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Mechanical Ventilation Discontinuation Practices in Asia: A Multinational Survey

2020· article· en· W3112253797 on OpenAlexaff
Chi Hung Czarina Leung, Anna Lee, Yaseen M. Arabi, Jason Phua, Jigeeshu V. Divatia, Younsuck Koh, Bin Du, Cheng Cheng Tan, Jose Emmanuel M. Palo, Karen E. A. Burns, Tae‐Hyung Kim, Moritoki Egi, Mohammad Omar Faruq, Babu Raja Shrestha, Shih‐Feng Liu, Tuan Dang Nguyen, Bambang Wahjuprajitno, Madiha Hashmi, Boonsong Patjanasoontorn, Zulaidi Latif, Kanishka Indraratna, Hussain N. Al Rahma, Seyed Mohammad Reza Hashemian, Charles D. Gomersall

Bibliographic record

VenueAnnals of the American Thoracic Society · 2020
Typearticle
Languageen
FieldMedicine
TopicRespiratory Support and Mechanisms
Canadian institutionsImpactMcMaster UniversityUniversity of TorontoSt. Michael's Hospital
Fundersnot available
KeywordsMedicineIntensivistMechanical ventilationDiscontinuationIntensive careIntensive care unitEmergency medicineWeaningIntensive care medicineInternal medicine

Abstract

fetched live from OpenAlex

Abstract Rationale There are limited data on mechanical discontinuation practices in Asia. Objectives To document self-reported mechanical discontinuation practices and determine whether there is clinical equipoise regarding protocolized weaning among Asian Intensive Care specialists. Methods A survey using a validated questionnaire, distributed using a snowball method to Asian Intensive Care specialists. Results Of the 2,967 invited specialists from 20 territories, 2,074 (69.9%) took part. The majority of respondents (60.5%) were from China. Of the respondents, 42% worked in intensive care units (ICUs) where respiratory therapists were present; 78.9% used a spontaneous breathing trial as the initial weaning step; 44.3% frequently/always used pressure support (PS) alone, 53.4% intermittent spontaneous breathing trials with PS in between, and 19.8% synchronized intermittent mandatory ventilation with PS as a weaning mode. Of the respondents, 56.3% routinely stopped feeds before extubation, 71.5% generally followed a sedation protocol or guideline, and 61.8% worked in an ICU with a weaning protocol. Of these, 78.2% frequently always followed the protocol. A multivariate analysis involving a modified Poisson regression analysis showed that working in an ICU with a weaning protocol and frequently/always following it was positively associated with an upper–middle-income territory, a university-affiliated hospital, or in an ICU that employed respiratory therapists; and negatively with a low-income or lower–middle-income territory or a public hospital. There was no significant association with “in-house” intensivist at night, multidisciplinary ICU, closed ICU, or nurse–patient ratio. There was heterogeneity in agreement/disagreement with the statement, “evidence clearly supports protocolized weaning over nonprotocolized weaning.” Conclusions A substantial minority of Asian Intensive Care specialists do not wean patients in accordance with the best available evidence or current guidelines. There is clinical equipoise regarding the benefit of protocolized weaning.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.012
Threshold uncertainty score0.023

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.243
GPT teacher head0.457
Teacher spread0.214 · 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; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

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Citations27
Published2020
Admission routes1
Has abstractyes

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