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Thongprayoon, Charat

Mayo Clinic

Mayo Clinic

Citations 12

AI-Driven Patient Education in Chronic Kidney Disease: Evaluating Chatbot Responses against Clinical Guidelines
Acharya, Prakrati , Alba, R. Maniega, Krisanapan, Pajaree , Acharya, Chirag , Csongrádi, Éva, Mao, Michael A. , Craici, Iasmina , Miao, Jing , Thongprayoon, Charat, Cheungpasitporn, Wisit , Acharya, Chirag , Mao, Michael A , Craici, Iasmina M, Miao, Jing , Cheungpasitporn, Wisit , Krisanapan, Pajaree , Suppadungsuk, Supawadee , Thongprayoon, Charat

Diseases | August 16, 2024 | Volume: 12 | Issue: 8 | Pages: 185

10.3390/diseases12080185 Get It

Chronic kidney disease (CKD) patients can benefit from personalized education on lifestyle and nutrition management strategies to enhance healthcare outcomes. The potential use of chatbots, introduced in 2022, as a tool for educating CKD patients has been explored. A set of 15 questions on lifestyle modification and nutrition, derived from a thorough review of three specific KDIGO guidelines, were developed and posed in various formats, including original, paraphrased with different adverbs, incomplete sentences, and misspellings. Four versions of AI were used to answer these questions: ChatGPT 3.5 (March and September 2023 versions), ChatGPT 4, and Bard AI. Additionally, 20 questions on lifestyle modification and nutrition were derived from the NKF KDOQI guidelines for nutrition in CKD (2020 Update) and answered by four versions of chatbots. Nephrologists reviewed all answers for accuracy. ChatGPT 3.5 produced largely accurate responses across the different question complexities, with occasional misleading statements from the March version. The September 2023 version frequently cited its last update as September 2021 and did not provide specific references, while the November 2023 version did not provide any misleading information. ChatGPT 4 presented answers similar to 3.5 but with improved reference citations, though not always directly relevant. Bard AI, while largely accurate with pictorial representation at times, occasionally produced misleading statements and had inconsistent reference quality, although an improvement was noted over time. Bing AI from November 2023 had short answers without detailed elaboration and sometimes just answered “YES”. Chatbots demonstrate potential as personalized educational tools for CKD that utilize layman’s terms, deliver timely and rapid responses in multiple languages, and offer a conversational pattern advantageous for patient engagement. Despite improvements observed from March to November 2023, some answers remained potentially misleading. ChatGPT 4 offers some advantages over 3.5, although the differences are limited. Collaboration between healthcare professionals and AI developers is essential to improve healthcare delivery and ensure the safe incorporation of chatbots into patient care.
Incidence and Mortality of Renal Cell Carcinoma after Kidney Transplantation: A Meta-Analysis
Chewcharat, Api , Thongprayoon, Charat, Cheungpasitporn, Wisit , Aeddula, Narothama Reddy , Kaewput, Wisit , Watthanasuntorn, Kanramon , Lertjitbanjong, Ploypin , Sharma, Konika , Torres-Ortiz, Aldo, Leeaphorn, Napat, Khoury, Nadeen , Cheungpasitporn, Wisit , Aeddula, Narothama Reddy , Kaewput, Wisit , Chewcharat, Api , Khoury, Nadeen , Thongprayoon, Charat , Boonpheng, Boonphiphop , Torres-Ortiz, Aldo, Mao, Michael A.

Journal of Clinical Medicine | April 17, 2019 | Volume: 8 | Issue: 4 | Pages: 530

10.3390/jcm8040530 Get It

Background: The incidence and mortality of renal cell carcinoma (RCC) after kidney transplantation (KTx) remain unclear. This study’s aims were (1) to investigate the pooled incidence/incidence trends, and (2) to assess the mortality/mortality trends in KTx patients with RCC. Methods: A literature search was conducted using the MEDLINE, EMBASE and Cochrane databases from inception through October 2018. Studies that reported the incidence or mortality of RCC among kidney transplant recipients were included. The pooled incidence and 95% CI were calculated using a random-effect model. The protocol for this meta-analysis is registered with PROSPERO; no. CRD42018108994. Results: A total of 22 observational studies with a total of 320,190 KTx patients were enrolled. Overall, the pooled estimated incidence of RCC after KTx was 0.7% (95% CI: 0.5–0.8%, I2 = 93%). While the pooled estimated incidence of de novo RCC in the native kidney was 0.7% (95% CI: 0.6–0.9%, I2 = 88%), the pooled estimated incidence of RCC in the allograft kidney was 0.2% (95% CI: 0.1–0.4%, I2 = 64%). The pooled estimated mortality rate in KTx recipients with RCC was 15.0% (95% CI: 7.4–28.1%, I2 = 80%) at a mean follow-up time of 42 months after RCC diagnosis. While meta-regression analysis showed a significant negative correlation between year of study and incidence of de novo RCC post-KTx (slopes = −0.05, p = 0.01), there were no significant correlations between the year of study and mortality of patients with RCC (p = 0.50). Egger’s regression asymmetry test was performed and showed no publication bias in all analyses. Conclusions: The overall estimated incidence of RCC after KTX was 0.7%. Although there has been a potential decrease in the incidence of RCC post-KTx, mortality in KTx patients with RCC has not decreased over time.