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Record W3200941961 · doi:10.2196/30473

Sustaining a Multidisciplinary, Single-Institution, Postoperative Mobilization Clinical Practice Improvement Program Following Hepatopancreatobiliary Surgery During the COVID-19 Pandemic: Prospective Cohort Study

2021· article· en· W3200941961 on OpenAlexvenueno aff
Kai Siang Chan, Bei Wang, Yen Pin Tan, Jaclyn Jie Ling Chow, Ee Ling Ong, Sameer P. Junnarkar, Jee Keem Low, Cheong Wei Terence Huey, Vishal G. Shelat

Bibliographic record

VenueJMIR Perioperative Medicine · 2021
Typearticle
Languageen
FieldMedicine
TopicEnhanced Recovery After Surgery
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineSurgeryRetrospective cohort studyProspective cohort study

Abstract

fetched live from OpenAlex

BACKGROUND: The Enhanced Recovery After Surgery (ERAS) protocol has been recently extended to hepatopancreatobiliary (HPB) surgery, with excellent outcomes reported. Early mobilization is an essential facet of the ERAS protocol, but compliance has been reported to be poor. We recently reported our success in a 6-month clinical practice improvement program (CPIP) for early postoperative mobilization. During the COVID-19 pandemic, we experienced reduced staffing and resource availability, which can make CPIP sustainability difficult. OBJECTIVE: We report outcomes at 1 year following the implementation of our CPIP to improve postoperative mobilization in patients undergoing major HPB surgery during the COVID-19 pandemic. METHODS: We divided our study into 4 phases-phase 1: before CPIP implementation (January to April 2019); phase 2: CPIP implementation (May to September 2019); phase 3: post-CPIP implementation but prior to the COVID-19 pandemic (October 2019 to March 2020); and phase 4: post-CPIP implementation and during the pandemic (April 2020 to September 2020). Major HPB surgery was defined as any surgery on the liver, pancreas, and biliary system with a duration of >2 hours and with an anticipated blood loss of ≥500 ml. Study variables included length of hospital stay, distance ambulated on postoperative day (POD) 2, morbidity, balance measures (incidence of fall and accidental dislodgement of drains), and reasons for failure to achieve targets. Successful mobilization was defined as the ability to sit out of bed for >6 hours on POD 1 and ambulate ≥30 m on POD 2. The target mobilization rate was ≥75%. RESULTS: A total of 114 patients underwent major HPB surgery from phases 2 to 4 of our study, with 33 (29.0%), 45 (39.5%), and 36 (31.6%) patients in phases 2, 3, and 4, respectively. No baseline patient demographic data were collected for phase 1 (pre-CPIP implementation). The majority of the patients were male (n=79, 69.3%) and underwent hepatic surgery (n=92, 80.7%). A total of 76 (66.7%) patients underwent ON-Q PainBuster insertion intraoperatively. The median mobilization rate was 22% for phase 1, 78% for phases 2 and 3 combined, and 79% for phase 4. The mean pain score was 2.7 (SD 1.0) on POD 1 and 1.8 (SD 1.5) on POD 2. The median length of hospitalization was 6 days (IQR 5-11.8). There were no falls or accidental dislodgement of drains. Six patients (5.3%) had pneumonia, and 21 (18.4%) patients failed to ambulate ≥30 m on POD 2 from phases 2 to 4. The most common reason for failure to achieve the ambulation target was pain (6/21, 28.6%) and lethargy or giddiness (5/21, 23.8%). CONCLUSIONS: This follow-up study demonstrates the sustainability of our CPIP in improving early postoperative mobilization rates following major HPB surgery 1 year after implementation, even during the COVID-19 pandemic. Further large-scale, multi-institutional prospective studies should be conducted to assess compliance and determine its sustainability.

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)0.003
metaresearch head score (Gemma)0.007
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 score0.010
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.007
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.002
Science and technology studies0.0020.001
Scholarly communication0.0020.002
Open science0.0010.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.000

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 head0.055
GPT teacher head0.414
Teacher spread0.359 · 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".

Quick stats

Citations10
Published2021
Admission routes1
Has abstractyes

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