ArticleInternational journal of clinical practice2021
Performance of the CURB-65, ISARIC-4C and COVID-GRAM scores in terms of severity for COVID-19 patients.
Article in International journal of clinical practice, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 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
18 citing papers in PubMed.
- Predicting 7-day mortality in COVID-19 pneumonia: performance of NEWS2, qSOFA, and CRB-65 and development of the CCP-7 prediction scores.IJID regions · 2025Article
- Article
- Evaluating the predictive performance of PIRO score against six clinical prediction scores for COVID-19 outcomes in the emergency department.Scientific reports · 2025Article
- External Validation of the Predictive Accuracy of Clinical and Immunological Scores in COVID-19 Outcomes in a Retrospective Cohort Study.Biomedicines · 2024Article
- The SpOJournal of clinical medicine · 2024Article
- Evaluating the Utility of Clinical Scores APACHE, CURB, SOFA, and NEWS2 at Admission and 5-Days after Symptom Onset in Predicting Severe COVID-19 in Patients with Diabetes.Journal of personalized medicine · 2024Article
- Predicting mortality risk in hospitalized COVID-19 patients: an early model utilizing clinical symptoms.BMC pulmonary medicine · 2024Article
- The prognostic value of rapid risk scores among patients with community-acquired pneumonia : A retrospective cohort study.Wiener klinische Wochenschrift · 2023Article
- A Transcriptomic Severity Classifier IMX-SEV-3b to Predict Mortality in Intensive Care Unit Patients with COVID-19: A Prospective Observational Pilot Study.Journal of clinical medicine · 2023Article
- Clinical and Laboratory Predictors of Mortality in Severe COVID-19 Pneumonia: A Retrospective Study from India.Thoracic research and practice · 2023Article
- Review
- External Validation of COVID-19 Risk Scores during Three Waves of Pandemic in a German Cohort-A Retrospective Study.Journal of personalized medicine · 2022Article
- The Usefulness of the COVID-GRAM Score in Predicting the Outcomes of Study Population with COVID-19.International journal of environmental research and public health · 2022Article
- Prognostication of COVID-19 patients using ROX index and CURB-65 score - A retrospective observational study.Journal of family medicine and primary care · 2022Article
- Comparison of prognostic scores for inpatients with COVID-19: a retrospective monocentric cohort study.BMJ open respiratory research · 2022Article
- A novel model to predict severe COVID-19 and mortality using an artificial intelligence algorithm to interpret chest radiographs and clinical variables.ERJ open research · 2022Article
- Evaluation and Comparison of the Predictive Value of 4C Mortality Score, NEWS, and CURB-65 in Poor Outcomes in COVID-19 Patients: A Retrospective Study from a Single Center in Romania.Diagnostics (Basel, Switzerland) · 2022Article
- Performance of the CURB-65, ISARIC-4C and COVID-GRAM scores in terms of severity for COVID-19 patients.International journal of clinical practice · 2021Article
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.
Funding
Abstract
backgroundIn the COVID-19 pandemic, difficulties have been experienced in the provision of healthcare services because of excessive patient admissions to hospitals and emergency departments. It has become important to use clear and objective criteria for the early diagnosis of patients with high-risk classification and clinical worsening risk.
objectiveThe aim of this study was to assess the prognostic accuracy of CURB-65, ISARIC-4C and COVID-GRAM scores in patients hospitalised for COVID-19 and to compare the scoring systems in terms of predicting in-hospital mortality and intensive care unit requirement.
methodsThe files of all COVID-19 patients over the age of 18 who were admitted to the emergency department and hospitalised between September 1, 2020 and December 1, 2020 were retrospectively scanned. The area under the receiver operating characteristic curve and Youden J Index were used to compare scoring systems for predicting in-hospital mortality and intensive care requirement.
resultsThere were 481 patients included in this study. The median age of the patients was 67 (52-79). In terms of in-hospital mortality, the AUC of CURB-65, ISARIC-4C and COVID-GRAM were 0.846, 0.784 and 0.701 respectively. In terms of intensive care requirement, the AUC of CURB-65, ISARIC-4C and COVID-GRAM were 0.898, 0.797 and 0.684 respectively. In our study, Youden's J indexes of CURB-65, ISARIC-4C and COVID-GRAM scores were found to be 0.59, 0.27 and 0.01 respectively, for mortality prediction of COVID-19 patients. Whereas Youden's J indexes were found to be 0.63, 0.26 and 0.01 respectively for determining intensive care requirement.
conclusionsAmong the scoring systems assessed, CURB-65 score had better performance in predicting in-hospital mortality and ICU requirement in COVID-19 patients. ISARIC-4C has been found successful in identifying low-risk patients and the use of the ISARIC-4C score with CURB-65 increases the accuracy of risk assessment.
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.