Anxiety in cirrhosis: a prospective study on prevalence and development of a practical screening nomogram
Bibliographic record
Abstract
Objectives The prevalence and effects of anxiety on health-related quality of life and clinical outcomes in cirrhosis are not well understood. This is increasingly relevant during COVID-19. Our aim was to use the Mini-International Neuropsychiatric Interview (MINI) to determine the prevalence of anxiety, its association with clinical outcomes in cirrhosis and to develop a rapid cirrhosis-specific anxiety screening nomogram. Methods Adults with a diagnosis of cirrhosis were prospectively recruited as outpatients at three tertiary care hospitals across Alberta and followed for up to 6 months to determine the association with unplanned hospitalization/death. The Hospital Anxiety and Depression scale (HADS) was used as a screening tool as it is free of influence from somatic symptoms. Anxiety was diagnosed using the MINI. Results Of 304 patients, 17% of patients had anxiety by the MINI and 32% by the HADS. Anxious patients had lower health-related quality of life as assessed by the chronic liver disease questionnaire (P < 0.001) and EuroQol Visual Analogue Scale (P < 0.001), and also had higher levels of frailty using the Clinical Frailty score (P = 0.004). Multivariable analysis revealed smoking and three HADS subcomponents as independent predictors of anxiety. These were used to develop a rapid screening nomogram. Conclusion A formal diagnosis of anxiety was made in approximately one in five patients with cirrhosis, and it was associated with worse HrQoL and frailty. The use of a 4-question nonsomatic symptom-based nomogram requires validation but is promising as a rapid screen for anxiety in cirrhosis.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".