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.

Immune system markers may predict affective disorder treatment response, but whether an overall immune system marker predicts bipolar disorder treatment effect is unclear.

Bipolar CHOICE (N = 482) and LiTMUS (N = 283) were similar comparative effectiveness trials treating patients with bipolar disorder for 24 weeks with four different treatment arms (standard-dose lithium, quetiapine, moderate-dose lithium plus optimised personalised treatment (OPT) and OPT without lithium). We performed secondary mixed effects linear regression analyses adjusted for age, gender, smoking and body mass index to investigate relationships between pre-treatment white blood cell (WBC) levels and clinical global impression scale (CGI) response.

Compared to participants with WBC counts of 4.5–10 × 109/l, participants with WBC < 4.5 or WBC ≥ 10 showed similar improvement within each specific treatment arm and in gender-stratified analyses.

An overall immune system marker did not predict differential treatment response to four different treatment approaches for bipolar disorder all lasting 24 weeks.