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Record W2014338514 · doi:10.1186/cc5309

Retrospective study of dysphagia following hospital discharge of intensive care patients

2007· article· en· W2014338514 on OpenAlexfundno aff
Peter Isherwood, F Baldwin

Bibliographic record

VenueCritical Care · 2007
Typearticle
Languageen
FieldHealth Professions
TopicDysphagia Assessment and Management
Canadian institutionsnot available
FundersCanadian Institutes of Health Research
KeywordsMedicineDysphagiaRetrospective cohort studyEmergency medicineHospital dischargePatient dischargeIntensive careIntensive care medicineMEDLINEInternal medicineSurgery

Abstract

fetched live from OpenAlex

A retrospective study to assess the incidence and causal factors associated with long-term dysphagia following intensive care discharge. A questionnaire was sent out 4 months post ICU discharge to 193 intensive care patients (Level 3 care with a stay of over 48 hours). We reviewed the case notes of those patients who reported swallowing difficulties to establish whether they had undergone, had any characteristics of or received therapies potentially associated with dysphagia. We had a 50% response rate to our questionnaire. An overall dysphagia post ICU stay rate of 19.5% was observed. Fever and age over 65 were both common findings as one may expect and showed the highest association with subsequent dysphagia. We did not find any suggestion of a relationship between changing tracheostomy (suggesting repeat procedures) and subsequent difficulty swallowing. One patient within this group subsequently developed a tracheal stenosis. See Table 1 . We found the percentage of patients reporting swallowing difficulties post percutaneous tracheostomy (PCT) (Portex Blue Line Ultra tracheostomy tube) to be higher than one would expect. This may be confounded by neurological injury necessitating the need for a PCT, but we feel this may be an area of concern meriting further investigation given frequent PCT in ICU practice.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation 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 score0.403
Threshold uncertainty score0.610

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.026
GPT teacher head0.421
Teacher spread0.395 · 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 teacher head, 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

Citations1
Published2007
Admission routes1
Has abstractyes

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