Abstract
Background Lower respiratory tract infections are a major cause of hospitalization and mortality worldwide. Identifying the specific causative pathogens remains a significant challenge in clinical practice. This study aimed to establish the epidemiological profile of hospitalized patients with suspected lower respiratory tract infections in northern Morocco by analyzing pathogen distribution, co-detections, and antimicrobial resistance genes, with variations according to age and season. Methods A retrospective descriptive study was conducted over a two-year period from December 2023 to November 2025 in the Microbiology Laboratory of Mohammed VI University Hospital Center, Tangier, Morocco. In total, 258 respiratory specimens (sputum, bronchoalveolar lavage, and mini-bronchoalveolar lavage) from hospitalized patients with suspected lower respiratory tract infection were analyzed using the BioFire® FilmArray® Pneumonia Panel Plus (BioFire Diagnostics, LLC, Salt Lake City, UT, USA). The panel targets 27 respiratory pathogens and seven resistance genes. Data were analyzed using descriptive statistics and Pearson's chi-square and Fisher's exact tests as appropriate, with a p-value < 0.05 considered statistically significant. Results The diagnostic yield was high, with at least one pathogen detected in 205 (79.5%) specimens. Co-detections were identified in 139 (52.7%) cases, with the highest frequency observed in children under five years of age and in elderly patients. The microbial landscape was largely dominated by opportunistic Gram-negative bacilli, particularly the Klebsiella pneumoniae group, 89 (34.5%), and the Acinetobacter baumannii complex, 81 (31.4%), which showed a consistent, non-seasonal distribution. Resistance genes were detected in 133 (51.6%) patients, with a predominance of CTX-M and NDM, detected in 63 (24.4%) and 57 (22.1%) samples, respectively. Conclusion This study improved understanding of the distribution of pathogens causing lower respiratory tract infections in hospitalized patients and underscores the utility of multiplex polymerase chain reaction (PCR) for respiratory pathogen identification, providing valuable insights for epidemiological surveillance and diagnosis.