Somani, Bhaskar K

Introduction: Adequate bladder distention is critical for safe and efficient transurethral morcellation during endoscopic prostate enucleation. Traditional assessment methods are subjective and may compromise safety and efficiency. We evaluated the feasibility and impact of continuous intravesical pressure (IVP) monitoring using a handheld pressure meter during morcellation compared with conventional manual bladder assessment. Material and Methods: In this prospective, randomized pilot study, 30 patients undergoing transurethral morcellation after bipolar prostate enucleation were randomized 1:1 to continuous IVP monitoring with a handheld pressure meter (Group A) or manual suprapubic bladder assessment by a urology fellow (Group B). In Group A, morcellation was performed while IVP remained within a predefined safe range (15–60 mmHg), with pauses for pressure correction as needed. The primary outcome was the number of morcellation pauses. Secondary outcomes included morcellation time, morcellation efficiency (g/min), total operative time, hemoglobin deficit, complications, and functional outcomes (International Prostate Symptom Score, maximum urinary flow rate, and post-void residual) at 3 and 6 months. Results: Baseline characteristics were comparable between groups. Morcellation time was significantly shorter in Group A (8.9 ± 3.7 vs 13.3 ± 2.1 minutes; p = 0.0008), with fewer morcellation pauses (3.3 ± 0.7 vs 5.7 ± 1.2; p < 0.0001) and higher morcellation efficiency (9.9 ± 2.0 vs 5.9 ± 0.6 g/min; p < 0.0001). Enucleation time, total operative time, tissue weight, and hemoglobin deficit were similar. No bladder injuries or postoperative fever occurred. Functional outcomes at 3 and 6 months were comparable. Conclusion: Continuous IVP monitoring using a handheld pressure meter during transurethral morcellation is feasible, reduces interruptions, and significantly improves morcellation efficiency without compromising safety or functional outcomes. This inexpensive technique may be a valuable safety adjunct, particularly for less experienced surgeons, and merits evaluation in larger randomized trials.

Artificial intelligence (AI) is an emerging technological system that provides a platform to manage and analyze data by emulating human cognitive functions with greater accuracy, revolutionizing patient care and introducing a paradigm shift to the healthcare industry. The purpose of this study is to identify the underlying factors that affect the adoption of artificial intelligence in healthcare (AIH) by healthcare providers and to understand “What are the factors that influence healthcare providers’ behavioral intentions to adopt AIH in their routine practice?” An integrated survey was conducted among healthcare providers, including consultants, residents/students, and nurses. The survey included items related to performance expectancy, effort expectancy, initial trust, personal innovativeness, task complexity, and technology characteristics. The collected data were analyzed using structural equation modeling. A total of 392 healthcare professionals participated in the survey, with 72.4% being male and 50.7% being 30 years old or younger. The results showed that performance expectancy, effort expectancy, and initial trust have a positive influence on the behavioral intentions of healthcare providers to use AIH. Personal innovativeness was found to have a positive influence on effort expectancy, while task complexity and technology characteristics have a positive influence on effort expectancy for AIH. The study’s empirically validated model sheds light on healthcare providers’ intention to adopt AIH, while the study’s findings can be used to develop strategies to encourage this adoption. However, further investigation is necessary to understand the individual factors affecting the adoption of AIH by healthcare providers.

Background: Wearable device technology has recently been involved in the healthcare industry substantially. India is the world’s third largest market for wearable devices and is projected to expand at a compound annual growth rate of ~26.33%. However, there is a paucity of literature analyzing the factors determining the acceptance of wearable healthcare device technology among low-middle-income countries. Methods: This cross-sectional, web-based survey aims to analyze the perceptions affecting the adoption and usage of wearable devices among the Indian population aged 16 years and above. Results: A total of 495 responses were obtained. In all, 50.3% were aged between 25–50 years and 51.3% belonged to the lower-income group. While 62.2% of the participants reported using wearable devices for managing their health, 29.3% were using them daily. technology and task fitness (TTF) showed a significant positive correlation with connectivity (r = 0.716), health care (r = 0.780), communication (r = 0.637), infotainment (r = 0.598), perceived usefulness (PU) (r = 0.792), and perceived ease of use (PEOU) (r = 0.800). Behavioral intention (BI) to use wearable devices positively correlated with PEOU (r = 0.644) and PU (r = 0.711). All factors affecting the use of wearable devices studied had higher mean scores among participants who were already using wearable devices. Male respondents had significantly higher mean scores for BI (p = 0.034) and PEOU (p = 0.009). Respondents older than 25 years of age had higher mean scores for BI (p = 0.027) and Infotainment (p = 0.032). Conclusions: This study found a significant correlation with the adoption and acceptance of wearable devices for healthcare management in the Indian context.

Objective To develop a standardised tool to evaluate flexible ureterorenoscopes (fURS). Materials and Methods A three‐stage consensus building approach based on the modified Delphi technique was performed under guidance of a steering group. First, scope‐ and user‐related parameters used to evaluate fURS were identified through a systematic scoping review. Then, the main categories and subcategories were defined, and the expert panel was selected. Finally, a two‐step modified Delphi consensus project was conducted to firstly obtain consensus on the relevance and exact definition of each (sub)category necessary to evaluate fURS, and secondly on the evaluation method (setting, used tools and unit of outcome) of those (sub)categories. Consensus was reached at a predefined threshold of 80% high agreement. Results The panel consisted of 30 experts in the field of endourology. The first step of the modified Delphi consensus project consisted of two questionnaires with a response rate of 97% ( n = 29) for both. Consensus was reached for the relevance and definition of six main categories and 12 subcategories. The second step consisted of three questionnaires (response rate of 90%, 97% and 100%, respectively). Consensus was reached on the method of measurement for all (sub)categories. Conclusion This modified Delphi consensus project reached consensus on a standardised grading tool for the evaluation of fURS – The Uniform grading tooL for flexIble ureterorenoscoPes (TULIP) tool. This is a first step in creating uniformity in this field of research to facilitate future comparison of outcomes of the functionality and handling of fURS.