Evidence map›Paper›PMID 32070393›Full record

ArticleCritical care (London, England)2020

Defining persistent critical illness based on growth trajectories in patients with sepsis.

Zhongheng Zhang, Kwok M Ho, Hongqiu Gu, Yucai Hong, Yunsong Yu

Open access · goldAbstract read
In one paragraph

Article in Critical care (London, England), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 31 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
31citing papers in PubMed, 2 pooled it
3.6field-weighted citation impact, top 6% of its field
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

31 citing papers in PubMed, 2 syntheses or guidelines pooled it, 49 citations in OpenAlex.

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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

5 authors at 3 institutions in 2 countries.

Zhongheng ZhangDepartment of Emergency Medicine, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, 310016, China.
Kwok M HoDepartment of intensive care Medicine, Royal Perth Hospital, School of Population & Global Health, University of Western Australia, Crawley, Australia.
Hongqiu GuChina National Clinical Research Center for Neurological Diseases; National Center for Healthcare Quality Management in Neurological Diseases, Beijing Tiantan Hospital, Capital Medical University, Beijing, 10070, China.
Yucai HongDepartment of Emergency Medicine, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, 310016, China.
Yunsong YuDepartment of Infectious Diseases, Sir Run Run Shaw Hospital, School of Medicine, Zhejiang University, Zhejiang, 310016, Hangzhou, China. yvys119@zju.edu.cn.ORCID 0000-0003-2903-918X
Sir Run Run Shaw Hospital · CNCapital Medical University · CNThe University of Western Australia · AU

Funding

National Natural Science Foundation of China 81901929Zhejiang Province Public Welfare Technology Application Research Project LGF18H150005
6 · The paper itself

Abstract

backgroundPersistent critical illness is common in critically ill patients and is associated with vast medical resource use and poor clinical outcomes. This study aimed to define when patients with sepsis would be stabilized and transitioned to persistent critical illness, and whether such transition time varies between latent classes of patients.

methodsThis was a retrospective cohort study involving sepsis patients in the eICU Collaborative Research Database. Persistent critical illness was defined at the time when acute physiological characteristics were no longer more predictive of in-hospital mortality (i.e., vital status at hospital discharge) than antecedent characteristics. Latent growth mixture modeling was used to identify distinct trajectory classes by using Sequential Organ Failure Assessment score measured during intensive care unit stay as the outcome, and persistent critical illness transition time was explored in each latent class.

resultsThe mortality was 16.7% (3828/22,868) in the study cohort. Acute physiological model was no longer more predictive of in-hospital mortality than antecedent characteristics at 15 days after intensive care unit admission in the overall population. Only a minority of the study subjects (n = 643, 2.8%) developed persistent critical illness, but they accounted for 19% (15,834/83,125) and 10% (19,975/198,833) of the total intensive care unit and hospital bed-days, respectively. Five latent classes were identified. Classes 1 and 2 showed increasing Sequential Organ Failure Assessment score over time and transition to persistent critical illness occurred at 16 and 27 days, respectively. The remaining classes showed a steady decline in Sequential Organ Failure Assessment scores and the transition to persistent critical illness occurred between 6 and 8 days. Elevated urea-to-creatinine ratio was a good biochemical signature of persistent critical illness.

conclusionsWhile persistent critical illness occurred in a minority of patients with sepsis, it consumed vast medical resources. The transition time differs substantially across latent classes, indicating that the allocation of medical resources should be tailored to different classes of patients.

Indexed as

Critical IllnessHealth ResourcesIntensive Care UnitsSepsisAgedCohort StudiesDatabases, FactualFemaleHospitalizationHospital MortalityHumansMaleMiddle AgedOrgan Dysfunction ScoresPatient DischargeRetrospective StudiesPersistent critical illnessSepsisUnsupervised machine learning

Identifiers

PMID32070393
PMCPMC7029548
OpenAlexW3010717854

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.