Nuevos datos sobre el balance hídrico en el acuífero de la Vega de Granada a partir de un modelo de flujo
Bibliographic record
Abstract
Poor retention in HIV care is associated with poor clinical outcomes and mortality. Previous studies of predictors of poor retention have been conducted with a wide variety of populations, using different measures of retention, and occasionally have conflicting results. We studied demographic and psychosocial factors associated with inter-visit interval length in a setting of universal health care and modern cART. Patients attending ≥2 appointments with an HIV specialist at the Toronto General Hospital Immunodeficiency Clinic from 2004 to 2013 were studied. A sub-analysis included psychosocial measures from annual questionnaires for Ontario HIV Treatment Network Cohort Study (OCS) participants. Median inter-visit interval and constancy (percentage of 4-month intervals with ≥1 visit) were calculated by patient. Multivariable generalized estimating equation models identified factors associated with inter-visit interval length and intervals ≥12 months. 1591 patients were included. 615 patients completed an OCS questionnaire and were more likely to be older white MSM from Canada with a viral load (VL) <50 copies/ml. The median (IQR) of patients' median inter-visit intervals was 3.15 (2.78, 3.84) months and median (IQR) constancy was 90% (71%, 100%). Two percent of inter-visit intervals were ≥12 months and 25% of patients had ≥1 interval ≥12 months. Longer inter-visit intervals were associated with younger age, white race, earlier calendar year, longer duration of HIV, VL < 50 copies/mL and higher CD4 counts. Patients who were younger, white, had injection drug use as a risk factor, had a longer duration of HIV, and had VL ≥50 copies/mL were more likely to have an inter-visit interval ≥12 months. In the OCS sub-analysis including psychosocial variables, lower levels of depression were associated with longer inter-visit intervals. Retention at this tertiary care centre was high. Efforts to maximize attendance should focus on younger patients and those with substance abuse issues.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.001 |
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 teacher head, 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".