Nurse Practitioner Care Compared with Primary Care or Nephrologist Care in Early CKD
Bibliographic record
Abstract
BACKGROUND: Early interventions in CKD have been shown to improve health outcomes; however, gaps in access to nephrology care remain common. Nurse practitioners can improve access to care; however, the quality and outcomes of nurse practitioner care for CKD are uncertain. METHODS: In this propensity score-matched cohort study, patients with CKD meeting criteria for nurse practitioner care were matched 1:1 on their propensity scores for ( 1 ) nurse practitioner care versus primary care alone and ( 2 ) nurse practitioner versus nephrologist care. Processes of care were measured within 1 year after cohort entry, and clinical outcomes were measured over 5 years of follow-up and compared between propensity score-matched groups. RESULTS: A total of 961 (99%) patients from the nurse practitioner clinic were matched on their propensity score to 961 (1%) patients receiving primary care only while 969 (100%) patients from the nurse practitioner clinic were matched to 969 (7%) patients receiving nephrologist care. After matching to patients receiving primary care alone, those receiving nurse practitioner care had greater use of angiotensin-converting enzyme inhibitors/angiotensin receptor blocker (82% versus 79%; absolute differences [ADs] 3.4% [95% confidence interval, 0.0% to 6.9%]) and statins (75% versus 66%; AD 9.7% [5.8% to 13.6%]), fewer prescriptions of nonsteroidal anti-inflammatory drugs (10% versus 17%; AD -7.2% [-10.4% to -4.2%]), greater eGFR and albuminuria monitoring, and lower rates of all-cause hospitalization (34.1 versus 43.3; rate difference -9.2 [-14.7 to -3.8] per 100 person-years) and all-cause mortality (3.3 versus 6.0; rate difference -2.7 [-3.6 to -1.7] per 100 person-years). When matched to patients receiving nephrologist care, those receiving nurse practitioner care were also more likely to be prescribed angiotensin-converting enzyme inhibitors/angiotensin receptor blockers and statins, with no difference in the risks of experiencing adverse clinical outcomes. CONCLUSIONS: Nurse practitioner care for patients with CKD was associated with better guideline-concordant care than primary care alone or nephrologist care, with clinical outcomes that were better than or equivalent to primary care alone and similar to those with care by nephrologists. PODCAST: This article contains a podcast at https://dts.podtrac.com/redirect.mp3/www.asn-online.org/media/podcast/CJASN/2023_12_08_CJN0000000000000305.mp3.
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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 | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".