Nocturia, or waking at night at least once to void, is a common and bothersome lower
urinary tract symptom (LUTS) that results from an imbalance between functional
bladder storage capacity and urine production [1]. Inadequate functional bladder storage
results in small voided volumes and can be caused by different underlying conditions,
such as urinary tract infections, idiopathic/neurogenic detrusor over activity and
bladder outlet obstruction due to benign prostate enlargement (BPE). Increased
urinary output, which can be overnight only or during a 24h period, can also develop
for a variety of reasons such as heart failure, diabetes insipidus or mellitus, decreased
vasopressin levels, venous insufficiency, or obstructive sleep apnea. In order to initiate
appropriate treatment, a frequency volume chart (FVC) is recommended as an
indispensable tool to subtype nocturia patients according to the underlying etiology:
reduced functional bladder capacity (FBC), 24h polyuria, nocturnal polyuria (NP), or
combined etiology [2]. Treatments to improve FBC include anticholinergics in patients
with detrusor over activity and symptoms of overactive bladder (OAB), whereas recent
introduced treatment for OAB, beta-3-agonist stimulates beta-3 receptors, causing
smooth muscle relaxation in the bladder and α-blockers or 5α-reductase inhibitors in
case of BPE. Therapeutic measures directed to reduce nocturnal urinary output include
evening fluid restriction, leg elevation during daytime, timed diuretics, and antidiuretic
treatment with desmopressin [3,4]. Despite this knowledge, management of nocturia
patients remains to be challenging because unambiguous definitions of NP and
reduced FBC are lacking and as there is little evidence in reference to the effect of all
possible combinations of treatment modalities in case of a combined etiology of
nocturia [2,3,5,6].
Based on a pooled analysis of frequency volume charts of 183 elderly subjects both males and
females we developed a multivariate logistic regression model that could differentiate nights
with and without nocturia. By identifying the most important determinants for nocturia nights, the mixed etiology of
nocturia is recognized. In addition, the effect of influencing any of the parameters can lead to
estimating the probability of nocturia free nights using the multivariate model, which is of
clinical benefit for the patients.
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In the left column of this page, you can find the way to determine if the patient suffers from nocturia.
(1) Ferring pharmaceuticals
(2) Universiteit Gent Faculteit Geneeskunde en Gezondheidswetenschappen
Department of Uro-gynaecology
(3) DNAlytics
The model used to determine wether or not the patient suffers from nocturia is the model specified on the first row of the following table.
Selection of determinants |
Number of determinants |
Type of classification |
AUC (%) |
Sensitivity (%) |
Specificity (%) |
BCR (%) |
Kuncheva |
Random Forest |
7 | Logistic Regression |
98 (96-99) |
91 (86-97) |
93 (89-98) |
92 (90-95) |
0.944 |
LARS | 8 | EULR | 90 (85-94) |
86 (77-95) |
77 (69-85) |
82 (77-86) |
0.846 |
LARS | 6 | Random Forest |
93 (89-96) |
69 (60-78) |
93 (89-97) |
81 (76-86) |
0.847 |
BCR = balanced classification rate; EULR = ensemble of univariate logistic regressions; LARS = Least Angle Regression. |
To cite this calculator, use this reference: "Bastin M(3), Olesen TK(1), Denys MA(2), Goessaert AS(1), Bruneel E(1), Decalf V(1), Helleputte T(3),Paul J(3), Gramme P(3), Everaert K(2) - Online multivariate prediction model for nocturia, based on urinary tract etiologies, http://www.nocturia.dnalytics.com, 2018.".
To cite the scientific work behind this calculator, use this reference: Olesen TK, Denys MA, Goessaert AS, Bruneel E, Decalf V, Helleputte T, Paul J, Gramme P, Everaert K. 2018, Development of a multivariate prediction model for nocturia, based on urinary tract etiologies. International Journal of Clinical Practice