A Survey of Rheumatologists’ Practice for Prescribing Pneumocystis Prophylaxis
Bibliographic record
Abstract
OBJECTIVE: Pneumocystis pneumonia (PCP) occurs in immunocompromised hosts, in both the presence and absence of human immunodeficiency virus (HIV) infection, with substantial morbidity and a heightened mortality. We assessed practice patterns among rheumatologists for prescribing PCP prophylaxis. METHODS: Invitations to an online international survey were e-mailed to 3150 consecutive members of the American College of Rheumatology. RESULTS: Completed surveys were returned by 727 (23.1%) members. Among respondents, 505 (69.5%) reported prescribing prophylaxis. Factors associated with significantly higher frequency of prescribing PCP prophylaxis included female gender (OR 1.47, p = 0.03), US-based (OR 1.77, p = 0.004), academic-based (OR 2.75, p < 0.001), in practice less than 10 years (OR 4.08, p < 0.001), having previously treated PCP (OR 2.62, p < 0.001), and in a practice with a higher proportion of patients maintained on chronic glucocorticoids (OR 2.04, p < 0.001) or other immunosuppressant medications (OR 3.19, p = 0.003). In multivariate analysis, rheumatologists early in their careers and those with academic and US-based practices were more likely to prescribe prophylaxis. Among prescribers, the most important determinants for issuing prophylaxis were treatment regimen (68.6%), rheumatologic diagnosis (9.3%), and medication dosage (8.3%). CONCLUSION: Nearly one-third (30%) of the rheumatologists surveyed reported that they never prescribed PCP prophylaxis. While the patient characteristics for which prophylaxis was prescribed varied widely, physician demographics were strongly predictive of PCP prophylaxis use. These findings suggest that development of consensus guidelines might influence clinical decision-making regarding PCP prophylaxis in HIV-negative patients with rheumatologic diagnoses.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".