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Background: End-of-life care (EOLC) is a critical aspect of healthcare, yet accessing reliable information remains challenging, particularly in culturally diverse contexts like India. Objective: This study investigates the potential of artificial intelligence (AI) in addressing the informational gap by analyzing patient information leaflets (PILs) generated by AI chatbots on EOLC. Methodology: Using a comparative research design, PILs generated by ChatGPT and Google Gemini were evaluated for readability, sentiment, accuracy, completeness, and suitability. Readability was assessed using established metrics, sentiment analysis determined emotional tone, accuracy, and completeness were rated by subject experts, and suitability was evaluated using the Patient Education Materials Assessment Tool (PEMAT). Results: Google Gemini PILs exhibited superior readability and actionability compared to ChatGPT PILs. Both conveyed positive sentiments and high levels of accuracy and completeness, with Google Gemini PILs showing slightly lower accuracy scores. Conclusion: The findings highlight the promising role of AI in enhancing patient education in EOLC, with implications for improving care outcomes and promoting informed decision-making in diverse cultural settings. Ongoing refinement and innovation in AI-driven patient education strategies are needed to ensure compassionate and culturally sensitive EOLC. How to cite this article: Gondode PG, Khanna P, Sharma P, Duggal S, Garg N. End-of-life Care Patient Information Leaflets-A Comparative Evaluation of Artificial Intelligence-generated Content for Readability, Sentiment, Accuracy, Completeness, and Suitability: ChatGPT vs Google Gemini. Indian J Crit Care Med 2024;28(6):561-568.
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Background The COVID-19 pandemic has introduced unprecedented challenges to global healthcare systems, including heightened psychological stress among patients. This study evaluates the preoperative anxiety levels among patients scheduled for surgery during the COVID-19 pandemic. Methods This cross-sectional observational study was conducted between April 2020 and March 2022. Adult patients aged 18-80 years, scheduled for elective or emergency surgery, were included. Exclusion criteria were mental illness, impaired communication, and hemodynamic instability. A pre-validated questionnaire addressing demographics, prior surgery exposure, surgery-related anxiety, and COVID-19-related fears was administered. Anxiety levels were scored on a 1-5 Likert scale. Data were analyzed using SPSS version 22 (IBM Corp., Armonk, USA). Results A total of 112 patients participated, with a mean age of 42.3±14.2 years. The majority were female (61 patients, 54.5%), married (96 patients, 85.7%), and resided in urban areas (85 patients, 75.9%). Most patients had no prior surgical history (87 patients, 77.7%). Surgery-related fears were prevalent, with 110 patients (98.2%) fearing surgical complications and 111 patients (99.1%) fearing postoperative pain. COVID-19-related fears were also significant, with 108 patients (96.4%) fearing infection during hospital stay and 100 patients (89.3%) fearing infecting family members. Mild fear was the most common anxiety level (70 patients, 62.95%), followed by moderate fear (25 patients, 22.5%). Discussion The study highlights the dual stressors of surgery and the pandemic, contributing to heightened preoperative anxiety. Findings indicate that significant anxiety levels were present, driven by fears related to surgery, anesthesia, and COVID-19. This aligns with other studies that report high preoperative anxiety levels exacerbated by the pandemic. The comprehensive assessment of anxiety factors underscores the need for tailored interventions to mitigate these anxieties. Conclusion The COVID-19 pandemic has significantly increased preoperative anxiety among surgical patients. Addressing both surgical and pandemic-related anxieties is crucial for improving patient outcomes. Healthcare providers should implement psychological support programs to alleviate these anxieties. Understanding the multifaceted nature of preoperative anxiety during the pandemic can enhance patient care.
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Aim: Diabetic peripheral neuropathy (DPN) induces chronic neuropathic pain in diabetic patients. Current treatments like pregabalin and duloxetine offer limited efficacy. This study evaluates combining pregabalin and duloxetine versus pregabalin alone for DPN pain relief, and explores gene modulation (PPARγ and Akt) to understand neuropathic pain's molecular basis.Materials & methods: Diabetic patients with DPN were randomized into groups receiving combination therapy or pregabalin alone for 4 weeks. Pain intensity, gene expression and quality of life were assessed.Results: Combination therapy significantly reduced pain, improved quality of life and upregulated PPARγ and Akt genes compared with monotherapy.Conclusion: Pregabalin and duloxetine combination therapy in DPN led to PPARγ mRNA upregulation and negative correlation of Akt gene expression with pain scores. This combination therapy effectively reduced pain and improved quality of life.Clinical Trial Registration: CTRI/2021/02/031068.
Combining medicines to reduce nerve pain in diabetic patientsWhat is this article about? People with diabetes often have nerve pain called diabetic peripheral neuropathy (DPN). Some medicines like pregabalin and duloxetine help, but are not enough. This study tested if using both medicines together works better than using just pregabalin. The study also looked at how these medicines affect certain genes.What were the results? Patients with DPN took either both medicines or just pregabalin for 4 weeks. The combined treatment reduced pain, improved life quality and affected certain genes.What do the results of the study mean? Using pregabalin and duloxetine together can reduce DPN pain more effectively. This offers hope for better treatment options.