Discontinuing <i>Pneumocystis jirovecii</i> Pneumonia Prophylaxis in HIV-Infected Patients With a CD4 Cell Count <200 cells/mm <sup>3</sup>
Bibliographic record
Abstract
OBJECTIVE: To review the evidence for discontinuing primary and secondary Pneumocystis jirovecii pneumonia (PJP) prophylaxis in HIV-infected patients with a CD4 count <200 cells/mm(3). DATA SOURCES: We conducted a literature search in MEDLINE, EMBASE, Cochrane Library, Google Scholar, and the International Aids Society Library (up to August 2015) using the following key search terms: Pneumocystis jirovecii, pneumonia, human immunodeficiency virus, primary prophylaxis, secondary prophylaxis, and discontinuation. STUDY SELECTION AND DATA EXTRACTION: All English-language studies that evaluated discontinuation of primary and/or secondary PJP prophylaxis in HIV-infected patients with CD4 count <200 cells/mm(3) were included. DATA SYNTHESIS: Five studies were identified, which varied in design, sample size, outcomes, and duration of follow-up. Three studies examined discontinuation of primary and secondary PJP prophylaxis; 1 study evaluated discontinuing primary PJP prophylaxis; and 1 study evaluated stopping secondary PJP prophylaxis. Two out of the 5 studies pooled data for all opportunistic infections. Overall, there was a low incidence of PJP among HIV-infected patients who discontinued primary PJP prophylaxis and were well controlled on antiretroviral therapy (ART). CONCLUSIONS: Discontinuation of primary PJP prophylaxis appears to be safe in patients on combination ART with a suppressed HIV viral load and a CD4 count >100 cells/mm(3). Additional data are needed to support the safety of discontinuing secondary PJP prophylaxis. Decisions to discontinue PJP prophylaxis in patients with a CD4 count <200 cells/mm(3) should be done on an individual patient basis, taking into consideration clinical factors, including ongoing adherence to ART.
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 | 0.006 | 0.033 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".