Background Experiences from the first wave of the 2019 coronavirus disease (COVID-19) pandemic can aide in the development of future preventive strategies. To date, risk prediction models for COVID-19-related incidence and outcomes in haemodialysis (HD) patients are missing. Methods We developed risk prediction models for COVID-19 incidence and mortality among HD patients. We studied 38 256 HD patients from a multi-national dialysis cohort between March 3rd and July 3rd 2020. Risk prediction models were developed and validated, based on predictors readily available in outpatient haemodialysis units. We compared mortality among patients with and without COVID-19, matched for age, sex, and diabetes. Results During the observational period, 1 259 patients (3.3%) acquired COVID-19. Of these, 62% were hospitalised or died. Mortality was 22% among COVID-19 patients with odds ratios 219.8 (95% CI 80.6-359) to 342.7 (95% CI 60.6-13595.1), compared to matched patients without COVID-19. Since the first wave of the pandemic affected mostly European countries during the study, the risk prediction model for incidence of COVID-19 was developed and validated in European patients only (N = 22 826, AUCDev 0.64, AUCVal 0.69). The model for prediction of mortality was developed in all COVID-19 patients (AUCDev 0.71, AUCVal 0.78). Angiotensin receptor blockers were independently associated with a lower incidence of COVID-19 in European patients. Conclusions We identified modifiable risk factors for COVID-19 incidence and outcome in HD patients. Our risk prediction tools can be readily applied in clinical practice. The current study can aid in the development of preventive strategies for future waves of COVID-19.

Background Dialysis patients are at risk for lower SARS-CoV-2-vaccine immunogenicity than the normal population. We assessed immunogenicity to a first mRNA- or vector-based SARS-CoV-2-vaccination dose in dialysis patients. Methods In a multicenter observational pilot study, 2 weeks after a first vaccination (BNT162b2/Pfizer-BioNTech [Comirnaty] or ChAdOx1 nCoV-19/Oxford-Astra-Zeneca [Vaxzevria]), hemodialysis patients (N = 23), peritoneal dialysis patients (N = 4) and healthy staff (N = 14) were tested for SARS-CoV-2-spike IgG/IgM, Nucleocapsid-protein-IgG-antibodies and plasma ACE2-receptor-binding-inhibition capacity. Hemodialysis patients who had had prior COVID-19 infection (N = 18) served as controls. Both response to first SARS-CoV-2 vaccination and IgG spike-positivity following prior COVID-19 infection were defined as SARS-CoV-2 spike IgG levels ≥ 50 AU/mL. Results Vaccination responder rates were 17.4% (4/23) in hemodialysis patients, 100% (4/4) in peritoneal dialysis patients and 57.1% (8/14) in staff (HD vs. PD: p = 0.004, HD vs. staff: p = 0.027). Among hemodialysis patients, type of vaccine (Comirnaty N = 11, Vaxzevria N = 12, 2 responders each) did not appear to influence antibody levels (IgG spike: Comirnaty median 0.0 [1.–3. quartile 0.0–3.8] versus Vaxzevria 4.3 [1.6–20.1] AU/mL, p = 0.079). Of responders to the first dose of SARS-CoV-2 vaccination among hemodialysis patients (N = 4/23), median IgG spike levels and ACE2-receptor-binding-inhibition capacity were lower than that of IgG spike-positive hemodialysis patients with prior COVID-19 infection (13/18, 72.2%): IgG spike: median 222.0, 1.–3. quartile 104.1–721.9 versus median 3794.6, 1.–3. quartile 793.4–9357.9 AU/mL, p = 0.015; ACE2-receptor-binding-inhibition capacity: median 11.5%, 1.–3. quartile 5.0–27.3 versus median 74.8%, 1.–3. quartile 44.9–98.1, p = 0.002. Conclusions Two weeks after their first mRNA- or vector-based SARS-CoV-2 vaccination, hemodialysis patients demonstrated lower antibody-related response than peritoneal dialysis patients and healthy staff or unvaccinated hemodialysis patients following prior COVID-19 infection. Graphic abstract

Objetive: To estimate the growth parameters of Peruvian children and adolescents living at different altitudes. Methods: The sample comprised 10 795 Peruvian children and adolescents (5781 girls, aged 6-7 years) from sea level, the Amazon region, and high altitude. Height was measured with standardized techniques. Mathematical and biological growth parameters were estimated using the Preece-Baines growth model I.Results: Sea-level children and adolescents experienced peak height velocity (PHV) at an earlier age (girls, 8.56 ± 2.37 years; boys, 12.03 ± 0.58 years) were taller at the time of PHV (girls, 144.1 ± 1.9 cm; boys, 154.3 ± 1.4 cm), had higher PHV (girls, 6.23 ± 3.87 cm/year; boys, 7.52 ± 2.31 cm/year), and had a taller estimated final height (girls, 154.2 ± 0.3 cm; boys, 166.3 ± 1.0 cm) compared to those living at high altitude (girls, 152.7 ± 0.7 cm; boys, 162.8 ± 0.8 cm) or in the Amazon region (152.1 ± 0.4 cm; boys, 162.2 ± 0.6 cm). Across all geographical areas, PHV occurred approximately 2 years earlier in girls (9.68 ± 0.99 years) than in boys (12.61 ± 0.42 years), their estimated PHV was 5.88 ± 1.92 cm/year vs 6.45 ± 1.09 cm/year, their size at PHV was 142.2 ± 1.4 cm vs 152.8 ± 0.7 cm, and their final adult height was estimated to be 153.1 ± 0.3 cm vs 164.2 ± 0.7 cm. Conclusions: Peruvian children and adolescents' physical growth timing and tempo were influenced by their living altitudes. Those living at sea level experienced an earlier age at PHV were taller at time of PHV, had a higher PHV, and had a taller estimated final height compared to those living at higher altitudes. Girls and boys also differed significantly in their growth parameters.

This study investigated the associations between biological and environmental factors and gross-motor coordination (GMC) in Peruvian children and adolescents. The sample comprised 7401 boys and girls, aged 6–14 years, recruited from three geographical regions: sea-level, Amazon and high-altitude. Biological variables included age, sex, height, BMI, physical fitness, stunting, and maturational status. Environmental influences included geographical region and school characteristics. Gross-motor coordination was tested with the Körperkoordinationstest für Kinder and the data analyzed by multilevel logistic regression. Results showed a high prevalence of below normal GMC scores. Sex, age, geographical area, biological maturation, BMI (normal versus overweight/obesity), and stunting were all significant predictors of GMC. There was also an interaction between age, sex, and geographical area indicating that older girls who lived at sea-level and high-altitude were more likely to display below normal GMC scores. The school context was less important in predicting GMC problems than the interplay between biological characteristics and geographical region. These results suggest that early identification, as well as educational and pediatric care interventions, are of importance in reducing below normal GMC among Peruvian children and adolescents.

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Stunting, defined as linear growth retardation, is a serious public health problem in developing countries. We aimed to (1) describe the prevalence of stunting in Peruvian youth living in three geographical regions, and to (2) determine height and physical fitness (PF) differences between stunted and normal-growth children across age and sex. We sampled 7918 subjects (7074 normal-growth and 844 stunted), aged 6–15 year, from sea-level, Amazon and high-altitude regions of Peru. PF was assessed with standardized tests, and stunting was computed following World Health Organization (WHO) standards. A two-factor analysis of variance (ANOVA) model was used. Results showed that stunting prevalence increased with age (from 6% at 6 year to 18.4% at 15 year in girls, and 9.3% at 6 year to 16.4% at 15 year in boys); was higher in boys (12.3%) than in girls (9.3%), and was higher in the Amazon region (25.3%), followed by high-altitude (24.3%) and sea-level (8.1%). Stunting had a negative overall impact on girls’ and boys’ statures. Further, the age-by-stunting interactions were statistically significant for both sexes, and significant differences in height varied to some degree across age. Stunted children performed worse in handgrip and standing long jump, but outperformed their normal-growth peers in shuttle-run (only boys), and in 12 min run. Further, significant differences in the age-by-stunting interaction occurred in all PF tests, varying to some degree across age. In conclusion, stunting significantly affects Peruvian youth’s PF levels, and this influence is sex-, age- and PF test-specific.

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Background and Aim. Overweight prevalence in children and adolescents shows great variability which is related to individual-level and environmental-level factors. The present study aimed to determine the prevalence of and factors associated with overweight in Peruvian children and adolescents living at different altitudes. Methods. 8568 subjects, aged 6–16 y, from the sea level, Amazon, and high-altitude regions were sampled. Overweight was identified using BMI; biological maturation and physical fitness were measured; school characteristics were assessed via an objective audit. Results. Overweight prevalence decreased with age (28.3% at 6 y to 13.9% at 16 y); it was higher in girls (21.7%) than boys (19.8%) and was higher at the sea level (41.3%), compared with Amazon (18.8%) and high-altitude (6.3%) regions. Approximately 79% of the variance in overweight was explained by child-level characteristics. In Model 1, all child-level predictors were significant (p<0.001); in Model 2, six out of nine added school-level predictors (number of students, existence of policies and practices for physical activity, multisports-roofed, duration of Physical Education classes, and extracurricular activities) were significant (p<0.001); in Model 3, subjects living at high altitudes were less likely to be overweight than those living at the sea level. Conclusions. Child- and school-level variables played important roles in explaining overweight variation. This information should be taken into account when designing more efficient strategies to combat the overweight and obesity epidemic.