Impact of Respiratory Discomfort on Vocal Quality and Perceived Effort: The Moderating Role of Fear.

Objectives/hypothesis: The goal of this study was to investigate the relationship between respiratory discomfort and voice measures, including perceived vocal effort and selected acoustic parameters. A secondary aim was to examine whether threat appraisal-measured as susceptibility to experience fear of suffocation-modulated these relationships. We hypothesized that greater dyspnea would predict worse voice outcomes, especially in speakers with greater fear susceptibility.

Importance of early transfer to higher levels of in-patient care - an experience from a lower-middle-income country.

Objective: To ascertain the frequency of hospitalised internal medicine patients requiring escalation to a higher level of care, and in-hospital mortality in such cases.

Methods: The prospective, observational study was conducted from September 1 to October 15, 2021 at a tertiary care hospital in Karachi, and comprised adult patients of either gender admitted to the internal medicine general wards and high dependency units. Data was collected prospectively using a proforma.

Basic is Better? An Assessment of National Outcomes in Prehospital Airway Management in Critical Acuity Pediatric Trauma.

Background: Consensus is lacking regarding prehospital airway management in pediatric trauma patients (PTPs).

Objectives: This retrospective study compared prehospital basic-airway procedures (B-AP) vs. advanced-AP (A-AP) among PTPs, comparing scene time, transport time, and improvement in acuity from scene to emergency department.

G2PDeep-v2: a web-based deep-learning framework for phenotype prediction and biomarker discovery for all organisms using multi-omics data.

The G2PDeep-v2 server is a web-based platform powered by deep learning, for phenotype prediction and markers discovery from multi-omics data in any organisms including humans, plants, animals, and viruses. The server provides multiple services for researchers to create deep-learning models through an interactive interface and train these models using an automated hyperparameter tuning algorithm on high-performance computing resources. Users can visualize the results of phenotype and markers predictions and perform Gene Set Enrichment Analysis for the significant markers to provide insights into the molecular mechanisms underlying complex diseases, conditions and other biological phenotypes being studied.

Tele-Dermatology during crisis, comparison of patients' perspective between tele and onsite clinics.

Objective: To assess patients' satisfaction with tele-dermatology versus face-to-face visits, and to identify their attitude toward the new modality.

Methods: The cross-sectional study was conducted from January to December 2021 at the Department of Dermatology, Aga Khan University Hospital, Karachi, and comprised patients of either gender. Those who opted to personally visit the outpatient department were placed in group A, while those opting for tele-dermatology were placed in group B.