Evidence map›Paper›PMID 40455670›Full record

ArticleMSMR2025

Trends of sepsis hospitalizations among female active component U.S. service members, 2011-2022.

Alexis A McQuistan, Michael T Fan, Sithembile L Mabila

Abstract read
In one paragraph

Article in MSMR, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Alexis A McQuistanArmed Forces Health Surveillance Division, Public Health Directorate, Defense Health Agency, Silver Spring, MD.
Michael T FanArmed Forces Health Surveillance Division, Public Health Directorate, Defense Health Agency, Silver Spring, MD.
Sithembile L MabilaArmed Forces Health Surveillance Division, Public Health Directorate, Defense Health Agency, Silver Spring, MD.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Studies of sepsis within the U.S. military population have consistently shown that rates of sepsis have increased over time. The observed higher incidence of sepsis in studies among women compared to men of the active component U.S. military population is of concern and warrants further evaluation, as it diverges from incidence typically observed in the U.S. general population. The objectives of this study were to examine cases of sepsis among active component U.S. service women between January 1, 2011 and December 31, 2022, compare them to active component men in the U.S. military, and identify factors associated with sepsis among female active component service members. In this study, female active component service members evinced higher rates (66.5 per 100,000 person-years) compared to males (36.7 per 100,000 person-years), with a rate of sepsis 1.9 times higher after adjusting for demographic and military-related factors. Rates of sepsis were higher among women with a history of co-morbidities. Rates of sepsis hospitalizations among female active component service members have consistently been higher compared to male active component members. Female active component members had 1.9 times higher rates for hospitalization for sepsis compared to active component service men after adjusting for demographic and military-related factors.

Indexed as

HospitalizationMilitary PersonnelSepsisAdultFemaleHumansIncidenceMaleMiddle AgedRisk FactorsSex FactorsUnited StatesYoung Adultarmed forcesfemalegenderhospitalizationinfectionmilitarysepsissexUnited Stateswomen

Identifiers

PMID40455670
PMCPMC12186817

What OpenQuestion holds

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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.