Antimicrobial-resistance in Enterobacterales is a serious concern in Saudi Arabia. The present study retrospectively analyzed the antibiograms of Enterobacterales identified from 1 January 2019 to 31 December 2019 from a referral hospital in the Aljouf region of Saudi Arabia. The revised document of the Centers for Disease Control (CDC) CR-2015 and Magiorakos et al.’s document were used to define carbapenem resistance and classify resistant bacteria, respectively. The association of carbapenem resistance, MDR, and ESBL with various sociodemographic characteristics was assessed by the chi-square test and odds ratios. In total, 617 Enterobacterales were identified. The predominant (n = 533 (86.4%)) isolates consisted of 232 (37.6%), 200 (32.4%), and 101 (16.4%) Escherichia coli, Klebsiella pneumoniae, and Proteus mirabilis, respectively. In general, 432 (81.0%) and 128 (24.0%) isolates were of MDR and ESBL, respectively. The MDR strains were recovered in higher frequency from intensive care units (OR = 3.24 (1.78–5.91); p < 0.01). E. coli and K. pneumoniae resistance rates to imipenem (2.55 (1.21–5.37); p < 0.01) and meropenem (2.18 (1.01–4.67); p < 0.04), respectively, were significantly higher in winter. The data emphasize that MDR isolates among Enterobacterales are highly prevalent. The studied Enterobacterales exhibited seasonal variation in antimicrobial resistance rates towards carbapenems and ESBL activity.

Intensive care units are complex environments favoring high resistance in microorganisms. This study evaluated the resistance and the distribution dynamics of resistant Gram-negative bacteria (GNB) in patients admitted to intensive care units. This retrospective, record-based, cross-sectional study analyzed all of the antibiograms of patients admitted to the ICUs. The BD Phoenix system (BD Diagnostics, Sparks, MD, USA) was used for bacterial identification and antimicrobial testing. Clinical and Laboratory Standard Institute recommendations were used for antimicrobial testing. Frequencies and percentages of multidrug and pan-drug resistance were calculated. A total of 570 bacterial growths were observed, out of which 437 (76.7%) were of GNB. K. pneumoniae (21.0%), P. aeruginosa (11.8%), and Staphylococcus aureus (13.2%) were the most frequent disease-causing bacteria in intensive care patients. Resistance rates of 73.2% and 70.1% were observed for third- and fourth-generation cephalosporins, respectively, while 48.2% carbapenem and > 65% fluoroquinolones resistance rates were observed. Amikacin was the most effective antibiotic, with a sensitivity rate of 69.5%. A total of 372 (85.1%) of GNB were multidrug resistant. The majority of infections in intensive care patients are caused by multidrug-resistant (MDR) Gram-negative bacteria. Female gender and advancing age are factors favoring MDR. Enhanced surveillance and strengthening of the antimicrobial stewardship program are warranted.

Background and Objectives: In women of reproductive age, leukocytosis is a risk factor that bridges low-grade chronic inflammation (metabolic inflammation), metabolic changes, and polycystic ovary syndrome (PCOS) and is a potential early predictor of PCOS. This study aims to explore the predictive role of quantitative changes in white blood cells (WBCs) and neutrophils in PCOS-associated metabolic changes. Materials and Methods: A total number of 176 blood samples were obtained from age-matched women of the reproductive period, comprising 88 PCOS cases and 88 healthy controls. Hematological, metabolic, and anthropometric indices and ultrasonic assessment were recorded. Results: Elevated levels of luteinizing hormone, testosterone, and lipid parameters except HDL-C levels, and the prevalence of metabolic syndrome in PCOS were statistically significant (p < 0.001). The neutrophil count and neutrophil–lymphocyte ratio (NLR) in PCOS patients were significantly higher (p < 0.001) than their counterparts. The predictive ability of the neutrophil count and neutrophil–lymphocyte ratio (NLR) for PCOS, and possibly its associating subclinical inflammation at optimum cut-off values for the neutrophil count and NLR of >46.62% (sensitivity 94.32% and specificity 74.42%) and >1.23 (sensitivity 71.59% and specificity 100%), respectively. With regard to the areas under the curve (AUC) and Youden indices, they constituted 0.922 and 0.697 for neutrophil count and 0.926 and 0.716 for NLR, respectively. The comparative ROC z-statistic value was 2.222 and a p = 0.026. The multiple linear regression analysis revealed no significant influence for hormonal and metabolic independent variables on the neutrophil count in PCOS cases, but, as can be expected, revealed a significant negative relationship with the other components of WBCs. Conclusion: In conclusion, relative neutrophilia and elevated NLR are potential cost-effective, sensitive, and specific predictors of PCOS that may also shed light on the mechanism of chronic low-grade inflammation that is characteristic of the disease.

Purpose: The antimicrobial prescription in urinary tract infections (UTI) is driven by local data on its pathogenic spectrum and the resistance pattern exhibited by the disease-causing pathogens. We aimed to determine the bacteriological diversity of UTI causing pathogens and antimicrobial resistance in mostly gram-negative bacteria. Methods: This retrospective hospital-based cross-sectional study analyzed the culture and sensitivity reports of urine samples from a referral centre of Aljouf region of Saudi Arabia. All the antibiograms from January 1, 2020, to December 31st 2020 were included. The bacterial identification and antimicrobial testing were carried out by the BD Phoenix system (BD Diagnostics, Sparks, MD, USA). Antimicrobial testing was performed as per the Clinical and Laboratory Standard Institute recommendations. Frequencies of multidrug- and extensively drug-resistance were calculated. Results: Of the 1334 non-duplicate urine samples received, 422 (31.6%) bacterial growths were observed. Of these, 383 (90.8%) and 39 (9.2%) were gram-negative and gram-positive bacterial isolations, respectively. E. coli 161 (38.1%), K. pneumoniae 97 (23.0%), and E. faecalis 18 (4.3%) were frequent aetiologies of UTI. 309 (80.7%) of gram-negative bacteria were multidrug-resistant including 88 (23.0%) extensively drug-resistant. Overall, a resistance rate of > 55 % to 1st through 4th generation cephalosporins was observed except for cefoxitin (43.7%). A resistance rate of 37.6% was observed towards carbapenems with the lowest rate (34.0%) to meropenem. Conclusion: Multi-drug resistant gram-negative bacteria dominate the pathogenic spectrum of UTI in the region. A high resistance rate to cephalosporins and carbapenems exist in gram-negative organisms causing UTI.

Alenzi M, et al. Investig Clin Urol. 2017 May;58(3):210-216. https://doi.org/10.4111/icu.2017.58.3.210

The treatment and outcome of respiratory virus infections differ. SARS-CoV-2, as well as other respiratory viruses such as influenza virus (A and B) and respiratory syncytial virus (RSV), require simultaneous, cost-effective, and rapid differential detection. We used a gold standard five-target single-step RT-PCR to detect influenza viruses, RSV, and SARS-CoV-2, and this method can be extended to detect influenza virus subtypes. As a result, this five-target single-step RT-PCR method is ideal for differentiating respiratory viruses. The 5’ nuclease activity of Taq DNA polymerase is used in the real-time reverse transcription PCR assay. The Taq man fast viral 1-step enzyme is a 4× Master mix and five-target primer probe mix that detects influenza A, influenza B, SARS-CoV-2 ORF1ab, respiratory syncytial viruses A/B and actin. When compared with TaqMan ^TM and Invitrogen superscript ^TM III Platinum and the Meril Kit for SARS-CoV-2, the assay demonstrated 100% sensitivity, specificity, and amplification efficiency of 90.1% for target genes. In conclusion, our one-tube multiplex RT-PCR assay offers a rapid and reliable method for the simultaneous detection of influenza A/B, RSV, and SARS-CoV-2 from nasopharyngeal swabs. This assay has the potential to enhance diagnostic capabilities and improve public health responses during respiratory outbreaks, enabling timely interventions and informed decision making.