Pulmonary Infections After Bone Marrow Transplantation: High-Resolution CT Findings in 111 Patients
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Bibliographic record
Abstract
OBJECTIVE: The purpose of this study was to review the high-resolution CT findings in patients with pulmonary infection after bone marrow transplantation and to determine distinguishing features among the various types of infection. MATERIALS AND METHODS: This study included 111 consecutive bone marrow transplant recipients who had documented pulmonary infection, high-resolution CT of the chest performed within 24 hr of the beginning of symptoms, and proven diagnosis within 1 week of the onset of symptoms. Two radiologists analyzed the CT scans and reached final decisions regarding the findings by consensus. Statistical analysis was performed using the Fisher's exact test and multivariate analysis; a p value of less than 0.05 was considered statistically significant. RESULTS: The pulmonary infections were due to viruses (n = 57), bacteria (n = 26), fungi (n = 21), and protozoa (n = 1). Six patients had more than one organism responsible for the infection. Nodules that were 1 cm or more in diameter were seen in 13 (62%) of 21 patients with fungal pneumonia, five (19%) of 26 patients with bacterial pneumonia (p = 0.0059), three (10%) of 30 with respiratory syncytial virus (RSV) pneumonia (p = 0.0001), and three (14%) of 22 with cytomegalovirus pneumonia (p = 0.0016). The halo sign was present in 10 of 21 patients with fungal pneumonia, two of 26 with bacterial pneumonia (p = 0.0026), three of 30 with RSV pneumonia (p = 0.0036), and one of 22 with cytomegalovirus pneumonia (p = 0.0015). There was no statistically significant difference in the prevalence of the other CT patterns including small nodules, ground-glass attenuation, and air-space consolidation among viral, bacterial, and fungal infections (all p > 0.05). CONCLUSION: The presence of large nodules and visualization of the halo sign are most suggestive of fungal infection. Other high-resolution CT patterns are not helpful in distinguishing among the various types of infection seen in bone marrow transplant recipients.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it