Abdulaziz S. AlQahtani

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.

Background Tonsillectomy is a common surgical procedure for recurrent tonsillitis and obstructive sleep apnea. Its effects on quality-of-life outcomes using validated instruments remain limited. This study aimed to evaluate the impact of tonsillectomy on health-related quality of life over 12 months using disease-specific and generic outcome measures. Methods This is a prospective cohort study involving 103 adult patients (aged 18–50 years) undergoing elective tonsillectomy. Participants completed the Tonsil and Adenoid Health Status Instrument (TAHSI) and Short Form-12 (SF-12) Health Survey at baseline, 6 months, and 12 months post-operatively. Primary indications included recurrent infection (84.5%), sleep apnea (3.9%), and tonsillar stones (11.7%). Repeated measures ANOVA assessed temporal changes, effect sizes were calculated using Cohen’s d, and multiple regression identified outcome predictors. Results Study participants comprised 53 males (51.5%) and 50 females (48.5%) with a mean age of 30.41 ± 7.63 years. TAHSI scores improved significantly from baseline (46.8) to 6 months (8.9; 80.8% improvement) and 12 months (11.2; 76.1% improvement). All domains showed substantial improvements, with infection symptoms demonstrating the greatest effect (Cohen’s d = 2.01). Clinical significance was achieved by 91.6% of patients for throat infections and 84.2% for overall quality of life. SF-12 Mental Component Scores increased from 47.82 to 54.91, while Physical Component Scores improved from 46.15 to 53.27 at 12 months. Baseline symptom severity predicted outcomes, while age showed no significant association. Conclusion Tonsillectomy produces substantial, sustained improvements in disease-specific symptoms and general quality-of-life measures in adult patients, with benefits maintained over 12 months across multiple health domains.

Noise induced hearing loss is the one of the most preventable causes of hearing loss in all age groups. Occupational, environmental, infectious and genetic factors all play a role in determining the level of hearing loss. However, the use of headphones and personal listening devices is now very common, especially in younger generations. Healthy habits are needed to prevent them from developing hearing loss over time. We aim to assess the awareness level of hearing loss among residents of Hail region and its relation to personal listening devices. This is a cross-sectional survey based study that was conducted in 2021 over a duration of four months. The survey purpose was to assess the level of awareness about the Relation of Noise-Induced Hearing Loss and Use of Headphones. The questionnaire had a total of 37 questions which were divided into 6 categories. All data was analyzed using SPSS 21, and a p-value of <0.05 was deemed significant. The study included a total of 1086 participants. Sampled population age ranged from 18 to 55 years with a mean age of 24.8 ± 12.6 years old. Meanwhile, 636 (58.6%) of the participants were females and 1074 (98.9%) were Saudi. Hearing problems were significantly higher among those who were exposed to noise at work setting than others (26% vs. 15.9%, respectively; P = .001). Duration of the listening session/per day for more than 5 h was significantly associated with higher rates of hearing problems among participants (33.9% vs. 16.5%, respectively = .001). Typical level of TV or radio volume of 90–100 was associated with hearing problems among 32% compared to 11.2% for 0–49% (P = .001). There is a low awareness level of hearing loss and its causes among the population with more than half of the respondent having unhealthy habits in listening to sounds through their personal devices. Factors related to develop hearing loss included age, volume level and duration of weekly sessions.