Observational studyInfectious diseases of poverty2020
Abnormal immunity of non-survivors with COVID-19: predictors for mortality.
Observational study in Infectious diseases of poverty, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 63 papers, 7 of them syntheses that pooled it.
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
63 citing papers in PubMed, 7 syntheses or guidelines pooled it, 113 citations in OpenAlex.
- Identification of Parameters Representative of Immune Dysfunction in Patients with Severe and Fatal COVID-19 Infection: a Systematic Review and Meta-analysis.Clinical reviews in allergy & immunology · 2023Pooled it
- Pooled it
- The effect of cardiovascular disease and acute cardiac injury on fatal COVID-19: a meta-analysis.The American journal of emergency medicine · 2021Pooled it
- Coronary heart disease and COVID-19: A meta-analysis.Medicina clinica · 2021Pooled it
- Nervous system diseases are associated with the severity and mortality of patients with COVID-19: a systematic review and meta-analysis.Epidemiology and infection · 2021Pooled it
- Chronic Diseases as a Predictor for Severity and Mortality of COVID-19: A Systematic Review With Cumulative Meta-Analysis.Frontiers in medicine · 2021Pooled it
- Serum Complement C3 and C4 and COVID-19 Severity and Mortality: A Systematic Review and Meta-Analysis With Meta-Regression.Frontiers in immunologyPooled it
- Complement Hyperactivation Is Mediated by Alternative and Lectin Pathways During Early Phase of Severe Vaccination-Omicron BA.5 Infection.Journal of medical virology · 2026Article
- The neutrophil-to-lymphocyte ratio as a marker of immunosenescence and COVID-19 outcomes in the elderly: A narrative review.Physiological reports · 2026Review
- Observational
- Decoding Immuno-Competence: A Novel Analysis of Complete Blood Cell Count Data in COVID-19 Outcomes.Biomedicines · 2024Article
- Review
- Early decrease in blood lymphocyte count is associated with poor prognosis in COVID-19 patients: a retrospective cohort study.BMC pulmonary medicine · 2023Article
- Complement and COVID-19: Three years on, what we know, what we don't know, and what we ought to know.Immunobiology · 2023Review
- Circulating Soluble Urokinase Plasminogen Activator Receptor as a Predictive Indicator for COVID-19-Associated Acute Kidney Injury and Mortality: Clinical and Bioinformatics Analysis.International journal of molecular sciences · 2023Article
- Evaluation of Inflammation-Based Prognostic Risk Scores in Predicting in-Hospital Mortality Risk in COVID-19 Patients: A Cross-Sectional Retrospective Study.Infectious diseases & clinical microbiology · 2023Article
- Proteomics Investigation of Diverse Serological Patterns in COVID-19.Molecular & cellular proteomics : MCP · 2023Article
- High-dimensional comparison of monocytes and T cells in post-COVID and idiopathic pulmonary fibrosis.Frontiers in immunology · 2023Article
- Mitochondrial oxidative stress, mitochondrial ROS storms in long COVID pathogenesis.Frontiers in immunology · 2023Review
- Laboratory predictors for COVID-19 Intensive Care Unit admissions in Trinidad and Tobago.Dialogues in health · 2022Article
3 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
10 authors at 1 institution in 1 country.
Funding
Abstract
backgroundThe number of coronavirus disease 2019 (COVID-19) cases has rapidly increased all over the world. Specific information about immunity in non-survivors with COVID-19 is scarce. This study aimed to analyse the clinical characteristics and abnormal immunity of the confirmed COVID-19 non-survivors.
methodsIn this single-centered, retrospective, observational study, we enrolled 125 patients with COVID-19 who were died between January 13 and March 4, 2020 in Renmin Hospital of Wuhan University. A total of 414 randomly recruited patients with confirmed COVID-19 who were discharged from the same hospital during the same period served as control. The demographic, clinical characteristics and laboratory findings at admission, and treatment used in these patients were collected. The immunity-related risk factors associated with in-hospital death were tested by logistic regression models and Receiver Operating Characteristic (ROC) curve.
resultsNon-survivors (70 years, IQR: 61.5-80) were significantly older than survivors (54 years, IQR: 37-65) (P < 0.001). 56.8% of non-survivors was male. Nearly half of the patients (44.9%) had chronic medical illness. In non-survivors, hypertension (49.6%) was the most common comorbidity, followed by diabetes (20.0%) and coronary heart disease (16.0%). The common signs and symptoms at admission of non-survivors were fever (88%), followed by cough (64.8%), dyspnea (62.4%), fatigue (62.4%) and chest tightness (58.4%). Compared with survivors, non-survivors had higher white blood cell (WBC) count (7.85 vs 5.07 × 10
conclusionsAbnormal cellular immunity and humoral immunity were key features of non-survivors with COVID-19. Neutrophilia, lymphocytopenia, low CD4
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.