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Journal of clinical medicine · 2024

Enhancing SAPS-3 Predictive Accuracy with Initial, Peak, and Last Lactate Measurements in Septic Shock.

СтатьяНазвание и аннотация: Перевод в очереди
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Stoiber Arthur, Hermann Alexander, Wanka Sophie-Theres, Heinz Gottfried, Speidl Walter S, Hengstenberg Christian, Schellongowski Peter, Staudinger Thomas, Zilberszac Robert

Аннотация

Background/Objectives: Septic shock is a severe condition with high mortality necessitating precise prognostic tools for improved patient outcomes. This study aimed to evaluate the collective predictive value of the Simplified Acute Physiology Score 3 (SAPS-3) and lactate measurements (initial, peak, last, and clearance rates within the first 24 h) in patients with septic shock. Specifically, it sought to determine how these markers enhance predictive accuracy for 28-day mortality beyond SAPS-3 alone. Methods: This retrospective cohort study analyzed data from 66 septic shock patients at two ICUs of Vienna General Hospital (2017-2019). SAPS-3 and lactate levels (initial, peak, last measurement within 24 h, and 24 h clearance) were obtained from electronic health records. Logistic regression models were constructed to identify predictors of 28-day mortality, and receiver operating characteristic (ROC) curves assessed predictive accuracy. Results: Among 66 patients, 36 (55%) died within 28 days. SAPS-3 scores significantly differed between survivors and non-survivors (76 vs. 85 points; p = 0.016). First, last, and peak lactate were significantly higher in non-survivors compared to survivors (all p < 0.001). The combination of SAPS-3 and first lactate produced the highest predictive accuracy (AUC = 80.6%). However, 24 h lactate clearance was not predictive of mortality. Conclusions: Integrating SAPS-3 with lactate measurements, particularly first lactate, improves predictive accuracy for 28-day mortality in septic shock patients. First lactate serves as an early, robust prognostic marker, providing crucial information for clinical decision-making and care prioritization. Further large-scale studies are needed to refine these predictive tools and validate their efficacy in guiding treatment strategies.

ИП Урсолов Владлен Сергеевич

ИНН 500118482352 · ОГРНИП 314500117700049

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