The modified HALP score is associated with short-term mortality in critically ill patients with sepsis - A cohort

Lanzhi Lin1, Huifang Huang1, Meiying Wu1

  • 1Intensive Care Unit, Fujian Maternity and Child Health Hospital, College of Clinical Medicine for Obstetrics & Gynecology and Pediatrics, Fujian Medical University, Fuzhou 350001, China.

Abstract

Insights

The modified HALP (m-HALP) score shows strong prognostic value for critically ill septic patients, predicting short-term mortality effectively. This sepsis biomarker offers a promising tool for assessing patient outcomes in intensive care units.

Area of Science:

  • Critical Care Medicine
  • Biomarker Discovery
  • Prognostic Modeling

Background:

  • Sepsis poses a significant threat to critically ill patients.
  • Accurate prognostic tools are crucial for timely intervention.
  • The prognostic value of the modified HALP (m-HALP) score in sepsis requires systematic evaluation.

Purpose of the Study:

  • To assess the prognostic predictive value of the m-HALP score in critically ill septic patients.
  • To evaluate the association between m-HALP scores and 30-day mortality.
  • To compare the predictive performance of m-HALP with existing scores.

Main Methods:

  • Utilized data from the MIMIC-IV database for score computation and survival analysis (Cox regression, K-M curves).
  • Employed restricted cubic splines to model the association with mortality.
  • Validated findings using logistic regression and ROC curves from the eICU database.

Main Results:

  • The m-HALP score demonstrated an L-shaped association with 30-day mortality (HR: 0.84).
  • Higher m-HALP scores correlated with favorable survival outcomes (p < 0.001).
  • m-HALP showed superior predictive value for short-term sepsis mortality compared to HALP and qSOFA scores.

Conclusions:

  • The m-HALP score is a significant predictor of short-term mortality in septic patients.
  • m-HALP exhibits promising prognostic relevance as a sepsis biomarker.
  • This score can aid in risk stratification and clinical decision-making for sepsis management.