: a systematic review and meta‐analysis
Taylor, E. H., Marson, E. J., Elhadi, M., Macleod, K., Yu, Y., Davids, R. A., Boden, R., Overmeyer, R. C., Ramakrishnan, R., Thomson, D. A., et al. (2021) · Anaesthesia · doi:10.1111/anae.15532 · Cited by 98 · see citing works
Differences in Outcomes and Factors Associated With Mortality Among Patients With SARS-CoV-2 Infection and Cancer Compared With Those Without Cancer
Khoury, E. G., Nevitt, S. J., Madsen, W. R., Turtle, L. C. W., Davies, G., & Palmieri, C. (2022) · JAMA Network Open · doi:10.1001/jamanetworkopen.2022.10880 · Cited by 85 · see citing works
Does Unprecedented ICU Capacity Strain, As Experienced During the COVID-19 Pandemic, Impact Patient Outcome?
Wilcox, M. E., Rowan, K., Harrison, D. A., & Doidge, J. (2022) · Critical Care Medicine · doi:10.1097/ccm.0000000000005464 · Cited by 78 · see citing works
Self-citation
Association Between Socioeconomic Status and Outcomes in Critical Care: A Systematic Review and Meta-Analysis
McHenry, R. D., Moultrie, C. E., Quasim, T., Mackay, D., & Pell, J. P. (2022) · Critical Care Medicine · doi:10.1097/ccm.0000000000005765 · Cited by 64 · see citing works
Global prevalence and effect of comorbidities and smoking status on severity and mortality of COVID-19 in association with age and gender: a systematic review, meta-analysis and meta-regression
Chenchula, S., Vidyasagar, K., Pathan, S., Sharma, S. K., Chavan, M. R., Bhagavathula, A. S., Padmavathi, R., Manjula, M., Chhabra, M., Gupta, R., et al. (2023) · Scientific Reports · doi:10.1038/s41598-023-33314-9 · Cited by 59 · see citing works
Trends in COVID-19 hospital outcomes in England before and after vaccine introduction, a cohort study
Kirwan, P., Charlett, A., Birrell, P., Elgohari, S., Hope, R., Mandal, S., Angelis, D. D., & Presanis, A. M. (2022) · Nature Communications · doi:10.1038/s41467-022-32458-y · Cited by 37 · see citing works
Epidemiology and outcomes of early-onset AKI in COVID-19-related ARDS in comparison with non-COVID-19-related ARDS: insights from two prospective global cohort studies
McNicholas, B., Rezoagli, E., Simpkin, A. J., Khanna, S., Suen, J. Y., Yeung, P., Brodie, D., Bassi, G. L., Pham, T. O., Bellani, G., et al. (2023) · Critical Care · doi:10.1186/s13054-022-04294-5 · Cited by 32 · see citing works
Risk of Covid-19 Severe Outcomes and Mortality in Migrants and Ethnic Minorities Compared to the General Population in the European WHO Region: a Systematic Review
Mazzalai, E., Giannini, D., Tosti, M. E., D’Angelo, F., Declich, S., Jaljaa, A., Caminada, S., Turatto, F., Marchi, C. D., Gatta, A., et al. (2023) · Journal of International Migration and Integration / Revue de l integration et de la migration internationale · doi:10.1007/s12134-023-01007-x · Cited by 33 · see citing works
Coronavirus disease 2019 subphenotypes and differential treatment response to convalescent plasma in critically ill adults: secondary analyses of a randomized clinical trial
Fish, M., Rynne, J., Jennings, A. R., Lam, C., Lamikanra, A., Ratcliff, J., Trevelin, S. C., Timms, E. M., Jiriha, J., Tosi, I., et al. (2022) · Intensive Care Medicine · doi:10.1007/s00134-022-06869-w · Cited by 28 · see citing works
Self-citation
Heterogeneity and Risk of Bias in Studies Examining Risk Factors for Severe Illness and Death in COVID-19: A Systematic Review and Meta-Analysis
Degarege, A., Naveed, Z., Kabayundo, J., & Brett‐Major, D. M. (2022) · Pathogens · doi:10.3390/pathogens11050563 · Cited by 26 · see citing works
A Review of Routine Laboratory Biomarkers for the Detection of Severe COVID-19 Disease
Keykavousi, K., Nourbakhsh, F., Abdollahpour, N., Fazeli, F., Sedaghat, A., Soheili, V., & Sahebkar, A. (2022) · International Journal of Analytical Chemistry · doi:10.1155/2022/9006487 · Cited by 23 · see citing works
Changes in characteristics and outcomes of critically ill COVID-19 patients in Tyrol (Austria) over 1 year
Mayerhöfer, T., Klein, S., Peer, A., Perschinka, F., Lehner, G. F., Haßlacher, J., Bellmann, R., Gasteiger, L., Mittermayr, M., Eschertzhuber, S., et al. (2021) · Wiener klinische Wochenschrift · doi:10.1007/s00508-021-01945-5 · Cited by 22 · see citing works
Clinical outcomes following COVID-19 infection in ethnic minority groups in the UK: a systematic review and meta-analysis
Siddiq, S., Ahmed, S., & Akram, I. (2022) · Public Health · doi:10.1016/j.puhe.2022.05.019 · Cited by 22 · see citing works
Indications for Tracheal Intubation in Patients With Coronavirus Disease 2019 (COVID-19)
Pisano, A., Yavorovskiy, A. G., Verniero, L., & Landoni, G. (2020) · Journal of Cardiothoracic and Vascular Anesthesia · doi:10.1053/j.jvca.2020.11.062 · Cited by 20 · see citing works
Intensive Care and Organ Support Related Mortality in Patients With COVID-19: A Systematic Review and Meta-Analysis
Chandel, A., Leazer, S. T., Alcover, K. C., Farley, J., Berk, J., Jayne, C., McNutt, R., Olsen, M. L., Allard, R. J., Yang, J., et al. (2023) · Critical Care Explorations · doi:10.1097/cce.0000000000000876 · Cited by 20 · see citing works
Changes over time in characteristics, resource use and outcomes among ICU patients with COVID‐19—A nationwide, observational study in Denmark
Haase, N., Plovsing, R. R., Christensen, S., Poulsen, L. M., Brøchner, A. C., Rasmussen, B. S., Helleberg, M., Jensen, J. S., Andersen, L. P. K., Siegel, H., et al. (2022) · Acta Anaesthesiologica Scandinavica · doi:10.1111/aas.14113 · Cited by 18 · see citing works
Disrupted Peyer’s Patch Microanatomy in COVID-19 Including Germinal Centre Atrophy Independent of Local Virus
Trevelin, S. C., Pickering, S., Todd, K., Bishop, C., Pitcher, M. J., Garrido‐Mesa, J., Montorsi, L., Spada, F., Petrov, N., Green, A. C., et al. (2022) · Frontiers in Immunology · doi:10.3389/fimmu.2022.838328 · Cited by 17 · see citing works
Self-citation
External validation of the 4C Mortality Score for hospitalised patients with COVID-19 in the RECOVER network
Gordon, A. J., Govindarajan, P., Bennett, C., Matheson, L. W., Kohn, M. A., Camargo, C. A., & Kline, J. A. (2022) · BMJ Open · doi:10.1136/bmjopen-2021-054700 · Cited by 18 · see citing works
Prognostic factors and outcomes in COVID-19 patients requiring prolonged mechanical ventilation: a retrospective cohort study
Melamed, R., Paz, F., Jepsen, S. L., Smith, C. S., Saavedra-Romero, R., Mulder, M., Masood, A., Huelster, J., Kirkland, L. L., Guenther, A., et al. (2022) · Therapeutic Advances in Respiratory Disease · doi:10.1177/17534666221086415 · Cited by 17 · see citing works
Assessment of 28-Day In-Hospital Mortality in Mechanically Ventilated Patients With Coronavirus Disease 2019: An International Cohort Study
Bassi, G. L., Suen, J. Y., White, N. M., Dalton, H. J., Fanning, J. P., Corley, A., Shrapnel, S., Hinton, S. R., Forsyth, S. J., Parsons, R., et al. (2021) · Critical Care Explorations · doi:10.1097/cce.0000000000000567 · Cited by 12 · see citing works
Lactate/Albumin Ratio as a Prognostic Factor for Short-time Mortality in Critically Ill Patients with Coronavirus Disease-2019
Gök, A., Kasapoğlu, U. S., Delen, L. A., Özmen, F., & Banazılı, S. (2021) · Türk yoğun bakım derneği dergisi/Türk yoğun bakım dergisi · doi:10.4274/tybd.galenos.2021.37167 · Cited by 10 · see citing works
Clinical outcomes of and risk factors for secondary infection in patients with severe COVID-19: a multicenter cohort study in South Korea
Na, Y. S., Baek, A.-R., Baek, M. S., Kim, W., Kim, J. H., Lee, B. Y., Seong, G. M., & Lee, S. (2022) · The Korean Journal of Internal Medicine · doi:10.3904/kjim.2022.084 · Cited by 10 · see citing works
AZD1222 effectiveness against severe COVID-19 in individuals with comorbidity or frailty: The RAVEN cohort study
Meeraus, W. H., Joy, M., Ouwens, M., Taylor, K., Venkatesan, S., Dennis, J., Tran, T. N., Dashtban, A., Fan, X., Williams, R., et al. (2024) · Journal of Infection · doi:10.1016/j.jinf.2024.106129 · Cited by 10 · see citing works
A simple prognostic score based on troponin and presepsin for COVID-19 patients admitted to the emergency department: a single-center pilot study.
Dell'Aquila, P., Raimondo, P., Orso, D., Luca, P. D., Pozzessere, P., Parisi, C. V., Bove, T., Vetrugno, L., Grasso, S., & Procacci, V. (2021) · Acta bio-medica dell'Ateneo parmense/Acta biomedica · doi:10.23750/abm.v92i4.11479 · Cited by 9 · see citing works
Rapid Evaluation of Coronavirus Illness Severity (RECOILS) in intensive care: Development and validation of a prognostic tool for in‐hospital mortality
Plečko, D., Bennett, N., Mårtensson, J., Dam, T. A., Entjes, R., Rettig, T. C. D., Dongelmans, D. A., Boelens, A. D., Rigter, S., Hendriks, S. H. A., et al. (2021) · Acta Anaesthesiologica Scandinavica · doi:10.1111/aas.13991 · Cited by 10 · see citing works
Assess and validate predictive performance of models for in-hospital mortality in COVID-19 patients: A retrospective cohort study in the Netherlands comparing the value of registry data with high-granular electronic health records
Vagliano, I., Schut, M. C., Abu–Hanna, A., Dongelmans, D. A., de Lange, D. W., Gommers, D. A. M. P. J., Cremer, O. L., Bosman, R. J., Rigter, S., Wils, E., et al. (2022) · International Journal of Medical Informatics · doi:10.1016/j.ijmedinf.2022.104863 · Cited by 9 · see citing works
The intertwining of healthcare-associated infections and COVID-19 in Italian intensive care units: an analysis of the SPIN-UTI project from 2006 to 2021
Barchitta, M., Maugeri, A., Favara, G., Lio, R. M. S., Rosa, M. C. L., D’Ancona, F. “., Agodi, A., Murgia, P., Masiá, M. D., Mura, I., et al. (2023) · Journal of Hospital Infection · doi:10.1016/j.jhin.2023.07.021 · Cited by 9 · see citing works
Strategies to ensure continuity of nutritional care in patients with COVID-19 infection on discharge from hospital: A rapid review
Latif, J., Weekes, C. E., Julian, A., Frost, G. S., Murphy, J. L., Hernández, Y. A. T., & Hickson, M. (2021) · Clinical Nutrition ESPEN · doi:10.1016/j.clnesp.2021.11.020 · Cited by 9 · see citing works
Diabetes mellitus is associated with 90-day mortality in old critically ill COVID-19 patients: a multicenter prospective observational cohort study
Mayerhöfer, T., Klein, S., Wernly, B., Flaatten, H. K., Guidet, B., de Lange, D. W., Fjølner, J., Leaver, S. K., Beil, M., Sviri, S., et al. (2023) · Infection · doi:10.1007/s15010-023-02001-2 · Cited by 9 · see citing works
Prevalence of overweight and obesity and their effect on COVID‐19 severity and hospitalization among younger than 50 years versus older than 50 years population: A systematic review and meta‐analysis
Chenchula, S., Sharma, S., Tripathi, M., Chavan, M., Misra, A. K., & Rangari, G. M. (2023) · Obesity Reviews · doi:10.1111/obr.13616 · Cited by 9 · see citing works
Comparison of COVID-19 with influenza A in the ICU: a territory-wide, retrospective, propensity matched cohort on mortality and length of stay
Chu, R. B. H., Zhao, S., Zhang, J. Z., Chan, K. C. K., Ng, P. Y., Chan, C., Fong, K. M., Au, S. Y., Yeung, A. W. T., Chan, J. K. H., et al. (2023) · BMJ Open · doi:10.1136/bmjopen-2022-067101 · Cited by 8 · see citing works
Microbial dynamics, risk factors and outcomes of secondary pneumonia in critically ill patients with COVID-19: A multicenter retrospective cohort study
Hu, G. J., Liu, W., Chang, C., Ruan, S., Chung, K., Chien, J., & Yu, C. (2024) · Journal of the Formosan Medical Association · doi:10.1016/j.jfma.2024.07.013 · Cited by 8 · see citing works
Hemodynamic, Oxygenation and Lymphocyte Parameters Predict COVID-19 Mortality
Windradi, C., Asmarawati, T. P., Rosyid, A. N., Marfiani, E., Mahdi, B. A., Martani, O. S., Giarena, G., Agustin, E. D., & Rosandy, M. G. (2023) · Pathophysiology · doi:10.3390/pathophysiology30030025 · Cited by 7 · see citing works
Trends in risks of severe events and lengths of stay for COVID-19 hospitalisations in England over the pre-vaccination era: results from the Public Health England SARI-Watch surveillance schemePreprint
Kirwan, P., Elgohari, S., Jackson, C., Tom, B. D. M., Mandal, S., Angelis, D. D., & Presanis, A. M. (2021) · arXiv (Cornell University) · doi:10.48550/arxiv.2103.04867 · Cited by 7 · see citing works
Revisiting ethnic discrepancies in COVID-19 hospitalized cohorts: a correction for collider bias
Learoyd, A., Nicholas, J. M., Hart, N., & Douiri, A. (2023) · Journal of Clinical Epidemiology · doi:10.1016/j.jclinepi.2023.06.014 · Cited by 6 · see citing works
Patient characteristics, management and outcomes in a Nordic subset of the “large observational study to understand the global impact of severe acute respiratory failure” ( LUNG SAFE ) study
Laake, J. H., Småstuen, M. C., Møller, M. H., Larsson, A., Aslam, T. N., Hofsø, K., Pham, T. O., Fan, E., Bellani, G., Laffey, J. G., et al. (2022) · Acta Anaesthesiologica Scandinavica · doi:10.1111/aas.14069 · Cited by 5 · see citing works
Factors influencing death in COVID-19 patients treated in the ICU: a single-centre, cross-sectional study
Kokoszka-Bargieł, I., Cyprys, P., Madeja, P., Rutkowska, K., Wajda-Pokrontka, M., Madowicz, J., & Knapik, P. (2022) · Anaesthesiology Intensive Therapy · doi:10.5114/ait.2022.116231 · Cited by 5 · see citing works
Airway Management of Patients with Suspected or Confirmed COVID-19: Survey Results from Physicians from 19 Countries in Latin America
Granell, M., Sanchis, N., Delgado, C. F., Lozano, M., Pinho, M., Sandoval, C., Romero, C. S., Aldecoa, C., Cata, J. P., Neira, J., et al. (2022) · Journal of Clinical Medicine · doi:10.3390/jcm11164731 · Cited by 5 · see citing works
Expert consensus on the diagnosis and treatment of severe and critical coronavirus disease 2019 (COVID-19)
Shang, Y., Wu, J., Liu, J., Long, Y., Xie, J., Zhang, D., Hu, B., Zong, Y., Liao, X., Shang, X., et al. (2022) · Journal of Intensive Medicine · doi:10.1016/j.jointm.2022.07.001 · Cited by 5 · see citing works
Application of information from external data to correct for collider bias in a Covid-19 hospitalised cohort
Learoyd, A., Nicholas, J. M., Hart, N., & Douiri, A. (2024) · BMC Medical Research Methodology · doi:10.1186/s12874-023-02129-7 · Cited by 5 · see citing works
Rapid systematic review of respiratory rate as a vital sign of clinical deterioration in COVID-19
Tredinnick‐Rowe, J., & Symonds, R. F. (2022) · Expert Review of Respiratory Medicine · doi:10.1080/17476348.2023.2169138 · Cited by 4 · see citing works
Development and validation of a survival prediction model for patients received mechanical ventilation in the intensive care unit: a large sample size cohort from the MIMIC database
Lin, Z., Huang, X., & Shan, X. (2022) · Annals of Palliative Medicine · doi:10.21037/apm-22-646 · Cited by 4 · see citing works
The impact of enteral feeding intolerance on the prognosis of patients with septic shock in South Korea
Park, H.-J., Ahn, Y. H., Lee, H. Y., Lee, S.-M., & Lee, J. (2025) · Acute and Critical Care · doi:10.4266/acc.000700 · Cited by 3 · see citing works
Association of Area Deprivation Index With Mortality in Critically Ill Adults With COVID-19
Harris, R. M., Rosser, M. A., Chowdhury, A. M., Ohnuma, T., Raghunathan, K., Haines, K., & Krishnamoorthy, V. K. (2024) · American Journal of Critical Care · doi:10.4037/ajcc2024898 · Cited by 3 · see citing works
Prognosis of Old Intensive Care COVID-19 Patients at a Glance: The Senior COVID Study
Vacheron, C., Bitker, L., Thiollière, F., Subtil, F., Abraham, P., Collange, V., Balança, B., Haïne, M., Guichon, C., Leroy, C., et al. (2022) · Türk anesteziyoloji ve reanimasyon derneği dergisi · doi:10.5152/tjar.2022.21321 · Cited by 3 · see citing works
Impacto del decúbito prono en pacientes con COVID-19 grave en un hospital de agudos de la Ciudad Autónoma de Buenos Aires.
Echegaray, J. C., Maldonado, S., Pellicioni, M., Ossemani, S., & Maddonni, P. (2023) · Revista americana de medicina respiratoria · doi:10.56538/ramr.cdim9893 · Cited by 2 · see citing works
Obesity is associated with lower 30-day mortality in critically ill patients: A retrospective study of over 5400 patients
Genton, L., Maluf, V. A. B., Herrmann, F. R., Prado, C. M., de Watteville, A., Dupertuis, Y. M., Collet, T., Platon, A., & Heidegger, C. P. (2025) · Clinical Nutrition ESPEN · doi:10.1016/j.clnesp.2025.06.046 · Cited by 2 · see citing works
Gas-exchange deficit and systemic hypoperfusion in COVID-19 and non-COVID-19 young adult patients with pneumonia
Franchini, S., Mette, F., Landoni, G., Setti, E., Ferrante, L., Calcaterra, B., Pagliula, G., Barbieri, A., FONTANI, D., Borio, G., et al. (2022) · Panminerva Medica · doi:10.23736/s0031-0808.22.04562-1 · Cited by 2 · see citing works
The impact of nontuberculous mycobacterial lung disease in critically ill patients: Significance for survival and ventilator use
Chien, Y., Chang, C.-H., Huang, C., Chen, Y., Liu, C.-J., Chen, C., Wang, P.-H., Shu, C., Kuo, L.-C., Wang, J., et al. (2024) · Journal of Microbiology Immunology and Infection · doi:10.1016/j.jmii.2023.12.009 · Cited by 2 · see citing works
Long term outcomes in the critically ill: Investigating the association between frailty and survival. LONG a SWARM regional observational study
Garland, A., Womersley, J., & Clark, T. (2024) · Journal of the Intensive Care Society · doi:10.1177/17511437231199897 · Cited by 1 · see citing works
Association between nutritional status, daily nutrition delivery and clinical outcomes of critically ill adult patients admitted to the intensive care unit: a protocol for Isfahan multicentre prospective observational cohort ICU study (the Isfahan-ICU study)
Mashhadi, N. S., Schlesinger, S., Feizi, A., Rajaei, S., & Jounaghani, M. N. (2025) · BMJ Open · doi:10.1136/bmjopen-2024-090825 · Cited by 1 · see citing works
Do Mechanically Ventilated COVID-19 Patients Present a Higher Case-Fatality Rate Compared With Other Infectious Respiratory Pandemics? A Systematic Review and Meta-Analysis
Blumenfeld, O., Fein, S., Miller, A., Hershkovitz, Y., Caspi, I., Niv, Y., & Keinan‐Boker, L. (2022) · Infectious Diseases in Clinical Practice · doi:10.1097/ipc.0000000000001134 · Cited by 1 · see citing works
Adiposity and mortality among intensive care patients with COVID-19 and non-COVID-19 respiratory conditions: a cross-context comparison study in the UK
Bell, J. A., Carslake, D., Hughes, A., Tilling, K. M., Dodd, J. W., Doidge, J., Harrison, D. A., Rowan, K., & Smith, G. D. (2024) · BMC Medicine · doi:10.1186/s12916-024-03598-3 · Cited by 1 · see citing works
Self-citation
Prehospital critical care drug-therapy and 30-day mortality in patients with acute respiratory disease
Palomo, J. J., Martín‐Conty, J. L., López, B. P., Picón, C. R., López‐Izquierdo, R., Vegas, C. D. P., Castro, P. Á. D. S., García, A. S., & Rodríguez, F. M. (2024) · World Journal of Emergency Medicine · doi:10.5847/wjem.j.1920-8642.2025.008 · Cited by 1 · see citing works
Beta-Blocker Treatment in Ventilated COVID-19 patients – A Cox Regression with Time Dependent Covariate AnalysisPreprint
Mistry, D., Hossain, M. A., Sun, J., Veenith, T., Lall, R., Bion, J., & Whitehouse, T. (2021) · Research Square · doi:10.21203/rs.3.rs-921813/v1 · Cited by 1 · see citing works
Risk Factors for 28-Day in-Hospital Mortality in Mechanically Ventilated Patients with COVID-19: An International Cohort StudyPreprint
Bassi, G. L., Suen, J. Y., White, N. M., Dalton, H. J., Fanning, J. P., Corley, A., Shrapnel, S., Hinton, S. R., Forsyth, S. J., Parsons, R., et al. (2021) · Research Square · doi:10.21203/rs.3.rs-751869/v1 · Cited by 1 · see citing works
A Tale of a Two Waves Epidemic: Characteristics and Mortality Risk Factors for COVID-19 ICU Patients in the French West IndiesPreprint
Pommier, J., Martino, F., Kevin Bleakley, A., Flurin, L., Roy, F. V., Carlès, M., Valette, M., & Camous, L. (2021) · Research Square · doi:10.21203/rs.3.rs-200243/v1
Development and Validation of a Prediction Model for 28-Day in-Hospital Mortality in Critically Ill Patients with COVID-19Preprint
Ferrando-Vivas, P., Gould, D. W., Doidge, J., Thomas, K., Mouncey, P. R., Shankar‐Hari, M., Young, D., Rowan, K., & Harrison, D. A. (2021) · Preprints.org · doi:10.20944/preprints202102.0059.v1
Self-citation
The Lactate/Albumin Ratio As A Prognostic Factor For Short Time Mortality In Critically Ill COVID-19 PatientsPreprint
Gök, A., Kasapoğlu, U. S., Delen, L. A., Özmen, F., & Banazılı, S. (2021) · Research Square · doi:10.21203/rs.3.rs-478051/v1
Ethnicity and outcomes in COVID-19 in the United Kingdom: a systematic review and meta-analysisPreprint
Siddiq, S., Ahmed, S., & Akram, I. (2021) · medRxiv · doi:10.1101/2021.11.07.21266027
Analysis of Increasing D-Dimer, Decreasing P/F Ratio and Rox Index As Predictors Of HFNC Therapy Failure In Covid-19 Patients
Arsan, A. E. H., Kusuma, E., Abbas, K. A., Hamzah, H., & Christrijogo (2021) · International Journal of Research Publications · doi:10.47119/ijrp100921120222740
Hohes Alter korreliert mit erhöhter Mortalität bei schwerer COVID-19-Erkrankung
(2021) · Journal Club AINS · doi:10.1055/a-1470-1472
The Effect of Prone and Awake Prone Position Duration on the Outcomes of COVID-19 Patients: A Systematic Review and Meta-AnalysisPreprint
Yao, Y., Tian, Y., & Wang, S. (2022) · SSRN Electronic Journal · doi:10.2139/ssrn.4150492
Impact of vaccination on COVID-19-associated admissions to critical care in England: a population cohort study of linked dataPreprint
Harrison, D. A., Watkinson, P., Doidge, J., Shankar‐Hari, M., Mouncey, P. R., Patone, M., Coupland, C. A. C., Hippisley‐Cox, J., & Rowan, K. (2022) · medRxiv · doi:10.1101/2022.10.03.22280649
Self-citation
Adiposity and Mortality among Patients Severely Ill with COVID-19 and non-COVID-19 Respiratory Conditions: A Cross-Context Comparison Study in the UKPreprint
Bell, J. A., Carslake, D., Hughes, A., Tilling, K. M., Dodd, J. W., Doidge, J., Harrison, D. A., Rowan, K., & Smith, G. D. (2022) · medRxiv · doi:10.1101/2022.12.22.22283842
Self-citation
Risk Factors Associated with 28-Day Mortality of COVID-19 Patients at RSUP Dr. M. Djamil Padang
Arda, L. A., Khairsyaf, O., Russilawati, R., & Handayani, T. (2023) · Jurnal Respirologi Indonesia · doi:10.36497/jri.v43i1.238
Long-term outcomes of COVID-19 infection in patients with solid tumors
Ünsal, O., Yazıcı, O., Özkan, Ö. F., Savaş, G., Özdemir, N., Üner, A., Günel, N., & Özet, A. (2023) · The European Research Journal · doi:10.18621/eurj.1251443
Assessment of longitudinal changes in immune responses in critically ill adults with COVID-19Preprint
Rynne, J., Fish, M., Jennings, A., Smith, P., Mosavie, M., Lam, C., Kelly, S., Sanderson, B., Arbane, G., Lucchese, G., et al. (2024) · Research Square · doi:10.21203/rs.3.rs-3758193/v1
Self-citation
A prediction model for prognosis of nephrotic syndrome with tuberculosis in intensive care unit patients: a nomogram based on the MIMIC-IV v2.2 database
Du, S., Su, N., Yu, Z., Li, J., Jiang, Y., Zeng, L., & Hu, J. (2024) · Frontiers in Medicine · doi:10.3389/fmed.2024.1413541
The role of socio-economic determinants in SARS-CoV-2 health outcomes: systematic review of population-based studies.Preprint
Ghattas, J., Makovski, T. T., Monnier-Besnard, S., Cavillot, L., Ambrožová, M., Budikova, B., Feteira-Santos, R., Bezzegh, P., Bollmann, F. D. P., Cottam, J., et al. (2024) · medRxiv · doi:10.1101/2024.06.18.24309062
Biomarkers of invasive mechanical ventilation in obesity and metabolic syndrome in patients with COVID-19
Perpiñán, C., Bertran, L., & Auguet, T. (2024) · Elsevier eBooks · doi:10.1016/b978-0-323-95646-8.00044-5
Correlation between worsening pneumonitis and right ventricular systolic function in critically ill patients with COVID-19
Lashin, H., Aron, J., Lee, S. W. H., & Fletcher, N. (2024) · Echo Research and Practice · doi:10.1186/s44156-024-00054-z
Additional file 21 of Adiposity and mortality among intensive care patients with COVID-19 and non-COVID-19 respiratory conditions: a cross-context comparison study in the UK
Bell, J. A., Carslake, D., Hughes, A., Tilling, K., Dodd, J. W., Doidge, J., Harrison, D. A., Rowan, K. M., & Smith, G. D. (2024) · Figshare · doi:10.6084/m9.figshare.27019428
Self-citation
Additional file 29 of Adiposity and mortality among intensive care patients with COVID-19 and non-COVID-19 respiratory conditions: a cross-context comparison study in the UK
Bell, J. A., Carslake, D., Hughes, A., Tilling, K., Dodd, J. W., Doidge, J., Harrison, D. A., Rowan, K. M., & Smith, G. D. (2024) · Figshare · doi:10.6084/m9.figshare.27019452
Self-citation
Additional file 7 of Adiposity and mortality among intensive care patients with COVID-19 and non-COVID-19 respiratory conditions: a cross-context comparison study in the UK
Bell, J. A., Carslake, D., Hughes, A., Tilling, K., Dodd, J. W., Doidge, J., Harrison, D. A., Rowan, K. M., & Smith, G. D. (2024) · Figshare · doi:10.6084/m9.figshare.27019386
Self-citation
Additional file 17 of Adiposity and mortality among intensive care patients with COVID-19 and non-COVID-19 respiratory conditions: a cross-context comparison study in the UK
Bell, J. A., Carslake, D., Hughes, A., Tilling, K., Dodd, J. W., Doidge, J., Harrison, D. A., Rowan, K. M., & Smith, G. D. (2024) · Figshare · doi:10.6084/m9.figshare.27019416
Self-citation
Additional file 6 of Adiposity and mortality among intensive care patients with COVID-19 and non-COVID-19 respiratory conditions: a cross-context comparison study in the UK
Bell, J. A., Carslake, D., Hughes, A., Tilling, K., Dodd, J. W., Doidge, J., Harrison, D. A., Rowan, K. M., & Smith, G. D. (2024) · Figshare · doi:10.6084/m9.figshare.27019383
Self-citation
Additional file 27 of Adiposity and mortality among intensive care patients with COVID-19 and non-COVID-19 respiratory conditions: a cross-context comparison study in the UK
Bell, J. A., Carslake, D., Hughes, A., Tilling, K., Dodd, J. W., Doidge, J., Harrison, D. A., Rowan, K. M., & Smith, G. D. (2024) · Figshare · doi:10.6084/m9.figshare.27019446
Self-citation
Additional file 13 of Adiposity and mortality among intensive care patients with COVID-19 and non-COVID-19 respiratory conditions: a cross-context comparison study in the UK
Bell, J. A., Carslake, D., Hughes, A., Tilling, K., Dodd, J. W., Doidge, J., Harrison, D. A., Rowan, K. M., & Smith, G. D. (2024) · Figshare · doi:10.6084/m9.figshare.27019404
Self-citation
Additional file 3 of Adiposity and mortality among intensive care patients with COVID-19 and non-COVID-19 respiratory conditions: a cross-context comparison study in the UK
Bell, J. A., Carslake, D., Hughes, A., Tilling, K., Dodd, J. W., Doidge, J., Harrison, D. A., Rowan, K. M., & Smith, G. D. (2024) · Figshare · doi:10.6084/m9.figshare.27019371
Self-citation
Additional file 1 of Application of information from external data to correct for collider bias in a Covid-19 hospitalised cohort
Learoyd, A., Nicholas, J. M., Hart, N., & Douiri, A. (2024) · Figshare · doi:10.6084/m9.figshare.26749844
Additional file 2 of Adiposity and mortality among intensive care patients with COVID-19 and non-COVID-19 respiratory conditions: a cross-context comparison study in the UK
Bell, J. A., Carslake, D., Hughes, A., Tilling, K., Dodd, J. W., Doidge, J., Harrison, D. A., Rowan, K. M., & Smith, G. D. (2024) · Figshare · doi:10.6084/m9.figshare.27019368
Self-citation
Additional file 15 of Adiposity and mortality among intensive care patients with COVID-19 and non-COVID-19 respiratory conditions: a cross-context comparison study in the UK
Bell, J. A., Carslake, D., Hughes, A., Tilling, K., Dodd, J. W., Doidge, J., Harrison, D. A., Rowan, K. M., & Smith, G. D. (2024) · Figshare · doi:10.6084/m9.figshare.27019410
Self-citation
Additional file 2 of Epidemiology and outcomes of early-onset AKI in COVID-19-related ARDS in comparison with non-COVID-19-related ARDS: insights from two prospective global cohort studies
McNicholas, B. A., Rezoagli, E., Simpkin, A. J., Khanna, S., Suen, J. Y., Yeung, P., Brodie, D., Bassi, G. L., Pham, T. O., Bellani, G., et al. (2023) · Figshare · doi:10.6084/m9.figshare.22610959
Additional file 22 of Adiposity and mortality among intensive care patients with COVID-19 and non-COVID-19 respiratory conditions: a cross-context comparison study in the UK
Bell, J. A., Carslake, D., Hughes, A., Tilling, K., Dodd, J. W., Doidge, J., Harrison, D. A., Rowan, K. M., & Smith, G. D. (2024) · Figshare · doi:10.6084/m9.figshare.27019431
Self-citation
Additional file 14 of Adiposity and mortality among intensive care patients with COVID-19 and non-COVID-19 respiratory conditions: a cross-context comparison study in the UK
Bell, J. A., Carslake, D., Hughes, A., Tilling, K., Dodd, J. W., Doidge, J., Harrison, D. A., Rowan, K. M., & Smith, G. D. (2024) · Figshare · doi:10.6084/m9.figshare.27019407
Self-citation
Additional file 20 of Adiposity and mortality among intensive care patients with COVID-19 and non-COVID-19 respiratory conditions: a cross-context comparison study in the UK
Bell, J. A., Carslake, D., Hughes, A., Tilling, K., Dodd, J. W., Doidge, J., Harrison, D. A., Rowan, K. M., & Smith, G. D. (2024) · Figshare · doi:10.6084/m9.figshare.27019425
Self-citation
Additional file 26 of Adiposity and mortality among intensive care patients with COVID-19 and non-COVID-19 respiratory conditions: a cross-context comparison study in the UK
Bell, J. A., Carslake, D., Hughes, A., Tilling, K., Dodd, J. W., Doidge, J., Harrison, D. A., Rowan, K. M., & Smith, G. D. (2024) · Figshare · doi:10.6084/m9.figshare.27019443
Self-citation
Additional file 23 of Adiposity and mortality among intensive care patients with COVID-19 and non-COVID-19 respiratory conditions: a cross-context comparison study in the UK
Bell, J. A., Carslake, D., Hughes, A., Tilling, K., Dodd, J. W., Doidge, J., Harrison, D. A., Rowan, K. M., & Smith, G. D. (2024) · Figshare · doi:10.6084/m9.figshare.27019434
Self-citation
Additional file 18 of Adiposity and mortality among intensive care patients with COVID-19 and non-COVID-19 respiratory conditions: a cross-context comparison study in the UK
Bell, J. A., Carslake, D., Hughes, A., Tilling, K., Dodd, J. W., Doidge, J., Harrison, D. A., Rowan, K. M., & Smith, G. D. (2024) · Figshare · doi:10.6084/m9.figshare.27019419
Self-citation
Additional file 1 of Epidemiology and outcomes of early-onset AKI in COVID-19-related ARDS in comparison with non-COVID-19-related ARDS: insights from two prospective global cohort studies
McNicholas, B. A., Rezoagli, E., Simpkin, A. J., Khanna, S., Suen, J. Y., Yeung, P., Brodie, D., Bassi, G. L., Pham, T. O., Bellani, G., et al. (2023) · Figshare · doi:10.6084/m9.figshare.22610956
Additional file 8 of Adiposity and mortality among intensive care patients with COVID-19 and non-COVID-19 respiratory conditions: a cross-context comparison study in the UK
Bell, J. A., Carslake, D., Hughes, A., Tilling, K., Dodd, J. W., Doidge, J., Harrison, D. A., Rowan, K. M., & Smith, G. D. (2024) · Figshare · doi:10.6084/m9.figshare.27019389
Self-citation
Additional file 16 of Adiposity and mortality among intensive care patients with COVID-19 and non-COVID-19 respiratory conditions: a cross-context comparison study in the UK
Bell, J. A., Carslake, D., Hughes, A., Tilling, K., Dodd, J. W., Doidge, J., Harrison, D. A., Rowan, K. M., & Smith, G. D. (2024) · Figshare · doi:10.6084/m9.figshare.27019413
Self-citation

CAPRL Scoring System for Prediction of 30-day Mortality in 949 Patients with Coronavirus Disease 2019 in Wuhan, China: A Retrospective, Observational Study
Chen, H., Yan, W., Chen, G., Zhang, X., Zeng, Z., Wang, X., Qi, W.-P., Wang, M., Li, W., Ma, K., et al. (2021) · Infectious Diseases & Immunity · doi:10.1097/id9.0000000000000001 · Cited by 2 · see citing works
Prognostic factors for COVID-19 patients
Önal, U., Güçlü, Ö. A., Akalın, H., Öztürk, N. A. A., Semet, C., Demirdöğen, E., Dilektaşlı, A. G., Sağlık, İ., Kazak, E., Özkaya, G., et al. (2022) · The Journal of Infection in Developing Countries · doi:10.3855/jidc.15845 · Cited by 5 · see citing works
Improving survival of critical care patients with coronavirus disease 2019 in England: a national cohort study, March to June 2020
Dennis, J. M., McGovern, A. P., Vollmer, S. J., & Mateen, B. A. (2021) · Critical Care Medicine · doi:10.1097/ccm.0000000000004747 · Cited by 214 · see citing works
Factors associated with death in critically ill patients with coronavirus disease 2019 in the US
Gupta, S., Hayek, S. S., Wang, W., Chan, L., Mathews, K. S., Melamed, M. L., Brenner, S. K., Leonberg-Yoo, A., Schenck, E. J., Radbel, J., et al. (2020) · JAMA Internal Medicine · doi:10.1001/jamainternmed.2020.3596 · Cited by 957 · see citing works
Critically Ill Patients with Coronavirus Disease 2019 in a Designated ICU: Clinical Features and Predictors for Mortality
Zh, W., Shu, C., Ran, X., Ch, X., & Zhang, L. (2020) · DOAJ (DOAJ: Directory of Open Access Journals) · Cited by 6 · see citing works

Authors: Ferrando-Vivas, P., Doidge, J., Thomas, K., Gould, D. W., Mouncey, P., Shankar-Hari, M., Young, J. D., Rowan, K. M., & Harrison, D. A.
Affiliations: Intensive Care National Audit & Research Centre (GB)
Intensive Care, Unit, Guy’s and St Thomas’ NHS Foundation Trust, London, United Kingdom.
Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom.
Intensive Care National Audit & Research Centre (ICNARC), London, United Kingdom.
ORCID: Ferrando-Vivas, Paloma
Doidge, James
Thomas, Karen
Gould, Doug W.
Mouncey, Paul
Harrison, David A.
Venue: Critical Care Medicine
Publisher: Ovid Technologies (Wolters Kluwer Health)
Published: 2020-10-28
Volume: 49
Issue: 1
Pages: 102-111
ISSN: 0090-3493 (ISSN-L)
DOI: 10.1097/ccm.0000000000004740
PMC: PMC7737692
OpenAlex: W3097123511
Cited by: 113
References: 34
Citations by year: 2026: 3 · 2025: 3 · 2024: 43 · 2023: 15 · 2022: 26 · 2021: 21 · 2020: 2
FWCI: 2.10
Type: journal article
Language: en
Open access: green
www.ncbi.nlm.nih.gov
Locations: Critical Care Medicine (publishedVersion)
PubMed Central (publishedVersion)
PubMed (publishedVersion)
Topics: Health Sciences › Medicine › Infectious Diseases › COVID-19 Clinical Research Studies
Health Sciences › Medicine › Epidemiology › Sepsis Diagnosis and Treatment
Health Sciences › Medicine › Pulmonary and Respiratory Medicine › Respiratory Support and Mechanisms
Keywords: COVID-19 pandemic, 30-day mortality, prognostic factors, critically ill patients, intensive care, mortality prediction model, body mass index, immunocompromised patients, lactate, PaO2/FiO2 ratio, mechanical ventilation, blood pressure, platelet count, socioeconomic deprivation, ethnicity
MeSH terms: COVID-19, Adult, England, Female, Humans, Male, Middle Aged, Northern Ireland, Prognosis, Respiration, Artificial, Severity of Illness Index, Wales, Cohort Studies, Critical Illness, Hospital Mortality

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.

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

Prognostic Factors for 30-Day Mortality in Critically Ill Patients With Coronavirus Disease 2019: An Observational Cohort Study

Abstract

Integrity signals

Claims the paper makes

Claims other papers make about this one

Cites

Cited by

Related

Record

About these checks