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Record W4296475585 · doi:10.1136/gutjnl-2022-basl.89

P38 Feasibility of detection and quantification of post ICU syndrome in a cohort of cirrhosis patients

2022· article· en· W4296475585 on OpenAlexaboutno aff
Sreelakshmi Kotha, Alexandra Agorogianni, Alex S Hong, Chithra Mohan, Katie Susser, Andrew Slack, Joel N. Meyer, Philip Berry

Bibliographic record

VenueAbstracts · 2022
Typearticle
Languageen
FieldMedicine
TopicLiver Disease and Transplantation
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineCirrhosisHospital Anxiety and Depression ScaleAnxietyIntensive care unitMechanical ventilationCohortDepression (economics)Intensive careGeneralized anxiety disorderInternal medicineEmergency medicineIntensive care medicinePsychiatry

Abstract

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Background and Aims Cirrhosis accounts for 3 to 4.5% of admissions to the Intensive Care Unit (ICU) and modern advances in ICU care have improved survival. Prolonged ICU stays are associated with physical and psychological sequelae like post -traumatic stress disorder, anxiety, depression and sexual dysfunction. Post intensive care syndrome (PICS) affects patients and families, and is associated with increased healthcare costs. Hitherto, the prevalence and severity of PICS in cirrhosis has not been investigated. This pilot study aims to determine its prevalence and the feasibility of using common psychological measures in its assessment. Method We identified patients with cirrhosis admitted to ICU for organ support from 2017 to 2021. Non-cirrhotic controls were randomly selected for the same period. Demographic data, aetiology and severity of cirrhosis, reason for ITU admission, mechanical ventilation duration, previous psychological morbidity, dependency and sedation details were recorded. Validated questionnaires [Pittsburgh Sleep Quality Index (PSQI), Montreal Cognitive Assessment (MOCA), Patient Health Questionnaire (PHQ-9), Impact of Events Scale, Generalized Anxiety Disorder 7 (GAD-7), and sexual dysfunction questionnaire] were used to assess for features of PICS in a post-ICU survival clinic or following contact by investigators. Mann-Whitney U test was used to detect statistical significance. Results 36 chronic liver disease patients were screened for eligibility. 6 patients had died at the time of recruitment, 8 did not require organ support and 2 did not have a definitive diagnosis of cirrhosis and were excluded. 3 patients could not be contacted. 17 were included in the study. Controls were selected from an existing database of ICU patients. Mean age was 52 years in the cirrhosis group and 47 in controls. Aetiology of cirrhosis was alcohol in 70.6%, non-alcoholic fatty liver disease in 11.8%, autoimmune in 5.9% and cryptogenic in 5.9%. Mean MELD was 19 and mean ACLF score was 48. The mean intubation period was 13 days in the cirrhosis group and 23 in controls. 64.7% of the cirrhosis patients were sedated with propofol and fentanyl compared to 47.1% of controls. 35.3% of patients in cirrhosis group had a psychiatric background versus 17.6% of controls. 47.1% of cirrhosis patients required psychological support after ICU admission versus 35.29% of control. 5 of 6 psychological morbidity scores were numerically higher in the cirrhosis cohort, however statistical difference was not detected (see table 1). Conclusion We identified an increased need for psychiatric support post-ICU in cirrhosis patients compared to controls, though in this pilot study significant differences in morbidity was not detected through questionnaire returns. This signal requires further study in larger cohorts.

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)0.000
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 score0.003
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.018
GPT teacher head0.257
Teacher spread0.240 · 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
Published2022
Admission routes1
Has abstractyes

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