Emergence of colistin-resistant gram-negative rods in intensive care units: A cross-sectional study from a developing country.

Objectives: To determine the clinical features, outcomes, and factors associated with the emergence of colistin-resistant gram-negative rods isolated from patients admitted to intensive care units. Methods: This cross-sectional study was conducted at the intensive care units of Liaquat National Hospital, from April 2019 to February 2020. Gram-negative rods resistant to colistin with minimum inhibitory concentrations ⩾ 4 mcg/mL according to Clinical and Laboratory Standards Institute criteria as reported in cultures were included. Clinical, demographical data and treatment given were recorded and analyzed using SPSS version 25. Results: A total of 93 patients were included; 58.1% were males. The mean age of patients was 59.48 ± 18.36 years. The most common organism isolated was Klebsiella pneumoniae (91.4%). The most common specimen was the tracheal (62.4%). Ventilator-acquired pneumonia was seen in 38.7%. The most common co-morbid disease seen in patients was diabetes (41%); 77% had a symptomatic infection and were treated with a combination of 2 or more antibiotics, most commonly meropenem plus fosfomycin. The most common susceptible antibiotics were fosfomycin (72%) and tigecycline (50.5%). Mean intensive care unit stay and total duration of hospital stay were prolonged (16.83 ± 12.93 and 23.34 ± 17.52 days, respectively). Forty-eight (62.3%) patients with symptomatic infection with colistin-resistant isolates were treated and discharged, and mortality was seen in 23 (29.9%). A significant association was found between mortality and symptomatic infection, endotracheal intubation with mechanical ventilation (p = 0.003), and a prolonged hospital stay of >20 days (p = 0.041). Conclusion: Colistin-resistant gram-negative rods pose a significant problem especially in developing countries because of limited therapeutic options. Stringent infection control and comprehensive antimicrobial stewardship programs are needed to overcome this challenge.

Heartbeat Classification and Arrhythmia Detection Using a Multi-Model Deep-Learning Technique.

Cardiac arrhythmias pose a significant danger to human life; therefore, it is of utmost importance to be able to efficiently diagnose these arrhythmias promptly. There exist many techniques for the detection of arrhythmias; however, the most widely adopted method is the use of an Electrocardiogram (ECG). The manual analysis of ECGs by medical experts is often inefficient. Therefore, the detection and recognition of ECG characteristics via machine-learning techniques have become prevalent. There are two major drawbacks of existing machine-learning approaches: (a) they require extensive training time; and (b) they require manual feature selection. To address these issues, this paper presents a novel deep-learning framework that integrates various networks by stacking similar layers in each network to produce a single robust model. The proposed framework has been tested on two publicly available datasets for the recognition of five micro-classes of arrhythmias. The overall classification sensitivity, specificity, positive predictive value, and accuracy of the proposed approach are 98.37%, 99.59%, 98.41%, and 99.35%, respectively. The results are compared with state-of-the-art approaches. The proposed approach outperformed the existing approaches in terms of sensitivity, specificity, positive predictive value, accuracy and computational cost.

Bleeding complications post ultrasound guided renal biopsy - A single centre experience from Pakistan.

INTRODUCTION: Renal biopsy is the diagnostic modality of choice for the diagnosis of renal parenchymal diseases. The advent of improved imaging techniques and biopsy needles over the years has increased the safety of the procedure and the ability to obtain adequate renal tissue for diagnosis. However, there is paucity of data in this regard from Pakistan. This study shall help in establishing the local perspective of the frequency of bleeding complications in percutaneous ultrasound guided renal biopsy. MATERIALS AND METHODS: This is a prospective case series of hospitalized patients from January till December 2015 at Nephrology Department, Aga Khan University Hospital, Karachi, Pakistan. After enrolment, each participant was followed for 24 h after renal biopsy. RESULTS: A total of 220 patients were included. Mean age was 41.65 ± 8.627 years, 82 (37.2%) were male and 138 (62.8%) were female. Pre and post biopsy haemoglobin, pre and post biopsy haematocrit were 10.92 ± 1.25 and 10.60 ± 1.22, and 30.82 ± 4.73 and 30.49 ± 4.68 respectively. Out of 220 patients, 16 (7.27%) developed major complications and 26 (11.8%) developed minor complications in 24 h after renal biopsy. CONCLUSIONS: Percutaneous kidney biopsy is a relatively safe procedure. Complication rates following the procedure are minimal. It is important that all nephrology programs train the trainees in performing biopsies, so that there is a wider clinical use of this important investigation even in underprivileged & developing countries.