| Abstrakt: |
Background: Predicting neurological outcomes following in-hospital cardiac arrest is crucial for guiding subsequent clinical treatments. This study seeks to validate the effectiveness of the CASPRI, GO-FAR, and PIHCA tools in predicting favorable neurological outcomes after in-hospital cardiac arrest. Method: This retrospective study utilized a Utstein-style structured form to review the medical records of patients who experienced in-hospital cardiac arrest between March 2018 and March 2023. Predictors were examined using multivariable logistic regression, and the validity of the tools was assessed using ROC curves. Statistical analysis was conducted using SPSS version 25 software. Results: Out of the 1100 patients included in the study, 42 individuals (3.8%) achieved a favorable neurological outcome. multivariable regression analysis revealed that age, respiratory failure, resuscitation shift, duration of renal failure, and CPC score 24 h before cardiac arrest were significantly associated with favorable neurological outcomes. The predictive abilities of the CASPRI, GO-FAR, and PIHCA scores were calculated as 0.99 (95% CI, 0.98–1.00), 0.98 (95% CI, 0.97–0.99), and 0.96 (95% CI, 0.94–0.99) respectively. A statistically significant difference was observed in the predictive abilities of the CASPRI and PIHCA scores (P = 0.001), while the difference between CASPRI and GO-FAR did not reach significance (P = 0.057). Additionally, there was no significant difference between the predictive abilities of GO-FAR and PIHCA scores (P = 0.159). Conclusion: The study concludes that CASPRI and GO-FAR scores show strong potential as objective measures for predicting favorable neurological outcomes post-cardiac arrest. Integrating these scores into clinical decision-making may enhance treatment and care strategies, in the Iranian healthcare context. [ABSTRACT FROM AUTHOR] |
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