Infections are the most common non-cardiovascular cause of death among dialysis patients. Earlier studies have shown similar or higher risk of infectious complications in peritoneal dialysis (PD) ...compared to hemodialysis (HD) patients, but comparisons to home HD patients have been rare. We investigated the risk of severe infections after start of continuous ambulatory PD (CAPD) and automated PD (APD) as compared to home HD.
All adult patients (n = 536), who were on home dialysis at day 90 from starting kidney replacement therapy (KRT) between 2004 and 2017 in Helsinki healthcare district, were included. We defined severe infection as an infection with C-reactive protein of 100 mg/l or higher. Cumulative incidence of first severe infection was assessed considering death as a competing risk. Hazard ratios were estimated using Cox regression with propensity score adjustment.
The risk of getting a severe infection during the first year of dialysis was 35% for CAPD, 25% for APD and 11% for home HD patients. During five years of follow-up, the hazard ratio of severe infection was 2.8 95% CI 1.6-4.8 for CAPD and 2.2 95% CI 1.4-3.5 for APD in comparison to home HD. Incidence rate of severe infections per 1000 patient-years was 537 for CAPD, 371 for APD, and 197 for home HD patients. When excluding peritonitis, the incidence rate was not higher among PD than home HD patients.
CAPD and APD patients had higher risk of severe infections than home HD patients. This was explained by PD-associated peritonitis.
Comorbidities are associated with increased mortality among patients receiving long-term kidney replacement therapy (KRT). However, it is not known whether primary kidney disease modifies the effect ...of comorbidities on KRT patients' survival.
An incident cohort of all patients (n = 8696) entering chronic KRT in Finland in 2000-2017 was followed until death or end of 2017. All data were obtained from the Finnish Registry for Kidney Diseases. Information on comorbidities (coronary artery disease, peripheral vascular disease, left ventricular hypertrophy, heart failure, cerebrovascular disease, malignancy, obesity, underweight, and hypertension) was collected at the start of KRT. The main outcome measure was relative risk of death according to comorbidities analyzed in six groups of primary kidney disease: type 2 diabetes, type 1 diabetes, glomerulonephritis (GN), polycystic kidney disease (PKD), nephrosclerosis, and other or unknown diagnoses. Kaplan-Meier estimates and Cox regression were used for survival analyses.
In the multivariable model, heart failure increased the risk of death threefold among PKD and GN patients, whereas in patients with other kidney diagnoses the increased risk was less than twofold. Obesity was associated with worse survival only among GN patients. Presence of three or more comorbidities increased the age- and sex-adjusted relative risk of death 4.5-fold in GN and PKD patients, but the increase was only 2.5-fold in patients in other diagnosis groups.
Primary kidney disease should be considered when assessing the effect of comorbidities on survival of KRT patients as it varies significantly according to type of primary kidney disease.
Mortality prediction is critical on long-term kidney replacement therapy (KRT), both for individual treatment decisions and resource planning. Many mortality prediction models already exist, but as a ...major shortcoming most of them have only been validated internally. This leaves reliability and usefulness of these models in other KRT populations, especially foreign, unknown. Previously two models were constructed for one- and two-year mortality prediction of Finnish patients starting long-term dialysis. These models are here internationally validated in KRT populations of the Dutch NECOSAD Study and the UK Renal Registry (UKRR).
We validated the models externally on 2051 NECOSAD patients and on two UKRR patient cohorts (5328 and 45493 patients). We performed multiple imputation for missing data, used c-statistic (AUC) to assess discrimination, and evaluated calibration by plotting average estimated probability of death against observed risk of death.
Both prediction models performed well in the NECOSAD population (AUC 0.79 for the one-year model and 0.78 for the two-year model). In the UKRR populations, performance was slightly weaker (AUCs: 0.73 and 0.74). These are to be compared to the earlier external validation in a Finnish cohort (AUCs: 0.77 and 0.74). In all tested populations, our models performed better for PD than HD patients. Level of death risk (i.e., calibration) was well estimated by the one-year model in all cohorts but was somewhat overestimated by the two-year model.
Our prediction models showed good performance not only in the Finnish but in foreign KRT populations as well. Compared to the other existing models, the current models have equal or better performance and fewer variables, thus increasing models' usability. The models are easily accessible on the web. These results encourage implementing the models into clinical decision-making widely among European KRT populations.
Background Necrotizing myopathies and muscle necrosis can be caused by immune-mediated mechanisms, drugs, ischemia, and infections, and differential diagnosis may be challenging. Case presentation We ...describe a case of diabetic myonecrosis complicated by pyomyositis and abscess caused by Escherichia coli. A white woman in her late forties was admitted to the hospital with a 1.5 week history of bilateral swelling, weakness, and mild pain of the lower extremities and inability to walk. She had a history of type 1 diabetes complicated by diabetic retinopathy, neuropathy, nephropathy, and end-stage renal disease. C-reactive protein was 203 mg/l, while creatinine kinase was only mildly elevated to 700 IU/l. Magnetic resonance imaging of her lower limb muscles showed extensive edema, and muscle biopsy was suggestive of necrotizing myopathy with mild inflammation. No myositis-associated or myositis-specific antibodies were detected. Initially, she was suspected to have seronegative immune-mediated necrotizing myopathy, but later her condition was considered to be explained better by diabetic myonecrosis with multifocal involvement. Her symptoms alleviated without any immunosuppressive treatment. After a month, she developed new-onset and more severe symptoms in her right posterior thigh. She was diagnosed with emphysematous urinary tract infection and emphysematous myositis and abscess of the right hamstring muscle. Bacterial cultures of drained pus from abscess and urine were positive for Escherichia coli. In addition to abscess drainage, she received two 3-4-week courses of intravenous antibiotics. In the discussion, we compare the symptoms and findings typically found in pyomyositis, immune-mediated necrotizing myopathy, and diabetic myonecrosis (spontaneous ischemic necrosis of skeletal muscle among people with diabetes). All of these diseases may cause muscle weakness and pain, muscle edema in imaging, and muscle necrosis. However, many differences exist in their clinical presentation, imaging, histology, and extramuscular symptoms, which can be useful in determining diagnosis. As pyomyositis often occurs in muscles with pre-existing pathologies, the ischemic muscle has likely served as a favorable breeding ground for the E. coli in our case. Conclusions Identifying the etiology of necrotizing myopathy is a diagnostic challenge and often requires a multidisciplinary assessment of internists, pathologists, and radiologists. Moreover, the presence of two rare conditions concomitantly is possible in cases with atypical features. Keywords: Case report, Diabetic myonecrosis, Infectious myositis
Type 2 diabetic (T2DM) patients on renal replacement therapy (RRT) seldom receive a kidney transplant, which is partly due to age and comorbidities. Adjusting for case mix, we investigated whether ...T2DM patients have equal opportunity for renal transplantation compared to other patients on dialysis, and whether survival after transplantation is comparable.
Patients who entered RRT in Finland in 2000-2010 (n = 5419) were identified from the Finnish Registry for Kidney Diseases and followed until the end of 2012. Of these, 20% had T2DM, 14% type 1 diabetes (T1DM) and 66% other than diabetes as the cause of ESRD. Uni-/multivariate survival analysis techniques were employed to assess the probability of kidney transplantation after the start of dialysis and survival after transplantation.
T2DM patients had a relative probability of renal transplantation of 0.18 (95% CI 0.15-0.22, P<0.001) compared to T1DM patients: this increased to 0.51 (95% CI 0.36-0.72, P<0.001) after adjustment for case mix (age, gender, laboratory values and comorbidities). When T2DM patients were compared to non-diabetic patients, the corresponding relative probabilities were 0.25 (95% CI 0.20-0.30, P<0.001) and 0.59 (95% CI 0.43-0.83, P = 0.002). After renal transplantation when adjusted for age and gender, relative risk of death was 1.25 (95% CI 0.64-2.44, P = 0.518) for T1DM patients and 0.72 (0.43-1.22, P = 0.227) for other patients compared to T2DM patients.
T2DM patients had a considerably lower probability of receiving a kidney transplant, which could not be fully explained by differences in the patient characteristics. Survival within 5 years after transplantation is comparably good in T2DM patients.
Mortality risk of patients with end-stage renal disease (ESRD) is highly elevated. Methods to estimate individual mortality risk are needed to provide individualized care and manage expanding ESRD ...populations. Many mortality prediction models exist but have shown deficiencies in model development (data comprehensiveness, validation) and in practicality. Therefore, our aim was to design 2 easy-to-apply prediction models for 1- and 2-year all-cause mortality in patients starting long-term renal replacement therapy (RRT).
We used data from the Finnish Registry for Kidney Diseases with complete national coverage of RRT patients. Model training group included all incident adult patients who started long-term dialysis in Finland in 2000 to 2008 (n
4335). The external validation cohort consisted of those who entered dialysis in 2009 to 2012 (n
1768). Logistic regression with stepwise variable selection was used for model building.
We developed 2 prognostic models, both of which only included 6 to 7 variables (age at RRT start, ESRD diagnosis, albumin, phosphorus, C-reactive protein, heart failure, and peripheral vascular disease) and showed sufficient discrimination (c-statistic 0.77 and 0.74 for 1- and 2-year mortality, respectively). Due to a significantly lower mortality in the newer cohort, the models, to a degree, overestimated mortality risk.
Mortality prediction algorithms could be more widely implemented into management of ESRD patients. The presented models are practical with only a limited number of variables and fairly good performance.
Cardiovascular diseases are an important cause of mortality in patients who have undergone kidney transplantation, but the knowledge on trends of cardiovascular mortality and specific causes of ...cardiovascular death among these patients is scarce.
Our aim was to compare the cardiovascular mortality rates after kidney transplantation in Finland between 1990-1999, 2000-2009, and 2010-2019 using data from the Finnish Registry for Kidney Diseases. We analyzed 1-year and long-term cardiovascular mortality rates as well as the specific causes of cardiovascular death and the trends in them.
In total, 4946 patients underwent first kidney transplantation in 1990-2019. During the follow-up time (median 8.3 years, interquartile range 4.0-14.5), there were 1392 deaths, of which 582 were cardiovascular deaths. In an unadjusted Cox regression model, the risk of long-term cardiovascular mortality was similar in the different periods. However, when adjusted for age, sex, duration of dialysis, and cause of kidney disease, the long-term cardiovascular mortality risk was significantly lower in 2000-2009 and 2010-2019 (hazard ratio 0.60 95% confidence interval, 0.49 to 0.73 and hazard ratio 0.51 95% confidence interval, 0.39 to 0.66, respectively) compared with 1990-1999. The results were similar regarding 1-year cardiovascular mortality. The distribution of different causes of cardiovascular death remained unchanged during the study period, with coronary artery disease accounting for 47% of deaths. During the first year after transplantation, pulmonary embolisms and arrhythmias were more common than in the long term.
Cardiovascular disease remained the most common cause of death in kidney transplant recipients, but adjusted cardiovascular mortality risk has decreased significantly during the past three decades. Coronary artery disease was the most frequent cause of cardiovascular death, and the proportion of coronary artery disease-related cardiovascular deaths increased after the first year after transplantation.
ABSTRACT
Background
Several studies have shown superior survival of patients on home haemodialysis (HD) compared with peritoneal dialysis (PD), but patients on automated PD (APD) and continuous ...ambulatory PD (CAPD) have not been considered separately. As APD allows larger fluid volumes and may be more efficient than CAPD, we primarily compared patient survival between APD and home HD.
Methods
All adult patients who started kidney replacement therapy (KRT) between 2004 and 2017 in the district of Helsinki-Uusimaa in Finland and who were on one of the home dialysis modalities at 90 days from starting KRT were included. We used intention-to-treat analysis. Survival of home HD, APD and CAPD patients was studied using Kaplan–Meier curves and Cox regression with adjustment for propensity scores that were based on extensive data on possible confounding factors.
Results
The probability of surviving 5 years was 90% for home HD, 88% for APD and 56% for CAPD patients. After adjustment for propensity scores, the hazard ratio of death was 1.1 95% confidence interval (CI) 0.52–2.4 for APD and 1.6 (95% CI 0.74–3.6) for CAPD compared with home HD. Censoring at the time of kidney transplantation (KTx) or at transfer to in-centre HD did not change the results. Characteristics of home HD and APD patients at the start of dialysis were similar, whereas patients on CAPD had higher median age and more comorbidities and received KTx less frequently.
Conclusions
Home HD and APD patients had comparable characteristics and their survival appeared similar.
To investigate how risk of end-stage renal disease (ESRD) among patients with type 1 diabetes has changed over time and further how the risk is affected by age, sex, and time period of diagnosis of ...diabetes.
A cohort including all patients <30 years old diagnosed with type 1 diabetes in Finland in 1965-2011 was followed until start of renal replacement therapy, death, or end of follow-up at the end of 2013. Altogether, 29,906 patients were included. The main outcome was cumulative risk of ESRD, accounting for death as a competing risk.
The patients were followed up for a median of 20 years. During 616,403 patient-years, 1,543 ESRD cases and 4,185 deaths were recorded. The cumulative risk of ESRD was 2.2% after 20 years and 7.0% after 30 years from the diabetes diagnosis. The relative risk of ESRD was 0.13 (95% CI 0.08-0.22) among patients diagnosed in 1995-2011 compared with those diagnosed in 1965-1979. Patients <5 years old at the time of diagnosis had the lowest risk of ESRD after diagnosis. With the cumulative risk of ESRD estimated from time of birth, the patients aged 5-9 years at diabetes diagnosis were at highest risk.
The cumulative risk of ESRD has decreased markedly during the past five decades. This highlights the importance of modern treatment of diabetes and diabetic nephropathy.
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