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Lee Hooper - One of the best experts on this subject based on the ideXlab platform.
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diagnostic accuracy of calculated Serum Osmolarity to predict dehydration in older people adding value to pathology laboratory reports
BMJ Open, 2015Co-Authors: Lee Hooper, Diane Bunn, Asmaa Abdelhamid, Amy Jennings, Garry W John, Susan Kerry, Gregor Lindner, Carmen A Pfortmueller, Fredrik Sjostrand, Neil P WalshAbstract:Objectives To assess which Osmolarity equation best predicts directly measured Serum/plasma osmolality and whether its use could add value to routine blood test results through screening for dehydration in older people. Design Diagnostic accuracy study. Participants Older people (≥65 years) in 5 cohorts: Dietary Strategies for Healthy Ageing in Europe (NU-AGE, living in the community), Dehydration Recognition In our Elders (DRIE, living in residential care), Fortes (admitted to acute medical care), Sjostrand (emergency room) or Pfortmueller cohorts (hospitalised with liver cirrhosis). Reference standard for hydration status Directly measured Serum/plasma osmolality: current dehydration (Serum osmolality >300 mOsm/kg), impending/current dehydration (≥295 mOsm/kg). Index tests 39 Osmolarity equations calculated using Serum indices from the same blood draw as directly measured osmolality. Results Across 5 cohorts 595 older people were included, of whom 19% were dehydrated (directly measured osmolality >300 mOsm/kg). Of 39 Osmolarity equations, 5 showed reasonable agreement with directly measured osmolality and 3 had good predictive accuracy in subgroups with diabetes and poor renal function. Two equations were characterised by narrower limits of agreement, low levels of differential bias and good diagnostic accuracy in receiver operating characteristic plots (areas under the curve >0.8). The best equation was Osmolarity=1.86×(Na + + K + )+1.15×glucose+urea+14 (all measured in mmol/L). It appeared useful in people aged ≥65 years with and without diabetes, poor renal function, dehydration, in men and women, with a range of ages, health, cognitive and functional status. Conclusions Some commonly used Osmolarity equations work poorly, and should not be used. Given costs and prevalence of dehydration in older people we suggest use of the best formula by pathology laboratories using a cutpoint of 295 mOsm/L (sensitivity 85%, specificity 59%), to report dehydration risk opportunistically when Serum glucose, urea and electrolytes are measured for other reasons in older adults. Trial registration numbers: DRIE: Research Register for Social Care, 122273; NU-AGE: ClinicalTrials.gov NCT01754012.
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Serum Osmolarity and haematocrit do not modify the association between the impedance index ht2 z and total body water in the very old the newcastle 85 study
Archives of Gerontology and Geriatrics, 2015Co-Authors: Mario Siervo, Carla M Prado, Lee Hooper, Alex Munro, Joanna Collerton, Karen Davies, Andrew Kingston, John C Mathers, Thomas B L Kirkwood, Carol JaggerAbstract:Abstract Purpose of the research Bioelectrical impedance is a non-invasive technique for the assessment of body composition; however, information on its accuracy in the very old (80 + years) is limited. We investigated whether the association between the impedance index and total body water (TBW) was modified by hydration status as assessed by haematocrit and Serum Osmolarity. Materials and methods This was a cross-sectional analysis of baseline data from the Newcastle 85 + Cohort Study. Anthropometric measurements [weight, height (Ht)] were taken and body mass index (BMI) calculated. Leg-to-leg bioimpedance was used to measure the impedance value (Z) and to estimate fat mass, fat free mass and TBW. The impedance index (Ht2/Z) was calculated. Blood haematocrit, haemoglobin, glucose, sodium, potassium, urea and creatinine concentrations were measured. Serum Osmolarity was calculated using a validated prediction equation. Principal results 677 men and women aged 85 years were included. The average BMI of the population was 24.3 ± 4.2 kg/m2 and the prevalence of overweight and obesity was 32.6% and 9.5%, respectively. The impedance index was significantly associated with TBW in both men (n = 274, r = 0.76, p Major conclusions The association between the impedance index and TBW was not modified by hydration status, which may support the utilisation of leg-to-leg bioimpedance for the assessment of body composition in the very old.
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accuracy of prediction equations for Serum Osmolarity in frail older people with and without diabetes
The American Journal of Clinical Nutrition, 2014Co-Authors: Mario Siervo, Diane Bunn, Carla M Prado, Lee HooperAbstract:Background: Serum osmolality is an accurate indicator of hydration status in older adults. Glucose, urea, and electrolyte concentrations are used to calculate Serum Osmolarity, which is an indirect estimate of Serum osmolality, but which Serum Osmolarity equations best predict Serum osmolality in the elderly is unclear. Objective: We assessed the agreement of measured Serum osmolality with calculated Serum Osmolarity equations in older people. Design: Serum osmolality was measured by using freezing point depression in a cross-sectional study. Plasma glucose, urea, and electrolytes were analyzed and entered into 38 Serum Osmolarity-prediction equations. The Bland-Altman method was used to evaluate the agreement and differential bias between measured osmolality and calculated Osmolarity. The sensitivity and specificity of the most-promising equations were examined against Serum osmolality (reference standard). Results: A total of 186 people living in UK residential care took part in the Dehydration Recognition In our Elders study (66% women; mean ± SD age: 85.8 ± 7.9 y; with a range of cognitive and physical impairments) and were included in analyses. Forty-six percent of participants had impending or current dehydration (Serum osmolality ≥295 mmol/kg). Participants with diabetes (n = 33; 18%) had higher glucose (P 80% of participants, regardless of diabetes or hydration status. The equation's sensitivity (79%) and specificity (89%) for impending dehydration (≥295 mmol/kg) and current dehydration (>300 mmol/kg) (69% and 93%, respectively) were reasonable. Conclusions: The assessment of a panel of equations for the prediction of Serum Osmolarity led to identification of one formula with a greater diagnostic performance. This equation may be used to predict hydration status in frail older people (as a first-stage screening) or to estimate hydration status in population studies. This trial was registered at the Research Register for Social Care (http://www.researchregister.org.uk) as 122273.
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accuracy of prediction equations for Serum Osmolarity in frail older people with and without diabetes
The American Journal of Clinical Nutrition, 2014Co-Authors: Mario Siervo, Diane Bunn, Carla M Prado, Lee HooperAbstract:Background: Serum osmolality is an accurate indicator of hydration status in older adults. Glucose, urea, and electrolyte concentrations are used to calculate Serum Osmolarity, which is an indirect estimate of Serum osmolality, but which Serum Osmolarity equations best predict Serum osmolality in the elderly is unclear. Objective: We assessed the agreement of measured Serum osmolality with calculated Serum Osmolarity equations in older people. Design: Serum osmolality was measured by using freezing point depression in a cross-sectional study. Plasma glucose, urea, and electrolytes were analyzed and entered into 38 Serum Osmolarity-prediction equations. The Bland-Altman method was used to evaluate the agreement and differential bias between measured osmolality and calculated Osmolarity. The sensitivity and specificity of the most-promising equations were examined against Serum osmolality (reference standard). Results: A total of 186 people living in UK residential care took part in the Dehydration Recognition In our Elders study (66% women; mean 6 SD age: 85.8 6 7.9 y; with a range of cognitive and physical impairments) and were included in analyses. Forty-six percent of participants had impending or current dehydration (Serum osmolality $295 mmol/kg). Participants with diabetes (n = 33; 18%) had higher glucose (P , 0.001) and Serum osmolality (P , 0.01). Of 38 predictive equations used to calculate Osmolarity, 4 equations showed reasonable agreement with measured osmolality. One [calculated Osmolarity = 1.86 3 (Na + +K + ) + 1.15 3 glucose + urea +14; all in mmol/L] was characterized by narrower limits of agreement and the capacity to predict Serum osmolality within 2% in .80% of participants, regardless of diabetes or hydration status. The equation’s sensitivity (79%) and specificity (89%) for impending dehydration ($295 mmol/kg) and current dehydration (.300 mmol/kg) (69% and 93%, respectively) were reasonable. Conclusions: The assessment of a panel of equations for the prediction of Serum Osmolarity led to identification of one formula with a greater diagnostic performance. This equation may be used to predict hydration status in frail older people (as a first-stage screening) or to estimate hydration status in population studies. This trial was registered at the Research Register for Social Care (http://www.researchregister.org.uk) as 122273. Am J Clin Nutr doi: 10.3945/ajcn.114.086769.
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o4 25 assessment of dehydration in older people agreement of measured Serum osmolality with calculated Serum Osmolarity equations
European Geriatric Medicine, 2014Co-Authors: Lee Hooper, K Bunn, M Prado, Mario SiervoAbstract:Introduction: Serum osmolality is the best indicator of hydration status in older adults. Serum glucose, urea and electrolytes are commonly analysed in health care situations, and are used to calculate Serum Osmolarity, an estimate of Serum osmolality, but it is unclear which equations best predict Serum osmolality. We assessed agreement of measured Serum osmolality with calculated Serum Osmolarity equations in older people. Methods: Serum osmolality (by freezing point depression) was measured at baseline in the Dehydration Recognition in our Elders, DRIE, cohort (http://driestudy.appspot.com/). Serum glucose, urea and electrolytes were entered into 38 Serum Osmolarity prediction equations. We evaluated agreement (Bland-Altman) and differential bias between measured osmolality and calculated Osmolarity. Sensitivity and specificity of the most promising equations were examined against Serum osmolality (reference standard). Results: 186 people living in UK residential care took part in DRIE (66% women, mean age 85.8±7.9 years, with a range of cognitive and physical impairments) and were included in analyses. 19% had current dehydration (Serum osmolality >300mmol/kg). Of 38 Osmolarity equations, four showed reasonable agreement and one (calculated Osmolarity= 1.86×(Na++K+)+1.15×glucose+urea+14, all in mmol/L)1 better predicted Serum osmolality (>80% of participants within 2%, regardless of diabetes or hydration status). Using a cut-off of >296mmol/L for calculated Osmolarity gave good sensitivity (97%) and specificity (76%) for current dehydration (>300mmol/kg) (table). Conclusions: One formula had clearly better diagnostic performance and could predict dehydration as a first stage screening in frail older people or estimate hydration status in population studies. 1. Khajuria & Krahn. Clin Biochem 2005;38:514-519.
Masanari Kuwabara - One of the best experts on this subject based on the ideXlab platform.
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hyperOsmolarity and increased Serum sodium concentration are risks for developing hypertension regardless of salt intake a five year cohort study in japan
Nutrients, 2020Co-Authors: Masanari Kuwabara, Ichiro Hisatome, Koichiro Niwa, Mehmet Kanbay, Ana Andreshernando, Carlos A Roncaljimenez, Gabriela Garcia, Laura G Sanchezlozada, Bernardo Rodrigueziturbe, Miguel A LanaspaAbstract:The potential contribution of Serum Osmolarity in the modulation of blood pressure has not been evaluated. This study was done to examine the relationship between hyperOsmolarity and hypertension in a five-year longitudinal design. We enrolled 10,157 normotensive subjects without diabetes who developed hypertension subsequently as determined by annual medical examination in St. Luke's International Hospital, Tokyo, between 2004 and 2009. High salt intake was defined as >12 g/day by a self-answered questionnaire and hyperOsmolarity was defined as >293 mOsm/L Serum Osmolarity, calculated using Serum sodium, fasting blood glucose, and blood urea nitrogen. Statistical analyses included adjustments for age, gender, body mass index, smoking, drinking alcohol, dyslipidemia, hyperuricemia, and chronic kidney disease. In the patients with normal Osmolarity, the group with high salt intake had a higher cumulative incidence of hypertension than the group with normal salt intake (8.4% versus 6.7%, p = 0.023). In contrast, in the patients with high Osmolarity, the cumulative incidence of hypertension was similar in the group with high salt intake and in the group with normal salt intake (13.1% versus 12.9%, p = 0.84). The patients with hyperOsmolarity had a higher incidence of hypertension over five years compared to that of the normal Osmolarity group (p < 0.001). After multiple adjustments, elevated Osmolarity was an independent risk for developing hypertension (OR (odds ratio), 1.025; 95% CI (confidence interval), 1.006-1.044), regardless of the amount of salt intake. When analyzed in relation to each element of calculated Osmolarity, Serum sodium and fasting blood glucose were independent risks for developing hypertension. Our results suggest that hyperOsmolarity is a risk for developing hypertension regardless of salt intake.
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Serum Osmolarity as a potential predictor for contrast induced nephropathy following elective coronary angiography
International Urology and Nephrology, 2020Co-Authors: Mehmet Kanbay, Masanari Kuwabara, Miguel A Lanaspa, Dimitrie Siriopol, Elif Ozdogan, Baris Afsar, Lale A Ertuglu, Mihaela Grigore, Alan A Sag, Alberto OrtizAbstract:Contrast-induced nephropathy (CIN) is a relatively common complication following primary coronary angiography (CAG) or percutaneous coronary intervention (PCI), especially in at-risk patients. The goal of this study is to evaluate the role of pre-procedural Serum Osmolarity as a risk factor for CIN in patients undergoing elective CAG for stable coronary artery disease (CAD). A total of 356 stable CAD patients scheduled to undergo CAG or PCI were included in this two-center study. Serum Osmolarity was calculated on admission. CIN was defined according to the KDIGO criteria. There were 45 (12.6%) patients who developed CIN 48–72 h after CAG or PCI. CIN patients had a higher prevalence of diabetes (51.1% in those with CIN vs 24.4% in those without CIN, p < 0.001), higher Serum glucose (129 mg/dL in those with CIN vs 108 mg/dL in those without CIN, p < 0.001), blood urea nitrogen (22.4 mg/dL in those with CIN vs 19.0 mg/dL in those without CIN, p = 0.01) and Serum Osmolarity (294.2 mOsm in those with CIN vs 290.1 mOsm in those without CIN, p < 0.001) levels, had received a higher dose of contrast (250 mL in those with CIN vs 200 mL in those without CIN, p = 0.03) but had lower hemoglobin (12.9 g/dL in those with CIN vs 13.6 g/dL in those without CIN, p = 0.04) level. In multivariate analysis, Serum Osmolarity [odds ratio (OR) 1.11; 95% confidence interval (CI) 1.04–1.18 for each mOsm/L increase; p = 0.001], diabetes (OR 2.43, 95% CI 1.26–4.71; p = 0.01), C-reactive protein (OR 1.04, 95% CI 1.01–1.08 for each mg/dL increase; p = 0.02) and contrast volume (OR 34.66, 95% CI 1.25–962.22 for each L increase; p = 0.04) remained as independent predictors of CIN. Serum sodium, glucose and blood urea nitrogen contributed to the excess Serum Osmolarity of CIN patients. Serum Osmolarity is a cheap and widely available marker that can reliably predict CIN after CAG or PCI. Future research should focus on determining a clinically optimal cutoff for Serum Osmolarity that would warrant preventive interventions. Furthermore, later research may investigate the role of Serum Osmolarity not only as a risk factor but also as a pathogenetic mechanism underlying CIN.
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Serum Osmolarity as a potential predictor for contrast induced nephropathy following elective coronary angiography
International Urology and Nephrology, 2020Co-Authors: Mehmet Kanbay, Masanari Kuwabara, Miguel A Lanaspa, Dimitrie Siriopol, Elif Ozdogan, Baris Afsar, Lale A Ertuglu, Mihaela Grigore, Alberto Ortiz, Richard J JohnsonAbstract:Background and objectives Contrast-induced nephropathy (CIN) is a relatively common complication following primary coronary angiography (CAG) or percutaneous coronary intervention (PCI), especially in at-risk patients. The goal of this study is to evaluate the role of pre-procedural Serum Osmolarity as a risk factor for CIN in patients undergoing elective CAG for stable coronary artery disease (CAD).
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increased Serum sodium and Serum Osmolarity are independent risk factors for developing chronic kidney disease 5 year cohort study
PLOS ONE, 2017Co-Authors: Masanari Kuwabara, Ichiro Hisatome, Carlos A Roncaljimenez, Koichiro Niwa, Petter Bjornstad, Tamara Milagres, Christina Cicerchi, Thomas Jensen, Ana Andreshernando, Zhilin SongAbstract:Background Epidemics of chronic kidney disease (CKD) not due to diabetes mellitus (DM) or hypertension have been observed among individuals working in hot environments in several areas of the world. Experimental models have documented that recurrent heat stress and water restriction can lead to CKD, and the mechanism may be mediated by hyperOsmolarity that activates pathways (vasopressin, aldose reductase-fructokinase) that induce renal injury. Here we tested the hypothesis that elevated Serum sodium, which reflects Serum osmolality, may be an independent risk factor for the development of CKD. Methods This study was a large-scale, single-center, retrospective 5-year cohort study at Center for Preventive Medicine, St. Luke’s International Hospital, Tokyo, Japan, between 2004 and 2009. We analyzed 13,201 subjects who underwent annual medical examination of which 12,041 subjects (age 35 to 85) without DM and/or CKD were enrolled. This analysis evaluated age, sex, body mass index, abdominal circumference, hypertension, dyslipidemia, hyperuricemia, fasting glucose, BUN, Serum sodium, potassium, chloride and calculated Serum Osmolarity. Results Elevated Serum sodium was an independent risk factor for development of CKD (OR: 1.03, 95% CI, 1.00–1.07) after adjusted regression analysis with an 18 percent increased risk for every 5 mmol/L change in Serum sodium. Calculated Serum Osmolarity was also an independent risk factor for CKD (OR: 1.04; 95% CI, 1.03–1.05) as was BUN (OR: 1.08; 95% CI, 1.06–1.10) (independent of Serum creatinine). Conclusions Elevated Serum sodium and calculated Serum Osmolarity are independent risk factors for developing CKD. This finding supports the role of limiting salt intake and preventing dehydration to reduce risk of CKD.
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Calculated Serum Osmolarity as a risk factor for chronic kidney disease between 2004 and 2009.
2017Co-Authors: Masanari Kuwabara, Ichiro Hisatome, Koichiro Niwa, Petter Bjornstad, Tamara Milagres, Christina Cicerchi, Thomas Jensen, Carlos A. Roncal-jimenez, Ana Andres-hernando, Zhilin SongAbstract:Calculated Serum Osmolarity as a risk factor for chronic kidney disease between 2004 and 2009.
Zhilin Song - One of the best experts on this subject based on the ideXlab platform.
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increased Serum sodium and Serum Osmolarity are independent risk factors for developing chronic kidney disease 5 year cohort study
PLOS ONE, 2017Co-Authors: Masanari Kuwabara, Ichiro Hisatome, Carlos A Roncaljimenez, Koichiro Niwa, Petter Bjornstad, Tamara Milagres, Christina Cicerchi, Thomas Jensen, Ana Andreshernando, Zhilin SongAbstract:Background Epidemics of chronic kidney disease (CKD) not due to diabetes mellitus (DM) or hypertension have been observed among individuals working in hot environments in several areas of the world. Experimental models have documented that recurrent heat stress and water restriction can lead to CKD, and the mechanism may be mediated by hyperOsmolarity that activates pathways (vasopressin, aldose reductase-fructokinase) that induce renal injury. Here we tested the hypothesis that elevated Serum sodium, which reflects Serum osmolality, may be an independent risk factor for the development of CKD. Methods This study was a large-scale, single-center, retrospective 5-year cohort study at Center for Preventive Medicine, St. Luke’s International Hospital, Tokyo, Japan, between 2004 and 2009. We analyzed 13,201 subjects who underwent annual medical examination of which 12,041 subjects (age 35 to 85) without DM and/or CKD were enrolled. This analysis evaluated age, sex, body mass index, abdominal circumference, hypertension, dyslipidemia, hyperuricemia, fasting glucose, BUN, Serum sodium, potassium, chloride and calculated Serum Osmolarity. Results Elevated Serum sodium was an independent risk factor for development of CKD (OR: 1.03, 95% CI, 1.00–1.07) after adjusted regression analysis with an 18 percent increased risk for every 5 mmol/L change in Serum sodium. Calculated Serum Osmolarity was also an independent risk factor for CKD (OR: 1.04; 95% CI, 1.03–1.05) as was BUN (OR: 1.08; 95% CI, 1.06–1.10) (independent of Serum creatinine). Conclusions Elevated Serum sodium and calculated Serum Osmolarity are independent risk factors for developing CKD. This finding supports the role of limiting salt intake and preventing dehydration to reduce risk of CKD.
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Calculated Serum Osmolarity as a risk factor for chronic kidney disease between 2004 and 2009.
2017Co-Authors: Masanari Kuwabara, Ichiro Hisatome, Koichiro Niwa, Petter Bjornstad, Tamara Milagres, Christina Cicerchi, Thomas Jensen, Carlos A. Roncal-jimenez, Ana Andres-hernando, Zhilin SongAbstract:Calculated Serum Osmolarity as a risk factor for chronic kidney disease between 2004 and 2009.
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Relative odds ratio of chronic kidney disease stratified among Serum Osmolarity quartile by sex between 2004 and 2009.
2017Co-Authors: Masanari Kuwabara, Ichiro Hisatome, Koichiro Niwa, Petter Bjornstad, Tamara Milagres, Christina Cicerchi, Thomas Jensen, Carlos A. Roncal-jimenez, Ana Andres-hernando, Zhilin SongAbstract:Relative odds ratio of chronic kidney disease stratified among Serum Osmolarity quartile by sex between 2004 and 2009.
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The correlation between Serum Osmolarity and kidney function.
2017Co-Authors: Masanari Kuwabara, Ichiro Hisatome, Koichiro Niwa, Petter Bjornstad, Tamara Milagres, Christina Cicerchi, Thomas Jensen, Carlos A. Roncal-jimenez, Ana Andres-hernando, Zhilin SongAbstract:Pearson’s correlation analysis demonstrated an inverse correlation (p
Norlina Ramli - One of the best experts on this subject based on the ideXlab platform.
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effect of nocturnal intermittent peritoneal dialysis on intraocular pressure and anterior segment optical coherence tomography parameters
Journal of Glaucoma, 2016Co-Authors: Ka Lung Chong, Amir Samsudin, Tee Chau Keng, Tengku Ain Kamalden, Norlina RamliAbstract:Purpose To evaluate the effect of nocturnal intermittent peritoneal dialysis (NIPD) on intraocular pressure (IOP) and anterior segment optical coherence tomography (ASOCT) parameters. Systemic changes associated with NIPD were also analyzed. Methods Observational study. Nonglaucomatous patients on NIPD underwent systemic and ocular assessment including mean arterial pressure (MAP), body weight, Serum Osmolarity, visual acuity, IOP measurement, and ASOCT within 2 hours both before and after NIPD. The Zhongshan Angle Assessment Program (ZAAP) was used to measure ASOCT parameters including anterior chamber depth, anterior chamber width, anterior chamber area, anterior chamber volume, lens vault, angle opening distance, trabecular-iris space area, and angle recess area. T tests and Pearson correlation tests were performed with P Results A total of 46 eyes from 46 patients were included in the analysis. There were statistically significant reductions in IOP (-1.8±0.6 mm Hg, P=0.003), MAP (-11.9±3.1 mm Hg, P 0.05). Conclusions NIPD results in reductions in IOP, MAP, body weight, and Serum Osmolarity in nonglaucomatous patients.
Mario Siervo - One of the best experts on this subject based on the ideXlab platform.
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Serum Osmolarity and haematocrit do not modify the association between the impedance index ht2 z and total body water in the very old the newcastle 85 study
Archives of Gerontology and Geriatrics, 2015Co-Authors: Mario Siervo, Carla M Prado, Lee Hooper, Alex Munro, Joanna Collerton, Karen Davies, Andrew Kingston, John C Mathers, Thomas B L Kirkwood, Carol JaggerAbstract:Abstract Purpose of the research Bioelectrical impedance is a non-invasive technique for the assessment of body composition; however, information on its accuracy in the very old (80 + years) is limited. We investigated whether the association between the impedance index and total body water (TBW) was modified by hydration status as assessed by haematocrit and Serum Osmolarity. Materials and methods This was a cross-sectional analysis of baseline data from the Newcastle 85 + Cohort Study. Anthropometric measurements [weight, height (Ht)] were taken and body mass index (BMI) calculated. Leg-to-leg bioimpedance was used to measure the impedance value (Z) and to estimate fat mass, fat free mass and TBW. The impedance index (Ht2/Z) was calculated. Blood haematocrit, haemoglobin, glucose, sodium, potassium, urea and creatinine concentrations were measured. Serum Osmolarity was calculated using a validated prediction equation. Principal results 677 men and women aged 85 years were included. The average BMI of the population was 24.3 ± 4.2 kg/m2 and the prevalence of overweight and obesity was 32.6% and 9.5%, respectively. The impedance index was significantly associated with TBW in both men (n = 274, r = 0.76, p Major conclusions The association between the impedance index and TBW was not modified by hydration status, which may support the utilisation of leg-to-leg bioimpedance for the assessment of body composition in the very old.
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accuracy of prediction equations for Serum Osmolarity in frail older people with and without diabetes
The American Journal of Clinical Nutrition, 2014Co-Authors: Mario Siervo, Diane Bunn, Carla M Prado, Lee HooperAbstract:Background: Serum osmolality is an accurate indicator of hydration status in older adults. Glucose, urea, and electrolyte concentrations are used to calculate Serum Osmolarity, which is an indirect estimate of Serum osmolality, but which Serum Osmolarity equations best predict Serum osmolality in the elderly is unclear. Objective: We assessed the agreement of measured Serum osmolality with calculated Serum Osmolarity equations in older people. Design: Serum osmolality was measured by using freezing point depression in a cross-sectional study. Plasma glucose, urea, and electrolytes were analyzed and entered into 38 Serum Osmolarity-prediction equations. The Bland-Altman method was used to evaluate the agreement and differential bias between measured osmolality and calculated Osmolarity. The sensitivity and specificity of the most-promising equations were examined against Serum osmolality (reference standard). Results: A total of 186 people living in UK residential care took part in the Dehydration Recognition In our Elders study (66% women; mean ± SD age: 85.8 ± 7.9 y; with a range of cognitive and physical impairments) and were included in analyses. Forty-six percent of participants had impending or current dehydration (Serum osmolality ≥295 mmol/kg). Participants with diabetes (n = 33; 18%) had higher glucose (P 80% of participants, regardless of diabetes or hydration status. The equation's sensitivity (79%) and specificity (89%) for impending dehydration (≥295 mmol/kg) and current dehydration (>300 mmol/kg) (69% and 93%, respectively) were reasonable. Conclusions: The assessment of a panel of equations for the prediction of Serum Osmolarity led to identification of one formula with a greater diagnostic performance. This equation may be used to predict hydration status in frail older people (as a first-stage screening) or to estimate hydration status in population studies. This trial was registered at the Research Register for Social Care (http://www.researchregister.org.uk) as 122273.
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accuracy of prediction equations for Serum Osmolarity in frail older people with and without diabetes
The American Journal of Clinical Nutrition, 2014Co-Authors: Mario Siervo, Diane Bunn, Carla M Prado, Lee HooperAbstract:Background: Serum osmolality is an accurate indicator of hydration status in older adults. Glucose, urea, and electrolyte concentrations are used to calculate Serum Osmolarity, which is an indirect estimate of Serum osmolality, but which Serum Osmolarity equations best predict Serum osmolality in the elderly is unclear. Objective: We assessed the agreement of measured Serum osmolality with calculated Serum Osmolarity equations in older people. Design: Serum osmolality was measured by using freezing point depression in a cross-sectional study. Plasma glucose, urea, and electrolytes were analyzed and entered into 38 Serum Osmolarity-prediction equations. The Bland-Altman method was used to evaluate the agreement and differential bias between measured osmolality and calculated Osmolarity. The sensitivity and specificity of the most-promising equations were examined against Serum osmolality (reference standard). Results: A total of 186 people living in UK residential care took part in the Dehydration Recognition In our Elders study (66% women; mean 6 SD age: 85.8 6 7.9 y; with a range of cognitive and physical impairments) and were included in analyses. Forty-six percent of participants had impending or current dehydration (Serum osmolality $295 mmol/kg). Participants with diabetes (n = 33; 18%) had higher glucose (P , 0.001) and Serum osmolality (P , 0.01). Of 38 predictive equations used to calculate Osmolarity, 4 equations showed reasonable agreement with measured osmolality. One [calculated Osmolarity = 1.86 3 (Na + +K + ) + 1.15 3 glucose + urea +14; all in mmol/L] was characterized by narrower limits of agreement and the capacity to predict Serum osmolality within 2% in .80% of participants, regardless of diabetes or hydration status. The equation’s sensitivity (79%) and specificity (89%) for impending dehydration ($295 mmol/kg) and current dehydration (.300 mmol/kg) (69% and 93%, respectively) were reasonable. Conclusions: The assessment of a panel of equations for the prediction of Serum Osmolarity led to identification of one formula with a greater diagnostic performance. This equation may be used to predict hydration status in frail older people (as a first-stage screening) or to estimate hydration status in population studies. This trial was registered at the Research Register for Social Care (http://www.researchregister.org.uk) as 122273. Am J Clin Nutr doi: 10.3945/ajcn.114.086769.
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o4 25 assessment of dehydration in older people agreement of measured Serum osmolality with calculated Serum Osmolarity equations
European Geriatric Medicine, 2014Co-Authors: Lee Hooper, K Bunn, M Prado, Mario SiervoAbstract:Introduction: Serum osmolality is the best indicator of hydration status in older adults. Serum glucose, urea and electrolytes are commonly analysed in health care situations, and are used to calculate Serum Osmolarity, an estimate of Serum osmolality, but it is unclear which equations best predict Serum osmolality. We assessed agreement of measured Serum osmolality with calculated Serum Osmolarity equations in older people. Methods: Serum osmolality (by freezing point depression) was measured at baseline in the Dehydration Recognition in our Elders, DRIE, cohort (http://driestudy.appspot.com/). Serum glucose, urea and electrolytes were entered into 38 Serum Osmolarity prediction equations. We evaluated agreement (Bland-Altman) and differential bias between measured osmolality and calculated Osmolarity. Sensitivity and specificity of the most promising equations were examined against Serum osmolality (reference standard). Results: 186 people living in UK residential care took part in DRIE (66% women, mean age 85.8±7.9 years, with a range of cognitive and physical impairments) and were included in analyses. 19% had current dehydration (Serum osmolality >300mmol/kg). Of 38 Osmolarity equations, four showed reasonable agreement and one (calculated Osmolarity= 1.86×(Na++K+)+1.15×glucose+urea+14, all in mmol/L)1 better predicted Serum osmolality (>80% of participants within 2%, regardless of diabetes or hydration status). Using a cut-off of >296mmol/L for calculated Osmolarity gave good sensitivity (97%) and specificity (76%) for current dehydration (>300mmol/kg) (table). Conclusions: One formula had clearly better diagnostic performance and could predict dehydration as a first stage screening in frail older people or estimate hydration status in population studies. 1. Khajuria & Krahn. Clin Biochem 2005;38:514-519.
