Clinical Identification of Geriatric Patients with Hypovitaminosis D: The 'Vitamin D Status Predictor for Geriatrics' Study.
Nutrients. 2017 Jun 27;9(7). pii: E658. doi: 10.3390/nu9070658.
Annweiler C1,2, Riou J3,4, Alessandri A5, Gicquel D6, Henni S7, Féart C8, Kabeshova A9.
Questions were asked of the elderly in the hospital setting
And compared to actual vitamin D tests
Machine Learning (ML) as used to determine the precise importance of each answer
ML is not constrained to having linear associations
ML was best at predicting extreme deficiency (less than 10 ng)
- Is a senior Vitamin D insufficient - a 2 minute questionnaire is 85 percent accurate – Nov 2019
- Vitamin D estimation nicely improved by neural networks – May 2015
- Vitamin D Status estimation of elderly by questionnaire – Oct 2017
- Both of the above studies appear to be the same study as the one on this page, but no mention of Machine Learning having been used
- Model has 80 percent chance of predicting vitamin D levels to within 10 ng – Feb 2012
- Predict Vitamin D category listing has
65 items along with related searches
- AI: Exciting opportunity for Vitamin D Researchers
The 16-item Vitamin D Status Predictor (VDSP) tool identifies healthy older community-dwellers at risk of hypovitaminosis D and may guide the use of blood tests in this population. The objective of the present hospital-based study was to test the efficacy of the VDSP to identify geriatric patients with hypovitaminosis D.
The study included 199 nonsupplemented geriatric in- and outpatients consecutively admitted to Angers University Hospital, France (mean ± SD, 82.0 ± 7.8 years; 53.3% female). Serum 25-hydroxyvitaminD (25(OH)D) was measured at the time of the physician-administered VDSP. Hypovitaminosis D was defined as serum 25(OH)D concentration ≤ 75 nmol/L for vitamin D insufficiency, 25(OH)D ≤ 50 nmol/L for vitamin D deficiency, and 25(OH)D ≤ 25 nmol/L for severe vitamin D deficiency. We found that 184 participants (92.4%) had vitamin D insufficiency, 136 (68.3%) had vitamin D deficiency, and 67 (33.7%) had severe vitamin D deficiency. The VDSP identified severe vitamin D deficiency with an area under curve (AUC) = 0.83 and OR = 24.0. The VDSP was able to identify vitamin D deficiency and vitamin D insufficiency with less accuracy (AUC = 0.71 and AUC = 0.73, respectively). In conclusion, the 16-item VDSP is a short questionnaire that accurately identifies geriatric patients with severe vitamin D deficiency. This tool may guide the use of blood collection for determining geriatric patients' vitamin D status.
age (in years),
number of therapeutic classes used per day,
body mass index (BMI, in kg/m2),
use walking aids,
use psychoactive drugs (i.e., benzodiazepines, anti-depressants or neuroleptics),
fear of falling,
history of falls in the preceding year,
History of vertebral fractures,
use anti-osteoporotic drugs (i.e., bisphosphonates, strontium, or calcium)Excellent prediction of very low vitamin D in elderly from just 16 questions (analyzed by ML) – June 2017
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