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Record W4408097830 · doi:10.1016/j.ijscr.2025.111109

Delayed diagnosis of congenital cystic adenomatoid malformation as pneumonia: A case report

2025· article· en· W4408097830 on OpenAlexaff
Mohammad Shafiqi, Mujtaba Yama, Oranoos Rayan, Dunya Moghul

Bibliographic record

VenueInternational Journal of Surgery Case Reports · 2025
Typearticle
Languageen
FieldMedicine
TopicCongenital Diaphragmatic Hernia Studies
Canadian institutionsMcGill University Health CentreMontreal Children's Hospital
Fundersnot available
KeywordsMedicineCongenital Cystic Adenomatoid MalformationPneumoniaPathologyPediatricsInternal medicinePregnancyGenetics

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.005
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: Case report
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.096
Threshold uncertainty score0.716

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.019
GPT teacher head0.307
Teacher spread0.288 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designCase report
Domainnot available
GenreEmpirical

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".

Quick stats

Citations2
Published2025
Admission routes1
Has abstractyes

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