Evidence map›Paper›PMID 39070840›Full record

ArticleWorld journal of clinical cases2024

Advancing critical care recovery: The pivotal role of machine learning in early detection of intensive care unit-acquired weakness.

Georges Khattar, Elie Bou Sanayeh

Abstract readEditorial
In one paragraph

Article in World journal of clinical cases, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

2 authors.

Georges KhattarDepartment of Medicine, Staten Island University Hospital, Staten Island, NY 10305, United States.
Elie Bou SanayehDepartment of Medicine, Staten Island University Hospital, Staten Island, NY 10305, United States. elie.h.bousanayeh@gmail.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This editorial explores the significant challenge of intensive care unit-acquired weakness (ICU-AW), a prevalent condition affecting critically ill patients, characterized by profound muscle weakness and complicating patient recovery. Highlighting the paradox of modern medical advances, it emphasizes the urgent need for early identification and intervention to mitigate ICU-AW's impact. Innovatively, the study by Wang

Indexed as

Critical illness myopathyCritical illness polyneuropathyEarly detectionIntensive care unit-acquired weaknessNeural network modelsPatient outcomesPersonalized intervention strategiesPredictive modeling

Identifiers

PMID39070840
PMCPMC11235497

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.