Delayed diagnosis of congenital cystic adenomatoid malformation as pneumonia: A case report
Bibliographic record
Abstract
INTRODUCTION: Congenital cystic adenomatoid malformation (CCAM) is a rare pulmonary anomaly typically diagnosed prenatally. In developing countries like Afghanistan, limited medical infrastructure leads to delayed diagnosis and improper treatment. This case highlights diagnostic challenges in resource-constrained settings. PRESENTATION OF CASE: A 3.5-month-old boy presented with respiratory distress, cough, fever, and tachypnea. Symptoms began at 15 days, with repeated ineffective pneumonia treatments. A pediatric surgeon's referral led to a chest CT scan revealing CCAM in the right lung's upper and middle lobes. The patient required oxygen and bronchodilators but avoided intubation. A right upper and middle lobectomy was performed, with discharge four days later. DISCUSSION: This case illustrates challenges in diagnosing congenital lung anomalies in resource-limited environments. CCAM misdiagnosis as pneumonia underscores the need for comprehensive diagnostic approaches. Key observations include the necessity of advanced imaging, increased clinical awareness, and robust pediatric respiratory disease management. Healthcare providers must maintain high suspicion when treating recurrent respiratory conditions unresponsive to standard treatments. CONCLUSION: Improving maternal healthcare access and diagnostic capabilities in low-income countries is crucial for timely CCAM detection. Addressing challenges requires expanding diagnostic capabilities, enhancing healthcare education, and investing in medical technologies. These improvements will ensure better patient outcomes in resource-constrained settings.
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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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.006 | 0.005 |
| Insufficient payload (model declined to judge) | 0.002 | 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".