ArticleHeliyon2024
Laboratory biomarkers associated with COVID-19 mortality among inpatients in a Peruvian referral hospital.
Article in Heliyon, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
6 citing papers in PubMed.
- Admission Hyperglycemia as an Early Predictor of Severity and Poor Prognosis in COVID-19: A Retrospective Cohort Study of Hospitalized Adults.Journal of clinical medicine · 2025Article
- Biomarkers for predicting COVID-19 mortality: A study at Sulianti Saroso Infectious Disease Hospital, Indonesia.Narra J · 2025Article
- Association Between Nursing Diagnoses and Mortality in Hospitalized Patients with COVID-19: A Retrospective Cohort Study.Nursing reports (Pavia, Italy) · 2025Article
- Analysis of six consecutive waves of ICU-admitted COVID-19 patients: key findings and insights from a Portuguese population.GeroScience · 2025Article
- Association between SARS-CoV-2 viral load and serum biomarkers with mortality in Mexican patients.Journal of education and health promotion · 2025Article
- Association of Clinical Characteristics, Hematological Indices, and Acute Inflammatory Markers in Hospitalized COVID-19 Patients with Disease Severity and Mortality: A Single-center Retrospective Study.Saudi journal of medicine & medical sciencesArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Aim: To evaluate the biochemical and hematological markers associated with the risk of death due to COVID-19 in a clinical cohort with a severe clinical profile. Methods: A retrospective study was conducted among 215 anonymized inpatient records from the Hospital Nacional Almanzor Aguinaga Asenjo, Peru, between April and June 2020. The association between biomarkers and death due to COVID-19 was assessed using Cox regression, with a multivariable modeling of 1) biochemical and 2) hematological markers. Kaplan-Meier analyses and time-dependent receiver operating characteristic curves were calculated for each associated biomarker (p < 0.05). Results: Data analysis of 215 inpatient records revealed an overall mortality rate of 51.30% (95% CI 44.70-58.50), a mean age of 63.90 ± 14.10 years, and a median oxygen saturation of 88% (interquartile range 82-92%). The best-fitted biochemical model included higher levels of C-reactive protein (CRP), D-dimer, fibrinogen, urea, and lactate dehydrogenase. Similarly, the best-fitted hematological model included higher absolute neutrophil and prothrombin time, and lower absolute platelet counts. The best area under the curve values in both models were found to be CRP and D-dimer values (>0.74) and the absolute neutrophil count (0.63). Conclusions: Some specific biochemical markers outperformed hematological markers. Evaluated hematological counts analyzed in multivariable models proved to be better markers and could be useful to discriminate COVID-19 patients at high risk of death.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.