Assessing bacterial prevalence and resistance in paediatric meningitis: safeguarding the central nervous system.

Introduction: Paediatric bacterial meningitis (PBM) represents a major contributor to childhood morbidity and mortality globally, with heightened susceptibility in low- and middle-income nations where antimicrobial resistance (AMR) is highly prevalent. Pakistan exemplifies this setting, with widespread antibiotic overuse driving AMR expansion. Thus, expediting PBM diagnosis and targeted antibiotic therapy is imperative yet challenged by the dynamic local epidemiology. This study aimed to delineate the recent bacterial etiologies and AMR profiles of PBM from a major Pakistani diagnostics laboratory to inform empirical treatment. Materials and methods: This prospective observational investigation evaluated PBM epidemiology in patients under 18 years old admitted to the study hospital. Standard cerebrospinal fluid analysis identified bacterial pathogens and antibiotic susceptibility patterns. Results: Among 171 PBM cases, 152 (88.9%) had bacterial isolates confirmed via culture. The cohort was 42.7% male with a mean age of 3 months. The most prevalent pathogens among infants younger than 3 months were Escherichia coli, Enterococcus faecium, and Staphylococcus epidermidis, contrasting with S. epidermidis, Streptococcus pneumoniae, and Staphylococcus hominis predominating in older children. Staphylococcal isolates exhibited considerable penicillin and erythromycin resistance but maintained vancomycin and linezolid susceptibility. Other resistance patterns varied. Conclusion: These findings highlight the pressing threat of paediatric AMR in Pakistan, underscoring the need for vigilant AMR surveillance and judicious antimicrobial use. This study provides a reference to current PBM epidemiology to guide context-specific empirical therapy.

Cyberbullying detection: advanced preprocessing techniques & deep learning architecture for Roman Urdu data.

Social media have become a very viable medium for communication, collaboration, exchange of information, knowledge, and ideas. However, due to anonymity preservation, the incidents of hate speech and cyberbullying have been diversified across the globe. This intimidating problem has recently sought the attention of researchers and scholars worldwide and studies have been undertaken to formulate solution strategies for automatic detection of cyberaggression and hate speech, varying from machine learning models with vast features to more complex deep neural network models and different SN platforms. However, the existing research is directed towards mature languages and highlights a huge gap in newly embraced resource poor languages. One such language that has been recently adopted worldwide and more specifically by south Asian countries for communication on social media is Roman Urdu i-e Urdu language written using Roman scripting. To address this research gap, we have performed extensive preprocessing on Roman Urdu microtext. This typically involves formation of Roman Urdu slang- phrase dictionary and mapping slangs after tokenization. We have also eliminated cyberbullying domain specific stop words for dimensionality reduction of corpus. The unstructured data were further processed to handle encoded text formats and metadata/non-linguistic features. Furthermore, we performed extensive experiments by implementing RNN-LSTM, RNN-BiLSTM and CNN models varying epochs executions, model layers and tuning hyperparameters to analyze and uncover cyberbullying textual patterns in Roman Urdu. The efficiency and performance of models were evaluated using different metrics to present the comparative analysis. Results highlight that RNN-LSTM and RNN-BiLSTM performed best and achieved validation accuracy of 85.5 and 85% whereas F1 score was 0.7 and 0.67 respectively over aggression class.

Factors associated with renal dysfunction in hepatitis C-related cirrhosis and its correlation with Child-Pugh score.

OBJECTIVES: To assess factors associated with renal dysfunction (RD) in hepatitis C virus (HCV) cirrhosis, correlate renal parameters with Child-Pugh score (CPS) and find a cut-off value of CPS to determine RD. MATERIALS AND METHODS: It was a cross-sectional study that included 70 cases of liver cirrhosis secondary to HCV from a period of 6 months at Combined Military Hospital, Multan. Diagnosis of HCV was confirmed by serological assay and liver cirrhosis by ultrasonography. CPS was determined and lab reports were taken. Patients were divided into two groups as not having RD (serum creatinine≤1.5 mg/dL) and having RD (serum creatinine≥1.5 mg/dL). Estimated glomerular filtration rate (eGFR) was calculated by chronic kidney disease epidemiology collaboration (CKD-EPI) formula. Data were analyzed using SPSS V.23.0. χ2, Kruskal-Wallis test and Pearson coefficient of correlation were applied. ROC curve was drawn to evaluate cut-off value of CPS for the presence of RD. Level of significance was set at p<0.05. RESULTS: Patients with CP grade B or C develop RD as compared to patients with CP grade A (p=0.000). Mean age, urea, creatinine and eGFR varies significantly among patients who develop RD and patients who do not (p=0.02, p=0.000, p=0.000 and p=0.000, respectively). eGFR negatively correlates with CPS (r=-0.359, p=0.002). Creatinine, urea and ALBI score positively correlates with CPS (r=+0.417, p=0.000; r=+0.757, p=0.000; r=+0.362, p=0.002, respectively). CONCLUSION: Ascites and encephalopathy are associated with RD in HCV cirrhosis.