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Record W4411169023 · doi:10.2196/68053

Post–Critical Illness Dysphagia in the Intensive Care Unit (the Dysphagia-ICU Study): Protocol for a Prospective Cohort Study

2025· article· en· W4411169023 on OpenAlexaffvenue
Waleed Alhazzani, Jamala Saleh Selan, Haifa Alotaibi, Sara Alnasser, Afaf Alrwais, Atheer Alhomoud, Rawabi M. Alsayer, Hani Tamim

Bibliographic record

VenueJMIR Research Protocols · 2025
Typearticle
Languageen
FieldHealth Professions
TopicDysphagia Assessment and Management
Canadian institutionsMcMaster University
Fundersnot available
KeywordsDysphagiaMedicinePreprintIntensive care unitProtocol (science)Prospective cohort studyCohort studyDementiaCohortEmergency medicineIntensive care medicineAlternative medicineInternal medicineSurgeryDiseaseComputer scienceWorld Wide Web

Abstract

fetched live from OpenAlex

BACKGROUND: Post-critical illness dysphagia occurs in about 10% to 62% of patients in the intensive care unit (ICU). Studies focusing on risk factors for dysphagia following endotracheal intubation are scarce and provide conflicting results. More research is required to determine the true prevalence of dysphagia, possible mechanisms, and risk factors. OBJECTIVE: The aims of the study are to determine (1) risk factors associated with post-critical illness dysphagia, (2) the prevalence of post-critical illness dysphagia, (3) outcomes of patients with post-critical illness dysphagia, and (4) the diagnostic accuracy of the water sip test compared to fiber-optic endoscopic evaluation of swallowing (FEES). METHODS: We plan to undertake a single-center prospective cohort study of patients with post-critical illness dysphagia admitted to the ICU at Prince Sultan Military Medical City, Saudi Arabia. Our inclusion criteria are as follows: (1) being an adult (age 18 years and older), (2) having undergone invasive mechanical ventilation for >24 hours, (3) having been extubated for >24 hours, (4) being able to participate in a FEES, and (5) being hemodynamically stable. Each day, the research coordinator will screen all patients in the ICU for enrollment in the study. The research coordinator will collect daily data on the use of advanced life support, the need for mechanical ventilation, and outcomes (mortality, duration of mechanical ventilation, ICU length of stay, and hospital length of stay). Enrolled patients will undergo a water sip test in the ICU and FEES performed by a certified speech-language pathologist. Patients will then be followed during a hospital stay truncated for analysis at 30 days as two cohorts: (1) patients that have dysphagia, that is, abnormal FEES results; and (2) patients who have normal FEES results. Logistic regression will identify dysphagia risk factors (eg, age, Acute Physiology and Chronic Health Evaluation II score, and ventilation duration), while sensitivity and specificity tests will be used to compare the results of the water sip test to the FEES. Survival analysis will be used to evaluate 30-day outcomes. RESULTS: The study anticipates enrolling 200 patients over 18 months. Key outcomes include dysphagia prevalence and risk factors. Final results will be analyzed and reported upon completion of the 30-day follow-up for all participants. As of July 13, 2025, a total of 45 patients had been enrolled, with an average recruitment rate of 7.5 patients per month. CONCLUSIONS: The study findings will promote early intervention for patients with post-critical illness dysphagia, improve multidisciplinary care, and inform policymakers for better resource allocation. This study lays the groundwork for future research and clinical guidelines tailored to Saudi Arabia's health care context. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/68053.

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)0.038
metaresearch head score (Gemma)0.022
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: none
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.038
Threshold uncertainty score0.199

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0380.022
Meta-epidemiology (narrow)0.0040.003
Meta-epidemiology (broad)0.0050.003
Bibliometrics0.0030.004
Science and technology studies0.0040.002
Scholarly communication0.0020.003
Open science0.0030.002
Research integrity0.0040.004
Insufficient payload (model declined to judge)0.0250.006

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 head0.240
GPT teacher head0.655
Teacher spread0.415 · 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
GenreProtocol

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
Published2025
Admission routes2
Has abstractyes

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