Evidence map›Paper›PMID 41815598›Full record

ArticleCureus2026

Epidemiological Analysis and Susceptibility Profile of Pathogens Isolated in Blood Cultures From Hospital Angeles Lindavista in Mexico City.

Mauricio Castillo-Salazar, Erika Perez Sanjulian-Krasovsky, María Citlali Martínez-Sánchez, José Luis Pinacho-Velázquez, Carlos Andrey Diosdado-Franco, Luis Gerardo Balcázar-Ochoa, Laura Gomez-Virgilio

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Article in Cureus, 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

What it found

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

7 authors.

Mauricio Castillo-SalazarLaboratory and Blood Bank, Hospital Angeles Lindavista, Mexico City, MEX.
Erika Perez Sanjulian-KrasovskyMedical Education, Hospital Angeles Lindavista, Mexico City, MEX.
María Citlali Martínez-SánchezMedical Education, Hospital Angeles Lindavista, Mexico City, MEX.
José Luis Pinacho-VelázquezPediatrics, Hospital Angeles Lindavista, Mexico City, MEX.
Carlos Andrey Diosdado-FrancoGeneral Management, Hospital Angeles Lindavista, Mexico City, MEX.
Luis Gerardo Balcázar-OchoaPhysiology, Facultad de Medicina de la Universidad Nacional Autónoma de México, Mexico City, MEX.
Laura Gomez-VirgilioResearch and Teaching Coordination, Hospital Angeles Lindavista, Mexico City, MEX.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background Bloodstream infections contribute to morbidity and mortality. A wide variety of microorganisms can be identified and recovered from these infections, and blood culture is the primary method for detecting them and determining their antimicrobial susceptibility. This helps clinicians confirm the efficacy of the initial empiric therapy or select an appropriate alternative based on the susceptibility of the isolated microorganism, thereby reducing the risks associated with antimicrobial misuse. We aimed to describe and analyze the bacteria isolated in blood culture samples, their antimicrobial resistance at Hospital Angeles Lindavista, and their association with demographic and clinical characteristics; to provide tools for the effective antimicrobial treatment of bacteremia; and to monitor the evolution of microbial resistance in this institution. Methods A retrospective observational study was conducted at Hospital Angeles Lindavista, including all patients with suspected sepsis, as determined by the physician's judgement, who had at least one blood sample collected from January 2024 to December 2024. Variables examined included age, gender, clinical service, comorbidities, risk factors, diagnoses, detected pathogens, and antibiogram. The relationship between a specific bacterium and an affected organ system was analyzed using a chi-square test, followed by residual analysis. To explore potential associations between clinical variables, regression models were used. Finally, to verify the stability of the results, we performed a sensitivity analysis using only complete cases and compared these findings to those from the entire dataset. The statistical analysis was conducted using R version 4.4.1 (2024-06-14 ucrt) (R Foundation for Statistical Computing, Vienna, Austria) in RStudio (Posit Software, Boston, MA). Results We identified an adult population with a median age of 49 years and a predominance of men. The median hospital stay was eight days; hospitalization was the most common service, and the gastrointestinal system was most affected. Regarding risk factors, 31 patients (16%) had type 2 diabetes mellitus, and sepsis was the most frequent diagnosis (n = 18, 9%).

Indexed as

antimicrobial susceptibilitybloodstream infectionsclinical predictorsempiric antibiotic selectionmicrobial resistance

Identifiers

PMID41815598
PMCPMC12973916

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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.