Related Experiment Video

Updated: Jun 12, 2025

Inverse Probability of Treatment Weighting Propensity Score using the Military Health System Data Repository and National Death Index
06:55

Inverse Probability of Treatment Weighting Propensity Score using the Military Health System Data Repository and National Death Index

Published on: January 8, 2020

14.4K

CAUSAL ASSOCIATION BETWEEN MEDICATION USE AND SEPSIS: A TWO-SAMPLE MENDELIAN RANDOMIZATION STUDY

Mingfen Sun1, Yi Chen2, Zhaoquan Jin1

  • 1Department of Emergency Medicine, The First People's Hospital of Changzhou, Changzhou, China.

Shock (Augusta, Ga.)
|March 18, 2025
PubMed

Insights

Genetically predicted diuretic use may increase sepsis risk. Evidence for other medications, including diabetes drugs and thyroid preparations, was inconclusive in this Mendelian randomization study.

Area of Science:

  • Pharmacogenomics
  • Infectious Disease Epidemiology

Background:

  • Sepsis is a life-threatening condition with significant morbidity and mortality.
  • Understanding the influence of prior medication use on sepsis risk is crucial for prevention and treatment strategies.

Purpose of the Study:

  • To investigate the potential causal relationship between genetically predicted medication use and the risk of developing sepsis.
  • To differentiate between potential associations and causal links using robust genetic methods.

Main Methods:

  • Employed a two-sample Mendelian randomization (MR) design using summary data from genome-wide association studies (GWAS).
  • Utilized Inverse Variance Weighted (IVW), weighted median, and MR-Egger regression methods for primary analysis.
  • Conducted sensitivity analyses including MR-Egger, MR-PRESSO, Cochran's Q, and leave-one-out methods to assess robustness and rule out pleiotropy.

Main Results:

  • Initial analysis suggested potential causal links between genetically predicted use of diuretics, drugs used in diabetes, thyroid preparations, and adrenergics with increased sepsis risk.
  • After adjusting for confounders, only genetically predicted diuretic use remained significantly associated with a higher risk of sepsis (OR = 1.17, P = 0.018).
  • Sensitivity analyses indicated minimal evidence of horizontal pleiotropy or heterogeneity influencing the association between diuretic use and sepsis.

Conclusions:

  • Prior use of diuretics may causally increase the risk of sepsis.
  • Evidence for a causal association between the use of other investigated medications (e.g., diabetes drugs, thyroid preparations) and sepsis risk was not supported by this study.
  • The findings highlight diuretics as a potential factor influencing sepsis risk, warranting further clinical investigation.
Keywords:
Mendelian randomization analysisSepsiscausalitydiuretics

More Related Videos

Evaluation of a Reliable Biomarker in a Cecal Ligation and Puncture-Induced Mouse Model of Sepsis05:28

Evaluation of a Reliable Biomarker in a Cecal Ligation and Puncture-Induced Mouse Model of Sepsis

Published on: December 9, 2022

3.4K
Cecal Ligation Puncture Procedure11:53

Cecal Ligation Puncture Procedure

Published on: May 7, 2011

54.8K

Related Concept Videos

Causality in Epidemiology01:21

Causality in Epidemiology

Causality or causation is a fundamental concept in epidemiology, vital for understanding the relationships between various factors and health outcomes. Despite its importance, there's no single, universally accepted definition of causality within the discipline. Drawing from a systematic review, causality in epidemiology encompasses several definitions, including production, necessary and sufficient, sufficient-component, counterfactual, and probabilistic models. Each has its strengths and...
338
Comparing the Survival Analysis of Two or More Groups01:20

Comparing the Survival Analysis of Two or More Groups

Survival analysis is a cornerstone of medical research, used to evaluate the time until an event of interest occurs, such as death, disease recurrence, or recovery. Unlike standard statistical methods, survival analysis is particularly adept at handling censored data—instances where the event has not occurred for some participants by the end of the study or remains unobserved. To address these unique challenges, specialized techniques like the Kaplan-Meier estimator, log-rank test, and...
158
Types of Biopharmaceutical Studies: Controlled and Non-Controlled Approaches01:23

Types of Biopharmaceutical Studies: Controlled and Non-Controlled Approaches

Biopharmaceutical studies constitute a vital field aiming to enhance drug delivery methods and refine therapeutic approaches, drawing upon diverse interdisciplinary knowledge. In research methodologies, the choice between controlled and non-controlled studies significantly influences the study's reliability and accuracy.
Non-controlled studies, commonly employed for initial exploration, lack a control group, rendering them susceptible to biases and external influences. In contrast,...
124
Statistical Methods for Analyzing Epidemiological Data01:25

Statistical Methods for Analyzing Epidemiological Data

Epidemiological data primarily involves information on specific populations' occurrence, distribution, and determinants of health and diseases. This data is crucial for understanding disease patterns and impacts, aiding public health decision-making and disease prevention strategies. The analysis of epidemiological data employs various statistical methods to interpret health-related data effectively. Here are some commonly used methods:
316
Censoring Survival Data01:09

Censoring Survival Data

Survival analysis is a statistical method used to analyze time-to-event data, often employed in fields such as medicine, engineering, and social sciences. One of the key challenges in survival analysis is dealing with incomplete data, a phenomenon known as "censoring." Censoring occurs when the event of interest (such as death, relapse, or system failure) has not occurred for some individuals by the end of the study period or is otherwise unobservable, and it might have many different...
69
Relative Risk01:12

Relative Risk

Relative risk (RR) is a statistical measure commonly used in epidemiology to compare the likelihood of a particular event occurring between two groups. This metric is important for evaluating the relationship between exposure to a specific risk factor and the probability of a particular outcome. It plays a crucial role in medical research, public health studies, and risk assessment. Relative risk quantifies how much more (or less) likely an event is to occur in an exposed group compared to an...
123