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Record W4410204565 · doi:10.1371/journal.pone.0323311

Prevalence of Post-intensive care syndrome among intensive care unit-survivors and its association with intensive care unit length of stay: Systematic review and meta-analysis

2025· review· en· W4410204565 on OpenAlexaboutno aff
Temesgen Ayenew, Menberu Gete, Mihretie Gedfew, ፟Addisu Getie, Abebe Dilie Afenigus, Afework Edmealem, Haile Amha, Girma Alem, Bekele Getenet Tiruneh, Mengistu Abebe Messelu

Bibliographic record

VenuePLoS ONE · 2025
Typereview
Languageen
FieldMedicine
TopicIntensive Care Unit Cognitive Disorders
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineMeta-analysisFunnel plotChecklistIntensive care unitConfidence intervalMEDLINEStudy heterogeneityPublication biasPopulationIntensive careMeta-regressionSystematic reviewEmergency medicineIntensive care medicineInternal medicineEnvironmental healthPsychology

Abstract

fetched live from OpenAlex

BACKGROUND: Post-intensive Care Syndrome (PICS) is defined as various physical, psychological, and cognitive, impairments that can arise during an ICU stay, continue after leaving the ICU, or even persist following hospital discharge. It impacts both patients and their family's quality of life. Various primary studies worldwide have reported prevalence of PICS among ICU survivors. However, these studies exhibit inconsistency and wide variations. Therefore, this systematic review and meta-analysis aimed to estimate the pooled prevalence of post intensive care syndrome among intensive care unit survivors along with its association with ICU length of stay. METHODS: We used the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020 checklist for this review. We searched PubMed/Medline, CINHAL, Embase, and Google scholar to retrieve articles. The Newcastle Ottawa Scale (NOS) was used for quality assessment of articles. The random effects model with I-squared test was used to estimate the prevalence of PICS and its association with ICU length of stay. To identify the source of heterogeneity within the included studies, meta-regression and subgroup analysis were used. We employed Egger's regression test and funnel plots for assessing publication bias. STATA version 17.0 software was used for all statistical analyses. A p-value of < 0.05 with 95% confidence interval was used declare statistically significant. RESULTS: A total of 19 articles with a population of 10179 ICU-survivors were included in this review. The pooled prevalence of PICS was found to be 54.35% (95% CI = 45.54, 63.15). In sub-group analysis by region, the highest prevalence was observed in studies done in south and north America with overall prevalence of 61.95% (95% CI = 28.33, 95.62). Among the three domains of PICS (physical, cognitive and mental domains), the highest prevalence score was observed in the physical domain with overall prevalence of 45.99% (95% CI = 34.66, 57.31). In this meta-analysis, those patients who stayed more than four days in the ICU were 1.207 [95% CI = 1.119, 1.295] times more likely to develop at least one among the three domains of PICS in the post-intensive care period than their counterparts. CONCLUSION: This systematic review and meta-analysis demonstrate a high prevalence of PICS among ICU survivors, and highlight the significant association between ICU length of stay and the development of PICS. These findings underscore the need for targeted interventions to mitigate the long-term effects of critical illness, particularly for patients with prolonged ICU stays.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.072
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Meta-epidemiology (broad)
Consensus categoriesMeta-epidemiology (narrow)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.482
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.072
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0180.002
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.074
GPT teacher head0.309
Teacher spread0.234 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; both teacher heads agree on what is shown here.

Study designSystematic review
Domainnot available
GenreReview

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations37
Published2025
Admission routes1
Has abstractyes

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