Outpatient Diabetic Care in a Public Central Hospital: Patient Characteristics, Therapeutic Regimens and Results
Bibliographic record
Abstract
Background: Report of patient characteristics, treatment and results of diabetic patients assisted at a public tertiary hospital. Patients and Methods: Standardized clinical and analytical data regarding patients assisted during 2 years. Results: Nine hundred and seventy-one visits and 271 patients were studied. Patients with type 1 (DM1) (15%), type 2 treated with insulin (DM2-IT) (23%) and type 2 treated with oral agents (DM2-NIT) (56%) were included. On referral, long-standing disease (11 ± 9 years) was present with poor metabolic control (glycated hemoglobin, HbA1c 8.4 ± 2.0%). Microvascular disease (33-40%), high blood pressure (HBP) (56%) and dyslipidemia (61%) were common. Intensive treatment was used in less than half of the patients. Most of DM2 patients were under medication for HBP and were using anti-platelet agents (76%) but less than half (46%) were using lipid-lowering drugs. Despite frequent medical visits, metabolic control remained poor, HbA1c 8.0 ± 1.9%. In almost half of DM2 patients, systolic blood pressure (45%), serum cholesterol (36%), serum triglycerides (42%) and HDLc (37%) remain higher or lower than recommended. Conclusions: Two fundamental vectors seem to underlie the clinical evolution: aging and beta-cell function. DM2-IT represents a group of specially difficult patients. Intensive medical assistance of diabetic patients is still far from routine even in tertiary hospitals. J Endocrinol Metab. 2014;4(1-2):13-24 doi: http://dx.doi.org/ 10.14740 / jem205w
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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 | 0.000 |
| 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".