Romania rural health dataset 2015-2017
Bibliographic record
Abstract
Abstract Data from 2988 subjects were collected during health campaigns aimed at providing free medical care in rural, remote areas of Romania. Rural residents underwent medical examinations and blood tests, to evaluate the prevalence CVDs and of their major risk factors, i.e. hypertension (HT), obesity, smoking, diabetes, and dyslipidemia. The overall prevalence of CVD was 14%: coronary heart disease (9%), stroke (2.9%), peripheral artery disease (1.3%) and atrial fibrillation (3.2%). Prevalence of HT was unexpectedly high (72.8%) as was the proportion of newly diagnosed HT (33.3%). Of those aware, 65% were treated, but only 17.2% were on target. Other CV risk factors prevalence was: obesity (31.3%), diabetes mellitus (12.6%), dyslipidemia (64.7%) and smoking (16.2%). Obesity, smoking, and diabetes increased the likelihood of developing CVD by 1.7 times, with HT being the leading risk factor by 2.7-fold. The 10-year risk of a cardiovascular event (Framingham score) was high (over 20%) in one third of the subjects, while the risk of a fatal CV event in the following 10 years (SCORE) was above 5% in almost a quarter (22%) of the studied population. In this study, the first focusing on the health of the rural population in Romania, the prevalence of HT was unexpectedly high, as was the cardiovascular risk, pointing to the need of strategies to improve medical care. Methods Information regarding the health of rural residents was collected during campaigns organized by the “Doctors’ Caravan Association” - a non-governmental organization composed of physicians and medical students volunteering to travel to Romania’s rural regions and offer free medical services. The selection of the settlements was done according to the association’s objectives, aimed at providing basic medical care to people in rural areas with low accessibility to medical services. The study was conducted between 2015 and 2017 in 20 villages/small towns located mostly in the South and East of Romania. A total of 2988 patients were examined by the volunteering physicians. After obtaining an informed consent, blood tests were drawn from the inhabitants willing to be examined. The blood panel included a complete blood count, lipid profile (cholesterol, triglycerides, low density lipids), glucose and glycated hemoglobin, as well as markers for liver and kidney function (alanine transaminase and creatinine) and chronic hepatitis B and C markers. On a second visit, a team of medical doctors recorded a standardized medical history, measured the blood pressure (BP), performed a full physical exam and gave treatment recommendations based on the clinical findings and the laboratory tests.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.024 | 0.011 |
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".