A case of hypercalcemia from Pneumocystis jirovecii in an immunosuppressed non-HIV patient
Bibliographic record
Abstract
BACKGROUND: The prevalence of non-HIV related Pneumocystis jirovecii pneumonia (PJP) is increasing with use of immunosuppressive therapies. There are case reports of solid organ transplant recipients on immunosuppressive therapy presenting with mild hypercalcemia, leading to a diagnosis of PJP. Recent studies have shown efficacy of PJP prophylaxis for patients treated with rituximab with a favourable adverse effect profile. CASE PRESENTATION: A 78-year-old male with a history of PR3-ANCA vasculitis, chronic kidney disease and heart failure with reduced ejection fraction presented to our tertiary care hospital with a two-week history of confusion and non-productive cough. Background immunosuppression with rituximab was completed every six months. The patient was found to have hypercalcemia and new infiltrates and ground glass opacities on cross-sectional imaging. Bronchoscopy was performed that was positive for Pneumocystis jirovecii. He was treated with 21 days of trimethoprim-sulfamethoxazole and prednisone with resolution of symptoms and hypercalcemia. CONCLUSIONS: Herein, we present a novel case of PJP in a non-transplant recipient preceded by hypercalcemia. Our case demonstrates the importance for a high suspicion for PJP in chronically immunosuppressed patients on rituximab presenting with PTH-independent hypercalcemia.
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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 | 0.000 | 0.004 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.006 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 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".