The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.
Letter to the Editor: Low-density lipoprotein is a potential predictor of poor prognosis in patients with coronavirus disease 2019
Open accessAbstract
Background The pandemic of coronavirus disease 2019 (COVID-19) has become a global threat to public health. The lipid pathophysiology in COVID-19 is unknown. Methods In this retrospective longitudinal study, we monitored the serum lipids in 17 surviving and 4 non-surviving COVID-19 cases prior to their viral infections and duration the entire disease courses. Results In surviving cases, the low-density lipoprotein (LDL) levels decreased significantly on admission as compared with the levels before infection; the LDL levels remained constantly low during the disease progression and resumed to the original levels when patients recovered (pre-infection: 3.5 (3.0–4.4); on admission: 2.8 (2.3–3.1), p < 0.01; progression: 2.5 (2.3–3.0); discharge: 3.6 (2.7–4.1); median (IQR), in mmol/L). In non-surviving patients, LDL levels showed an irreversible and continuous decrease until death (1.1 (0.9–1.2), p = 0.02 versus the levels on admission). The ratio changes of LDL levels inversely correlated with ratio changes of high-sensitivity C-reactive protein levels. Logistic regression analysis showed increasing odds of lowered LDL levels associated with disease progression (odds ratio: 4.48, 95% IC: 1.55–12.92, p = 0.006) and in-hospital death (odds ratio: 21.72, 95% IC: 1.40–337.54, p = 0.028). Conclusions LDL levels inversely correlated to disease severities, which could be a predictor for disease progress and poor prognosis.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Pathological findings of COVID-19 associated with acute respiratory distress syndrome
Xu, Z., Shi, L., Wang, Y., Zhang, J., Huang, L., Zhang, C., Liu, S., Zhao, P., Liu, H., Zhu, L., et al. (2020) · The Lancet Respiratory Medicine · doi:10.1016/s2213-2600(20)30076-x · Cited by 8,545
Wan, Y., Shang, J., Graham, R., Baric, R. S., & Li, F. (2020) · Journal of Virology · doi:10.1128/jvi.00127-20 · Cited by 4,341
Cited by
Lipid metabolism in cancer: New perspectives and emerging mechanisms
Broadfield, L. A., Pane, A. A., Talebi, A., Swinnen, J. V., & Fendt, S.-M. (2021) · Developmental Cell · doi:10.1016/j.devcel.2021.04.013 · Cited by 758
de Almeida-Pititto, B., Dualib, P. M., Zajdenverg, L., Dantas, J. R., de Souza, F. D., Rodacki, M., Bertoluci, M. C., & Brazilian Diabetes Society Study Group (SBD) (2020) · Diabetology & Metabolic Syndrome · doi:10.1186/s13098-020-00586-4 · Cited by 391
Hypolipidemia is associated with the severity of COVID-19
Wei, X., Zeng, W., Su, J., Wan, H., Yu, X., Cao, X., Tan, W., & Wang, H. (2020) · Journal of Clinical Lipidology · doi:10.1016/j.jacl.2020.04.008 · Cited by 355
Self-citationCholesterol-induced toxicity: An integrated view of the role of cholesterol in multiple diseases
Song, Y., Liu, J., Zhao, K., Gao, L., & Zhao, J. (2021) · Cell Metabolism · doi:10.1016/j.cmet.2021.09.001 · Cited by 322
Low-density lipoprotein cholesterol levels are associated with poor clinical outcomes in COVID-19
Aparisi, Á., Iglesias-Echeverría, C., Ybarra-Falcón, C., Cusácovich, I., Uribarri, A., García-Gómez, M., Ladrón, R., Fuertes, R., Candela, J., Tobar, J., et al. (2021) · Nutrition, Metabolism and Cardiovascular Diseases · doi:10.1016/j.numecd.2021.06.016 · Cited by 48
Metadata
- Authors
- Fan, J., Wang, H., Ye, G., Cao, X., Xu, X., Tan, W., & Zhang, Y.
- Venue
- Metabolism
- Publisher
- Elsevier BV
- Published
- 2020-06
- Volume
- 107
- Pages
- 154243
- ISSN
- 0026-0495 (ISSN-L)
- OpenAlex
- W3016493664
- Cited by
- 164
- References
- 2
- Type
- journal article
- Language
- en
- Open access
- bronze
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
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Letter to the Editor: Low-density lipoprotein is a potential predictor of poor prognosis in patients with coronavirus disease 2019. https://app.cochat.ai/papers/10.1016/j.metabol.2020.154243
- The paper
- Fan, J., Wang, H., Ye, G., Cao, X., Xu, X., Tan, W., & Zhang, Y. (2020). Letter to the Editor: Low-density lipoprotein is a potential predictor of poor prognosis in patients with coronavirus disease 2019. Metabolism. https://doi.org/10.1016/j.metabol.2020.154243
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.