Impact of COVID-19 pandemic on medicine supply chain for patients with chronic diseases: Experiences of the community pharmacists.

Problem considered: Coronavirus disease(COVID-19) outbroke towards the end of December 2019 in China, soon it started spreading rapidly to various countries leading to an outburst of pandemic. Due to the restrictions imposed to control the spread of the infection, globally the manufacturing, import and export of medicine and the healthcare services to patients with chronic illness had been affected. This study aimed to explore the perspectives of the pharmacists on the medicine supply chain for patients with chronic diseases during COVID-19 pandemic in India. Methods: This study is a prospective, qualitative research involving telephonic, semi-structured in-depth interviews. An interview guide for pharmacists was prepared and validated using "Interview Protocol Refinement" method. Purposive sampling method was used to recruit the pharmacists; a telephonic oral consent was obtained. The interview session was audio recorded and the recordings were transcribed verbatim. Further, transcripts were validated and later analysed using NVivo software. Results: A total of 8 participants were interviewed during our study. Thematic analysis of the transcripts resulted in seven main themes. The study showed that there was deficiency in medicine supply during the COVID-19 pandemic and the pharmacists faced several challenges in procuring and storing the medication, arranging for unavailable medicines, medication dispensing and provision of the services such as medicine delivery, patient counselling. There was also scarcity of manpower leading to extra workload and working overtime. Conclusion: Uninterrupted supply of essential medicine is the backbone of health care system. An effective plan and appropriate strategies are vital to combat such future emergencies.

Artificial intelligence in acute respiratory distress syndrome: A systematic review.

BACKGROUND AND OBJECTIVE: Acute respiratory distress syndrome (ARDS) is a life-threatening pulmonary disease with a high clinical and cost burden across the globe. Artificial intelligence (AI), an emerging area, has been used for various purposes in ARDS. We aim to summarize the currently available literature on various applications of AI in ARDS through a systematic review. METHODOLOGY: PubMed was searched from inception to February 2021 to collate all the studies. Additionally, a bibliographic search of included studies and a random search on Google, Google Scholar, and Research Gate were performed to identify relevant articles. Studies published in English language that employed data about developing and/or assessing the role of AI in the various aspects of ARDS were considered for this review. Three independent reviewers performed study selection and data extraction; any disagreements were settled through consensus or discussion with another member of the research team. RESULTS: A total of 19 studies published between the year 2002 and 2020 were included. In these included studies, AI was used for various purposes in ARDS such as diagnosis (n = 10; 53 %), risk stratification (n = 1; 5 %), prediction of severity (n = 3; 17 %), management (n = 2; 10 %), prediction of mortality (n = 2; 10 %), and decision making (n = 1; 5 %). The area under the curve among the developed models in the included studies ranged between 0.8 and 1, which is considered to be very good to excellent. CONCLUSION: AI is revolutionizing healthcare and has a wide range of applications in ARDS, such as minimizing cost and enhancing outcomes.

Factors affecting the outcomes in patients with acute respiratory distress syndrome in a tertiary care setting.

Purpose: The clinical profile and factors affecting outcomes in acute respiratory distress syndrome (ARDS) from adequately sample-sized Indian studies are still lacking. We aimed to investigate the clinical profile, treatment pattern, outcomes; and to assess factors affecting non-recovery in ARDS patients. Patients and methods: A retrospective observational study was conducted among adult ARDS patients admitted during five year period (January 2014-December 2018) in a South Indian tertiary care setting. The relevant data were collected from the medical records to the data collection form. The univariate and multivariate logistic regression analyses were conducted to identify the predictors of outcomes using SPSS v20. Results: A total of 857 participants including 496 males and 361 females with a mean age of 46.86 ± 15.81 years were included in this study. Fever (70.9%), crepitation (58.3%), breathlessness (56.9%), and cough (45%) were the major clinical presentation. Hypertension (25.2%), kidney disease (23.8%), and diabetes (22.3%) were the major comorbidities; and sepsis (37.6%), pneumonia (33.3%), and septic shock (27.5%) were the major etiological factors observed. Antibiotics and steroids were administered to 97.9% and 52.3% of the population, respectively. The recovery rate was 47.49%. The patients with scrub typhus, dengue, pancreatitis, and oxygen supplementation had significantly lower mortality. The factors such as advanced age, sepsis, septic shock, liver diseases, and ventilation requirements were observed to be the independent predictors of non-recovery in ARDS patients. Conclusion: A comparable recovery rate was observed in our population. Advanced age, sepsis, septic shock, liver diseases, and ventilation requirements were the independent predictors of non-recovery.