Digital health and acute kidney injury: consensus report of the 27th Acute Disease Quality Initiative workgroup

Kashani, Kianoush B.; Awdishu, Linda; Bagshaw, Sean M.; Barreto, Erin F.; Claure-Del Granado, Rolando; Evans, Barbara J.; Forni, Lui G.; Ghosh, Erina; Goldstein, Stuart L.; Kane-Gill, Sandra L.; Koola, Jejo; Koyner, Jay L.; Liu, Mei; Murugan, Raghavan; Nadkarni, Girish N.; Neyra, Javier A.; Ninan, Jacob; Ostermann, Marlies; Pannu, Neesh; Rashidi, Parisa; Ronco, Claudio; Rosner, Mitchell H.; Selby, Nicholas M.; Shickel, Benjamin; Singh, Karandeep; Soranno, Danielle E.; Sutherland, Scott M.; Bihorac, Azra; Mehta, Ravindra L.

doi:10.1038/s41581-023-00744-7

Cited by 17 publications

(5 citation statements)

References 120 publications

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“…Research investigations are strengthened by the inclusion of team members with a broad array of expertise, such as the inclusion of clinical researchers on pre-clinical work and health service researchers, patients and patient advocates, and implementation scientists to understand how to optimally deploy clinical and research findings [ 44 ]. A truly integrated research approach includes not only investigations throughout the basic science to epidemiologic spectrum, but also incorporates digital health tools and community partnerships to better meet patients and families in their communities and make them partners in health [ 100 ]. Health service and epidemiological studies may benefit from inclusion of specific outcome measures guided by pre-clinical work.…”

Section: Resultsmentioning

confidence: 99%

Advances in pediatric acute kidney injury pathobiology: a report from the 26th Acute Disease Quality Initiative (ADQI) conference

Starr,

Barreto,

Charlton

et al. 2023

Pediatr Nephrol

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Background In the past decade, there have been substantial advances in our understanding of the pathobiology of pediatric acute kidney injury (AKI). In particular, animal models and studies focused on the relationship between kidney development, nephron number, and kidney health have identified a number of heterogeneous pathophysiologies underlying AKI. Despite this progress, gaps remain in our understanding of the pathobiology of pediatric AKI. Methods During the 26th Acute Disease Quality Initiative (ADQI) Consensus conference, a multidisciplinary group of experts discussed the evidence and used a modified Delphi process to achieve consensus on recommendations for opportunities to advance translational research in pediatric AKI. The current state of research understanding as well as gaps and opportunities for advancement in research was discussed, and recommendations were summarized. Results Consensus was reached that to improve translational pediatric AKI advancements, diverse teams spanning pre-clinical to epidemiological scientists must work in concert together and that results must be shared with the community we serve with patient involvement. Public and private research support and meaningful partnerships with adult research efforts are required. Particular focus is warranted to investigate the pediatric nuances of AKI, including the effect of development as a biological variable on AKI incidence, severity, and outcomes. Conclusions Although AKI is common and associated with significant morbidity, the biologic basis of the disease spectrum throughout varying nephron developmental stages remains poorly understood. An incomplete understanding of factors contributing to kidney health, the diverse pathobiologies underlying AKI in children, and the historically siloed approach to research limit advances in the field. The recommendations outlined herein identify gaps and outline a strategic approach to advance the field of pediatric AKI via multidisciplinary translational research.

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Section: Resultsmentioning

confidence: 99%

Advances in pediatric acute kidney injury pathobiology: a report from the 26th Acute Disease Quality Initiative (ADQI) conference

Starr,

Barreto,

Charlton

et al. 2023

Pediatr Nephrol

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“…As an example, rural patients may be better reached with virtual rather than in-person visits to limit transportation burden. 15 , 31 , 40 A care coordinator could be an important resource for survivors of AKI; however, the availability and reimbursement for such a dedicated individual is uncertain and center-specific.…”

Section: Methodsmentioning

confidence: 99%

Optimum Care of AKI Survivors Not Requiring Dialysis after Discharge: An AKINow Recovery Workgroup Report

Barreto,

Cerda,

Freshly

et al. 2023

Kidney360

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Acute kidney injury (AKI) affects one in five hospitalized patients and is associated with poor short- and long-term clinical and patient-centered outcomes. Among those who survive to discharge, significant gaps in documentation, education, communication, and follow-up have been observed. The American Society of Nephrology established the AKINow taskforce to address these gaps and improve AKI care. The AKINow Recovery workgroup convened two focus groups, one each focused on dialysis-independent and dialysis-requiring AKI, to summarize the key considerations, challenges, and opportunities in the care of AKI survivors. This manuscript highlights the discussion surrounding care of AKI survivors discharged without the need for dialysis. On May 3, 2022, 48 patients and multidisciplinary clinicians from diverse settings were gathered virtually. The agenda included a patient testimonial, plenary sessions, facilitated small group discussions and debriefing. Core challenges and opportunities for AKI care identified were in the domains of transitions of care, education, collaborative care delivery, diagnostic and therapeutic interventions, and digital health applications. Integrated multispecialty care delivery was identified as one of the greatest challenges to AKI survivor care. Adequate templates for communication and documentation, education of patients, care partners, and clinicians about AKI, and a well-coordinated multidisciplinary post-hospital follow-up plan form the basis for a successful care transition at hospital discharge. The AKINow Recovery workgroup concluded that advancements in evidence-based, patient-centered care of AKI survivors are needed to improve health outcomes, care quality, and patient and provider experience. Tools are being developed by the AKINow Recovery workgroup for use at the hospital discharge to facilitate care continuity.

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“…AI and ML have shown tremendous potential in the medical field, including in identifying and managing SA-AKI. However, utilizing these tools is not without challenges and ethical considerations [54,[65][66][67].…”

Section: Constraints and Ethical Considerationsmentioning

confidence: 99%

Artificial intelligence and machine learning’s role in sepsis-associated acute kidney injury

Cheungpasitporn,

Thongprayoon,

Kashani

2024

Kidney Res Clin Pract

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Sepsis-associated acute kidney injury (SA-AKI) is a serious complication in critically ill patients, resulting in higher mortality, morbidity, and cost. The intricate pathophysiology of SA-AKI requires vigilant clinical monitoring and appropriate, prompt intervention. While traditional statistical analyses have identified severe risk factors for SA-AKI, the results have been inconsistent across studies. This has led to growing interest in leveraging artificial intelligence (AI) and machine learning (ML) to predict SA-AKI better. ML can uncover complex patterns beyond human discernment by analyzing vast datasets. Supervised learning models like XGBoost and RNN-LSTM have proven remarkably accurate at predicting SA-AKI onset and subsequent mortality, often surpassing traditional risk scores. Meanwhile, unsupervised learning reveals clinically relevant sub-phenotypes among diverse SA-AKI patients, enabling more tailored care. In addition, it potentially optimizes sepsis treatment to prevent SA-AKI through continual refinement based on patient outcomes. However, utilizing AI/ML presents ethical and practical challenges regarding data privacy, algorithmic biases, and regulatory compliance. AI/ML allows early risk detection, personalized management, optimal treatment strategies, and collaborative learning for SA-AKI management. Future directions include real-time patient monitoring, simulated data generation, and predictive algorithms for timely interventions. However, a smooth transition to clinical practice demands continuous model enhancements and rigorous regulatory oversight. In this article, we outlined the conventional methods used to address SA-AKI and explore how AI and ML can be applied to diagnose and manage SA-AKI, highlighting their potential to revolutionize SA-AKI care.

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Digital health and acute kidney injury: consensus report of the 27th Acute Disease Quality Initiative workgroup

Cited by 17 publications

References 120 publications

Advances in pediatric acute kidney injury pathobiology: a report from the 26th Acute Disease Quality Initiative (ADQI) conference

Advances in pediatric acute kidney injury pathobiology: a report from the 26th Acute Disease Quality Initiative (ADQI) conference

Optimum Care of AKI Survivors Not Requiring Dialysis after Discharge: An AKINow Recovery Workgroup Report

Artificial intelligence and machine learning’s role in sepsis-associated acute kidney injury

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