Identifying early predictors of dialysis requirements in earthquake-related injuries is crucial for optimal resource allocation and timely intervention. This study aimed to develop a predictive scoring system, named SAFE-QUAKE (Seismic Assessment of Kidney Function to Rule Out Dialysis Requirement), to identify patients at high risk of developing acute kidney injury (AKI) and requiring dialysis.

A retrospective analysis was conducted on a cohort of 205 patients presenting with earthquake-related injuries. Patients were divided into two groups based on their need for dialysis: the no dialysis group (n = 170) and the dialysis group (n = 35). Demographic, clinical, and laboratory data were collected and compared between the two groups to identify significant predictors of dialysis requirements. The parameters that would form the score were determined by conducting an importance analysis using artificial neural networks (ANNs) to identify parameters that exhibited statistically significant differences in univariate analysis.

The dialysis group had a significantly longer median duration of being trapped under debris (48 hours) compared to the no dialysis group (eight hours). Blood gas and laboratory analyses revealed significant differences in pH levels, lactate values, creatinine levels, lactate dehydrogenase (LDH) levels, and aspartate transaminase (AST)-to-alanine transaminase (ALT) ratio between the two groups. Based on these findings, the SAFE-QUAKE rule-out scoring system was developed, incorporating entrapment duration (<45 hours), pH levels (>7.31), creatinine levels (<2mg/dL), LDH levels (<1600mg/dL), and the AST-to-ALT ratio (<2.4) as key predictors of dialysis requirements. This score included 139 patients, and among them, only one patient required dialysis, resulting in a negative predictive value of 99.29%.

The SAFE-QUAKE scoring system demonstrated a high negative predictive value of 99.29% in ruling out the need for dialysis among earthquake-related injury cases. This scoring system offers a practical approach for health care providers to identify patients at high risk of developing AKI and requiring dialysis in earthquake-affected regions.

This study compared the prognostic performances of the Brescia-COVID Respiratory Severity Scale (BCRSS) and the Quick COVID-19 Severity Index (qCSI) scores in hospitalized patients diagnosed with COVID-19.

The data of all adult patients (over 18 y of age) who were admitted into a state hospital with confirmed COVID-19 between May 1, 2020, and October 31, 2020, were retrospectively examined. The area under the receiver operating characteristic (ROC) curve, known as the area under the curve (AUC), was used to assess the BCRSS prediction rule and the qCSI score to assess the discriminatory power in predicting in-hospital mortality and intensive care unit (ICU) admission.

There were 341 patients included in this study. The mean age of the patients was 58.2 ± 17.2, of which 165 were men and 176 were women, and 61.3% of patients had at least 1 comorbidity. The most common comorbidity was hypertension. The predictive power scores of BCRSS and qCSI were found as very good in terms of in-hospital mortality (AUC 0.804 and 0.847, respectively) and likewise in terms of ICU admission (AUC 0.842 and 0.851, respectively).

Both BCRSS and qCSI scoring systems were found to be successful in predicting in-hospital mortality and ICU admission in our patient population.