External validation of 4c ISARIC mortality score in critically ill COVID-19 patients from Saudi Arabia

4C mortality score and COVID-19 mortality risk score: an analysis in four different age groups of an Italian population

To evaluate the prognostic stratification ability of 4C Mortality Score and COVID-19 Mortality Risk Score in different age groups. Retrospective study, including all patients, presented to the Emergency Department of the University Hospital Careggi, between February, 2020 and May, 2021, and admitted for SARS-CoV2. Patients were divided into four subgroups based on the quartiles of age distribution: patients < 57 years (G1, n = 546), 57-71 years (G2, n = 508), 72-81 years (G3, n = 552), and > 82 years (G4, n = 578). We calculated the 4C Mortality Score and COVID-19 Mortality Risk Score. The end-point was in-hospital mortality. In the whole population (age 68 ± 16 years), the mortality rate was 19% (n = 424), and increased with increasing age (G1: 4%, G2: 11%, G3: 22%, and G4: 39%, p < 0.001). Both scores were higher among non-survivors than survivors in all subgroups (4C-MS, G1: 6 [3-7] vs 3 [2-5]; G2: 10 [7-11] vs 7 [5-8]; G3: 11 [10-14] vs 10 [8-11]; G4: 13 [12-15] vs 11 [10-13], all p < 0.001; COVID-19 MRS, G1: 8 [7-9] vs 9 [9-11], G2: 10 [8-11] vs 11 [10-12]; G3: 11 [10-12] vs 12 [11-13]; G4: 11 [10-13] vs 13 [12-14], all p < 0.01). The ability of both scores to identify patients at higher risk of in-hospital mortality, was similar in different age groups (4C-MS: G1 0.77, G2 0.76, G3 0.68, G4 0.72; COVID-19 MRS: G1 0.67, G2 0.69, G3 0.69, G4 0.72, all p for comparisons between subgroups = NS). Both scores confirmed their good performance in predicting in-hospital mortality in all age groups, despite their different mortality rate.

External validation of the ISARIC 4C Mortality Score to predict in-hospital mortality among patients with COVID-19 in a Canadian intensive care unit: a single-centre historical cohort study

PURPOSE

With uncertain prognostic utility of existing predictive scoring systems for COVID-19-related illness, the International Severe Acute Respiratory and Emerging Infection Consortium (ISARIC) 4C Mortality Score was developed by the International Severe Acute Respiratory and Emerging Infection Consortium as a COVID-19 mortality prediction tool. We sought to externally validate this score among critically ill patients admitted to an intensive care unit (ICU) with COVID-19 and compare its discrimination characteristics to that of the Acute Physiology and Chronic Health Evaluation (APACHE) II and Sequential Organ Failure Assessment (SOFA) scores.

METHODS

We enrolled all consecutive patients admitted with COVID-19-associated respiratory failure between 5 March 2020 and 5 March 2022 to our university-affiliated and intensivist-staffed ICU (Jewish General Hospital, Montreal, QC, Canada). After data abstraction, our primary outcome of in-hospital mortality was evaluated with an objective of determining the discriminative properties of the ISARIC 4C Mortality Score, using the area under the curve of a logistic regression model.

RESULTS

A total of 429 patients were included, 102 (23.8%) of whom died in hospital. The receiver operator curve of the ISARIC 4C Mortality Score had an area under the curve of 0.762 (95% confidence interval [CI], 0.717 to 0.811), whereas those of the SOFA and APACHE II scores were 0.705 (95% CI, 0.648 to 0.761) and 0.722 (95% CI, 0.667 to 0.777), respectively.

CONCLUSIONS

The ISARIC 4C Mortality Score is a tool that had a good predictive performance for in-hospital mortality in a cohort of patients with COVID-19 admitted to an ICU for respiratory failure. Our results suggest a good external validity of the 4C score when applied to a more severely ill population.

Performance of CURB-65 and ISARIC 4C mortality scores for hospitalized patients with confirmed COVID-19 infection in Saudi Arabia

Background

The COVID-19 pandemic continues with new waves that could persist with the arrival of new SARS-CoV-2 variants. Therefore, the availability of validated and effective triage tools is the cornerstone for proper clinical management. Thus, this study aimed to assess the validity of the ISARIC-4C score as a triage tool for hospitalized COVID-19 patients in Saudi Arabia and to compare its performance with the CURB-65 score.

Material and methods

This retrospective observational cohort study was conducted between March 2020 and May 2021 at KFHU, Saudi Arabia, using 542 confirmed COVID-19 patient data on the variables relevant to the application of the ISARIC-4C mortality score and the CURB-65 score. Chi-square and t-tests were employed to study the significance of the CURB-65 score and the ISARIC-4C score variables considering the ICU requirements and the mortality of COVID-19 hospitalized patients. In addition, logistic regression was used to predict the variables related to COVID-19 mortality. In addition, the diagnostic accuracy of both scores was validated by calculating sensitivities, specificities, positive predictive value, negative predictive value, and Youden's J indices (YJI).

Results

ROC analysis showed an AUC value of 0.834 [95% CI; 0.800-0.865]) for the CURB-65 score and 0.809 [95% CI; 0.773-0.841]) for the ISARIC-4C score. The sensitivity for CURB-65 and ISARIC-4C is 75% and 85.71%, respectively, while the specificity was 82.31% and 62.66%, respectively. The difference between AUCs was 0.025 (95% [CI; -0.0203-0.0704], p = 0.2795).

Conclusion

Study results support external validation of the ISARIC-4C score in predicting the mortality risk of hospitalized COVID-19 patients in Saudi Arabia. In addition, the CURB-65 and ISARIC-4C scores showed comparable performance with good consistent discrimination and are suitable for clinical utility as triage tools for hospitalized COVID-19 patients.

Quality Performance Evaluation of the Largest COVID-19-Designated Intensive Care Unit in the Western Region of Saudi Arabia

Introduction Mortality is generally higher among patients with coronavirus disease 2019 (COVID-19) than non-COVID-19 patients, especially critically ill patients. The Acute Physiology and Chronic Health Evaluation IV (APACHE IV) predicts mortality rate (MR); however, it was not designed for COVID-19 patients. Multiple indicators have been utilized in healthcare to measure the performance of intensive care unit (ICU) departments, including length of stay (LOS) and MR. The 4C mortality score was recently developed using the ISARIC WHO clinical characterization protocol. This study aims to evaluate intensive care unit performance using LOS, MR, and 4C mortality scores at East Arafat Hospital (EAH), Makkah region, which is considered the largest COVID-19-designated intensive care unit in the Western region of Saudi Arabia. Materials and methods A retrospective observational cohort study was conducted on data from patients' records during the COVID-19 pandemic, from March 1, 2020, to October 31, 2021, at EAH, Makkah Health Affairs. Data to calculate LOS, MR, and 4C mortality scores were collected from the eligible patients' files by a trained team. Demographic (age and gender) and clinical data on admission were collected for statistical purposes. Results A total of 1298 patient records were included in the study; 417 (32%) of the patients were female and 872 (68%) were male. The cohort included 399 deaths (total MR=30.7%). Most deaths occurred in the 50-69-year age group, with significantly more deaths among female patients than male patients (p=0.004). A significant association was found between the 4C mortality score and death (p<0.000). Furthermore, the mortality odds ratio (OR) was significant (OR=1.3, 95% CI=1.178-1.447) for each added 4C score. Conclusion Our study metrics regarding LOS were generally higher than most internationally reported values and slightly lower than locally reported values. Our reported MR was comparable with overall published MRs. The ISARIC 4C mortality score was highly compatible with our reported MR between scores 4 and 14; however, the MR was higher for scores 0-3 and lower for scores ≤15. The overall performance of the ICU department was considered generally good. Our findings are helpful for benchmarking and motivating better outcomes.

Prognostic models in COVID-19 infection that predict severity: a systematic review

Current evidence on COVID-19 prognostic models is inconsistent and clinical applicability remains controversial. We performed a systematic review to summarize and critically appraise the available studies that have developed, assessed and/or validated prognostic models of COVID-19 predicting health outcomes. We searched six bibliographic databases to identify published articles that investigated univariable and multivariable prognostic models predicting adverse outcomes in adult COVID-19 patients, including intensive care unit (ICU) admission, intubation, high-flow nasal therapy (HFNT), extracorporeal membrane oxygenation (ECMO) and mortality. We identified and assessed 314 eligible articles from more than 40 countries, with 152 of these studies presenting mortality, 66 progression to severe or critical illness, 35 mortality and ICU admission combined, 17 ICU admission only, while the remaining 44 studies reported prediction models for mechanical ventilation (MV) or a combination of multiple outcomes. The sample size of included studies varied from 11 to 7,704,171 participants, with a mean age ranging from 18 to 93 years. There were 353 prognostic models investigated, with area under the curve (AUC) ranging from 0.44 to 0.99. A great proportion of studies (61.5%, 193 out of 314) performed internal or external validation or replication. In 312 (99.4%) studies, prognostic models were reported to be at high risk of bias due to uncertainties and challenges surrounding methodological rigor, sampling, handling of missing data, failure to deal with overfitting and heterogeneous definitions of COVID-19 and severity outcomes. While several clinical prognostic models for COVID-19 have been described in the literature, they are limited in generalizability and/or applicability due to deficiencies in addressing fundamental statistical and methodological concerns. Future large, multi-centric and well-designed prognostic prospective studies are needed to clarify remaining uncertainties.

Utility of the 4C ISARIC mortality score in hospitalized COVID-19 patients at a large tertiary Saudi Arabian center

Background

The International Severe Acute Respiratory and Emerging Infections Consortium (ISARIC) 4C mortality score has been used before as a valuable tool for predicting mortality in COVID-19 patients. We aimed to address the utility of the 4C score in a well-defined Saudi population with COVID-19 admitted to a large tertiary referral hospital in Saudi Arabia.

Methods

A retrospective study was conducted that included all adults COVID‑19 patients admitted to the Armed Forces Hospital Southern Region (AFHSR), between January 2021 and September 2022. The receiver operating characteristic (ROC) curve depicted the diagnostic performance of the 4C Score for mortality prediction.

Results

A total of 1,853 patients were enrolled. The ROC curve of the 4C score had an area under the curve of 0.73 (95% CI: 0.702-0.758), p<0.001. The sensitivity and specificity with scores >8 were 80% and 58%, respectively, the positive and negative predictive values were 28% and 93%, respectively. Three hundred and sixteen (17.1%), 638 (34.4%), 814 (43.9%), and 85 (4.6%) patients had low, intermediate, high, and very high values, respectively. There were significant differences between survivors and non-survivors with regard to all variables used in the calculation of the 4C score. Multivariable logistic regression analysis revealed that all components of the 4C score, except gender and O2 saturation, were independent significant predictors of mortality.

Conclusions

Our data support previous international and Saudi studies that the 4C mortality score is a reliable tool with good sensitivity and specificity in the mortality prediction of COVID-19 patients. All components of the 4C score, except gender and O2 saturation, were independent significant predictors of mortality. Within the 4C score, odds ratios increased proportionately with an increase in the score value. Future multi-center prospective studies are warranted.

Stratification of patients admitted for SARS-CoV2 infection: prognostic scores in the first and second wave of the pandemic

To test the prognostic performance of different scores, both specifically designed for patients with COVID-19 and generic, in predicting in-hospital mortality and the need for mechanical ventilation (MV). We retrospectively collected clinical data of patients admitted to the Emergency Department of the University Hospital AOU Careggi, Florence, Italy, between February 2020 and January 2021, with a confirmed infection by SARS-CoV2. We calculated the following scores: Sequential Organ Failure Assessment (SOFA) score, CALL score, 4C Mortality score, QUICK score, CURB-65 and MuLBSTA score. The end-points were in-hospital mortality and the need for MV. We included 1208 patients, mean age 60 ± 17 years, 57% male sex. Compared to survivors, non-survivors showed significantly higher values of all the prognostic scores (4C: 13 [10-15] vs 8 [4-10]; CALL: 11 [10-12] vs 9 [7-11]; QUICK: 4 [1-6] vs 0 [0-3]; SOFA: 5 [4-6] vs 4 [4-5]; CURB: 2 [1-3] vs 1 [0-1]; MuLBSTA: 11 [9-13] vs 9 [7-11], all p < 0.001). Discriminative ability evaluated by the Receiver Operating Curve analysis showed the following values of the Area under the Curve: 0.83 for 4C, 0.74 for CALL, 0.70 for QUICK, 0.68 for SOFA, 0.76 for CURB and 0.64 for MuLBSTA. The mortality rate significantly increased in increasing quartiles of 4C and CALL score (respectively, 2, 8, 24 and 54% for the 4C score and 1, 17, 33 and 68% for the CALL score, both p < 0.001). 4C and CALL score allowed an early and good prognostic stratification of patients admitted for pneumonia induced by SARS-CoV2.