Evaluation of Stool Frequency and Stool Form as Measures of HIV-Related Diarrhea
Bibliographic record
Abstract
PURPOSE: In the highly active antiretroviral therapy (HAART) era, HIV-related diarrhea remains common. Our aim was to evaluate stool frequency and form as measures of HIV-related diarrhea. METHOD: Forty-eight HIV-infected persons with self-reported diarrhea were studied. In Analysis 1, self-reported retrospective and 7-day prospective measurement of stool frequency and form were compared using Spearman's correlation coefficient. In Analysis 2, diarrhea was measured during two 8-hour study periods in a subgroup (n = 20) using stool weight (Wt), diarrhea symptom score (Sx Score), stool frequency (SP-freq), and stool form using the Bristol Stool Form Scale (SP-BSFS). SP-freq and SP-BSFS were modeled alone and in combination to predict Wt and Sx Score. RESULTS: In Analysis 1, correlation between measures of stool frequency was rs = 0.62 (p < .0001) but was rs = 0.16 (p = .26) between measures of stool form. In Analysis 2, the two-predictor model best predicted Wt, whereas the model using SP-freq only performed as well as the two-predictor model to predict Sx Score. CONCLUSION: Prospective measurement of stool frequency performed well; in some situations, it may be used alone to measure severity of HIV-related diarrhea. Our findings may be used to design more rigorous clinical trials in HIV.
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".