Assessing the impact of continuous positive airway pressure therapy on clinical outcomes in interstitial lung disease patients with coexisting obstructive sleep apnea: a systematic review.

PURPOSE: Interstitial lung disease (ILD) often coexists with obstructive sleep apnea (OSA), contributing to increased morbidity and mortality. However, the effectiveness of continuous positive airway pressure (CPAP) therapy in this population remains unclear. We conducted a systematic review to evaluate CPAP therapy's impact on clinical outcomes in patients with ILD and comorbid OSA. METHODS: Following PRISMA guidelines, we systematically searched multiple databases for studies assessing CPAP therapy's effects on ILD exacerbation, hospitalization, quality of life, and mortality in ILD-OSA patients. Studies were selected based on predefined inclusion criteria, and their quality was assessed using the Newcastle-Ottawa quality scale. RESULTS: Among 485 articles screened, 82 underwent full review, with four observational studies meeting inclusion criteria. CPAP therapy demonstrated potential benefits in improving quality of life and reducing ILD exacerbations in ILD-OSA patients. However, its impact on mortality was inconclusive due to variability in study definitions and methodology. CONCLUSION: CPAP therapy may improve outcomes in ILD-OSA patients, particularly in terms of quality of life and ILD exacerbations. Nonetheless, further research with standardized definitions and rigorous methodology is needed to confirm its efficacy, particularly regarding mortality outcome.

Outcomes of peritoneal dialysis in cirrhosis: A systematic review and meta-analysis.

BACKGROUND: Cirrhosis and end-stage kidney disease (ESKD) are significant global health concerns, contributing to high mortality and morbidity. Haemodialysis (HD) is frequently used to treat ESKD in patients with cirrhosis. However, it often presents challenges such as haemodynamic instability during dialysis sessions, leading to less than optimal outcomes. Peritoneal dialysis (PD), while less commonly used in cirrhotic patients, raises concerns about the risks of peritonitis and mortality. Our systematic review and meta-analysis aimed to assess outcomes in PD patients with cirrhosis. METHODS: We executed a comprehensive search in Ovid MEDLINE, EMBASE and Cochrane databases up to 25 September 2023. The search focused on identifying studies examining mortality and other clinical outcomes in ESKD patients with cirrhosis receiving PD or HD. In addition, we sought studies comparing PD outcomes in cirrhosis patients to those without cirrhosis. Data from each study were aggregated using a random-effects model and the inverse-variance method. RESULTS: Our meta-analysis included a total of 13 studies with 15,089 patients. Seven studies compared ESKD patients on PD with liver cirrhosis (2753 patients) against non-cirrhosis patients (9579 patients). The other six studies provided data on PD (824 patients) versus HD (1943 patients) in patients with cirrhosis and ESKD. The analysis revealed no significant difference in mortality between PD and HD in ESKD patients with cirrhosis (pooled odds ratio (OR) of 0.77; 95% confidence interval (CI), 0.53-1.14). In PD patients with cirrhosis, the pooled OR for peritonitis compared to non-cirrhosis patients was 1.10 (95% CI: 1.03-1.18). The pooled ORs for hernia and chronic hypotension in cirrhosis patients compared to non-cirrhosis controls were 2.48 (95% CI: 0.08-73.04) and 17.50 (95% CI: 1.90-161.11), respectively. The pooled OR for transitioning from PD to HD among cirrhotic patients was 1.71 (95% CI: 0.76-3.85). Mortality in cirrhosis patients on PD was comparable to non-cirrhosis controls, with a pooled OR of 1.05 (95% CI: 0.53-2.10). CONCLUSIONS: Our meta-analysis demonstrates that PD provides comparable mortality outcomes to HD in ESKD patients with cirrhosis. In addition, the presence of cirrhosis does not significantly elevate the risk of mortality among patients undergoing PD. While there is a higher incidence of chronic hypotension and a slightly increased risk of peritonitis in cirrhosis patients on PD compared to those without cirrhosis, the risks of hernia and the need to transition from PD to HD are comparable between both groups. These findings suggest PD as a viable and effective treatment option for ESKD patients with cirrhosis.

Global Trends in Kidney Stone Awareness: A Time Series Analysis from 2004-2023.

BACKGROUND: Despite the prevalence and incidence of kidney stones progressively increasing worldwide, public awareness of this condition remains unclear. Understanding trends of awareness can assist healthcare professionals and policymakers in planning and implementing targeted health interventions. This study investigated online search interest in "kidney stone" by analyzing Google Trends, focusing on stationarity of the trends and predicting future trends. METHODS: We performed time series analysis on worldwide Google monthly search data from January 2004 to November 2023. The Augmented Dickey-Fuller (ADF) test was used to assess the stationarity of the data, with a p-value below 0.05 indicating stationarity. Time series forecasting was performed using the autoregressive integrated moving average to predict future trends. RESULTS: The highest search interest for "kidney stone" (score 100) was in August 2022, while the lowest was in December 2007 (score 36). As of November 2023, search interest remained high, at 92. The ADF test was significant (p = 0.023), confirming data stationarity. The time series forecasting projected continued high public interest, likely reflecting ongoing concern and awareness. Notably, diverse regions such as Iran, the Philippines, Ecuador, the United States, and Nepal showed significant interest, suggesting widespread awareness of nephrolithiasis. CONCLUSION: This study highlighted that "kidney stone" is a consistently relevant health issue globally. The increase and stationarity of search trends, the forecasted sustained interest, and diverse regional interest emphasize the need for collaborative research and educational initiatives. This study's analysis serves as a valuable tool for shaping future healthcare policies and research directions in addressing nephrolithiasis related health challenges.

How to improve ChatGPT performance for nephrologists: a technique guide.

BACKGROUND: The integration of ChatGPT into nephrology presents opportunities for enhanced decision-making and patient care. However, refining its performance to meet the specific needs of nephrologists remains a challenge. This guide offers a strategic roadmap for advancing ChatGPT's effectiveness in nephrological applications. METHODS: Utilizing the advanced capabilities of GPT-4, we customized user profiles to optimize the model's response quality for nephrological inquiries. We assessed the efficacy of chain-of-thought prompting versus standard prompting in delineating the diagnostic pathway for nephrogenic diabetes insipidus-associated hypernatremia and polyuria. Additionally, we explored the influence of integrating retrieval-augmented generation on the model's proficiency in detailing pharmacological interventions to decelerate the progression from chronic kidney disease (CKD) G3 to end-stage kidney disease (ESKD), comparing it to responses without retrieval-augmented generation. RESULTS: In contrast to the standard prompting, the chain-of-thought method offers a step-by-step diagnostic process that mirrors the intricate thought processes needed for diagnosing nephrogenic diabetes insipidus-related hypernatremia and polyuria. This begins with an initial assessment, notably including a water deprivation test. After evaluating the outcomes of this test, the approach continues by identifying potential causes. Furthermore, if a patient's history suggests lithium usage, the chain-of-thought model adjusts by proposing a more customized course of action. In response to "List medication treatment to help slow progression of CKD G3 to ESKD?", GPT-4 only provides a general summary of medication options. Nevertheless, a specialized GPT-4 model equipped with a retrieval-augmented generation system delivers more precise responses, including renin-angiotensin system inhibitors, sodium-glucose cotransporter-2 inhibitors, and mineralocorticoid receptor antagonists. This aligns well with the 2024 KDIGO guidelines. CONCLUSIONS: GPT-4, when integrated with chain-of-thought prompting and retrieval-augmented generation techniques, demonstrates enhanced performance in the nephrology domain. This guide underscores the transformative potential of chain-of-thought and retrieval-augmented generation techniques in optimizing ChatGPT for nephrology, and highlights the ongoing need for innovative, tailored AI solutions in specialized medical fields.

Performance of GPT-4 Vision on kidney pathology exam questions.

OBJECTIVES: ChatGPT (OpenAI, San Francisco, CA) has shown impressive results across various medical examinations, but its performance in kidney pathology is not yet established. This study evaluated proficiencies of GPT-4 Vision (GPT-4V), an updated version of the platform with the ability to analyze images, on kidney pathology questions and compared its responses with those of nephrology trainees. METHODS: Thirty-nine questions (19 text-based questions and 20 with various kidney biopsy images) designed specifically for the training of nephrology fellows were employed. RESULTS: GPT-4V displayed comparable accuracy rates in the first and second runs (67% and 72%, respectively, P = .50). The aggregated accuracy, however-particularly, the consistent accuracy-of GPT-4V was lower than that of trainees (72% and 67% vs 79%). Both GPT-4V and trainees displayed comparable accuracy in responding to image-based and text-only questions (55% vs 79% and 81% vs 78%, P = .11 and P = .67, respectively). The consistent accuracy in image-based, directly asked questions for GPT-4V was 29%, much lower than its 88% consistency on text-only, directly asked questions (P = .02). In contrast, trainees maintained similar accuracy in directly asked image-based and text-based questions (80% vs 77%, P = .65). Although the aggregated accuracy for correctly interpreting images was 69%, the consistent accuracy across both runs was only 39%. The accuracy of GPT-4V in answering questions with correct image interpretation was significantly higher than for questions with incorrect image interpretation (100% vs 0% and 100% vs 33% for the first and second runs, P = .001 and P = .02, respectively). CONCLUSIONS: The performance of GPT-4V in handling kidney pathology questions, especially those including images, is limited. There is a notable need for enhancement in GPT-4V proficiency in interpreting images.

Perspectives on AI-based recommendations for mask-wearing and COVID-19 vaccination for transplant recipients in the post-COVID-19 era.

In the aftermath of the COVID-19 pandemic, the ongoing necessity for preventive measures such as mask-wearing and vaccination remains particularly critical for organ transplant recipients, a group highly susceptible to infections due to immunosuppressive therapy. Given that many individuals nowadays increasingly utilize Artificial Intelligence (AI), understanding AI perspectives is important. Thus, this study utilizes AI, specifically ChatGPT 4.0, to assess its perspectives in offering precise health recommendations for mask-wearing and COVID-19 vaccination tailored to this vulnerable population. Through a series of scenarios reflecting diverse environmental settings and health statuses in December 2023, we evaluated the AI's responses to gauge its precision, adaptability, and potential biases in advising high-risk patient groups. Our findings reveal that ChatGPT 4.0 consistently recommends mask-wearing in crowded and indoor environments for transplant recipients, underscoring their elevated risk. In contrast, for settings with fewer transmission risks, such as outdoor areas where social distancing is possible, the AI suggests that mask-wearing might be less imperative. Regarding vaccination guidance, the AI strongly advocates for the COVID-19 vaccine across most scenarios for kidney transplant recipients. However, it recommends a personalized consultation with healthcare providers in cases where patients express concerns about vaccine-related side effects, demonstrating an ability to adapt recommendations based on individual health considerations. While this study provides valuable insights into the current AI perspective on these important topics, it is crucial to note that the findings do not directly reflect or influence health policy. Nevertheless, given the increasing utilization of AI in various domains, understanding AI's viewpoints on such critical matters is essential for informed decision-making and future research.

Evaluating ChatGPT's efficacy in assessing the safety of non-prescription medications and supplements in patients with kidney disease.

Background: This study investigated the efficacy of ChatGPT-3.5 and ChatGPT-4 in assessing drug safety for patients with kidney diseases, comparing their performance to Micromedex, a well-established drug information source. Despite the perception of non-prescription medications and supplements as safe, risks exist, especially for those with kidney issues. The study's goal was to evaluate ChatGPT's versions for their potential in clinical decision-making regarding kidney disease patients. Method: The research involved analyzing 124 common non-prescription medications and supplements using ChatGPT-3.5 and ChatGPT-4 with queries about their safety for people with kidney disease. The AI responses were categorized as "generally safe," "potentially harmful," or "unknown toxicity." Simultaneously, these medications and supplements were assessed in Micromedex using similar categories, allowing for a comparison of the concordance between the two resources. Results: Micromedex identified 85 (68.5%) medications as generally safe, 35 (28.2%) as potentially harmful, and 4 (3.2%) of unknown toxicity. ChatGPT-3.5 identified 89 (71.8%) as generally safe, 11 (8.9%) as potentially harmful, and 24 (19.3%) of unknown toxicity. GPT-4 identified 82 (66.1%) as generally safe, 29 (23.4%) as potentially harmful, and 13 (10.5%) of unknown toxicity. The overall agreement between Micromedex and ChatGPT-3.5 was 64.5% and ChatGPT-4 demonstrated a higher agreement at 81.4%. Notably, ChatGPT-3.5's suboptimal performance was primarily influenced by a lower concordance rate among supplements, standing at 60.3%. This discrepancy could be attributed to the limited data on supplements within ChatGPT-3.5, with supplements constituting 80% of medications identified as unknown. Conclusion: ChatGPT's capabilities in evaluating the safety of non-prescription drugs and supplements for kidney disease patients are modest compared to established drug information resources. Neither ChatGPT-3.5 nor ChatGPT-4 can be currently recommended as reliable drug information sources for this demographic. The results highlight the need for further improvements in the model's accuracy and reliability in the medical domain.

Empowering inclusivity: improving readability of living kidney donation information with ChatGPT.

Background: Addressing disparities in living kidney donation requires making information accessible across literacy levels, especially important given that the average American adult reads at an 8th-grade level. This study evaluated the effectiveness of ChatGPT, an advanced AI language model, in simplifying living kidney donation information to an 8th-grade reading level or below. Methods: We used ChatGPT versions 3.5 and 4.0 to modify 27 questions and answers from Donate Life America, a key resource on living kidney donation. We measured the readability of both original and modified texts using the Flesch-Kincaid formula. A paired t-test was conducted to assess changes in readability levels, and a statistical comparison between the two ChatGPT versions was performed. Results: Originally, the FAQs had an average reading level of 9.6 ± 1.9. Post-modification, ChatGPT 3.5 achieved an average readability level of 7.72 ± 1.85, while ChatGPT 4.0 reached 4.30 ± 1.71, both with a p-value <0.001 indicating significant reduction. ChatGPT 3.5 made 59.26% of answers readable below 8th-grade level, whereas ChatGPT 4.0 did so for 96.30% of the texts. The grade level range for modified answers was 3.4-11.3 for ChatGPT 3.5 and 1-8.1 for ChatGPT 4.0. Conclusion: Both ChatGPT 3.5 and 4.0 effectively lowered the readability grade levels of complex medical information, with ChatGPT 4.0 being more effective. This suggests ChatGPT's potential role in promoting diversity and equity in living kidney donation, indicating scope for further refinement in making medical information more accessible.

Evaluating Global and Temporal Trends in Pancreas and Islet Cell Transplantation: Public Awareness and Engagement.

BACKGROUND: Pancreas transplantation is a crucial surgical intervention for managing diabetes, but it faces challenges such as its invasive nature, stringent patient selection criteria, organ scarcity, and centralized expertise. Despite the steadily increasing number of pancreas transplants in the United States, there is a need to understand global trends in interest to increase awareness of and participation in pancreas and islet cell transplantation. METHODS: We analyzed Google Search trends for "Pancreas Transplantation" and "Islet Cell Transplantation" from 2004 to 14 November 2023, assessing variations in search interest over time and across geographical locations. The Augmented Dickey-Fuller (ADF) test was used to determine the stationarity of the trends (p < 0.05). RESULTS: Search interest for "Pancreas Transplantation" varied from its 2004 baseline, with a general decline in peak interest over time. The lowest interest was in December 2010, with a slight increase by November 2023. Ecuador, Kuwait, and Saudi Arabia showed the highest search interest. "Islet Cell Transplantation" had its lowest interest in December 2016 and a more pronounced decline over time, with Poland, China, and South Korea having the highest search volumes. In the U.S., "Pancreas Transplantation" ranked 4th in interest, while "Islet Cell Transplantation" ranked 11th. The ADF test confirmed the stationarity of the search trends for both procedures. CONCLUSIONS: "Pancreas Transplantation" and "Islet Cell Transplantation" showed initial peaks in search interest followed by a general downtrend. The stationary search trends suggest a lack of significant fluctuations or cyclical variations. These findings highlight the need for enhanced educational initiatives to increase the understanding and awareness of these critical transplant procedures among the public and professionals.

COVID-19 and renal allograft rejection: insight from controlled and non-controlled studies.

AIM: Kidney transplant recipients (KTRs), due to their immunosuppressed status, are potentially more susceptible to both the severe effects of COVID-19 and complications in their transplanted organ. The aim of this study is to investigate whether COVID-19 infection increases the risk of rejection in kidney transplant recipients (KTRs). METHODS: This study involved a detailed literature review, conducted using PubMed, with the search being completed by September 7th, 2023. The search strategy incorporated a combination of relevant keywords: 'COVID', 'Renal', 'Kidney', 'Transplant', and 'Rejection'. The results from controlled and uncontrolled studies were separately collated and analyzed. RESULTS: A total of 11 studies were identified, encompassing 1,179 patients. Among these, two controlled studies reported the incidence of rejection in KTRs infected with COVID-19. Pooling data from these studies revealed no significant statistical correlation between COVID-19 infection and biopsy-proven rejection (p = 0.26). In addition, nine non-controlled studies were found, with rejection incidences ranging from 0% to 66.7%. The majority of these studies (eight out of nine) had small sample sizes, ranging from 3 to 75 KTRs, while the largest included 372 KTRs. The combined rejection rate across these studies was calculated to be 11.8%. CONCLUSION: In conclusion, the limited number of published controlled studies revealed no statistically significant association between COVID-19 infection and biopsy-proven rejection among KTRs. However, the broader analysis of non-controlled studies showed a variable rejection incidence with a pooled rejection rate of 11.8%. There is insufficient high-quality data to explore the association of COVID-19 infection and rejection.

Evaluating ChatGPT's Accuracy in Responding to Patient Education Questions on Acute Kidney Injury and Continuous Renal Replacement Therapy.

INTRODUCTION: Acute kidney injury (AKI) and continuous renal replacement therapy (CRRT) are critical areas in nephrology. The effectiveness of ChatGPT in simpler, patient education-oriented questions has not been thoroughly assessed. This study evaluates the proficiency of ChatGPT 4.0 in responding to such questions, subjected to various linguistic alterations. METHODS: Eighty-nine questions were sourced from the Mayo Clinic Handbook for educating patients on AKI and CRRT. These questions were categorized as original, paraphrased with different interrogative adverbs, paraphrased resulting in incomplete sentences, and paraphrased containing misspelled words. Two nephrologists verified the questions for medical accuracy. A χ2 test was conducted to ascertain notable discrepancies in ChatGPT 4.0's performance across these formats. RESULTS: ChatGPT provided notable accuracy in handling a variety of question formats for patient education in AKI and CRRT. Across all question types, ChatGPT demonstrated an accuracy of 97% for both original and adverb-altered questions and 98% for questions with incomplete sentences or misspellings. Specifically for AKI-related questions, the accuracy was consistently maintained at 97% for all versions. In the subset of CRRT-related questions, the tool achieved a 96% accuracy for original and adverb-altered questions, and this increased to 98% for questions with incomplete sentences or misspellings. The statistical analysis revealed no significant difference in performance across these varied question types (p value: 1.00 for AKI and 1.00 for CRRT), and there was no notable disparity between the artificial intelligence (AI)'s responses to AKI and CRRT questions (p value: 0.71). CONCLUSION: ChatGPT 4.0 demonstrates consistent and high accuracy in interpreting and responding to queries related to AKI and CRRT, irrespective of linguistic modifications. These findings suggest that ChatGPT 4.0 has the potential to be a reliable support tool in the delivery of patient education, by accurately providing information across a range of question formats. Further research is needed to explore the direct impact of AI-generated responses on patient understanding and education outcomes.

AI-driven translations for kidney transplant equity in Hispanic populations.

Health equity and accessing Spanish kidney transplant information continues being a substantial challenge facing the Hispanic community. This study evaluated ChatGPT's capabilities in translating 54 English kidney transplant frequently asked questions (FAQs) into Spanish using two versions of the AI model, GPT-3.5 and GPT-4.0. The FAQs included 19 from Organ Procurement and Transplantation Network (OPTN), 15 from National Health Service (NHS), and 20 from National Kidney Foundation (NKF). Two native Spanish-speaking nephrologists, both of whom are of Mexican heritage, scored the translations for linguistic accuracy and cultural sensitivity tailored to Hispanics using a 1-5 rubric. The inter-rater reliability of the evaluators, measured by Cohen's Kappa, was 0.85. Overall linguistic accuracy was 4.89 ± 0.31 for GPT-3.5 versus 4.94 ± 0.23 for GPT-4.0 (non-significant p = 0.23). Both versions scored 4.96 ± 0.19 in cultural sensitivity (p = 1.00). By source, GPT-3.5 linguistic accuracy was 4.84 ± 0.37 (OPTN), 4.93 ± 0.26 (NHS), 4.90 ± 0.31 (NKF). GPT-4.0 scored 4.95 ± 0.23 (OPTN), 4.93 ± 0.26 (NHS), 4.95 ± 0.22 (NKF). For cultural sensitivity, GPT-3.5 scored 4.95 ± 0.23 (OPTN), 4.93 ± 0.26 (NHS), 5.00 ± 0.00 (NKF), while GPT-4.0 scored 5.00 ± 0.00 (OPTN), 5.00 ± 0.00 (NHS), 4.90 ± 0.31 (NKF). These high linguistic and cultural sensitivity scores demonstrate Chat GPT effectively translated the English FAQs into Spanish across systems. The findings suggest Chat GPT's potential to promote health equity by improving Spanish access to essential kidney transplant information. Additional research should evaluate its medical translation capabilities across diverse contexts/languages. These English-to-Spanish translations may increase access to vital transplant information for underserved Spanish-speaking Hispanic patients.

Personalized Medicine Transformed: ChatGPT's Contribution to Continuous Renal Replacement Therapy Alarm Management in Intensive Care Units.

The accurate interpretation of CRRT machine alarms is crucial in the intensive care setting. ChatGPT, with its advanced natural language processing capabilities, has emerged as a tool that is evolving and advancing in its ability to assist with healthcare information. This study is designed to evaluate the accuracy of the ChatGPT-3.5 and ChatGPT-4 models in addressing queries related to CRRT alarm troubleshooting. This study consisted of two rounds of ChatGPT-3.5 and ChatGPT-4 responses to address 50 CRRT machine alarm questions that were carefully selected by two nephrologists in intensive care. Accuracy was determined by comparing the model responses to predetermined answer keys provided by critical care nephrologists, and consistency was determined by comparing outcomes across the two rounds. The accuracy rate of ChatGPT-3.5 was 86% and 84%, while the accuracy rate of ChatGPT-4 was 90% and 94% in the first and second rounds, respectively. The agreement between the first and second rounds of ChatGPT-3.5 was 84% with a Kappa statistic of 0.78, while the agreement of ChatGPT-4 was 92% with a Kappa statistic of 0.88. Although ChatGPT-4 tended to provide more accurate and consistent responses than ChatGPT-3.5, there was no statistically significant difference between the accuracy and agreement rate between ChatGPT-3.5 and -4. ChatGPT-4 had higher accuracy and consistency but did not achieve statistical significance. While these findings are encouraging, there is still potential for further development to achieve even greater reliability. This advancement is essential for ensuring the highest-quality patient care and safety standards in managing CRRT machine-related issues.

Integrating Retrieval-Augmented Generation with Large Language Models in Nephrology: Advancing Practical Applications.

The integration of large language models (LLMs) into healthcare, particularly in nephrology, represents a significant advancement in applying advanced technology to patient care, medical research, and education. These advanced models have progressed from simple text processors to tools capable of deep language understanding, offering innovative ways to handle health-related data, thus improving medical practice efficiency and effectiveness. A significant challenge in medical applications of LLMs is their imperfect accuracy and/or tendency to produce hallucinations-outputs that are factually incorrect or irrelevant. This issue is particularly critical in healthcare, where precision is essential, as inaccuracies can undermine the reliability of these models in crucial decision-making processes. To overcome these challenges, various strategies have been developed. One such strategy is prompt engineering, like the chain-of-thought approach, which directs LLMs towards more accurate responses by breaking down the problem into intermediate steps or reasoning sequences. Another one is the retrieval-augmented generation (RAG) strategy, which helps address hallucinations by integrating external data, enhancing output accuracy and relevance. Hence, RAG is favored for tasks requiring up-to-date, comprehensive information, such as in clinical decision making or educational applications. In this article, we showcase the creation of a specialized ChatGPT model integrated with a RAG system, tailored to align with the KDIGO 2023 guidelines for chronic kidney disease. This example demonstrates its potential in providing specialized, accurate medical advice, marking a step towards more reliable and efficient nephrology practices.

The impact of induction therapy on the risk of posttransplant lymphoproliferative disorder in adult kidney transplant recipients with donor-recipient serological Epstein-Barr virus mismatch.

Posttransplant lymphoproliferative disorder (PTLD) poses a significant concern in Epstein-Barr virus (EBV)-negative patients transplanted from EBV-positive donors (EBV R-/D+). Previous studies investigating the association between different induction agents and PTLD in these patients have yielded conflicting results. Using the Organ Procurement and Transplant Network database, we identified EBV R-/D+ patients >18 years of age who underwent kidney-alone transplants between 2016 and 2022 and compared the risk of PTLD with rabbit antithymocyte globulin (ATG), basiliximab, and alemtuzumab inductions. Among the 6620 patients included, 64.0% received ATG, 23.4% received basiliximab, and 12.6% received alemtuzumab. The overall incidence of PTLD was 2.5% over a median follow-up period of 2.9 years. Multivariable analysis demonstrated that the risk of PTLD was significantly higher with ATG and alemtuzumab compared with basiliximab (adjusted subdistribution hazard ratio [aSHR] = 1.98, 95% confidence interval [CI] 1.29-3.04, P = .002 for ATG and aSHR = 1.80, 95% CI 1.04-3.11, P = .04 for alemtuzumab). However, PTLD risk was comparable between ATG and alemtuzumab inductions (aSHR = 1.13, 95% CI 0.72-1.77, P = .61). Therefore, the risk of PTLD must be taken into consideration when selecting the most appropriate induction therapy for this patient population.

Association of Proton Pump Inhibitor Use and Immune Checkpoint Inhibitor Mediated Acute Kidney Injury: A Meta-Analysis and a Review of Related Outcomes.

INTRODUCTION: Immune checkpoint inhibitors (ICIs) have revolutionized cancer treatment. However, they pose the risk of immune-related adverse events, including ICI-mediated acute kidney injury (ICI-AKI). Recent studies have implicated proton pump inhibitors (PPIs) as potential contributors to ICI-AKI development. This meta-analysis examines the association between PPI use and ICI-AKI, exploring a potential modifiable risk factor in ICI therapy, while also reviewing the possible outcomes of ICI-AKI. METHODS: We conducted a comprehensive systematic review and meta-analysis of observational studies, assessing the risk of ICI-AKI in cancer patients concurrently using PPIs and potential outcomes. Odds ratios (ORs) were pooled using random-effects models. Subgroup analyses and sensitivity analyses were performed to evaluate heterogeneity and potential biases. RESULTS: A total of 14 studies involving 12,694 patients were included. In total, we analyzed 639 patients with all-cause AKI and 779 patients with ICI-AKI. The pooled OR for the overall incidence of AKI from all-cause was 1.57 (95% Confidence Interval (CI), 1.02 to 2.40) among patients on PPIs. Specifically, the risk of ICI-AKI associated with PPI use was significantly higher, with a pooled OR of 1.84 (95% CI 1.16 to 2.90). This indicates approximately 84% higher likelihood of developing ICI-AKI with concurrent use of PPIs. Additionally, among patients with ICI-AKI, 67% had complete or partial recovery of renal function, 32% progressed to chronic kidney disease (CKD) and about 36% died during a follow-up period of at least 3 months. CONCLUSION: This meta-analysis highlights the importance of cautious PPI prescription in cancer patients undergoing ICI therapy. Clinicians are advised to evaluate the risks and benefits of PPI use and consider alternative therapies when feasible.

Artificial Intelligence in Heart Failure and Acute Kidney Injury: Emerging Concepts and Controversial Dimensions.

BACKGROUND: The growing complexity of patient data and the intricate relationship between heart failure (HF) and acute kidney injury (AKI) underscore the potential benefits of integrating artificial intelligence (AI) and machine learning into healthcare. These advanced analytical tools aim to improve the understanding of the pathophysiological relationship between kidney and heart, provide optimized, individualized, and timely care, and improve outcomes of HF with AKI patients. SUMMARY: This comprehensive review article examines the transformative potential of AI and machine-learning solutions in addressing the challenges within this domain. The article explores a range of methodologies, including supervised and unsupervised learning, reinforcement learning, and AI-driven tools like chatbots and large language models. We highlight how these technologies can be tailored to tackle the complex issues prevalent among HF patients with AKI. The potential applications identified span predictive modeling, personalized interventions, real-time monitoring, and collaborative treatment planning. Additionally, we emphasize the necessity of thorough validation, the importance of collaborative efforts between cardiologists and nephrologists, and the consideration of ethical aspects. These factors are critical for the effective application of AI in this area. KEY MESSAGES: As the healthcare field evolves, the synergy of advanced analytical tools and clinical expertise holds significant promise to enhance the care and outcomes of individuals who deal with the combined challenges of HF and AKI.