Concurrent Infection with SARS-CoV-2 and Pneumocystis jirovecii in Immunocompromised and Immunocompetent Individuals
Bibliographic record
Abstract
Coronavirus disease 2019 (COVID-19) may occur with concurrent infections caused by bacterial and fungal microorganisms. This systematic review evaluated studies reporting concomitant COVID-19 and Pneumocystis jirovecii pneumonia (PJP). We found 39 patients (74% male, median age: 56.8 (range: 11–83) years), including 66% immunosuppressed individuals (23% HIV-infected and 41% on long-term corticosteroid therapy). Patients were characteristically severely ill (mechanical ventilation: 70%), associated with 41% mortality. The median lymphocyte count was 527 cells/mm3 (range: 110–2200), and the median CD4+ T cell count was 206 cells/mm3 (range: 8–1021). We identified three patterns of concurrent COVID-19 and P. jirovecii infection. The first pattern (airway colonization with a low burden of P. jirovecii) does not seem to modify the COVID-19 course of illness. However, P. jirovecii superinfection, typically occurring weeks after COVID-19 diagnosis as a biphasic illness, and P. jirovecii coinfection characteristically results in progressive multilobar pneumonia, which is associated with poor outcomes. To support this categorization, we reported three patients with concurrent PJP and COVID-19 identified in our institution, presenting these clinical scenarios. The diagnosis of PJP requires a high index of suspicion, since clinical and radiological characteristics overlap with COVID-19. Observational studies are necessary to determine the PJP burden in patients with COVID-19 requiring hospitalization.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".