Biomedical subjects

KE Renquist

Publications and source records attributed to KE Renquist.

3 recordsLinked to original sources

PubMed1996

Pay Status as a Predictor of Outcome in Surgical Treatment of Obesity.

BACKGROUND: Higher complication rates and lower success in surgery for severe obesity have been reported for patients with government pay status. We examined the effect of pay status upon outcome in surgical treatment of obesity. METHODS: This was an observational study from an aggregate data set of individual patient information. Government pay status (G) was defined as full or partial medical care payment through Medicare, Medicaid, or Veterans Administration. Payment entirely by private insurance was defined as private (P). Operations were classified as either simple (S, gastric restriction) or complex (C, gastric restriction with small bowel bypass). Two measures of outcome, perioperative complication rate and weight loss success (</= 50% excess weight), were examined to determine pay status effect. RESULTS: More G than P patients were treated with simple procedures (79% vs 51%, p < 0.05). Perioperative complication rates were more common for G than P patients (14.4% vs 9.1%, p < 0.05). One-year weight loss success was higher for P than G, regardless of operation type. CONCLUSION: Pay status should be included in characterization of patient groups and in the analysis of results when effectiveness of surgical treatment for severe obesity is reported.

Journal Article↗

PubMed1995

The Effect of Follow-up on Reporting Success for Obesity Surgery.

BACKGROUND: Much is written about the importance of follow-up in determining the effect of surgical treatment for obesity upon weight loss. When patients are lost to follow-up, it has been suggested that these patients should be considered as failures. This study was undertaken to determine the effect of incorporating patients not followed in a definition of success for weight loss at one year. METHODS: Data from 34 surgical practices were used to study the effect of using two different denominators, patients followed (Df) or patients eligible (De), to define success. The numerator used in both methods was the number of patients with </= 50% EW at 1 year. RESULTS: One-year follow-up was 61% (5091/8356). Success was 67% (3423/5091) when calculated using the denominator patients followed (Df). No correlation was found between success and follow-up when data within each surgical practice were averaged and used in a correlation analysis. CONCLUSIONS: This study does not support the thesis that patients who fall to return for follow-up should be considered as having failed in weight control.

Journal Article↗

PubMed1991

Weight Loss Curve Analysis.

The purpose of this study was to develop a mathematical model to describe weight loss trend over time and to determine differences, if any, among various weight loss trends. Weight change was studied following Roux-en-Y gastric bypass (RGB) and vertical banded gastroplasty (VBG). The total number of patients analyzed was 3172, 63.5% VBG and 36.5% RGB. Median age (years) for VBG was 36 (range 18-70) and RGB 38 (range 18-66). Median operative body mass index (BMI) (kg/m(2)) for VBG was 45.0 (range 30.1-90.5) and RGB 43.3 (range 30.4-80.6). Females represented 87% of the VBG patients and 89% of RGB patients. Obesity category percentages for each operative type were: super-VBG 20%, RGB 14%; morbid-VBG 78%, RGB 80%; obese-VBG 2%, RBG 6%. The development of a mathematical model to study weight loss over time was a two-stage process. First, weight loss trend was determined as evidenced by individual patient BMI values plotted over time. It was observed that plots represented quadratic curves, so the model BMI = B&inf0; + B&inf1;(time) + B&inf2;(time)(2) was used. Second, the estimated beta's (B&inf0;, B&inf1;, B&inf2;) were treated as response variables to estimate weight loss trend for the combination effect of three independent variables: gender (male and female), obesity category (super, morbid, obese) and operative type (VBG and RGB). It was found that the three independent variables simultaneously interact with patient weight loss (p = 0.0001).

Journal Article↗