Exploring treatment effects and fluid resuscitation strategies in septic shock: a deep learning-based causal inference approach

Septic shock exhibits diverse etiologies and patient characteristics, necessitating tailored fluid management. We aimed to compare resuscitation strategies using normal saline, Ringer's lactate, and albumin, and to determine which patient factors are associated with improved outcomes. We analyzed septic shock patients from the MIMIC-IV database, categorizing them by the fluid administered: normal saline, Ringer's lactate, albumin, or their combinations. A deep learning-based causal inference model estimated treatment effects on in-hospital mortality and kidney outcomes (defined as a doubling of creatinine or the initiation of kidney replacement therapy). Multivariable logistic regression was then applied to the individual treatment effects to identify patient characteristics linked to better outcomes for Ringer's lactate and additional albumin infusion compared to normal saline alone. Among 13,527 patients, 17.8% experienced in-hospital mortality and 16.2% developed kidney injury. Ringer's lactate reduced mortality by 2.33% and kidney injury by 1.41% compared to normal saline. Adding albumin to normal saline further reduced mortality by 1.20% and kidney outcomes by 0.71%. The combination of Ringer's lactate and albumin provided the greatest benefit (mortality: -3.07%, kidney injury: -3.00%). Patients with high SOFA scores, low albumin, or high lactate levels benefited more from normal saline, whereas those with low eGFR or on vasopressors were less likely to benefit from albumin. Ringer's lactate, particularly when combined with albumin, is superior to normal saline in reducing mortality and kidney injury in septic shock patients, underscoring the need for personalized fluid management based on patient-specific factors.