Evidence map›Paper›PMID 40037270›Full record

ArticleInternational journal of surgery case reports2025

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

Mohammad Shafiqi, Mujtaba Yama, Oranoos Rayan, Dunya Moghul

Abstract readCase Reports
In one paragraph

Article in International journal of surgery case reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Mohammad ShafiqiDepartment of Pediatric Surgery, Afghan Arya Complex Hospital, Herat, Afghanistan.
Mujtaba YamaDepartment of Pediatric Surgery, Afghan Arya Complex Hospital, Herat, Afghanistan.
Oranoos RayanDepartment of Pediatric Surgery, Afghan Arya Complex Hospital, Herat, Afghanistan.
Dunya MoghulMcGill University Faculty of Medicine and Health Sciences, Montreal, QC, Canada; Division of Pediatric Surgery, Montreal Children's Hospital, Montreal, QC, Canada. Electronic address: dunya.moghul@mail.mcgill.ca.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionCongenital 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.

conclusionImproving 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.

Indexed as

Case reportCongenital cystic adenomatoid malformationMisdiagnosisPneumonia

Identifiers

PMID40037270
PMCPMC11925165

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.