Comparison of Preventive Care Provided to Dialysis Patients by Nephrologists and to Patients Followed in General Medical Clinics: Compliance with American College of Physicians Guidelines
Bibliographic record
Abstract
Most end‐stage renal disease (ESRD) patients do not have primary‐care providers, and preventive medicine often is provided by their nephrologists. Little has been written about their success in providing this care. We studied all patients on dialysis at our hospital and compared their preventive care to a control group followed in the general medical clinic. The general medical group showed higher compliance with Pap smears (89% vs 48%), mammography (87% vs 62%), fecal occult blood testing (75% vs 50%), and pneumococcal vaccination (55% vs 28%). The ESRD group had better compliance with influenza vaccination (70% vs 55%) and lipid profile (100% vs 75%). When the subgroup of patients on hemodialysis (HD) was compared with patients on peritoneal dialysis (PD), it was shown that HD patients were more likely than PD patients to receive preventive care. We also compared diabetes‐specific care. The ESRD group had a higher rate of HbA 1C (100% vs 78%) and lipid monitoring (100% vs 76%), diabetes education (100% vs 84%), and podiatry visits (70% vs 38%). There was no difference in ophthalmologic examination or influenza vaccination. We found that nephrologists provide preventive care to ESRD patients with success approximately equal to primary‐care physicians in our institution, although in different parameters. Ready access to dialysis patients and their blood and unit‐specific policies contribute to compliance that is above national averages. Further improvements can be made by additional preventative measures policies, by physician and patient education, and by monitoring primary‐care compliance in the chart.
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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 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".