Seasonal variations in mortality and clinical indicators in international hemodialysis populations from the MONDO registry

Guinsburg, Adrián; Usvyat, Len; Etter, Michael; Xu, Xiaoqi; Thijssen, Stephan; Marcelli, Daniele; Canaud, Bernard; Marelli, Cristina; Barth, Cláudia; Wang, Yuedong; Carioni, Paola; Sande, Frank M. van der; Kotanko, Peter; Kooman, Jeroen P.

doi:10.1186/s12882-015-0129-y

Cited by 35 publications

(51 citation statements)

References 27 publications

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“…The incidence of cardiovascular disease and mortality in the general population is significantly higher in winter than in summer . A similar pattern of higher incidence of deaths during winter also has been reported in patients on chronic hemodialysis . It is unknown whether such a seasonal difference exists for mortality or graft failure among kidney transplant recipients in the US.…”

Section: Number Of Deaths and % Mean Annual Peak‐trough Difference Ammentioning

confidence: 81%

Seasonality of mortality and graft failure among kidney transplant recipients in the US - a retrospective study

et al. 2017

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Mortality in the general population and in patients on chronic hemodialysis is significantly higher in winter than summer. It is unknown whether such a seasonal difference exists for mortality or graft failure among kidney transplant recipients. We analyzed United Network for Organ Sharing (UNOS) data to assess whether the annual distribution of deaths and graft failures differed significantly from expected. There was significant annual variation in both deaths (n = 52 523) and graft failures (n = 50 301; both P < 0.001). The number of observed deaths exceeded the number expected by 8.9% in winter (P < 0.001), whereas the number of deaths was 4.8% lower than expected in summer (P < 0.01). The pattern was strongest for deaths attributable to cardiovascular disease (n = 11 509; 21.9%). Similarly, there was an excess of graft failures in winter (3.6%; P < 0.01) and a deficit in other seasons (all P ≤ 0.02). This pattern was observed for graft failures due to chronic rejection (P < 0.001) and other causes (P < 0.001), but not for acute rejection (P = 0.28) or recurrent disease (P = 0.27). Potential explanations for this variation include changes in physiologic parameters, changes in medication adherence and other behaviors, or changes in insurance coverage or clinical care. Further studies are necessary to identify specific mechanisms.

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Section: Number Of Deaths and % Mean Annual Peak‐trough Difference Ammentioning

confidence: 81%

Seasonality of mortality and graft failure among kidney transplant recipients in the US - a retrospective study

et al. 2017

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“…This is particularly of interest for this cat- ion, given the well-established seasonal variation of SNa and also the ultrafiltration volume in dialysis patient, which was shown in the paper by Li et al [11]. Given the 1-year observation period, the DR of SNa may to some extent also be subject to the influence of seasonal variation of temperature, fluid overload, interdialytic weight gain [11,[38][39][40]. Hence, all those aspects need to be taken into consideration when considering SNa variability in our study cohort.…”

Section: Discussionmentioning

confidence: 99%

Increased Mortality Associated with Higher Pre-Dialysis Serum Sodium Variability: Results of the International MONitoring Dialysis Outcome Initiative

Kooman

Sande

et al. 2018

Am J Nephrol

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Background: Low serum sodium (SNa) is associated with an increased mortality in chronic hemodialysis (HD) patients. Dialysis patients are thought to have an individual pre-dialysis SNa set-point, yet there is evidence for variability of pre-dialysis SNa in individual patient. In this study, we explored the association of several SNa variability metrics with all-cause mortality in a large patient population from the international MONitoring Dialysis Outcomes (MONDO) Initiative. Methods: All adult incident patients from the MONDO database with more than 5 SNa measurements during the first year on HD were included. All patients were required to survive the first year on HD (defined as the baseline). During the subsequent 2 years of follow-up, all-cause mortality was recorded. The following variability indicators were calculated during baseline: mean SNa and its SD; average real variability (ARV, average the absolute distance of the 2 consecutive SNa measurements), and average directional range (DR, the difference between minimum and maximum values). We used Cox Proportional hazard model with bivariate spline terms to analyze the joint association of SNa and SD, ARV and DR, respectively, with all-cause mortality. While conducting the multivariate Cox regression analyses, patients were stratified into 3 groups of DR (Negative DR: –20≤ DR ≤ –6, Null DR: –6< DR < 6 and Positive DR: 6≤ DR ≤20) with the Null DR as the reference group. Results: We included 20,216 patients in the study. A SNa ≤135 mEq/L was observed to be the strongest predictor of evaluated mortality risk. Higher SNa variability (quantified as SD, ARV, and DR) was also associated with an increased mortality irrespective of SNa levels. When compared with higher SD or ARV, greater DR showed a stronger association with an elevated risk of death. Controlling the Cox Proportional hazard models for additional parameters showed consistent results. Conclusion: Higher SNa variability associated with increased all-cause mortality at all levels of SNa. DR of SNa showed the strongest association with mortality and may constitute a Simple and novel prognostic indicator, easily applicable at the bedside.

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“…It is therefore possible that other factors also influence the difference in BP between the different seasons, such as sympathetic activity, vascular tone, and vitamin D levels [32][33][34]. Data from the Monitoring Dialysis Outcomes initiative showed comparable differences on a global level, with phase-shifted inverse patterns between the Northern and Southern hemispheres [35]. Interestingly, seasonal differences in body composition, with a higher fat mass in the winter and higher lean body mass in the summer, were observed [31].…”

Section: Seasonal Patternsmentioning

confidence: 80%

“…In addition, mortality in dialysis patients was significantly and consistently different between seasons with highest mortality in the winter and lowest in the summer months, both in a US population as well as at an international level [26,35] (Fig. 2).…”

Section: Seasonal Patternsmentioning

confidence: 99%

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

et al. 2018

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Patients with end-stage renal disease (ESRD) experience unique patterns in their lifetime, such as the start of dialysis and renal transplantation. In addition, there is also an intricate link between ESRD and biological time patterns. In terms of cyclic patterns, the circadian blood pressure (BP) rhythm can be flattened, contributing to allostatic load, whereas the circadian temperature rhythm is related to the decline in BP during hemodialysis (HD). Seasonal variations in BP and interdialytic-weight gain have been observed in ESRD patients in addition to a profound relative increase in mortality during the winter period. Moreover, nonphysiological treatment patters are imposed in HD patients, leading to an excess mortality at the end of the long interdialytic interval. Recently, new evidence has emerged on the prognostic impact of trajectories of common clinical and laboratory parameters such as BP, body temperature, and serum albumin, in addition to single point in time measurements. Backward analysis of changes in cardiovascular, nutritional, and inflammatory parameters before the occurrence as hospitalization or death has shown that changes may already occur within months to even 1–2 years before the event, possibly providing a window of opportunity for earlier interventions. Disturbances in physiological variability, such as in heart rate, characterized by a loss of fractal patterns, are associated with increased mortality. In addition, an increase in random variability in different parameters such as BP and sodium is also associated with adverse outcomes. Novel techniques, based on time-dependent analysis of variability and trends and interactions of multiple physiological and laboratory parameters, for which machine-learning approaches may be necessary, are likely of help to the clinician in the future. However, upcoming research should also evaluate whether dynamic patterns observed in large epidemiological studies have relevance for the individual risk profile of the patient.

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Seasonal variations in mortality and clinical indicators in international hemodialysis populations from the MONDO registry

Cited by 35 publications

References 27 publications

Seasonality of mortality and graft failure among kidney transplant recipients in the US - a retrospective study

Seasonality of mortality and graft failure among kidney transplant recipients in the US - a retrospective study

Increased Mortality Associated with Higher Pre-Dialysis Serum Sodium Variability: Results of the International MONitoring Dialysis Outcome Initiative

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

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