Vomiting, diarrhea and stiff neck: What is your call?
Bibliographic record
Abstract
Introduction: There are a number of well-established barriers to accessing primary care. The LINKED Study set out to improve primary care usage through 1-on-1 counseling and referrals for patients with diabetes being treated at local free clinics. We hypothesized that this educational intervention paired with expedited referral would increase the use of federally qualified health centers (FQHCs) as a source of health care and ultimately lead to improved diabetic health. Methods: Medical student volunteers counseled participants on the importance of primary care. The participants then completed surveys about diabetic health, socioeconomic status, and general demographics. Participants were subsequently assigned to 1 of 2 FQHCs; designated care coordinators facilitated appointments. At the end of a 9-month action period, participants repeated the initial surveys, now including appointment history and health data (hemoglobin A1c (%) [HbA1c], body mass index). Results: Sixty-eight participants were enrolled. The average time since a diagnosis of diabetes mellitus was 8.3 years (standard deviation [SD], 8.4 years), and 25% of participants used insulin. Mean baseline HbA1c for participants with a recorded value (n = 55) was 9.5 (SD, 2.5). FQHC appointments were scheduled by 68% of participants; 38% of the participants attended ≥2 appointments. The most common reported barriers to accessing primary care were no prior health insurance (85.3%) and cost of medical care (72.1%). In our follow-up assessment there was a statistically significant decrease in HbA1c for those linked to FQHCs (9.5 [SD, 2.3] to 8.3 [SD, 2.2]; n = 21). Conclusions: This study demonstrates the utility of a linkage program from free clinics to FQHCs. Those individuals with diabetes receiving health care from an FQHC demonstrated improved glycemic control.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.019 | 0.005 |
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".