Trimethoprim-Sulfamethoxazole (Bactrim) Dose Optimization in Pneumocystis jirovecii Pneumonia (PCP) Management: A Systematic Review
Bibliographic record
Abstract
pneumonia (PCP) has a substantial impact on the morbidity and mortality of patients, especially those with autoimmune disorders, thus requiring optimal dosing strategies of Trimethoprim-Sulfamethoxazole (TMP-SMX). Therefore, to ensure the safety of TMP-SMX, there is a high demand to review current evidence in PCP patients with a focus on dose optimization strategies; (2) Methods: Various databases were searched from January 2000 to December 2021 for articles in English, focusing on the dose optimization of TMP-SMX. The data were collected in a specific form with predefined inclusion and exclusion criteria. The quality of each article was evaluated using a Newcastle-Ottawa Scale (NOS) for retrospective studies, Joanna Briggs Institute (JBI) critical checklist for case reports, and Cochrane bias tool for randomized clinical trials (RCTs); (3) Results: Thirteen studies met the inclusion criteria for final analysis. Of the 13 selected studies, nine were retrospective cohort studies, two case reports, and two randomized controlled trials (RCT). Most of the studies compared the high-dose with low-dose TMP-SMX therapy for PCP. We have found that a low dose of TMP-SMX provides satisfactory outcomes while reducing the mortality rate and PCP-associated adverse events. This strategy reduces the economic burden of illness and enhances patients' compliance to daily regimen plan; (4) Conclusions: The large-scale RCTs and cohort studies are required to improve dosing strategies to prevent initial occurrence of PCP or to prevent recurrence of PCP in immune compromised patients.
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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 | 0.006 | 0.022 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.007 |
| Bibliometrics | 0.010 | 0.011 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 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".