Reducing the environmental impact of surgery on a global scale: systematic review and co-prioritization with healthcare workers in 132 countries

Abstract Background Healthcare cannot achieve net-zero carbon without addressing operating theatres. The aim of this study was to prioritize feasible interventions to reduce the environmental impact of operating theatres. Methods This study adopted a four-phase Delphi consensus co-prioritization methodology. In phase 1, a systematic review of published interventions and global consultation of perioperative healthcare professionals were used to longlist interventions. In phase 2, iterative thematic analysis consolidated comparable interventions into a shortlist. In phase 3, the shortlist was co-prioritized based on patient and clinician views on acceptability, feasibility, and safety. In phase 4, ranked lists of interventions were presented by their relevance to high-income countries and low–middle-income countries. Results In phase 1, 43 interventions were identified, which had low uptake in practice according to 3042 professionals globally. In phase 2, a shortlist of 15 intervention domains was generated. In phase 3, interventions were deemed acceptable for more than 90 per cent of patients except for reducing general anaesthesia (84 per cent) and re-sterilization of ‘single-use’ consumables (86 per cent). In phase 4, the top three shortlisted interventions for high-income countries were: introducing recycling; reducing use of anaesthetic gases; and appropriate clinical waste processing. In phase 4, the top three shortlisted interventions for low–middle-income countries were: introducing reusable surgical devices; reducing use of consumables; and reducing the use of general anaesthesia. Conclusion This is a step toward environmentally sustainable operating environments with actionable interventions applicable to both high– and low–middle–income countries

Psychosocial Correlates of Psychological Distress among First Time Pregnant Mothers

: Objective: The study investigated the relation of marital relationship and social support with psychological distress in first time pregnant women.Study Design: Correlational design.Setting and Duration: The study was carried out in Lahore, Pakistan, over a period of six months.Subjects and Methods: The sample of the present study includes 100 pregnant first time mothers. Sample of pregnant females was collected from the maternity ward of different hospital located in Lahore. Pregnant females included in sample were falling with the age range of 20-35 years, the minimum duration of their marriage was at least 2 years and minimum qualification was intermediate. Those women were selected who had no history of psychological problem and had never been on any kind of psychiatric/ psychological treatment (psychotropic medication /psychotherapy). The participants completed the Demographic Information sheet, Depression Anxiety and Stress Scale, Relationship assessment Scale and Social Provision Scale. Responses were scored according to the producer given in the manuals.Results: Mean ± SD of age was 26.21 ± 2.8 years. Significant (

Comparison of social support, depression and anger in diabetic and cardiac patients

Objective: The present study explores the role of social support, depression and anger among diabetic and cardiac patients. Method: This cross sectional study comprised of 200 patients who were selected through purposive sampling strategy from outpatient departments (Cardiology and Endocrinology) of Government hospitals of Lahore (Jinnah Hospital and Services Hospital) and Muridke (Tehsil Headquarter Hospital) from April 2015- September 2015. Cardiac patients were 101(Men=51, Women=50) and diabetic type II patients were 99 (Men= 50, Women= 49). Siddiqui-Shah Depression scale (SSDS), Interpersonal Support Evaluation List (ISEL) and Trait Anger and Expression Scale (TAES) were administered on the patients. Result: The findings revealed that cardiac patients exhibit higher level of depression and receive more social support than diabetic patients. Furthermore, results reveal that low social support is a significant negative predictor of anger and depression among diabetic and cardiac patients. Conclusion: On the basis of findings, it is concluded that social support is a significant factor in the treatment of diabetes and cardiac diseases. This research is helpful for hospital administration in the counseling/management of such patients. Continuous..

Entropy Generation Analysis of Hybrid Nanomaterial through Porous Space with Variable Characteristics

Salient features of hybrid nanofluid (MoS2-SiO2/water) for Darcy–Forchheimer–Brinkman porous space with variable characteristics is examined. Heat transfer analysis subject to viscous dissipation, nonlinear thermal radiation, and heat generation/absorption is carried out. Disturbance inflow is created by an exponentially stretching curved sheet. Relevant equations are simplified by employing boundary layer theory. Adequate transformations lead to a set of dimensionless equations. Velocity, temperature, and entropy generation rate are analyzed graphically. Comparative results are obtained for hybrid (MoS2-SiO2/water) and nanofluid (MoS2-water and SiO2-water). Physical quantities are analyzed through numerical data

Entropy Generation Analysis of Hybrid Nanomaterial through Porous Space with Variable Characteristics

Salient features of hybrid nanofluid (MoS2-SiO2/water) for Darcy–Forchheimer–Brinkman porous space with variable characteristics is examined. Heat transfer analysis subject to viscous dissipation, nonlinear thermal radiation, and heat generation/absorption is carried out. Disturbance inflow is created by an exponentially stretching curved sheet. Relevant equations are simplified by employing boundary layer theory. Adequate transformations lead to a set of dimensionless equations. Velocity, temperature, and entropy generation rate are analyzed graphically. Comparative results are obtained for hybrid (MoS2-SiO2/water) and nanofluid (MoS2-water and SiO2-water). Physical quantities are analyzed through numerical data