Molecular Diagnostic Surveillance, Antimicrobial Resistance, and Comorbidity Profiles in Major WHO-Critical-Priority-List Pathogens in a Saudi Tertiary-Care Hospital
Background: Timely integrated diagnostic microbiology combines automated identification and antimicrobial susceptibility testing (AST) with assay-specific molecular confirmation. This allows final resistance classifications to be interpreted within one clinical workflow. The novelty of this study is the integration of these complementary diagnostic outputs with organism identity, specimen source, care setting, and available host context across a mixed-pathogen tertiary-care cohort. We characterized the distribution of major clinical priority-pathogen resistance profiles and examined clinical factors associated with high-priority resistances. Methods: This retrospective cross-sectional laboratory-based study included 847 non-duplicate clinical isolates recovered during routine care from a pre-established surveillance cohort at King Salman Specialist tertiary-care hospital in Saudi Arabia from July 2025 to July 2026. Automated organism identification/AST was combined with assay-specific GeneXpert molecular confirmation where applicable. GeneXpert SA Nasal Complete was used for Staphylococcus aureus/MRSA confirmation and Xpert Carba-R for relevant carbapenemase targets; organisms outside these target panels, including Streptococcus pyogenes and Candida spp., were characterized by routine culture and automated identification. Carbapenem resistance was defined by imipenem and/or meropenem resistance and reported as carbapenem-resistant Enterobacterales (CRE) for Klebsiella pneumoniae and Escherichia coli, carbapenem-resistant Pseudomonas aeruginosa (CRPA), and carbapenem-resistant Acinetobacter baumannii (CRAB). Methicillin-resistant Staphylococcus aureus (MRSA) was classified by cefoxitin resistance with concordant GeneXpert confirmation. Exploratory multivariable logistic regression assessed clinical factors associated with CRE and MRSA detection. Results: Gram-negative organisms accounted for 546 isolates (64.5%), Gram-positive organisms accounted for 281 (33.2%), and fungi accounted for 20 (2.4%). Klebsiella pneumoniae was most frequent (176/847; 20.8%), followed by Staphylococcus aureus (169/847; 20.0%) and Escherichia coli (156/847; 18.4%). Priority resistance was highest in Acinetobacter baumannii, with CRAB in 73/74 isolates (98.6%), followed by CRPA in 38/83 P. aeruginosa (45.8%), MRSA in 68/164 S. aureus (41.5%), CRE in 57/176 K. pneumoniae (32.4%), and CRE in 10/156 E. coli (6.4%). In the complete-case CRE model (n = 246; 38 events), K. pneumoniae had higher adjusted odds of CRE than E. coli (aOR 3.91, 95% CI 1.74–9.73; p = 0.002). In the MRSA model (n = 160; 68 events), non-urinary specimens (aOR 3.31, 95% CI 1.21–10.16; p = 0.025) and recorded comorbidity (aOR 3.40, 95% CI 1.26–9.64; p = 0.017) were independently associated with MRSA detection. Conclusions: The integrated diagnostic workflow revealed marked organism-specific differences in resistance, led by a very high CRAB burden and substantial CRPA, MRSA, and K. pneumoniae CRE. Interpreting the final laboratory classification together with organism identity, specimen source, and care setting provides a practical framework for focused diagnostic reporting, antimicrobial stewardship, and infection-control prioritization in tertiary care.