Evidence map›Paper›PMID 42626216›Full record

ArticleWorld journal of methodology2026

Stepwise model to differentiate pathogenic from non-pathogenic organisms in lower-respiratory isolates: Effectiveness and feasibility prospective cohort study.

Shivnarayan Sahu, Balram Ji Omar, Mukesh Bairwa, Prakhar Sharma, Partha Sahu, Prasan Kumar Panda

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Article in World journal of methodology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Shivnarayan SahuDepartment of Medicine, All India Institute of Medical Sciences, Rishikesh 249203, India.
Balram Ji OmarDepartment of Microbiology, All India Institute of Medical Sciences, Rishikesh 249203, India.
Mukesh BairwaDivision of Internal Medicine, All India Institute of Medical Sciences, Rishikesh 249203, India.
Prakhar SharmaDivision of Pulmonary, Sleep and Critical Care Medicine, All India Institute of Medical Sciences Rishikesh, Rishikesh 249203, India.
Partha SahuDepartment of Medicine, All India Institute of Medical Sciences, Rishikesh 249203, India.
Prasan Kumar PandaInternal Medicine (ID Division), All India Institute of Medical Sciences, Rishikesh 249203, India. motherprasanna@rediffmail.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundLower respiratory tract infections remain a major cause of morbidity and mortality among hospitalized patients. However, isolating organisms from respiratory samples often leads to diagnostic uncertainty due to the coexistence of colonizers, commensals, and contaminants. To address this challenge, this study employed a structured, stepwise exploratory model to differentiate true pathogens from non-pathogens in aerobic respiratory cultures and multiplex polymerase chain reaction (Biofire FilmArray) results.

aimTo determine pathogen

methodsThis prospective, longitudinal time-bound study was conducted over three months (August 2024 to October 2024) at a tertiary care center in Northern India. Adult patients (≥ 18 years) with positive lower respiratory tract samples were enrolled. Each isolate was independently classified by the treating clinician, microbiologist, and study investigator using a six-step clinical-microbiological algorithm that incorporated clinical signs, Sequential Organ Failure Assessment score trends, alternative infection sources, host factors, and outcome data. The final classification was determined by the investigator. Outcomes, including treatment response and mortality at 28 days, were compared across pathogen and non-pathogen groups.

resultsOf the 145 included patients, 131 (90.3%) were classified as pathogens and 14 (9.7%) as non-pathogens. Cohen's Kappa between investigator and microbiologist classifications was 0.28, indicating fair agreement. Among pathogen cases, 68 (51.9%) responded to treatment. In contrast, 12 of 14 non-pathogen cases (85.7%) were not treated, with favorable outcomes in most, and only one unrelated death (7.1%).

conclusionThe structured clinico-microbiological model strongly correlates with treatment outcomes, making it useful for differentiating infection from colonization. Crucially, microbiological detection alone doesn't determine pathogenicity. Integrating clinical, laboratory, and outcome data is essential for rational antibiotic use and effective antimicrobial stewardship.

Indexed as

Aerobic respiratory cultureAntimicrobial stewardshipBiofire FilmArrayLower respiratory tract infectionsPathogen classificationSequential Organ Failure Assessment score

Identifiers

PMID42626216
PMCPMC13491173

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