Cycles, Arrows and Turbulence: Time Patterns in Renal Disease, a Path from Epidemiology to Personalized Medicine?

Variability of Mortality: Additional Information on Mortality and Morbidity Curves under Normal and Pathological Conditions [Commentary on the Article by A. G. Malygin “Programmed Risks of Death in Male Patients with Diabetes” Published in Biochemistry (Moscow), vol. 86, pp. 1553-1562 (2021)]

Analysis of demographic data indicates uneven distribution of mortality within a year, month, and even week time period. This is of great practical importance for the operation of medical institutions, including intensive care units, and makes it possible to calculate economic and labor requirements of medical institutions. All the above is especially relevant during the era of the COVID-19 pandemic. Malygin showed the presence of one to two fluctuations per week in the mortality of male patients with type 2 diabetes. The height of the peaks of such fluctuations is determined, as expected, by the regular parameter indicating their position on the axis of lifespan and random parameter reflecting adverse effects of external environmental factors on the body, as well as the extent of the periodically occurring sharp decrease in the nonspecific resistance. This article discusses results of recent research in the field of small (semi-weekly, weekly, monthly, and seasonal) fluctuations of mortality. Based on a large array of accumulated data, it can be concluded that the decrease in seasonal variability of mortality accompanies an increase in the life expectancy. Studying characteristics of mortality fluctuations makes it possible to move from investigating the impact of biorhythms (Master Clock) on the development of acute and chronic phenoptotic processes directly to studying the patterns of mortality rhythms themselves (rhythms of phenoptosis).

Informed decision-making in delivery of dialysis: combining clinical outcomes with sustainability

As the prevalence of chronic kidney disease is expected to rise worldwide over the next decades, provision of renal replacement therapy (RRT), will further challenge budgets of all healthcare systems. Most patients today requiring RRT are treated with haemodialysis (HD) therapy and are elderly. This article demonstrates the interdependence of clinical and sustainability criteria that need to be considered to prepare for the future challenges of delivering dialysis to all patients in need. Newer, more sustainable models of high-value care need to be devised, whereby delivery of dialysis is based on value-based healthcare (VBHC) principles, i.e. improving patient outcomes while restricting costs. Essentially, this entails maximizing patient outcomes per amount of money spent or available. To bring such a meaningful change, revised strategies having the involvement of multiple stakeholders (i.e. patients, providers, payers and policymakers) need to be adopted. Although each stakeholder has a vested interest in the value agenda often with conflicting expectations and motivations (or motives) between each other, progress is only achieved if the multiple blocs of the delivery system are advanced as mutually reinforcing entities. Clinical considerations of delivery of dialysis need to be based on the entire patient disease pathway and evidence-based medicine, while the non-clinical sustainability criteria entail, in addition to economics, the societal and ecological implications of HD therapy. We discuss how selection of appropriate modes and features of delivery of HD (e.g. treatment modalities and schedules, selection of consumables, product life cycle assessment) could positively impact decision-making towards value-based renal care. Although the delivery of HD therapy is multifactorial and complex, applying cost-effectiveness analyses for the different HD modalities (conventional in-centre and home HD) can support in guiding payability (balance between clinical value and costs) for health systems. For a resource intensive therapy like HD, concerted and fully integrated care strategies need to be urgently implemented to cope with the global demand and burden of HD therapy.

A Call for an Ethics and Governance Action Plan to Harness the Power of Artificial Intelligence and Digitalization in Nephrology

Digitalization in nephrology has progressed in a manner that is disparate and siloed, even though learning (under a broader Learning Health System initiative) has been manifested in all the main areas of clinical application. Most applications based on artificial intelligence/machine learning (AI/ML) are still in the initial developmental stages and are yet to be adequately validated and shown to contribute to positive patient outcomes. There is also no consistent or comprehensive digitalization plan, and insufficient data are a limiting factor across all of these areas. In this article, we first consider how digitalization along nephrology care pathways relates to the Learning Health System initiative. We then consider the current state of AI/ML-based software and devices in nephrology and the ethical and regulatory challenges in scaling them up toward broader clinical application. We conclude with our proposal to establish a dedicated ethics and governance framework that is centered around health care providers in nephrology and the AI/ML-based software to which their work relates. This framework should help to integrate ethical and regulatory values and considerations, involve a wide range of stakeholders, and apply across normative domains that are conventionally demarcated as clinical, research, and public health.

Artificial intelligence enabled applications in kidney disease

Artificial intelligence (AI) is considered as the next natural progression of traditional statistical techniques. Advances in analytical methods and infrastructure enable AI to be applied in health care. While AI applications are relatively common in fields like ophthalmology and cardiology, its use is scarcely reported in nephrology. We present the current status of AI in research toward kidney disease and discuss future pathways for AI. The clinical applications of AI in progression to end-stage kidney disease and dialysis can be broadly subdivided into three main topics: (a) predicting events in the future such as mortality and hospitalization; (b) providing treatment and decision aids such as automating drug prescription; and (c) identifying patterns such as phenotypical clusters and arteriovenous fistula aneurysm. At present, the use of prediction models in treating patients with kidney disease is still in its infancy and further evidence is needed to identify its relative value. Policies and regulations need to be addressed before implementing AI solutions at the point of care in clinics. AI is not anticipated to replace the nephrologists' medical decision-making, but instead assist them in providing optimal personalized care for their patients.

Wearable health devices and personal area networks: can they improve outcomes in haemodialysis patients?

Digitization of healthcare will be a major innovation driver in the coming decade. Also, enabled by technological advancements and electronics miniaturization, wearable health device (WHD) applications are expected to grow exponentially. This, in turn, may make 4P medicine (predictive, precise, preventive and personalized) a more attainable goal within dialysis patient care. This article discusses different use cases where WHD could be of relevance for dialysis patient care, i.e. measurement of heart rate, arrhythmia detection, blood pressure, hyperkalaemia, fluid overload and physical activity. After adequate validation of the different WHD in this specific population, data obtained from WHD could form part of a body area network (BAN), which could serve different purposes such as feedback on actionable parameters like physical inactivity, fluid overload, danger signalling or event prediction. For a BAN to become clinical reality, not only must technical issues, cybersecurity and data privacy be addressed, but also adequate models based on artificial intelligence and mathematical analysis need to be developed for signal optimization, data representation, data reliability labelling and interpretation. Moreover, the potential of WHD and BAN can only be fulfilled if they are part of a transformative healthcare system with a shared responsibility between patients, healthcare providers and the payors, using a step-up approach that may include digital assistants and dedicated ‘digital clinics’. The coming decade will be critical in observing how these developments will impact and transform dialysis patient care and will undoubtedly ask for an increased ‘digital literacy’ for all those implicated in their care.

Seasonal and Secular Trends of Cardiovascular, Nutritional, and Inflammatory Markers in Patients on Hemodialysis

BACKGROUND

All life on earth has adapted to the effects of changing seasons. The general and ESKD populations exhibit seasonal rhythms in physiology and outcomes. The ESKD population also shows secular trends over calendar time that can convolute the influences of seasonal variations. We conducted an analysis that simultaneously considered both seasonality and calendar time to isolate these trends for cardiovascular, nutrition, and inflammation markers.

METHODS

We used data from adult patients on hemodialysis (HD) in the United States from 2010 through 2014. An additive model accounted for variations over both calendar time and time on dialysis. Calendar time trends were decomposed into seasonal and secular trends. Bootstrap procedures and likelihood ratio methods tested if seasonal and secular variations exist.

RESULTS

We analyzed data from 354,176 patients on HD at 2436 clinics. Patients were 59±15 years old, 57% were men, and 61% had diabetes. Isolated average secular trends showed decreases in pre-HD systolic BP (pre-SBP) of 2.6 mm Hg (95% CI, 2.4 to 2.8) and interdialytic weight gain (IDWG) of 0.35 kg (95% CI, 0.33 to 0.36) yet increases in post-HD weight of 2.76 kg (95% CI, 2.58 to 2.97). We found independent seasonal variations of 3.3 mm Hg (95% CI, 3.1 to 3.5) for pre-SBP, 0.19 kg (95% CI, 0.17 to 0.20) for IDWG, and 0.62 kg (95% CI, 0.46 to 0.79) for post-HD weight as well as 0.12 L (95% CI, 0.11 to 0.14) for ultrafiltration volume, 0.41 ml/kg per hour (95% CI, 0.37 to 0.45) for ultrafiltration rates, and 3.30 (95% CI, 2.90 to 3.77) hospital days per patient year, which were higher in winter versus summer.

CONCLUSIONS

Patients on HD show marked seasonal variability of key indicators. Secular trends indicate decreasing BP and IDWG and increasing post-HD weight. These methods will be of importance for independently determining seasonal and secular trends in future assessments of population health.

Immunological Effects of a Single Hemodialysis Treatment

Immune disorders, involving both innate and adaptive response, are common in patients with end-stage renal disease under chronic hemodialysis. Endogenous and exogenous factors, such as uremic toxins and the extracorporeal treatment itself, alter the immune balance, leading to chronic inflammation and higher risk of cardiovascular events. Several studies have previously described the immune effects of chronic hemodialysis and the possibility to modulate inflammation through more biocompatible dialyzers and innovative techniques. On the other hand, very limited data are available on the possible immunological effects of a single hemodialysis treatment. In spite of the lacking information about the immunological reactivity related to a single session, there is evidence to indicate that mediators of innate and adaptive response, above all complement cascade and T cells, are implicated in immune system modulation during hemodialysis treatment. Expanding our understanding of these modulations represents a necessary basis to develop pro-tolerogenic strategies in specific conditions, like hemodialysis in septic patients or the last session prior to kidney transplant in candidates for receiving a graft.