Local body weight measurement of the spindle

2021 ◽  
Vol 56 (7) ◽  
pp. 871-872
Author(s):  
Masahito Tanaka ◽  
Yuta Shimamoto
Keyword(s):  
Body Weight ◽  
Weight Measurement ◽  
Local Body

P5407Body-composition analysis of patients with acute heart failure - preliminary results from the SCALE HF trial

2019 ◽  
Vol 40 (Supplement_1) ◽  
Author(s):  
F De Ieso ◽  
M Mutke ◽  
J Du Fay De Lavallaz ◽  
C Raichle ◽  
N Brasier ◽  
...  
Keyword(s):  
Heart Failure ◽  
Body Composition ◽  
Body Weight ◽  
Diuretic Therapy ◽  
Total Body Weight ◽  
Body Water ◽  
Extracellular Water ◽  
Raw Data ◽  
Weight Measurement ◽  
Total Body

Abstract Background Guidance for intensified diuretic therapy in acute heart failure (AHF) is mainly based on body weight measurement, frequently leading to a short episode of dehydration with kidney failure after recompensation. In addition, patients often present immobilized due to severe health issues making weight measurement stressful. Purpose Bioelectrical impedance analysis (BIA) may be a more direct approach to guide intensified diuretic therapy analysing patient's body composition. We hypothesized that patient's weight loss during therapy correlates with loss of body water measured by BIA. Therefore, we tested if this method could be an alternative to daily weight measurement. Methods We conducted an observational, single-centre study to evaluate and monitor body composition of patients hospitalised with AHF, adjudicated according to current ESC/HFA guidelines by a cardiologist. We used an eight-electrode, segmental, multi-frequency body composition analyser, previously validated against air displacement plethysmography, whole body MRI, deuterium and sodium bromide dilution. We investigated patients until hospital discharge or latest one day after ending intensified diuretic therapy. Disease specific properties, BIA and weight measurement were assessed daily. Furthermore, we investigated BIA raw data. Results 390 BIA were applied on 76 patients (47 men; 29 women; mean age 76±11 years; mean weight 75.6±15.7 kg). 34 patients presented with global, 27 with left-heart, 8 with right-heart and 7 with not specified AHF. 44 patients presented with pleural effusion. Pearson correlations showed that total body water (r=0.737, p≤0.001) and extracellular water (r=0.69, p≤0.001) correlated each with total body weight. Changes in total body water accurately (within a range of ± 1kg) reflected changes in total body weight in 40.28% of the patients and changes in extracellular water showed a similarly accurate reflection of total body weight change in 68.06% of the patients. BIA raw-data analysis showed significant changes using Wilcoxon test between measurements at the beginning of intensified diuretic therapy and at its end. We found a significant increase of resistance (mean from 334.6±67.5 to 362.8±69.5 Ohm/m; p=0.021) and reactance (mean from 21.3±7.1 to 24.1±6.2 Ohm/m; p=0.009) standardized to patients height and a non-significant increase of phase angle (mean from 3.6±0.9 to 3.8±0.8 °; p=0.149) during hospitalisation. Conclusion BIA is able to estimate changes in total body weight by analysing changes in extracellular body water in patients under intensified diuretic therapy and raw data analysis seems even more accurate and promising. This data derive from a heterogeneous AHF patient group, needing further investigation. Once validated, wearable BIA connected to an automated device monitoring system would enable an easy to use diuretic therapy monitoring for impaired patients or outpatients and could help reducing care efforts.

Deriving Weight from Big Data: A Comparison of Body Weight Measurement Cleaning Algorithms (Preprint)

2021 ◽  
Author(s):  
Richard Evans ◽  
Jennifer Burns ◽  
Anne Annis ◽  
Michelle Freitag ◽  
Susan Raffa ◽  
...  
Keyword(s):  
Body Weight ◽  
Veterans Health Administration ◽  
Primary Care Visit ◽  
Veterans Health ◽  
Health Administration ◽  
Weight Measurement ◽  
Care Visit ◽  
Complex Models ◽  
One Year ◽  
Weight Data

BACKGROUND Patient body weight is a frequently utilized measure in biomedical studies, yet there are exist no standard methods for processing and cleaning weight data. Conflicting documentation on constructing body weight measurements presents challenges for research and program evaluation. OBJECTIVE We sought to describe and compare methods for extracting and cleaning weight data from electronic health record (EHR) databases to develop guidelines for standardized approaches that promote reproducibility. METHODS We conducted a systematic review of studies that used Veterans Health Administration (VHA) EHR weight data, published from 2008 – 2018 and documented the algorithms for constructing patient weight. We applied these algorithms to a cohort of veterans with at least one Primary Care visit in 2016. The resulting weight measures were compared at the patient and site levels. RESULTS We identified 496 studies and included 62 that utilized weight as outcome variables; 48% included a replicable algorithm. Algorithms varied from cut-offs of implausible weights to complex models using measures within patient over time. We found differences in the number of weight values after applying the algorithms (86% to 99% of raw data) and decreased variance (SD = 68 to 54), but little difference in average weights across methods (216 to 220 lbs.). The percent of patients with at least 5% weight loss over one year ranged from 18% to 24%. CONCLUSIONS Determining the best method to assess weight using EHR data can be computationally demanding. Our results suggest that for many studies, applying simple cut-offs that require fewer computing resources and are easier to understand may be sufficient. We present guidelines for situations where more complex approaches may be warranted.

Body Weight Measurement Using Image Processing Based on Body Surface Area and Elliptical Tube Volume

2018 ◽  
Author(s):  
Tan Halim Supranata ◽  
Poh Steven Sean Davin ◽  
Darren Kent Jeremy ◽  
Anggy Eka Pratiwi ◽  
Meirista Wulandari
Keyword(s):  
Image Processing ◽  
Body Weight ◽  
Surface Area ◽  
Body Surface Area ◽  
Body Surface ◽  
Weight Measurement

Lack of body weight measurement is associated with mortality and hospitalization in community-dwelling frail elderly

2007 ◽  
Vol 26 (6) ◽  
pp. 764-770 ◽  
Author(s):  
Sachiko Izawa ◽  
Hiromi Enoki ◽  
Yoshihisa Hirakawa ◽  
Yuichiro Masuda ◽  
Mitsunaga Iwata ◽  
...  
Keyword(s):  
Body Weight ◽  
Frail Elderly ◽  
Community Dwelling ◽  
Weight Measurement

scholarly journals The Value of Body Weight Measurement to Assess Dehydration in Children

PLoS ONE ◽  
2013 ◽  
Vol 8 (1) ◽  
pp. e55063 ◽  
Author(s):  
Isabelle Pruvost ◽  
François Dubos ◽  
Emmanuel Chazard ◽  
Valérie Hue ◽  
Alain Duhamel ◽  
...  
Keyword(s):  
Body Weight ◽  
Weight Measurement

scholarly journals Is body weight measurement accurate in the ICU?

2017 ◽  
Vol 24 (6) ◽  
pp. 639-640
Author(s):  
Hiroaki Murata ◽  
Yasuhiro Honda ◽  
Yoko Yamaguchi ◽  
Shinjiro Saito ◽  
Yusuke Iizuka ◽  
...  
Keyword(s):  
Body Weight ◽  
Weight Measurement

506 Late-Breaking: Rapid Weight Assessment of Finishing Pigs

2021 ◽  
Vol 99 (Supplement_3) ◽  
pp. 209-209
Author(s):  
Victoria Abner ◽  
Jonathan P Holt ◽  
Mark Knauer ◽  
Sierra Young
Keyword(s):  
Body Weight ◽  
Animal Movement ◽  
Economic Loss ◽  
Finishing Pigs ◽  
Swine Farms ◽  
Weight Measurement ◽  
Final Study ◽  
Trained Individual ◽  
Swine Herds ◽  
Over Time

Abstract Accurate pig body weight assessment is an important factor in managing swine herds and imperative when determining acceptable market weights. Pigs marketed outside the desired weight range established by the packer can lead to severe economic loss to the producer. This study’s objective was to validate new weight measurement technologies and determine their usefulness on swine farms. Accuracy of three methods were evaluated: human observation, a walk-across platform scale (CIMA; Correggio, Italy), and PigVision mounted cameras (Asimetrix Inc; Durham, NC). Weights were validated with a calibrated livestock scale in all three studies. In the first study, a trained individual selected pigs estimated to be market weight at two sites. Site one had 468 pigs and an accuracy of 84.4%, site two had 522 pigs and an 82.5% accuracy. A 16-week study was then conducted to determine PigVision camera accuracy over time from placement to market. Cameras were mounted above 12 pens. Weights were validated every two weeks. The accuracy for pigs that weighed 32.7 kg (87.7%) was lower (P < 0.05) than the accuracy for pigs that weighed 117.5 kg (97.6%) or 125.7 kg (96.6%). The overall accuracy from placement to market was 94.1%. A final study at market compared human observation, the walk-across scale, and PigVision. A total of 91 pigs were weighed with each method. The accuracy for the walk-across scale was 98.2%. The walk-across scale did not register a weight for six pigs. Final accuracies were 88.2% for human observation, and 96.6% for PigVision. Human observation is the chosen method in many operations today yet offers the lowest accuracy. The walk-across scale is easy to operate but requires tactical animal movement. PigVision is the least arduous option, provides constant data, but does require maintenance. This work was funded by the National Pork Board.

scholarly journals Evaluation of the Accuracy of Horse Body Weight Estimation Methods

Animals ◽  
2020 ◽  
Vol 10 (10) ◽  
pp. 1750
Author(s):  
Wanda Górniak ◽  
Martyna Wieliczko ◽  
Maria Soroko ◽  
Mariusz Korczyński
Keyword(s):  
Body Weight ◽  
Estimation Methods ◽  
Body Measurements ◽  
Actual Body Weight ◽  
Weight Estimation ◽  
Research Groups ◽  
Healthy Horse ◽  
Weight Measurement ◽  
Measuring Tape ◽  
Measuring Stick

Methods of estimating horse body weight using mathematical formulae have better accuracy than methods of reading body weight from measuring tape. The aim of the study was to evaluate established formulae for estimating horse body weight from data gathered using measurement tape. The research was conducted in a group of 299 adult horses and ponies of selected breeds: ponies (n = 58), Polish Noble Half Breed (n = 150), Silesian Breed (n = 23), Wielkopolski Breed (n = 52), and Thoroughbred (n = 16). Body measurements were performed on each horse using a measuring stick and tape. The actual body weight of the horses was measured with electronic scale. Statistical analysis was carried out separately for individual breeds of horses. In each of the research groups formulae were selected, the results of which were closest to the actual horse body weight readings. The use of formulae for body weight estimation can be useful in determining feed dosages and additives, medicines or deworming agents. Regular weight measurement is important for maintaining a healthy horse.

scholarly journals The Protective Factor of Diarrhea Incidence in Toddler in Surabaya

2018 ◽  
Vol 6 (1) ◽  
pp. 51
Author(s):  
Rachmah Wahyu Ainsyah ◽  
Muhammad Farid Lusno
Keyword(s):  
Body Weight ◽  
Water Resource ◽  
Protective Factor ◽  
Simple Random Sampling ◽  
Community Group ◽  
Cross Sectional ◽  
Weight Measurement ◽  
Diarrhea Incidence ◽  
Water Resource Utilization ◽  
Cross Sectional Design

Background: Basic health research in 2013 found that diarrhea incidence in toddler was the highest. The working area of a public health center in Wonokusumo Surabaya found that the diarrhea incidence in toddler increased from 62 cases in 2015 to 385 cases in 2016. Purpose: This study was aimed to analyze the protective factor of diarrhea. Methods: This study was analytic observational with a cross sectional design. The study was conducted from 18 January to 23 February 2013 in community group (RW) 2 in Wonokusumo region, Surabaya city. The population of this study consisted of 210 mothers who had toddlers. There were 67 respondents selected through simple random sampling. Data were collected through questionnaire and observation and analyzed with multiple logistic regression. Results: These variables had significant influence on diarrhea incidence simultaneously, namely protected water resource utilization (PR = 0,10; 95% CI = 0,02 < PR < 0,64), healthy latrine utilization (PR = 0,06; 95% CI = 0,01 < PR < 0,50), washing hand habit (PR = 0,10; 95% CI = 0,01 < PR < 0,72), and monthly body weight measurement participation (PR = 0,04; 95% CI = 0,01 < PR < 0,29). The other variables such as mother’s employment, wage according to city minimum wage, and breastfeeding history. Conclusion: The protective factors of this study were the utilization of protective water resource, good latrine utilization, washing hand habit, and body weight measurement participation.

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