Evidence map›Paper›PMID 34559850›Full record

SynthesisPloS one2021

Risk prediction models for intensive care unit-acquired weakness in intensive care unit patients: A systematic review.

Wei Zhang, Yun Tang, Huan Liu, Li Ping Yuan, Chu Chu Wang, Shu Fan Chen, Jin Huang, Xin Yuan Xiao

Open access · goldAbstract readSystematic Review
In one paragraph

Synthesis in PloS one, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed, 1 pooled it
2.2field-weighted citation impact, top 13% 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

12 citing papers in PubMed, 1 synthesis or guideline pooled it, 23 citations in OpenAlex.

  1. Pooled it
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  3. Observational
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  5. Article
  6. Article
  7. Review
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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

8 authors at 1 institution in 1 country.

Wei ZhangDepartment of Neurosurgery Intensive Care Unit, The First Affiliated Hospital of Wannan Medical College, Wuhu, China.ORCID 0000-0002-4915-7223
Yun TangDepartment of Neurosurgery Intensive Care Unit, The First Affiliated Hospital of Wannan Medical College, Wuhu, China.
Huan LiuDepartment of Blood Purification Center, The First Affiliated Hospital of Wannan Medical College, Wuhu, China.
Li Ping YuanDepartment of Nursing, The First Affiliated Hospital of Wannan Medical College, Wuhu, China.
Chu Chu WangDepartment of Neurosurgery Intensive Care Unit, The First Affiliated Hospital of Wannan Medical College, Wuhu, China.
Shu Fan ChenDepartment of Neurosurgery Intensive Care Unit, The First Affiliated Hospital of Wannan Medical College, Wuhu, China.
Jin HuangDepartment of Neurosurgery Intensive Care Unit, The First Affiliated Hospital of Wannan Medical College, Wuhu, China.
Xin Yuan XiaoDepartment of Neurosurgery Intensive Care Unit, The First Affiliated Hospital of Wannan Medical College, Wuhu, China.
First Affiliated Hospital of Wannan Medical College · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

BACKGROUND AND

objectivesIntensive care unit-acquired weakness (ICU-AW) commonly occurs among intensive care unit (ICU) patients and seriously affects the survival rate and long-term quality of life for patients. In this systematic review, we synthesized the findings of previous studies in order to analyze predictors of ICU-AW and evaluate the discrimination and validity of ICU-AW risk prediction models for ICU patients.

methodsWe searched seven databases published in English and Chinese language to identify studies regarding ICU-AW risk prediction models. Two reviewers independently screened the literature, evaluated the quality of the included literature, extracted data, and performed a systematic review.

resultsUltimately, 11 studies were considered for this review. For the verification of prediction models, internal verification methods had been used in three studies, and a combination of internal and external verification had been used in one study. The value for the area under the ROC curve for eight models was 0.7-0.923. The predictor most commonly included in the models were age and the administration of corticosteroids. All the models have good applicability, but most of the models are biased due to the lack of blindness, lack of reporting, insufficient sample size, missing data, and lack of performance evaluation and calibration of the models.

conclusionsThe efficacy of most models for the risk prediction of ICU-AW among high-risk groups is good, but there was a certain bias in the development and verification of the models. Thus, ICU medical staff should select existing models based on actual clinical conditions and verify them before applying them in clinical practice. In order to provide a reliable basis for the risk prediction of ICU-AW, it is necessary that large-sample, multi-center studies be conducted in the future, in which ICU-AW risk prediction models are verified.

Indexed as

Area Under CurveBiasCritical CareHumansIntensive Care UnitsModels, TheoreticalMuscle WeaknessQuality of LifeRisk Assessment

Identifiers

PMID34559850
PMCPMC8462700
OpenAlexW3145771320

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.