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Multiplexed PCR Diagnosis of Bacterial Atypical Pneumonias in the After COVID Era

2025· article· en· W4415358267 on OpenAlex
H. Willoughby Ellis, Luis Carlos Moreno C., Ip Ada Y. F., Leung Ting Fan, C. H. Alvin, Yathish G.C., Qian Su Yun

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueCurrent Pediatric Reviews · 2025
Typearticle
Languageen
FieldMedicine
TopicPneumonia and Respiratory Infections
Canadian institutionsAlberta Children's HospitalUniversity of Calgary
Fundersnot available
KeywordsDoxycyclineMycoplasma pneumoniaeChlamydiaPneumoniaMycoplasmaAtypical pneumoniaStreptococcus pneumoniaeTetracycline

Abstract

fetched live from OpenAlex

Atypical Pneumonia (AP) is any type of pneumonia not caused by one of the common microorganisms, such as Streptococcus pneumoniae. The most common etiologic microorganisms are intracellular bacteria and viruses, including Chlamydia pneumoniae and Mycoplasma pneumoniae. These microorganisms have been difficult to culture. The pandemic of COVID-19 has changed the management of these APs as a result of the widespread usage of multiplexed PCR tests. We have audited 7 anonymized cases of AP to illustrate the utility of these multiplexed PCR-based tests, which can aid the diagnosis and prompt treatment of several AP cases. In conclusion, AP can be readily diagnosed with a multiplexed PCR test, so that efficacious treatment can be initiated without delay. Chlamydia and Bordetella diseases are readily diagnosed even with NPS specimens. Macrolides and doxycycline are readily available oral medications for treating AP in children. Doxycycline is efficacious for macrolide-resistant mycoplasma disease and does not have the side effects of tetracycline in the young pediatric population.

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.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.583
Threshold uncertainty score0.444

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
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 head0.046
GPT teacher head0.357
Teacher spread0.311 · 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