Does incontinence severity correlate with quality of life? Prospective analysis of 502 consecutive patients
Bibliographic record
Abstract
OBJECTIVE: The Fecal Incontinence Severity Index (FISI) is widely used in the assessment of patients with faecal incontinence, but the relationship between FISI and the measurements of quality of life, such as the Fecal Incontinence Quality of Life Scale (FIQL) and the Medical Outcomes Survey (SF-36) has not been evaluated previously. The aim of the present study was to evaluate the relationship between disease severity and quality of life in a large cohort of patients. METHOD: Five hundred and two consecutive patients (84.4% female, mean age 56 years) were evaluated for faecal incontinence between May 2004 and October 2005. Patients completed FISI, FIQL and SF-36 questionnaires. Pearson's coefficients were determined for the relationships between FISI and subscales of FIQL and SF-36. Quality of life scores were compared between groups of patients with different levels of incontinence severity (mild, moderate, severe) using Student's t-test. RESULTS: Sixty-eight per cent of patients were incontinent of solid stool, 62% of liquid stool, and 90% of gas or mucus. The average FISI score was 36 (0-61). Moderate correlations were found between FISI and all subscales in FIQL (negative 0.29 to 0.41; P < 0.0001). Weak correlations were found between FISI and the social functioning (-0.21) and mental health (-0.17) scales in SF-36 (P < 0.05). Scores on the FIQL differed significantly between mild, moderate and severe incontinence. CONCLUSION: FISI was only moderately correlated with a disease-specific quality of life measurement (FIQL). Even though this supports the common assumption that the quality of life in the patients with faecal incontinence worsens with an increase in disease severity, it also stresses the need of measuring both variables to determine the true impact of any treatment.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".