ArticleNorthern clinics of Istanbul2022
Does the Charlson comorbidity index help predict the risk of death in COVID-19 patients?
Article in Northern clinics of Istanbul, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers, 1 of them a synthesis 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
21 citing papers in PubMed, 1 synthesis or guideline pooled it, 32 citations in OpenAlex.
- Prognostic models in COVID-19 infection that predict severity: a systematic review.European journal of epidemiology · 2023Pooled it
- Prognostic Value of Charlson Comorbidity Index in Patients with COVID-19.Tropical medicine and infectious disease · 2026Article
- Effect of fasting duration on mortality after COVID-19 infection: A retrospective analysis at a single institution.Infectious medicine · 2025Article
- Frailty and comorbidity in COVID-19 patients with and without ICU admission restrictions: a retrospective observational study.Journal of anesthesia, analgesia and critical care · 2025Article
- Unlocking efficiency in real-world collaborative studies: a multi-site international study with one-shot lossless GLMM algorithm.NPJ digital medicine · 2025Article
- Predictors of Unfavorable Outcomes in COVID-19-Related Sepsis: A Prospective Cohort Study.Viruses · 2025Article
- Comparison of Clinical Characteristics and Mortality Outcome in Critical COVID-19 Patients Infected with Alpha and Omicron Variants.Infection and drug resistance · 2025Article
- Multimorbidity and COVID-19 Outcomes in the Emergency Department: Is the Association Mediated by the Severity of the Condition at Admission?Journal of clinical medicine · 2024Article
- Personalized Assessment of Mortality Risk and Hospital Stay Duration in Hospitalized Patients with COVID-19 Treated with Remdesivir: A Machine Learning Approach.Journal of clinical medicine · 2024Article
- Differences in Covid-19 mortality among persons 70 years and older in an integrated care setting in region Stockholm: a multi-level analysis between March 2020-February 2021.BMC public health · 2024Article
- Article
- A Multi-Layered GRU Model for COVID-19 Patient Representation and Phenotyping from Large-Scale EHR Data.ACM-BCB ... ... : the ... ACM Conference on Bioinformatics, Computational Biology and Biomedicine. ACM Conference on Bioinformatics, Computational Biology and Biomedicine · 2023Article
- Serum butyrylcholinesterase as a marker of COVID-19 mortality: Results of the monocentric prospective observational study.Chemico-biological interactions · 2023Observational
- Fungal Infections Identified with Multiplex PCR in Severe COVID-19 Patients during Six Pandemic Waves.Medicina (Kaunas, Lithuania) · 2023Article
- A retrospective cohort study of incidence and risk factors for severe SARS-CoV-2 breakthrough infection among fully vaccinated people.Scientific reports · 2023Article
- Investigating the role of obstructive pulmonary diseases and eosinophil count at admission on all-cause mortality in SARS-CoV-2 patients : A single center registry-based retrospective cohort study.Wiener klinische Wochenschrift · 2023Article
- Evaluation of risk scores as predictors of mortality and hospital length of stay for older COVID-19 patients.Aging medicine (Milton (N.S.W)) · 2023Article
- Article
- Cytokine Levels and Severity of Illness Scoring Systems to Predict Mortality in COVID-19 Infection.Healthcare (Basel, Switzerland) · 2023Article
- Risk Factors Associated with Mortality in COVID-19 Hospitalized Patients: Data from the Middle East.International journal of clinical practice · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Objective: Comorbidities are diseases that coexist with a disease of interest or an index disease, which can directly affect the prognosis of the disease of interest or indirectly affect the choice of treatment. The Charlson comorbidity index (CCI) is the most widely used comorbidity index. In this study, it was aimed to examine the predictive role of the CCI score on the mortality of patients with COVID-19. Methods: We have retrospectively analyzed COVID-19 patients whose diagnosis was confirmed by PCR and who were hospitalized in two centers between April 2020 and December 2020. The severity of comorbidity of the patients was categorized into five groups according to the CCI score: CCI score 0, CCI score 1-2, CCI score 3-4, CCI score 5-6, and CCI score ≥7. Factors affecting mortality and differences between groups classified by CCI were determined by logistic regression analysis and one-way analysis of variance. Results: A total of 1,559 COVID-19 patients were included in the study and 70 (4.49%) patients had deceased. Half of the study population (n=793, 50.9%) had different comorbidities. The CCI score was 3.8±2.7 in deceased patients and 1.3±1.9 in surviving individuals. There was a positive correlation between CCI scores and mortality in COVID-19 patients, with each point increase in the CCI score increasing the risk of death by 2.5%. CCI score of 4 and above predicted mortality with 87.2% sensitivity and 97.9% negative predictive value. Five (0.6%) of 766 patients with CCI scores of 0, 16 (3.6%) of 439 patients with CCI scores of 1-2, 13 (6.9%) of 189 patients with CCI scores of 3-4, and a CCI score of 5, 13 (15.7%) of 83 patients with -6 and 23 (28.0%) of 82 patients with a CCI score of ≥7 died. Conclusion: CCI is a simple, easily applicable, and valid method for classifying comorbidities and estimating COVID-19 mortality. The close relationship between the CCI score and mortality reveals the reality of how important vaccination is, especially in this group of patients. Increasing awareness of potential comorbidities in COVID-19 patients can provide insight into the disease and to improve outcomes by identifying and treating patients earlier and more effectively.
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.