Evaluation of the Recommended 30 cc/kg Fluid Dose for Patients With Septic Shock and Hypoperfusion With Lactate Greater Than 4 mmol/L.

The Surviving Sepsis Campaign Guidelines recommend fluid administration of 30 cc/kg ideal body weight (IBW) for patients with sepsis and lactate greater than 4 mmol/L within 3 hours of identification. In this study, we explore the impact of fluid dose on lactate normalization, treatment cost, length of stay, and mortality in patients with lactate greater than 4. DESIGN: Multicenter retrospective observational study. SETTING: Eight-hospital urban healthcare system in Northeastern United States. PATIENTS: Patients with sepsis, initial lactate value greater than 4 mmol/L, and received appropriate antibiotics within 3 hours. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: We stratified patients into five groups based on the dose of fluid administered within 3 hours after sepsis identification. The groupings were less than 15 cc/kg IBW, 15.1-25 cc/kg IBW, 25.1-35 cc/kg IBW, 35.1-50 cc/kg IBW, and greater than 50 cc/kg IBW. We used the group that received a fluid dose of 25.1-35 cc/kg IBW, as a reference group. The mean age was 66 years, and 56% were male. Three hundred seventy-one (25%) received less than 15 cc/kg of IBW of crystalloid fluid, 278 (17%) received 15-25 cc/kg of IBW, 316 (21%) received 25.1-35 cc/kg of IBW, 319 (21%) received 35.1-50 cc/kg of IBW, and 207 (14%) received greater than 50 cc/kg of IBW. After multilinear regression, there was no significant difference in lactate normalization between the reference group and any of the other fluid groups. We also found no statistically significant difference in the observed/expected cost, or observed/expected length of stay, between the reference group and any of the other fluid groups. Mortality was higher among patients who received greater than 50 cc/kg IBW when compared to the recommended dose. CONCLUSIONS: In patients with sepsis and lactate value greater than 4 mmol/L, high or low fluid doses were not associated with better lactate clearance or patient outcomes. Greater than 50 cc/kg IBW dose of fluids within 3 hours is associated with higher mortality.

Relationship Between Etiology of Cirrhosis and Survival Among Patients Hospitalized in Intensive Care Units.

OBJECTIVE: To determine short-term outcomes of patients with alcohol-associated cirrhosis (ALC) admitted to the intensive care unit (ICU) compared with other etiologies of liver disease. In addition, we investigate whether quick sequential organ failure assessment accurately predicts presence of sepsis and in-hospital mortality in critically ill patients with various etiologies of cirrhosis. METHODS: A retrospective cohort of 1174 consecutive patients with cirrhosis admitted to the ICU between January of 2006 and December of 2015 was analyzed. Outcomes of interest included survival rates within the ICU, post-ICU in-hospital, or at 30 days post-ICU discharge. RESULTS: Five hundred seventy-eight patients were found to have ALC with 596 in the non-ALC group. There was no significant difference in ICU mortality rates in ALC versus non-ALC cohorts (10.2% vs 11.7%, P=.40). However, patients with ALC had significantly higher post-ICU in-hospital death (10.0% vs 6.5%, P=.04) as well as higher mortality at 30-day post-ICU discharge (18.7% vs 11.2%, P<.001). Sustained alcohol abstinence did not offer survival advantage over nonabstinence. The predictive power for quick sequential organ failure assessment for sepsis and in-hospital mortality for patients with cirrhosis was limited. CONCLUSION: Critically ill patients with ALC have decreased survival after ICU discharge compared with patients with other etiologies of cirrhosis, independent of alcohol abstinence.

Relationship Between Body Mass Index and Survival Among Critically Ill Patients With Cirrhosis.

BACKGROUND: Obesity paradox is a phenomenon in which obesity increases the risk of obesity-related chronic diseases but paradoxically is associated with improved survival among obese patients with these diagnoses. OBJECTIVES: The aim of this study was to explore the obesity paradox among critically ill patients with cirrhosis admitted to the Intensive Care Unit. METHODS: A retrospective cohort of 1,143 consecutive patients with cirrhosis admitted to the ICU between January of 2006 and December of 2015 was analyzed. Primary outcome of interest was in-hospital mortality with secondary end points including ICU and short-term mortality at 30 days post ICU admission. RESULTS: Logistic regression with generalized additive models was used, controlling for clinically relevant and statistically significant factors to determine the adjusted relationship between body mass index (BMI) and ICU, post-ICU in-hospital, and 30 day mortality following ICU discharge. ICU and hospital length of stay was similar across all BMI classes. Adjusted ICU mortality was also similar when stratified by BMI. However, a significant reduction in post-ICU hospital mortality was observed in class I and II obese patients with cirrhosis (BMI 30-39.9 kg/m2) compared to normal BMI (OR = 0.41; 95% CI, 0.20 to 0.83; P = 0.014). Similarly, overweight (BMI 25-29.9 kg/m2) and class I and II obese patients with cirrhosis had significantly lower 30-day mortality following ICU discharge (OR = 0.52, 95% CI 0.31 to 0.87; P = 0.014; OR = 0.50, 95% CI 0.29 to 0.86; P = 0.012, respectively) compared to those with normal BMI. CONCLUSION: The signal of obesity paradox is suggested among critically ill patients with cirrhosis.

Machine learning in data abstraction: A computable phenotype for sepsis and septic shock diagnosis in the intensive care unit.

BACKGROUND: With the recent change in the definition (Sepsis-3 Definition) of sepsis and septic shock, an electronic search algorithm was required to identify the cases for data automation. This supervised machine learning method would help screen a large amount of electronic medical records (EMR) for efficient research purposes. AIM: To develop and validate a computable phenotype via supervised machine learning method for retrospectively identifying sepsis and septic shock in critical care patients. METHODS: A supervised machine learning method was developed based on culture orders, Sequential Organ Failure Assessment (SOFA) scores, serum lactate levels and vasopressor use in the intensive care units (ICUs). The computable phenotype was derived from a retrospective analysis of a random cohort of 100 patients admitted to the medical ICU. This was then validated in an independent cohort of 100 patients. We compared the results from computable phenotype to a gold standard by manual review of EMR by 2 blinded reviewers. Disagreement was resolved by a critical care clinician. A SOFA score ≥ 2 during the ICU stay with a culture 72 h before or after the time of admission was identified. Sepsis versions as V1 was defined as blood cultures with SOFA ≥ 2 and Sepsis V2 was defined as any culture with SOFA score ≥ 2. A serum lactate level ≥ 2 mmol/L from 24 h before admission till their stay in the ICU and vasopressor use with Sepsis-1 and-2 were identified as Septic Shock-V1 and-V2 respectively. RESULTS: In the derivation subset of 100 random patients, the final machine learning strategy achieved a sensitivity-specificity of 100% and 84% for Sepsis-1, 100% and 95% for Sepsis-2, 78% and 80% for Septic Shock-1, and 80% and 90% for Septic Shock-2. An overall percent of agreement between two blinded reviewers had a k = 0.86 and 0.90 for Sepsis 2 and Septic shock 2 respectively. In validation of the algorithm through a separate 100 random patient subset, the reported sensitivity and specificity for all 4 diagnoses were 100%-100% each. CONCLUSION: Supervised machine learning for identification of sepsis and septic shock is reliable and an efficient alternative to manual chart review.