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10: IMPACT OF A VIRTUAL ICU RECOVERY CLINIC IN SASKATCHEWAN, CANADA

2023· article· en· W4389731684 on OpenAlexaffabout
Eric Sy, Elena Deptuch, Jenna England, Sandy Kassir, Natasha L. Gallant, Jonathan Mailman

Bibliographic record

VenueCritical Care Medicine · 2023
Typearticle
Languageen
FieldMedicine
TopicPneumocystis jirovecii pneumonia detection and treatment
Canadian institutionsRoyal Jubilee HospitalSaskatchewan Health AuthorityUniversity of SaskatchewanUniversity of ReginaRegina General Hospital
Fundersnot available
KeywordsMedicineEmergency medicineIntensive care medicine

Abstract

fetched live from OpenAlex

Introduction: Many ICU survivors struggle with post-intensive care syndrome (PICS) and chronic health issues post-discharge. In Saskatchewan, >50% of the population lives rurally, making follow-up care difficult. The Virtual ICU Recovery Clinic (VIRC) was piloted to provide comprehensive, multidisciplinary care to ICU survivors, using virtual care including telehealth and phone visits. Methods: The VIRC recruited ICU survivors in Regina, Saskatchewan from June 2022-June 2023. They were followed for 180 days post-discharge. The VIRC multidisciplinary team included a physician, pharmacist, and clinical psychologist. We evaluated emergency department (ED) visits, hospital, and ICU readmissions; health-related quality of life; clinic interventions; and satisfaction with the clinic. Results: As follow-up is still underway, we present an interim analysis. We recruited 68 patients, with a median age 61 years (IQR 50-70), clinical frailty score 4 (IQR 3-5), SOFA score admission 11 (IQR 8-12), ICU length of stay 6 days (IQR 4-13) and hospital length of stay 19 (IQR 10-43) days. 50% were female, 49% lived >50 km from Regina, and 78% had a family physician. Of the 33 patients who were seen in the clinic so far, nine (27%) have had ED visits, with five (15%) requiring hospital readmission and two (6%) requiring ICU readmission, by time of clinic visit. Median EQ-5D-5L and EQ-VAS scores at time of clinic visit were 0.84 (IQR 0.64-0.96) and 70 (IQR 55-75). Of those working prior to hospitalization, only 20% had returned to work by the time of the clinic visit. In terms of clinic interventions, 34% were determined to have PICS symptoms and were newly referred onto Clinical Psychology, 12% were newly referred to physiotherapy, and 76% were seen by the Clinical Pharmacist. Of the nine patients who completed all visits and consented to a post-clinic survey, 100% agreed/strongly agreed that the clinic was useful in their care, 78% agreed/strongly agreed that the clinic would keep them out of hospital and 71% agreed/strongly agreed that the virtual technology was easy to use. Conclusions: An ICU recovery clinic could potentially be delivered virtually, with potential impacts on post-ICU care. ICU survivors were in general satisfied with the provision of post-ICU care and the use of virtual technology.

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)0.001
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 score0.039
Threshold uncertainty score0.237

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0050.001
Scholarly communication0.0020.001
Open science0.0020.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0100.001

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 head0.023
GPT teacher head0.341
Teacher spread0.318 · 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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Citations0
Published2023
Admission routes2
Has abstractyes

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