Applications of artificial intelligence in anesthesia: A systematic review.

This review article examines the utility of artificial intelligence (AI) in anesthesia, with a focus on recent developments and future directions in the field. A total of 19,300 articles were available on the given topic after searching in the above mentioned databases, and after choosing the custom range of years from 2015 to 2023 as an inclusion component, only 12,100 remained. 5,720 articles remained after eliminating non-full text. Eighteen papers were identified to meet the inclusion criteria for the review after applying the inclusion and exclusion criteria. The applications of AI in anesthesia after studying the articles were in favor of the use of AI as it enhanced or equaled human judgment in drug dose decision and reduced mortality by early detection. Two studies tried to formulate prediction models, current techniques, and limitations of AI; ten studies are mainly focused on pain and complications such as hypotension, with a P value of <0.05; three studies tried to formulate patient outcomes with the help of AI; and three studies are mainly focusing on how drug dose delivery is calculated (median: 1.1% ± 0.5) safely and given to the patients with applications of AI. In conclusion, the use of AI in anesthesia has the potential to revolutionize the field and improve patient outcomes. AI algorithms can accurately predict patient outcomes and anesthesia dosing, as well as monitor patients during surgery in real time. These technologies can help anesthesiologists make more informed decisions, increase efficiency, and reduce costs. However, the implementation of AI in anesthesia also presents challenges, such as the need to address issues of bias and privacy. As the field continues to evolve, it will be important to carefully consider the ethical implications of AI in anesthesia and ensure that these technologies are used in a responsible and transparent manner.

Investigating the influence of selected leadership styles on patient safety and quality of care: a systematic review and meta-analysis.

BACKGROUND: There is a popular belief that transformational leadership (TL) and servant leadership (SL) styles are influential in establishing a patient safety (PS) culture and improving the quality of care (QC). However, there are very few review articles investigating this phenomenon. PURPOSE: This study performs a systematic review and meta-analysis to ascertain the influences of TL and SL on PS and QC. METHODS: Published research work indexed in the two popular databases, that is, Scopus and PubMed, was selected based on the inclusion criteria. The systematic review was performed as per Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. Data such as country of publication, year, data type, research design, target population, sample size and conclusion were selected from the studies. RESULTS: There are pieces of evidence suggesting a medium to strong effect of TL on PS. At the same time, the effect of TL on QC is not direct but indirect and is mediated through variables such as fostering positive organisational culture and enhancing organisational outcomes such as job satisfaction, leader effectiveness and willingness of nurses to spend some extra effort. A total of 27 studies were selected for final evaluation and 11 reported a relationship between TL and PS. The 'Fisher r-to-z transformed correlation coefficients' ranged from 0.3769 to 0.8673. Similarly, a total of four studies reported the relationship between TL and QC, 'Fisher r-to-z transformed correlation coefficients' ranged from 0.0802 to 0.5101, with most estimates being positive (80%). CONCLUSION: TL has a strong and positive effect on PS but a positive and weak effect on the QC. There is not much evidence to establish SL's influence on PS and QC.

Unraveling the Link: A Comprehensive Literature Review of Type 2 Diabetes and Menopause Onset.

Women with diabetes mellitus (DM), a metabolic endocrine illness, may experience a variety of reproductive problems. The age at menopause onset has been extensively studied as a major predictor of women's health in the future; however, its relationship to diabetes in Indian women has received less attention. This literature review looked at the consequences of diabetes in women as well as the association between diabetes and the age at which menopause begins. The average age at menopause onset among women with type 2 diabetes mellitus (T2DM) has decreased globally. According to one Indian study, the average menopause age dropped to 45 years for 26% of women with T2DM. In the current review, 10 studies indicated that women with T2DM displayed an imbalanced hormonal profile resulting in an extended anovulatory period. Two investigations highlighted the significance of altered body composition of women with T2DM, thereby suggesting obesity as the primary risk factor of ovarian aging and early climacteric symptoms. T2DM may lower the average age at menopause onset; however, further research on Indian women is necessary. There is a need of studies on T2DM in premenopausal women are needed to demonstrate how the changes in body composition impact the age at which menopause begins. Delaying the onset of menopause in women with T2DM necessitates diet and lifestyle interventions to minimize ovarian aging and hormonal imbalance.

Factors to Overcoming Barriers Affecting Electronic Medical Record Usage by Physicians.

BACKGROUND: Hospitals are adopting electronic medical records (EMRs) in larger numbers; however, the barrier to derive its full utility is the low acceptance by physicians. AIMS AND OBJECTIVES: This study is done with an objective to identify the factors to overcome the barriers preventing the adoption of EMR by physicians. MATERIALS AND METHODS: This study is cross sectional in natures and a self-administered questionnaire is developed based on the Technology Acceptance Model. RESULTS: The four identified factors are positive attitude toward EMR, reliability, difficulty to use, and adaptability, these factors together, have explained 62.54 percent variance in the data set. CONCLUSION: The physician's acceptance for EMRs can be improved by focusing on the identified four factors, which are "positive attitude toward electronic medical records," reliability of electronic medical records," "difficulty level of use," and "adaptability of electronic medical records."