Tuberculosis and diabetes in Guyana
Bibliographic record
Abstract
OBJECTIVES: This study was conducted to determine the prevalence of diabetes mellitus among tuberculosis (TB) patients attending three TB clinics in Guyana. METHODS: A cross-sectional study was conducted among TB patients attending TB clinics in three regions in Guyana. A structured questionnaire was used to collect demographic, clinical, and risk factor data. Random blood sugar testing was done using the OneTouch UltraSmart glucometer (LifeScan, Inc., 2002). RESULTS: One hundred TB patients were recruited; 90 had pulmonary TB and 10 had extrapulmonary disease. Fourteen patients were classified as diabetic: 12 had been previously diagnosed as diabetic by a physician and two had abnormally high random blood sugar at the time of enrolment. Of the 12 known diabetics, seven had been diagnosed before TB was discovered, three were identified at the time TB was diagnosed, and two after TB was diagnosed. All 14 diabetic patients presented with pulmonary TB. Thirty-one patients were HIV-positive and 28 of these had pulmonary TB, whereas three had extrapulmonary TB. None of the diabetics were infected with HIV. TB-diabetic patients tended to be older than non-diabetics (median age 44 vs. 36.5 years), were more likely to have been incarcerated at the time of TB diagnosis than non-diabetics (p=0.06), and were more likely to have an elevated (random) blood sugar level (p=0.02). Clinically, diabetes did not influence the presentation of TB. CONCLUSIONS: This study clearly highlights that diabetes and HIV are frequent in Guyanese TB patients. Routine screening of TB patients for diabetes and diabetic patients for TB should be speedily implemented. The National TB Programme should work closely with the diabetes clinics so that TB patients who are diabetics are optimally managed.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".