Multinational Trends in Sepsis Mortality Between 1985 and 2019: a Temporal Analysis of the WHO Mortality Database

Overview

Journal BMJ Open

Specialty General Medicine

Date 2024 Sep 12

PMID 39266316

Authors

Matthieu Komorowski

Justin D Salciccioli

Joseph Shalhoub

Anthony C Gordon

Dominic C Marshall

Affiliations

Soon will be listed here.

Abstract

Objectives: Understanding the burden of disease of sepsis is essential for monitoring the effectiveness of international strategies to improve sepsis care. Our objective was to describe the multinational trend of sepsis-related mortality for the period 1985-2019 from the WHO Mortality Database.

Design: Retrospective analysis of the WHO Mortality Database.

Setting: We included data from all countries defined by the WHO as having 'high usability data' and at least 10 years of total available data.

Participants: From the WHO list of 50 countries with high usability data, 14 (28%) were excluded due to excessive missingness. We included and analysed data separately for male and female.

Primary And Secondary Outcome Measures: We analysed age-standardised mortality rates (ASMR) (weighted average of the age-specific mortality rates per 100 000 people, where the weights are the proportions of people in the corresponding age groups of the WHO standard population).

Results: We included 1104 country-years worth of data from 36 countries with high usability data, accounting for around 15% of the world's population. The median ASMR for men decreased from 37.8 deaths/100 000 (IQR 28.4-46.7) in 1985-1987 to 25.8 deaths/100 000 (IQR 19.2-37) in 2017-2019, an approximately 12% absolute (31.8% relative) decrease. For women, the overall ASMR decreased from 22.9 deaths/100 000 (IQR 17.7-32.2) to 16.2 deaths/100 000 (IQR 12.6-21.6), an approximately 6.7% absolute decrease (29.3% relative decrease). The analysis of country-level data revealed wide variations in estimates and trends.

Conclusions: We observed a decrease in reported sepsis-related mortality across the majority of analysed nations between 1985 and 2019. However, significant variability remains between gender and health systems. System-level and population-level factors may contribute to these differences, and additional investigations are necessary to further explain these trends.

Citing Articles

Machine Learning Models in Sepsis Outcome Prediction for ICU Patients: Integrating Routine Laboratory Tests-A Systematic Review.

Musat F, Paduraru D, Bolocan A, Palcau C, Copaceanu A, Ion D Biomedicines. 2025; 12(12.

PMID: 39767798 PMC: 11727033. DOI: 10.3390/biomedicines12122892.

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