Low body mass index, young age and female gender as risk factors predicting negative imaging of insulinomas by endoscopic ultrasound

Objective: Endoscopic ultrasound (EUS) is a highly reliable procedure to localize insulinomas preoperatively. It has been considered to be important in planning surgical strategy, especially considering a minimal invasive approach. However, even under ideal conditions experienced examiners miss about 10–20% of insulinomas by EUS imaging. Design and methods: This retrospective study aimed to identify factors associated with negative EUS imaging. Twenty-nine consecutive patients (24 benign and 5 malignant) with sporadic pancreatic insulinomas confirmed by successful surgery and positive histopathology were included. All EUS examinations were performed by one single experienced examiner over a period of one decade. Results: Three of the tumors were not detected by preoperative EUS as they were isoechoic to the surrounding healthy pancreatic tissue; 25 could be detected as hypoechoic lesions, (including all malignant tumors), and one lesion was hyperechoic. Low body mass index (P=0.053) and young age (P=0.037) were associated with negative EUS imaging. All patients with negative imaging were females. The position on the examiner’s learning curve, the diameter and location of insulinoma, and endocrine parameters (insulin concentrations and insulin–glucose ratios in the prolonged fasting test) had no influence on the success of EUS imaging. Conclusions: Some insulinomas are missed by preoperative EUS imaging as they are completely isoechoic. A low body mass index, female gender, and young age might be risk factors for negative imaging.

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Abstract 13944: J Relationship of Body Mass Index of 22-year Cardiovascular Disease Mortality versus Body Mass Index

Circulation ◽

10.1161/circ.132.suppl_3.13944 ◽

2015 ◽

Vol 132 (suppl_3) ◽

Author(s):

William J Kostis ◽

Javier Cabrera ◽

Fei Wang ◽

Sara J Guterl ◽

Dhammika Amaratunga ◽

...

Keyword(s):

Risk Factors ◽

Body Mass Index ◽

Body Mass ◽

Systolic Hypertension ◽

Female Gender ◽

The Elderly ◽

Linear Term ◽

Quadratic Term ◽

All Cause Mortality ◽

Cv Disease

Introduction: J relationships of body mass index (BMI) with mortality have been described. However, little data are available on long-term follow-up in controlled clinical trials with respect to cardiovascular (CV) and all cause mortality. Hypothesis: We tested whether there is a J shape relationship between BMI with CV and all cause mortality at 22 years in the Systolic Hypertension in the Elderly Program (SHEP). Methods: SHEP was a placebo controlled, randomized clinical trial of antihypertensive therapy in patients with isolated systolic hypertension aged 60 and older. The relationship between CV and all cause mortality with baseline BMI was examined in 4,211 SHEP participants. Results: In unadjusted analyses, a J relationship was observed for all-cause mortality (linear term p=0.0318, quadratic term p=0.3217 and tricubic term p=0.0046) and for CV mortality (linear term p=0.0962, quadratic term p=0.6866 and tricubic term p=0.0908, left figure). The lowest risk was at a BMI of 25.9 for all-cause and 25.5 for CV mortality. The J shaped relationship between BMI and mortality was attenuated after adjustment for age, gender, comorbidities (e.g. diabetes, heart failure) and risk factors for CV disease (e.g. smoking and dyslipidemia, right figure). Age and gender were significant predictors of both all- cause and CV mortality: age p<0.0001, female gender p=0.0063 for all-cause mortality and p<0.0001 for age and p=0.0004 for female gender for CV mortality. <br/Conclusions: This study indicates that both very low and very high BMI are markers of high risk. The J relationship between BMI and mortality is mediated by age, female gender, comorbidities and risk factors for CV disease.

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Risk Factors for Low Bone Density in Inflammatory Bowel Disease: Use of Glucocorticoids, Low Body Mass Index, and Smoking

Digestive Diseases ◽

10.1159/000496935 ◽

2019 ◽

Vol 37 (4) ◽

pp. 284-290 ◽

Cited By ~ 7

Author(s):

Razi Even Dar ◽

Yoav Mazor ◽

Amir Karban ◽

Sofia Ish-Shalom ◽

Elena Segal

Keyword(s):

Risk Factors ◽

Body Mass Index ◽

Inflammatory Bowel Disease ◽

Bone Density ◽

Body Mass ◽

Bowel Disease ◽

Mineral Density ◽

Low Bone Density ◽

Low Body Mass Index ◽

Inflammatory Bowel

Background: Inflammatory bowel disease (IBD) patients are reported to have lower bone density compared to healthy controls. There is limited consensus regarding factors affecting bone density among these patients. Our aim, therefore, was to determine clinical and genetic variables that contribute to lower bone mineral density (BMD) in IBD patients. Methods: A cross-sectional study of IBD patients treated in a tertiary referral center was performed. Epidemiological and clinical data were collected, and genetic testing for the common mutations in Nucleotide-binding Oligomerization Domain-containing protein (NOD)2 was performed. We examined correlations between the different variables and BMD in the total hip, femoral neck, and lumbar spine. Results: Eighty-nine patients (49% males, 67 Crohn’s disease [CD]) participated in the study. 42Forty-two (63%) of the CD and 13 (59%) of the ulcerative colitis patients met the criteria for osteoporosis/osteopenia. Factors associated with lower Z scores were low body mass index (BMI; r = –0.307, p = 0.005), use of glucocorticoids (likelihood ratio [LR] 5.1, p = 0.028), and a trend for male gender (LR = 3.4, p = 0.079). Among CD patients, low bone density showed borderline significance for association with gastrointestinal surgery (LR = 4.1, p = 0.07) and smoking (LR = 3.58, p = 0.06). Low levels of 25OHD were not associated with low BMD, nor were mutations in NOD2. No increased rate of fractures was seen among patients with osteopenia or osteoporosis. Conclusion: In addition to the generally accepted risk factors for osteoporosis (glucocorticoids, low BMI, smoking), male IBD patients had a trend toward lower BMD. Carrying a mutaticon in NOD2 did not confer a risk for bone loss.

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Low Body Mass Index and Low Intelligence Quotient Are Infection Risk Factors in Vagus Nerve Stimulation

World Neurosurgery ◽

10.1016/j.wneu.2019.06.235 ◽

2019 ◽

Vol 130 ◽

pp. e839-e845 ◽

Cited By ~ 2

Author(s):

Naoto Kuroda ◽

Ayataka Fujimoto ◽

Tohru Okanishi ◽

Keishiro Sato ◽

Shinji Itamura ◽

...

Keyword(s):

Risk Factors ◽

Body Mass Index ◽

Vagus Nerve ◽

Body Mass ◽

Nerve Stimulation ◽

Vagus Nerve Stimulation ◽

Intelligence Quotient ◽

Infection Risk ◽

Infection Risk Factors ◽

Low Body Mass Index

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Predicting the risk of sarcopenia in elderly patients with patellar fracture: Development and assessment of a new predictive nomogram

10.1101/702548 ◽

2019 ◽

Author(s):

Chen Yisheng ◽

Tao Jie

Keyword(s):

Risk Factors ◽

Body Mass Index ◽

Elderly Patients ◽

Prediction Model ◽

Predictive Model ◽

Body Mass ◽

Curve Analysis ◽

Decision Curve Analysis ◽

Low Body Mass Index ◽

Patellar Fractures

AbstractPurposeThis study was aimed at developing a risk prediction model for postoperative dysplasia in elderly patients with patellar fractures in China.Patients and methodsWe conducted a community survey of patients aged ≥55 years who underwent surgery for patellar fractures between January 2013 and October 2018, through telephone interviews, community visits, and outpatient follow-up. We established a predictive model for assessing the risk of sarcopenia after patellar fractures. We developed the prediction model by combining multivariate logistic regression analysis with the least absolute shrinkage model and selection operator regression (Lasso analysis). The predictive quality and clinical utility of the predictive model were determined using C-index, calibration plots, and decision curve analysis. We conducted internal sampling methods for qualitative assessment.ResultWe recruited 61 participants (males: 20, mean age: 68.1 years). Various risk factors were assessed, and low body mass index and diabetes mellitus were identified as the most important risk factors (P<0.05). The model showed a good prediction rate (C-index: 0.909; 95% confidence interval: 0.81–1.00) and good correction effect. The C-index remained high (0.828) even after internal sample verification. Decision curve analysis showed that the risk of sarcopenia was 8.3–80.0%, suggesting good clinical practicability.ConclusionOur prediction model shows promise as a cost-effective tool for predicting the risk of postoperative sarcopenia in elderly patients based on the following: advanced age, low body mass index, diabetes, longer postoperative hospital stay, no higher education, no postoperative rehabilitation, removal of internal fixation, and less outdoor exercise.

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Lifelong risk factors for osteoporosis and fractures in elderly women with low body mass index—A population-based study

Bone ◽

10.1016/j.bone.2006.01.143 ◽

2006 ◽

Vol 39 (2) ◽

pp. 385-391 ◽

Cited By ~ 45

Author(s):

R. Korpelainen ◽

J. Korpelainen ◽

J. Heikkinen ◽

K. Väänänen ◽

S. Keinänen-Kiukaanniemi

Keyword(s):

Risk Factors ◽

Body Mass Index ◽

Body Mass ◽

Elderly Women ◽

Population Based ◽

Population Based Study ◽

Low Body Mass Index

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Prognostic impact and risk factors of low body mass index in patients undergoing liver transplantation

Clinical Transplantation ◽

10.1111/ctr.13048 ◽

2017 ◽

Vol 31 (9) ◽

pp. e13048

Author(s):

Jin-Chiao Lee ◽

Wael M. A. Doush ◽

Yu-Chao Wang ◽

Chih-Hsien Cheng ◽

Tsung-Han Wu ◽

...

Keyword(s):

Risk Factors ◽

Body Mass Index ◽

Liver Transplantation ◽

Body Mass ◽

Prognostic Impact ◽

Low Body Mass Index

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Geriatric falls in the context of a hospital fall prevention program: delirium, low body mass index, and other risk factors

Clinical Interventions in Aging ◽

10.2147/cia.s115755 ◽

2016 ◽

Vol Volume 11 ◽

pp. 1253-1261 ◽

Cited By ~ 22

Author(s):

Jan Szewieczek ◽

Katarzyna Mazur ◽

Krzysztof Wilczyński

Keyword(s):

Risk Factors ◽

Body Mass Index ◽

Body Mass ◽

Fall Prevention ◽

Prevention Program ◽

Fall Prevention Program ◽

Low Body Mass Index

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Underweight increases the risk of pulmonary tuberculosis in adult

Zinc supplementation improves heme biosynthesis in rats exposed to lead ◽

10.18051/univmed.2017.v36.4-10 ◽

2017 ◽

Vol 36 (1) ◽

pp. 4

Author(s):

Galuh Chandra Irawan ◽

Ani Margawati ◽

Ali Rosidi

Keyword(s):

Risk Factors ◽

Body Mass Index ◽

Logistic Regression ◽

Risk Factor ◽

Pulmonary Tuberculosis ◽

Body Mass ◽

Low Income ◽

Smoking Behavior ◽

Significant Risk ◽

Low Body Mass Index

Background Tuberculosis (TB) is a leading cause of morbidity and mortality, especially in middle- and low-income countries. The risk of developing TB may be related to nutritional status. Socioeconomic and behavioral factors are also shown to increase the susceptibility to TB infection. The objective of this study was to determine nutritional factors as risk factors of pulmonary TB in adult.Methods This was an observational study of case control design. The study subjects were community members consisting of 19 adult cases of pulmonary tuberculosis and 38 controls. Data on nutritional intakes were obtained by semiquantitative food frequency questionnaire (FFQ), while smoking behavior, history of DM, body mass index, education, and income were obtained by structured interviews. The data were analyzed by independent t-test and logistic regression for calculation of the odds ratio (OR).Results The bivariate test showed that the adequacy levels for energy (OR=6.8; 95% CI: 1.51-30.54), protein (OR=5.1; 95% CI: 1.52-17.14), vitamin A (OR=4.2; 5% CI: 1.31-13.54), vitamin C (OR=3.8;95% CI: 1.21-12.36), selenium (OR=4.2; 95% CI: 1.34-13.58), body mass index (OR=4.4; 95% CI: 1.32-14.35) and smoking behavior (OR=3.7; 95% CI: 1.15-11.9), were significant risk factors for pulmonary tuberculosis. Multiple logistic regression test showed that low body mass index (<18.5 kg/m2) (OR=6.0; 95% CI: 1.32-27.18) was a the most influential risk factor of pulmonary tuberculosis.Conclusion Low body mass index is the most influential risk factor for pulmonary tuberculosis incidence in adult. Nutrition profile in adult is an important determinant of TB incidence.

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