Evidence map›Paper›PMID 39663293›Full record

ArticleInternal and emergency medicine2025

Bundle compliance patterns in septic shock and their association with patient outcomes: an unsupervised cluster analysis.

Aysun Tekin, Balázs Mosolygó, Nan Huo, Guohui Xiao, Amos Lal

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Article in Internal and emergency medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

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2citing papers in PubMed
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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Aysun TekinDivision of Nephrology and Hypertension, Department of Internal Medicine, Mayo Clinic, Rochester, MN, 55905, USA.ORCID 0000-0002-1891-2118
Balázs MosolygóUniversity of Bergen, Bergen, Norway.
Nan HuoDivision of Artificial Intelligence and Informatics, Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN, 55905, USA.
Guohui XiaoSchool of Computer Science and Engineering, Southeast University, Nanjing, 211189, China. guohui.xiao@seu.edu.cn.
Amos LalDivision of Pulmonary and Critical Care Medicine, Department of Internal Medicine, Mayo Clinic, Rochester, MN, 55905, USA. Lal.Amos@mayo.edu.ORCID 0000-0002-0021-2033

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Adhering to bundle-based care recommendations within stringent time constraints presents a profound challenge. Elements within these bundles hold varying degrees of significance. We aimed to evaluate the Surviving Sepsis Campaign (SSC) hour-one bundle compliance patterns and their association with patient outcomes. Utilizing the Medical Information Mart for Intensive Care-IV 1.0 dataset, this retrospective cohort study evaluated patients with sepsis who developed shock and were admitted to the intensive care unit between 2008 and 2019. The execution of five hour-one bundle interventions were assessed. Patients with similar treatment profiles were categorized into clusters using unsupervised machine learning. Primary outcomes included in-hospital and 1-year mortality. Four clusters were identified: C#0 (n = 4716) had the poorest bundle compliance. C#1 (n = 1117) had perfect antibiotic adherence with modest fluid and serum lactate measurement adherence. C#2 (n = 850) exhibited full adherence to lactate measurement and low adherence to fluid administration, blood culture, and vasopressors, while C#3 (n = 381) achieved complete adherence to fluid administration and the highest adherence to vasopressor requirements in the entire cohort. Adjusting for covariates, C#1 and C#3 were associated with reduced odds of in-hospital mortality compared to C#0 (adjusted odds ratio [aOR] = 0·83; 95% confidence interval [CI] 0·7-0·97 and aOR = 0·7; 95% CI 0·53-0·91, respectively). C#1 exhibited significantly better 1-year survival (adjusted hazard ratio [aHR] = 0·9; 95%CI 0·81-0·99). We were able to identify distinct clusters of SSC hour-one bundle adherence patterns using unsupervised machine learning techniques, which were associated with patient outcomes.

Indexed as

Guideline AdherencePatient Care BundlesShock, SepticAgedCluster AnalysisCohort StudiesFemaleHospital MortalityHumansIntensive Care UnitsMaleMiddle AgedRetrospective StudiesHour-one bundleIntensive careSepsisSeptic shockSurviving sepsis campaign

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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.