Search

Background: Many different internal factors have been proven to influence urine production such as age, weight, and quality of sleep. External factors such as consumption of caffeine and fluid consumption have been shown to have an impact on urine production., Aim: To investigate the impact of movement, physical activity and position on urine production., Methods: This prospective observational study was executed at Ghent University Hospital, Belgium. Study participation was open for anyone visiting the hospital. Participants collected one basic and two extended 24-hour urine collections and filled in questionnaires concerning their general health and physical activity. Urinary levels of osmolality, sodium and creatinine were determined. Data on movement, physical activity and position was described., Results: An increase in body movement leads to a significant increase in diuresis during daytime, night-time, and 24 hours (P = .002, P < .001, and P < .001, respectively). An increase in body movement leads to a significant decrease in osmolality during night-time and 24 hours (P = .009, and P = .004, respectively). However, no significant influence of movement on osmolality was found during daytime (P = .12). An increase in body movement leads to a significant decrease in creatinine during daytime, night-time and 24 hours (P = .001, <0.001, and P < .001, respectively). An increase in body movement leads to a significant increase in sodium during daytime (P = .046) but this was statistically significant during night-time and 24 hours (P = .32, and P = .84 respectively)., Conclusion: Our study demonstrates a statistically significant association of movement, physical activity, and position with urine production. It would therefore be interesting to explore this association further with the use of new technology to have more accurate data. Here, lays a potential role for conservative measurements and lifestyle adaptations in the management of patients with bothersome LUTS and more precisely nocturia., (© 2021 John Wiley & Sons Ltd.)

Background: Haptoglobin (Hp) displays three major phenotypes (Hp 1-1, Hp 2-2 and Hp 2-1). Hp 1-1 has been implicated in high blood pressure and salt sensitivity, and thus may mediate excess urine production., Aim: To explore the relationship between Hp polymorphisms and polyuria (>40 mL/kg/24 hours)., Methodology: Post hoc analysis of a prospective observational study of subjects who completed a renal function profile between October 2011 and February 2015 (n = 170). Hp phenotypes were determined by starch gel electrophoresis using haemoglobin-supplemented serum. The distribution of Hp phenotypes in subjects with and without polyuria was compared to a reference group of the same geography and ethnic composition. Diuresis rate, sodium clearance and free water clearance were compared within and between phenotypes., Results: The Hp1 allele frequency was significantly overexpressed in subjects with polyuria compared to the reference group (0.500 vs 0.400, P < .05). Consistently, the Hp 1-1 phenotype was more prevalent in subjects with polyuria compared to the reference group (28% vs 16%, P < .05). In contrast to Hp 2-1/2-2, Hp 1-1 demonstrated no circadian variation in diuresis rate, sodium clearance or free water clearance. A significant association between plasma Hp concentration and 24-hours sodium clearance was observed in Hp 1-1 subjects without polyuria (β = 0.222; 95% CI 0.003-0.441; P = .047)., Conclusion: The Hp1 allele was more frequent in subjects with polyuria, and participants with the Hp 1-1 phenotype were at greater risk for polyuria. Hp 1-1 subjects demonstrated an altered ability to concentrate urine with a slower continuous excretion of sodium throughout the day. Plasma Hp concentration of Hp 1-1 was positively correlated with 24-hours sodium clearance in subjects without polyuria., (© 2019 John Wiley & Sons Ltd.)

Purpose: The main objective of our study was to determine which combination of modifiable and non-modifiable parameters that could discriminate patients with nocturia from those without nocturia. This was a post-hoc analysis of 3 prospective, observational studies conducted in Ghent University. Participants completed frequency volume chart (FVC) to compare characteristics between patients with and without nocturia., Method: This was a post hoc analysis of three prospective, observational studies conducted in Ghent University. Participants completed frequency volume chart (FVC) to compare characteristics between adults with and without nocturia. Study 1: adults with and without nocturia (n = 148); Study 2: patients ≥65 years with and without nocturnal LUTS (n = 54); Study 3: menopausal women before and after hormone replacement therapy (n = 43). All eligible patients (n = 183) completed a FVC during 24 hours (n = 13), 48 hours (n = 30) or 72 hours (n = 140). The combination of algorithms and number of determinants obtaining the best average area under the receiver operating curve (AUC-ROC) led to the final model. Differences between groups were assessed using the AUC-ROC and Mann- Whitney-Wilcoxon tests. Holm corrections were applied for multiple statistical testing. Also, the stability of the feature selection was evaluated., Results: The best discrimination was obtained when 13 determinants were included. However, a logistic regression model based on seven determinants selected with random forest had comparable discrimination including an optimal signature stability. It was able to discriminate almost perfectly between nights with and without nocturia., Conclusion: Relevant information to accomplish the excellent predictability of the model is; functional bladder capacity, 24 hours urine output, nocturnal output, age, BMI. The multivariate model used in this analysis provides new insights into combination therapy as it allows simulating the effect of different available treatment modalities and its combinations., (© 2018 The Authors. International Journal of Clinical Practice Published by John Wiley & Sons Ltd.)