Biomedical subjects

Glen H Murata

Publications and source records attributed to Glen H Murata.

At least 19 recordsLinked to original sources

PubMed2006

Racial and ethnic disparities in the control of cardiovascular disease risk factors in Southwest American veterans with type 2 diabetes: the Diabetes Outcomes in Veterans Study.

BACKGROUND: Racial/ethnic disparities in cardiovascular disease complications have been observed in diabetic patients. We examined the association between race/ethnicity and cardiovascular disease risk factor control in a large cohort of insulin-treated veterans with type 2 diabetes. METHODS: We conducted a cross-sectional observational study at 3 Veterans Affairs Medical Centers in the American Southwest. Using electronic pharmacy databases, we randomly selected 338 veterans with insulin-treated type 2 diabetes. We collected medical record and patient survey data on diabetes control and management, cardiovascular disease risk factors, comorbidity, demographics, socioeconomic factors, psychological status, and health behaviors. We used analysis of variance and multivariate linear regression to determine the effect of race/ethnicity on glycemic control, insulin treatment intensity, lipid levels, and blood pressure control. RESULTS: The study cohort was comprised of 72 (21.3%) Hispanic subjects (H), 35 (10.4%) African Americans (AA), and 226 (67%) non-Hispanic whites (NHW). The mean (SD) hemoglobin A1c differed significantly by race/ethnicity: NHW 7.86 (1.4)%, H 8.16 (1.6)%, AA 8.84 (2.9)%, p = 0.05. The multivariate-adjusted A1c was significantly higher for AA (+0.93%, p = 0.002) compared to NHW. Insulin doses (unit/day) also differed significantly: NHW 70.6 (48.8), H 58.4 (32.6), and AA 53.1 (36.2), p < 0.01. Multivariate-adjusted insulin doses were significantly lower for AA (-17.8 units/day, p = 0.01) and H (-10.5 units/day, p = 0.04) compared to NHW. Decrements in insulin doses were even greater among minority patients with poorly controlled diabetes (A1c > or = 8%). The disparities in glycemic control and insulin treatment intensity could not be explained by differences in age, body mass index, oral hypoglycemic medications, socioeconomic barriers, attitudes about diabetes care, diabetes knowledge, depression, cognitive dysfunction, or social support. We found no significant racial/ethnic differences in lipid or blood pressure control. CONCLUSION: In our cohort, insulin-treated minority veterans, particularly AA, had poorer glycemic control and received lower doses of insulin than NHW. However, we found no differences for control of other cardiovascular disease risk factors. The diabetes treatment disparity could be due to provider behaviors and/or patient behaviors or preferences. Further research with larger sample sizes and more geographically diverse populations are needed to confirm our findings.

Black or African American↗

PubMed2005

Osmotic myelinolysis following chronic hyponatremia corrected at an overall rate consistent with current recommendations.

Rapid correction of chronic hyponatremia (CH) may lead to the development of osmotic myelinolysis (OM), a condition with high mortality and high incidence of devastating neurological sequelae. Treatment guidelines suggest "safe" overall rates of correction of serum sodium concentration ([Na](s)) over the first 24 and 48 hours of treatment of CH. We report a patient with CH who developed fatal OM despite overall rates of correction of [Na](s) that were within the recommended rates. The potential risk factors for the development of OM in this patient included short (within a few hours) rises in [Na](s) exceeding 0.5 mmol/l per hour and the presence of severe protein malnutrition. We suggest that the rate of correction of [Na](s) in CH should be uniformly slow and that the overall rate of correction should be slower than the currently recommended rate in severely malnourished patients.

Aged↗

PubMed2005

Prevention of nephropathy in patients with type 2 diabetes mellitus.

The rising incidence of type 2 diabetes mellitus and of its complications will make it the most important health care challenge in the first quarter of the 21st Century. Diabetic nephropathy left unchecked will overwhelm the renal resources. Simple methods (proper diet and exercise, prevention of obesity) are successful in preventing type 2 diabetes in the great majority of the persons at risk. In patients with established type 2 diabetes, nephropathy can be prevented or greatly delayed by strict metabolic control, strict control of blood pressure using angiotensin-converting enzyme inhibitors and angiotensin receptor blockers as the first line of drugs, tight control of serum lipids using statins as indicated, low protein diet, avoidance of smoking and other nephrotoxic influences, prevention of abnormalities in calcium/phosphorus metabolism, and prevention of renal anemia by the early use of erythropoietin. Current research offers the promise of definitive prevention of both type 2 diabetes and diabetic nephropathy.

Albuminuria↗

PubMed2005

Reliability and validity of the DCP among hispanic veterans.

The Diabetes Care Profile (DCP) was designed to measure psychosocial factors related to diabetes and its treatment. This study sought to determine the reliability and validity of the DCP in Hispanic veterans with Type 2 diabetes. Hispanic (n=81) and non-Hispanic White (n=238) patients were recruited at three southwestern VA hospitals. Scale reliabilities calculated by Cronbach's coefficient alpha revealed reliabilities ranging from .54 to .97 in Hispanics and .63 to .95 in non-Hispanic Whites. Only one scale, Monitoring Barriers, differed significantly between the two patient groups. Mean values on the DCP scales were consistent within and across ethnicities lending support for construct validity of the DCP in Hispanics. Convergent validity was also supported for DCP scales within the Hispanic patients as evidenced by correlations in expected directions with external measures.

Aged↗

PubMed2005

Lack of precision of indirect estimates of body water affects urea kinetic analysis in chronic peritoneal dialysis.

To test the precision of estimates of body water and urea clearance in peritoneal dialysis (PD), we compared, in 925 PD patients who underwent formal urea kinetics studies, estimates of V and Kt/V urea obtained by the use of the Watson, Hume, and Sahlgrenska anthropometric formulas and two novel formulas, one (Vcreat) computed using fat-free mass (FFM) estimated from creatinine kinetics as 0.73 x FFMcreat, and the other (VBMI) calculated as 0.73 x FFM(BMI) where FFM(BMI) was obtained by the Gallagher formula, which estimates body composition as a function of body mass index (BMI). Comparisons by twos were performed using the paired t-test and the Wilcoxon sign rank test with the Bonferroni correction for multiple (n=10) comparisons. The results for V (liters) were Watson, 36.7 +/- 7.1; Hume, 37.3 +/- 7.3; Sahlgrenska, 36.8 +/- 7.6; Vcreat, 32.2 +/- 9.8; and VBMP 37.2 +/- 7.8. With the exception of V(BMI) and V(Hume) which did not differ, all other values differed (p < 0.001) from one another regardless of whether a parametric or nonparametric comparison was performed. The results for weekly total Kt/V urea were Watson, 2.05 +/- 0.57; Hume, 2.03 +/- 0.57; Sahlgrenska, 2.06 +/- 0.59; from Vcreat 2.42 +/- 0.71; and from V(BMP) 2.03 +/- 0.58. All of those values differed from one another (p < 0.001) by both methods of comparison. Using cut-off values (1.50, 1.75, and 2.00) as indices of adequate total weekly Kt/V urea, the discrepancies between any two estimates by the five studied formulas varied in the range 1.1% - 34.2%. Despite numerically close mean values, estimates of V based on various anthropometric formulas differ substantially and cause substantial discrepancies in the classification of Kt/V urea as inadequate or adequate. This lack of precision, added to the known lack of accuracy of the estimates, confounds the interpretation of the clinical relevance of urea kinetic estimates in PD.

Body Composition↗

PubMed2004

A probabilistic model for predicting hypoglycemia in type 2 diabetes mellitus: The Diabetes Outcomes in Veterans Study (DOVES).

BACKGROUND: To develop and validate a method for estimating hypoglycemia risk in stable, insulin-treated subjects with type 2 diabetes mellitus. METHODS: Subjects (n = 195) monitored their blood glucose levels 4 times daily for 8 weeks. An 8-week mean blood glucose value (GLUMEAN) with standard deviation (GLUSD) was derived for each patient. Subjects were then randomly allocated to a derivation or validation set. For the derivation set, we developed a logistic function based on GLUMEAN and GLUSD to describe the 8-week risk of hypoglycemia (blood glucose < or =60 mg/dL [3.3 mmol/L]). This function was used to assign a predicted probability of hypoglycemia to each subject in the validation set. Subjects were assigned to risk quartiles and followed up for up to 52 weeks. RESULTS: We evaluated 195 subjects, 95% of whom were men and 69% of whom were non-Hispanic white. For 72 derivation subjects, GLUMEAN and GLUSD were highly influential determinants of hypoglycemia during intensified monitoring. The 123 validation subjects were followed up for 39.7 +/- 7.1 weeks (mean +/- SD). The occurrence of long-term hypoglycemia differed significantly across risk quartiles (19.4%, 36.7%, 61.3%, and 77.4%, respectively; P<.001). Receiver operating characteristic curve analysis showed that the area for the probability function (0.746 +/- 0.046) was significantly higher than the area for hemoglobin A1c (0.549 +/- 0.052) because their 95% confidence intervals did not overlap. The function also identified subjects who developed long-term hypoglycemia at a rate exceeding the median frequency. CONCLUSIONS: Self-monitoring of blood glucose is superior to hemoglobin A1c measurement in predicting long-term hypoglycemia in persons with type 2 diabetes. The risk of hypoglycemia associated with treatment intensification may be offset by strategies that reduce glucose variability.

Adult↗

PubMed2004

Hypoglycemia in type 2 diabetes: a critical review.

Hypoglycemia is the most important barrier to tight glycemic control. Although severe hypoglycemia is uncommon, milder events can occur so often that they represent a deterrent to intensifying treatment. High-risk patient behaviors are the most important cause for episodes for which a cause can be identified. Because symptoms are an unreliable way of establishing the diagnosis, SMBG should be considered for the patients at highest risk, particularly as they approach their glycemic targets. SMBG is superior to HbA1c in forecasting the hypoglycemia rate because it provides information about glucose variability--an independent risk factor. Patient education and medication changes are potential ways of reducing the hypoglycemia rate. However, it remains to be proven that patient education is beneficial in this regard.

Circadian Rhythm↗

PubMed2004

Factors affecting hypoglycemia awareness in insulin-treated type 2 diabetes: The Diabetes Outcomes in Veterans Study (DOVES).

OBJECTIVE: To identify clinical factors that affect hypoglycemia perception in type 2 diabetes. METHODS: Prospective observational study of 344 insulin-treated subjects randomly selected from pharmacy records at three large medical centers. At entry, subjects underwent an extensive psychological evaluation and then monitored their blood glucoses in their usual fashion for up to 52 weeks using a glucose meter capable of storing 1000 readings. For blood glucoses <or=3.33 mmol/l (60 mg/dl), subjects recorded the severity of symptoms in a log book. Symptoms were scored '0' if they were asymptomatic, '1' for symptoms that were mild-to-moderate, and '2' if the subject had a diminished level of consciousness or required the assistance of others. A mean blood glucose and mean symptom score were calculated for all hypoglycemic episodes detected by each patient. RESULTS: One hundred seventy-six subjects (51.2%) had a median of 4.5 hypoglycemic events during 42.5+/-8.0 weeks of follow-up. The mean hypoglycemic blood glucoses and mean symptom scores were modestly correlated (r=0.153; P=0.043). After adjusting for blood glucose, symptom scores were lower in the elderly and higher in subjects with higher diabetes knowledge scores, microvascular complications, and higher entry hemoglobin A1c. Multiple linear regression showed that the latter three factors were independently predictive of higher symptoms. CONCLUSIONS: Conventional clinical data may be useful in identifying patients with poor hypoglycemia perception. Patients with better long- and short-term glycemic control are at higher risk and may benefit from instruction on all aspects of hypoglycemia.

Aged↗

PubMed2004

Food frequency questionnaire results correlate with metabolic control in insulin-treated veterans with type 2 diabetes: the Diabetes Outcomes in Veterans Study.

OBJECTIVE: To validate food frequency analysis as a predictor of metabolic status in persons with type 2 diabetes and to identify psychosocial factors affecting dietary adherence. METHODS: Three hundred forty-seven subjects with stable, insulin-treated type 2 diabetes completed a food frequency questionnaire and six instruments measuring different psychosocial attributes. Eight metabolic parameters were used as principal endpoints. Data from the food frequency questionnaires were used to estimate daily energy intake and determine each subject's adherence to seven dietary standards derived from the 2003 Dietary Recommendations of the American Diabetes Association. We excluded 105 subjects reporting daily energy intake <1,000 kcal because these results were considered unreliable. Subjects were then categorized into three groups depending on their adherence rates to American Diabetes Association dietary standards. RESULTS: Subjects with the lowest dietary adherence had the poorest metabolic control. Adherence to dietary standards was particularly poor among subjects with metabolic syndrome (2.1%) and/or obesity (4.1%). The most important determinants of following recommended dietary practices were positive attitudes, fewer social barriers, and a conviction that diet could control diabetes. CONCLUSIONS: For subjects with type 2 diabetes reporting a dietary intake of >1,000 kcal/day, food frequency questionnaire data could identify those with poor metabolic control. Nutrition interventions to improve metabolic control should focus on reducing fat intake and emphasizing the importance of diet. Multidisciplinary efforts should be directed at overcoming social barriers to recommended dietary practices and to treating depression.

Aged↗

PubMed2004

Misclassifying the indications for prostate-specific antigen testing may bias case-control studies of the efficacy of prostate cancer screening.

BACKGROUND AND OBJECTIVE: In the absence of data from randomized controlled trials, prostate cancer (CaP) screening recommendations may be based on observational studies that contrast exposure to screening between cases and controls. We evaluated the potential bias from mis-classifying indications for PSA testing in observational studies of CaP screening. METHODS: We randomly selected men undergoing PSA testing and obtained data on PSA results and prostate biopsies. Data were linked with a tumor registry to identify incident and prevalent cases of CaP. We abstracted medical records for 45 incident cases with CaP and 118 controls without, recording information on lower urinary tract symptoms (LUTS), constitutional symptoms, and digital rectal examination findings. PSA testing was classified as definitely, likely, or possibly screening, or not screening based on clinical history. RESULTS: Changing the definitions for PSA screening to variably exclude men with LUTS and enlarged prostates differentially lowered the frequency of screening. With more restrictive screening definitions, the odds ratio for screening decreased from 0.47 to 0.07. CONCLUSION: Accurately classifying PSA testing status is difficult because LUTS are common among men targeted for CaP screening. Failing to correctly classify PSA tests may bias study results.

Aged↗

PubMed2004

Contributions of weekly mean blood glucose values to hemoglobin A1c in insulin-treated type 2 diabetes: the Diabetes Outcomes in Veterans Study (DOVES).

BACKGROUND: Daily self-monitored blood glucose testing is recommended for patients with insulin-treated type 2 diabetes. However, most patients do not test frequently enough for optimal glycemic control. Less frequent testing may be sufficient for assessing glycemic control among stable patients as well as improving patient compliance. The study objective was to evaluate the weekly contribution of glucose readings to hemoglobin (Hb)A1c during an 8-week period of intensified self-monitored blood glucose testing. METHODS: The authors randomly selected stable, insulin-treated subjects with type 2 diabetes. Subjects monitored their blood glucose four times daily for 8 weeks; the authors then downloaded glucose meters and measured an HbA1c. Mean blood glucose values were calculated for each of the 8 weeks. Multiple linear regression analyses examined the contribution of these mean values to the HbA1c. RESULTS: A total of 182 subjects completed the monitoring protocol; mean HbA1c was 7.63 +/- 1.42%, mean glucose was 9.78 +/- 2.27 mmol/L, the regression correlation was 0.77, P < 0.001. A fitted multiple linear model using all 8 weekly mean blood glucose values showed large variation in their independent contributions to the HbA1c. Mean blood glucose values from consecutive weeks were highly correlated and did not provide independent information about glycemic control. Stepwise regression showed that the mean blood glucose values from weeks 4, 6, and 8 significantly and equally influenced HbA1c. CONCLUSIONS: Glycemic control can be efficiently assessed by reviewing at least 5 weeks' worth of monitoring results, focusing on alternate weeks and giving less weight to more remote readings.

Aged↗

PubMed2004

Sources of glucose variability in insulin-treated type 2 diabetes: the Diabetes Outcomes in Veterans Study (DOVES).

OBJECTIVE: Glucose variability can be a significant barrier to glycaemic control for diabetic patients on insulin. The study identified clinical and behavioural factors associated with glucose variability in type 2 diabetes. DESIGN: Observational study. SUBJECTS: Randomly selected veterans with stable, insulin-treated type 2 diabetes. MEASUREMENTS: Baseline data included demographics, clinical characteristics, diet, activity and haemoglobin A1c. Subjects self-monitored blood glucose before all meals and at bedtime for 8 weeks. Monitoring data were used to derive an overall glucose mean and glucose coefficient of variation (100*SD/mean) for each subject. Univariate and multivariate analyses were used to evaluate the relationship between glucose coefficient of variation and clinical factors. RESULTS: Two-hundred and four subjects completed the protocol. The 8-week mean (+/- SD) glucose was 9.9 +/- 2.2 mmol/l, and the average overall coefficient of variation was 35.6 +/- 7.7%. Univariate analysis showed a higher variation in older subjects and in those with longer duration of insulin treatment, greater consumption of sugars and greater confidence in their self-care abilities. Variation was lower in subjects who were obese, more compliant with medications and receiving larger insulin doses. Multivariate analysis showed that treatment duration, sugar consumption, medication compliance and insulin dose were independently associated with glucose variation. Medication compliance was more influential for fasting variation, while body mass index was more influential for before lunch variation. CONCLUSIONS: Numerous behavioural, clinical and treatment factors were independently associated with glucose variability. Reducing sugar consumption and improving medication compliance might offset the greater glucose fluctuation observed in lean patients with longstanding diabetes.

Age Factors↗

PubMed2004

Obesity and patient survival in chronic dialysis.

Obesity shortens survival in the general population. In hemodialysis (HD), obesity is associated with improved short-term survival (around 3 years). The discrepancy in the survival of obese patients between HD and the general population may be attributable to survival bias. (Only a small percentage of patients with renal failure survive until HD, and they may have certain survival advantages, including obesity.) Bias is introduced through the mixture of prevalent and incident HD patients in most studies, better nutrition in obese HD patients, malnutrition-inflammation complex syndrome causing weight loss, or other reasons. In studies of peritoneal dialysis (PD), obesity has been associated with decreased patient survival, no noticeable effect on survival, and increased survival. Potential reasons for the differences include bias in the selection of PD for obese patients, effects of race, chronic inflammation in obese PD patients, differences in nutrition and adequacy of PD, adverse effects of the increased PD dose needed to achieve adequate small-solute clearances, differences in body composition, and time discrepancies among risk factors having opposite effects on PD patient survival. Some evidence exists that in the long-term (> 10 years), obesity is a risk factor for death in both HD and PD. Further studies are needed to identify the short- and long-term risks and benefits of obesity in the two dialysis modalities.

Humans↗

PubMed2003

Estimates of body water, fat-free mass, and body fat in patients on peritoneal dialysis by anthropometric formulas.

BACKGROUND: Anthropometric formulas that are used to estimate body water in peritoneal dialysis patients can also be used to estimate fat-free mass and body fat. Evaluation of body composition by the anthropometric formulas rests on two assumptions: (1) fat contains no water, and (2) the water content of the fat-free mass is constant (72%). METHODS: We compared estimates of body water, fat-free mass, and body fat by anthropometric formulas to estimates employing dilution of tracer substances to measure body water and standard methods to analyze body composition in studies performed on peritoneal dialysis patients. We also analyzed the potential errors of the estimates of body composition by the formulas. RESULTS: Estimates of the average body composition provided by the anthropometric formulas agreed with estimates provided by the standard methods. However, these formulas have the potential of introducing large errors when estimating body composition in individuals differing from the average subject, either because the anthropometric formulas do not account for major determinants of body composition, such as physical exercise, nutrition, and catabolic illness, or because these formulas systematically overestimate body water in subjects who are obese or experiencing volume excess. CONCLUSION: Anthropometric formulas currently in existence can provide only approximations of body composition and may be the sources of large errors in evaluating body composition in peritoneal dialysis patients. The potential errors include estimates of body water. These errors may alter the interpretation of urea kinetic studies in certain categories of peritoneal dialysis patients (e.g., obese subjects).

Adipose Tissue↗

PubMed2003

Intensified blood glucose monitoring improves glycemic control in stable, insulin-treated veterans with type 2 diabetes: the Diabetes Outcomes in Veterans Study (DOVES).

OBJECTIVE: To examine the effect of intensified self-monitored blood glucose (SMBG) testing on glycemic control. RESEARCH DESIGN AND METHODS: Subjects with stable, insulin-treated type 2 diabetes performed SMBG using an electronic blood glucose meter before all meals and at bedtime for 8 weeks. Baseline data were collected on demographics, clinical characteristics, diet, and exercise. HbA(1c) was measured at baseline, at 4 weeks, and at 8 weeks. After the intensified monitoring period, subjects resumed their usual monitoring. HbA(1c) was then measured at 24, 37, and 52 weeks. Multivariate linear regression was used to determine the effect of monitoring on glycemic control. RESULTS: A total of 201 subjects completed the monitoring period. The baseline HbA(1c) (8.10 +/- 1.67%) decreased during the monitoring period by 0.30 +/- 0.68% (P < 0.001) at 4 weeks and by 0.36 +/- 0.88% (P < 0.001) at 8 weeks. Although entry HbA(1c) and compliance independently predicted the week 8 HbA(1c) (r = 0.862, P < 0.001), standardized regression analysis found that compliance with the SMBG protocol influenced the week 8 HbA(1c) more than age, sex, BMI, exercise level, carbohydrate consumption, or treatment intensity at baseline. However, SMBG benefited only subjects whose testing compliance exceeded 75% or with an entry HbA(1c) >8.0%. Decreases in HbA(1c) (-0.31 +/- 1.17%, P = 0.001) persisted in the 159 subjects followed for 52 weeks. CONCLUSIONS: Intensified blood glucose monitoring improved glycemic control in a large cohort of stable, insulin-treated veterans with type 2 diabetes. SMBG provided a strong stimulus for improved self-care resulting in clinically important and sustained reductions in HbA(1c).

Biomarkers↗

PubMed2003

Normalization of protein nitrogen appearance by various size indicators in patients on continuous peritoneal dialysis.

Protein nitrogen appearance (PNA) estimated from urea nitrogen appearance (UNA) reflects dietary protein intake and is an important index of nutrition in peritoneal dialysis (PD). Normalization of PNA by several body size indicators has resulted in discrepancies between normalized PNA (nPNA) values and other nutrition indices in PD patients with varying weight status. To test whether a particular size indicator produces nPNA values that eliminate the discrepancies, we normalized PNA values obtained at the first clearance study in 925 PD patients by weight (W), by fat-free mass (FFM) obtained from body water, by lean body mass (LBM) derived from creatinine kinetics, by desirable weight (DW), by standard weight (SW), and by adjusted edema-fee body weight (aBW). We classified patients into three groups according to W/DW: an underweight group [group I: W/DW < 0.9, n = 147 (15.9%)], a normal-weight group [group II: 0.9 < or = W/DW < 1.2, n = 506 (54.7%)], and an obese group [group III: W/DW > or = 1.2, n = 272 (29.4%)]. The UNA and PNA increased progressively from group I to group III. The W, FFM, LBM, SW, and aBW also increased progressively, and the corresponding nPNA values decreased progressively from group I to group III--all at p < 0.001. The DW did not differ significantly between the three groups. The PNA values normalized by DW were 0.91 +/- 0.21 (group I), 0.96 +/- 0.24 (group II), and 1.07 +/- 0.25 (group III), p < 0.001. Of the six size indicators tested, only DW produced values of nPNA consistent with the nutrition status of PD patients with varying weight status. Our findings indicate that DW is the proper size indicator for normalizing PNA in PD patients.

Blood Urea Nitrogen↗

PubMed2003

Body composition evaluation in peritoneal dialysis patients using anthropometric formulas estimating body water.

In adult patients on peritoneal dialysis (PD), estimates of body water (V), fat-free mass (FFM), and body fat (BF) can be obtained by using anthropometric formulas for estimating V. Estimates of V, FFM, and BF can also be obtained by using reference (standard) methods in which V is evaluated by a standard dilution method. To test whether the estimates obtained by the various methods agree, we analyzed published studies that measured V by a standard method in adult PD patients. We then calculated V, FFM, and BF by the Watson, Hume, Sahlgrenska, Chumlea, Lee, and Chertow formulas for the "average subject" in the published studies. We compared the standard and the anthropometric estimates using the limits-of-agreement method of Bland and Altman. Our analysis included six studies involving a total of 262 patients (89 women, 173 men). The six studies measured V by a reference method and allowed calculation of anthropometric V, FFM, and BF for the average patient. We calculated these values: VStandard, 36.8 +/- 4.7 L; VSahlgrenska, 36.9 +/- 4.3 L [p = nonsignificant (NS); Bland-Altman limits of agreement: -3.1 L to 3.3 L]; FFMStandard 50.9 +/- 5.2 kg; FFMSahlgrenska, 50.6 +/- 4.3 kg (Bland-Altman limits of agreement: -5.4 kg to 4.8 kg); BFStandard, 20.3 +/- 3.0 kg; BFSahlgrenska, 20.6 +/- 2.3 kg (Bland-Altman limits of agreement: -4.8 kg to 5.4 kg). Results obtained using the Watson, Hume, Chumlea, and Lee formulas also agreed with the standard estimates. The Chertow formula produced results that systematically overestimated the standard V and FFM values and that underestimated the standard BF. The Watson, Hume, Sahlgrenska, Chumlea, and Lee anthropometric formulas used to calculate V provide estimates of body composition that approximate those obtained using standard methods in PD patients with average body composition. Anthropometric estimates may cause large systematic errors in PD patients whose body composition varies from the average, particularly obese or overhydrated patients.

Anthropometry↗

PubMed2003

Weight status classification of patients on continuous peritoneal dialysis.

We tested the agreement between classifications of the weight status of patients on peritoneal dialysis (PD) by body mass index (BMI) and by body fat (BF) content (BF/W, where W = actual weight), when BF was computed as BF = W - V/0.73 from the Sahlgrenska, Watson, or Hume anthropometric formulas estimating body water (V) in 933 patients on PD and 7,737 outpatients without hydration disorders. We used currently accepted cut-off values for classifying subjects as underweight, normal-weight, overweight, and obese by BMI and BF/W. We obtained these values: BMI: men on PD (n = 555), 25.5 +/- 4.3; men with normal renal function [NRF (n = 5,906)], 27.7 +/- 5.1; women on PD (n = 378), 25.9 +/- 6.1; women with NRF (n = 1,831), 28.3 +/- 6.5; BFSahlgrenska/W--men on PD, 0.238 +/- 0.063; men with NRF, 0.274 +/- 0.052; women on PD, 0.342 +/- 0.89; women with NRF, 0.366 +/- 0.075. We obtained these regressions: Women on PD BMI = 12.0832 + 38.9550 (BFSahlgrenska/W) -92.9252 (BFSahlgrenska/W)2 +254.0675 (BFSahlgrenska/W)3, r2 = 0.917; Men on PD BMI = 19.4729 - 29.1310 (BFSahlgrenska/W) +213.7045 (BFSahlgrenska/W)2, r2 = 0.888. From those regressions, the BMI value corresponding to the BFSahlgrenska/W cut-off for underweight was similar to the National Institutes of Health (NIH) BMI cut-off for underweight. The BMI value corresponding to the BFSahlgrenska/W cut-off for obesity was substantially lower than the NIH BMI cut-off for obesity. The kappa ratios of the classifications of weight status by BMI and BFSahlgrenska/W varied between 0.142 and 0.304 (poor agreement), with more than 50% of the subjects classified in a more obese weight category by BFSahlgrenska/W than by BMI. Classification of the subjects by BMI and by BFSahlgrenska/W in quintiles or quartiles led to much higher kappa ratios, particularly in women. The results were similar in subjects with NRF and with the use of the Watson and Hume formulas to estimate BF. The use of arbitrary cut-off values of BMI or anthropometric BF/W to classify PD patients or patients without edematous states as underweight, normal-weight, overweight, or obese leads to substantial disagreement between the two classifications. Classification of weight status by BMI or BF/W in quintiles or quartiles improves substantially the agreement between the two classifications and should be preferred.

Adipose Tissue↗