Model Included Body Mass Index Research Articles

Relationship Between Laryngopharyngeal Reflux and Obstructive Sleep Apnea in Adult Males

To investigate the relationship between laryngopharyngeal reflux (LPR) and obstructive sleep apnea (OSA). Patients diagnosed with OSA who were hospitalized in the Department of Otolaryngology-Head and Neck Surgery from November 2021 to April 2022 were selected, and male patients with non-OSA during the same period were selected as the control group. Patients who participated in the study completed the Reflux Symptom Index (RSI), the Reflux Finding Sign (RFS), and 24-hour multichannel intraluminal impedance-pH (MII-pH) monitoring. RSI, RFS, and outcomes of 24hour-MII-pH monitoring were compared between the OSA group and the control group. A total of 86 patients were enrolled, of whom 49 were OSA patients and 37 were non-OSA patients. The positive rate of LPR (97.96% vs75.68%) and the median number of LPR episodes (9 vs5) were significantly higher in OSA patients than in non-OSA patients (P<0.01, P<0.05, respectively). A logistic regression model including body mass index, alcohol consumption, and the presence of OSA showed that having OSA was a risk factor for the occurrence of LPR (P<0.05,OR [odds ratio]=9.995, 95% CI [confidence interval] 1.084-92.181). There were correlations between Apnea-Hypopnea Index and the number of non-acid LPR episodes and the number of alkaline LPR episodes (r=0.243,P<0.05, r=0.274, P<0.05,respectively). Having OSA is a risk factor for LPR, and LPR episodes occur more frequently in patients with OSA compared to those without OSA. When OSA is comorbid with LPR, the occurrence of alkaline LPR, such as bile reflux, should be a concurrent concern.

Non-insulin-based insulin resistance indices for predicting all-cause mortality and renal outcomes in patients with stage 1-4 chronic kidney disease: another paradox.

Non-insulin-based insulin resistance (IR) indices serve as the indicators of metabolic syndrome (MetS) but have limited value for predicting clinical outcomes. Whether the obesity paradox affects the predictive value of these indicators in patients with chronic kidney disease (CKD) remains unknown. We investigated whether MetS and non-insulin-based IR indices can predict all-cause mortality and renal outcomes in a prospective observational study with stage 1-4 CKD Asians (N = 2,457). These IR indices were associated with MetS. A Cox regression model including body mass index (BMI) revealed an association between MetS and renal outcomes. Among the IR indices, only high triglyceride-glucose (TyG) index was associated with adverse renal outcomes: the hazard ratio of Q4 quartile of the TyG index was 1.38 (1.12-1.70). All-cause mortality was marginally associated with MetS but not high IR indices. Low TyG and TyG-BMI indices as well as low BMI and triglyceride were paradoxically associated with increased risks of clinical outcomes. The triglyceride-to-high-density lipoprotein cholesterol ratio and metabolic score for IR indices were not associated with clinical outcomes. In conclusion, MetS and TyG index predict renal outcome and obesity paradox affects the prediction of IR indices in patients with stage 1-4 CKD.

Investigation of Genetic Variants Associated with Tryptophan Metabolite Levels via Serotonin and Kynurenine Pathways in Patients with Bipolar Disorder.

The kynurenine pathway (KP) may play a role in the pathophysiology of bipolar disorder (BD). We conducted a genome-wide association study (GWAS) to identify genetic variants associated with the plasma levels of the metabolites of tryptophan (TRP) via the serotonin (5-HT) and kynurenine (KYN) pathways in 44 patients with BD and 45 healthy controls. We assessed whether variants that were differentially associated with metabolite levels based on the diagnostic status improved the prediction accuracy of BD using penalized regression approaches. We identified several genetic variants that were significantly associated with metabolites (5-HT, 5-hydroxytryptophan (5-HTP), TRP, and quinolinic acid (QA) or metabolite ratios (5-HTP/TRP and KYN/TRP) and for which the diagnostic status exerted a significant effect. The inclusion of genetic variants led to increased accuracy in the prediction of the BD diagnostic status. Specifically, we obtained an accuracy of 0.77 using Least Absolute Shrinkage and Selection Operator (LASSO) regression. The predictors retained as informative in this model included body mass index (BMI), the levels of TRP, QA, and 5-HT, the 5-HTP/TRP ratio, and genetic variants associated with the levels of QA (rs6827515, rs715692, rs425094, rs4645874, and rs77048355) and TRP (rs292212) or the 5-HTP/TRP ratio (rs7902231). In conclusion, our study identified statistically significant associations between metabolites of TRP via the 5-HT and KYN pathways and genetic variants at the genome-wide level. The discriminative performance of penalized regression models incorporating clinical, genetic, and metabolic predictors warrants a follow-up analysis of this panel of determinants.

Development, validation and clinical utility of a risk prediction model for adverse pregnancy outcomes in women with gestational diabetes: The PeRSonal GDM model.

SummaryBackgroundThe ability to calculate the absolute risk of adverse pregnancy outcomes for an individual woman with gestational diabetes mellitus (GDM) would allow preventative and therapeutic interventions to be delivered to women at high-risk, sparing women at low-risk from unnecessary care. We aimed to develop, validate and evaluate the clinical utility of a prediction model for adverse pregnancy outcomes in women with GDM.MethodsA prediction model development and validation study was conducted on data from a observational cohort. Participants included all women with GDM from three metropolitan tertiary teaching hospitals in Melbourne, Australia. The development cohort comprised those who delivered between 1 July 2017 to 30 June 2018 and the validation cohort those who delivered between 1 July 2018 to 31 December 2018. The main outcome was a composite of critically important maternal and perinatal complications (hypertensive disorders of pregnancy, large-for-gestational age neonate, neonatal hypoglycaemia requiring intravenous therapy, shoulder dystocia, perinatal death, neonatal bone fracture and nerve palsy). Model performance was measured in terms of discrimination and calibration and clinical utility evaluated using decision curve analysis.FindingsThe final PeRSonal (Prediction for Risk Stratified care for women with GDM) model included body mass index, maternal age, fasting and 1-hour glucose values (75-g oral glucose tolerance test), gestational age at GDM diagnosis, Southern and Central Asian ethnicity, East Asian ethnicity, nulliparity, past delivery of an large-for-gestational age neonate, past pre-eclampsia, GWG until GDM diagnosis, and family history of diabetes. The composite adverse pregnancy outcome occurred in 27% (476/1747) of women in the development (1747 women) and in 26% (244/955) in the validation (955 women) cohorts. The model showed excellent calibration with slope of 0.99 (95% CI 0.75 to 1.23) and acceptable discrimination (c-statistic 0.68; 95% CI 0.64 to 0.72) when temporally validated. Decision curve analysis demonstrated that the model was useful across a range of predicted probability thresholds between 0.15 and 0.85 for adverse pregnancy outcomes compared to the alternatives of managing all women with GDM as if they will or will not have an adverse pregnancy outcome.InterpretationThe PeRSonal GDM model comprising of routinely available clinical data shows compelling performance, is transportable across time, and has clinical utility across a range of predicted probabilities. Further external validation of the model to a more disparate population is now needed to assess the generalisability to different centres, community based care and low resource settings, other healthcare systems and to different GDM diagnostic criteria.FundingThis work is supported by the Mothers and Gestational Diabetes in Australia 2 NHMRC funded project #1170847.

A logistic regression model based on inpatient health records to predict drug-induced liver injury caused by ramipril—An angiotensin-converting enzyme inhibitor

Drug-induced liver injury (DILI) is a rare side effect of angiotensin-converting enzyme inhibitors (ACEIs). Ramipril is a widely used ACE compound because of its effectiveness in the treatment of hypertension and heart failure, as well as its low risk of adverse effects. However, the clinical features of ramipril, and the risk of DILI, have not been adequately studied. A retrospective cohort study was performed based on data from 3909 inpatients to compare the risk of DILI conferred by ramipril and other ACEIs. A logistic regression model was then constructed and validated against data from 1686 patients using ramipril, of which 117 patients were diagnosed with DILI. The use of ramipril increased the risk of DILI by 2.68 times (odds ratio = 2.68; 95% confident interval (CI):1.96-3.71) compared with the group using other ACEIs. The clinical features of DILI in the ramipril group were similar to those from the ACEI group (P>0.05), except that the ALT level was higher (P<0.05). A logistic regression model including Body mass index (BMI), comorbidity, liver disease, daily dose, alanine aminotransferase (ALT), and alkaline phosphatase (ALP) was built and successfully validated for DILI risk prediction, with the area under the receiver operating characteristic curve of the model of 0.82 (95% CI: 0.752-0.888). We recommend that clinicians should be aware of the levels of ALT and ALP as well as BMI, comorbidities, and liver disease before prescribing ramipril to avoid the risk of DILI in patients.

Daily physical activity is negatively associated with thyroid hormone levels, inflammation, and immune system markers among men and women in the NHANES dataset.

The acute effects of exercise on metabolic energy expenditure and inflammation are well studied, but the long-term effects of regular daily physical activity on metabolic and endocrine effects are less clear. Further, prior studies investigating the impact of daily physical activity in large cohorts have generally relied on self-reported activity. Here, we used the U.S. National Health and Nutrition Examination Survey (NHANES) to investigate the relationship between daily physical activity and both thyroid and immune activity. Daily physical activity was assessed through accelerometry or accelerometry-validated survey responses. Thyroid activity was assessed from circulating levels of thyroid stimulating hormone (TSH) and thyroxine (T4). Immune function was assessed from circulating cytokines (C-reactive protein [CRP], immunoglobulin E [IgE], fibrinogen) and blood cell counts. In general linear models including body mass index, age, gender, activity and TSH as factors, active adults had a lower levels of T4 and reduced slope of the TSH:T4 relationship. Similarly, greater physical activity was associated with lower CRP and fibrinogen levels (but not IgE) and lower white blood cell, basophil, monocyte, neutrophil, and eosinophil (but not lymphocyte) counts. Daily physical activity was also associated with lower prevalence of clinically elevated CRP, WBC, and lymphocytes in a dose-response manner. These results underscore the long-term impact of daily physical activity on both systemic metabolic activity (thyroid) and on specific physiological tasks (immune). The regulatory effects of physical activity on other bodily systems are clinically relevant and should be incorporated into public health strategies promoting exercise.

An internally validated prediction model for critical COVID-19 infection and intensive care unit admission in symptomatic pregnant women

BackgroundPregnant women are at an increased risk of mortality and morbidity owing to COVID-19. Many studies have reported on the association of COVID-19 with pregnancy-specific adverse outcomes, but prediction models utilizing large cohorts of pregnant women are still lacking for estimating the risk of maternal morbidity and other adverse events.ObjectiveThe main aim of this study was to develop a prediction model to quantify the risk of progression to critical COVID-19 and intensive care unit admission in pregnant women with symptomatic infection.Study DesignThis was a multicenter retrospective cohort study including 8 hospitals from 4 countries (the United Kingdom, Austria, Greece, and Turkey). The data extraction was from February 2020 until May 2021. Included were consecutive pregnant and early postpartum women (within 10 days of birth); reverse transcriptase polymerase chain reaction confirmed SARS-CoV-2 infection. The primary outcome was progression to critical illness requiring intensive care. The secondary outcomes included maternal death, preeclampsia, and stillbirth. The association between the primary outcome and 12 candidate predictors having a known association with severe COVID-19 in pregnancy was analyzed with log-binomial mixed-effects regression and reported as adjusted risk ratios. All the potential predictors were evaluated in 1 model and only the baseline factors in another. The predictive accuracy was assessed by the area under the receiver operating characteristic curves.ResultsOf the 793 pregnant women who were positive for SARS-CoV-2 and were symptomatic, 44 (5.5%) were admitted to intensive care, of whom 10 died (1.3%). The ‘mini-COvid Maternal Intensive Therapy’ model included the following demographic and clinical variables available at disease onset: maternal age (adjusted risk ratio, 1.45; 95% confidence interval, 1.07–1.95; P=.015); body mass index (adjusted risk ratio, 1.34; 95% confidence interval, 1.06–1.66; P=.010); and diagnosis in the third trimester of pregnancy (adjusted risk ratio, 3.64; 95% confidence interval, 1.78–8.46; P=.001). The optimism-adjusted area under the receiver operating characteristic curve was 0.73. The ‘full-COvid Maternal Intensive Therapy’ model included body mass index (adjusted risk ratio, 1.39; 95% confidence interval, 1.07–1.95; P=.015), lower respiratory symptoms (adjusted risk ratio, 5.11; 95% confidence interval, 1.81–21.4; P=.007), neutrophil to lymphocyte ratio (adjusted risk ratio, 1.62; 95% confidence interval, 1.36–1.89; P<.001); and serum C-reactive protein (adjusted risk ratio, 1.30; 95% confidence interval, 1.15–1.44; P<.001), with an optimism-adjusted area under the receiver operating characteristic curve of 0.85. Neither model showed signs of a poor fit. Categorization as high-risk by either model was associated with a shorter diagnosis to intensive care unit admission interval (log-rank test P<.001, both), higher maternal death (5.2% vs 0.2%; P<.001), and preeclampsia (5.7% vs 1.0%; P<.001). A spreadsheet calculator is available for risk estimation.ConclusionAt presentation with symptomatic COVID-19, pregnant and recently postpartum women can be stratified into high- and low-risk for progression to critical disease, even where resources are limited. This can support the nature and place of care. These models also highlight the independent risk for severe disease associated with obesity and should further emphasize that even in the absence of other comorbidities, vaccination is particularly important for these women. Finally, the model also provides useful information for policy makers when prioritizing national vaccination programs to quickly protect those at the highest risk of critical and fatal COVID-19.

Disordered Eating, Development of Menstrual Irregularity, and Reduced Bone Mass Change After a 3-Year Follow-Up In Female Adolescent Endurance Runners.

This prospective study evaluated the 3-year change in menstrual function and bone mass among 40 female adolescent endurance runners (age 15.9 ± 1.0years) according to baseline disordered eating status. Three years after initial data collection, runners underwent follow-up measures including the Eating Disorder Examination Questionnaire and a survey evaluating menstrual function, running training, injury history, and prior sports participation. Dual-energy X-ray absorptiometry was used to measure bone mineral density and body composition. Runners with a weight concern, shape concern, or global score ≥4.0 or reporting >1 pathologic behavior in the past 28 days were classified with disordered eating. Compared with runners with normal Eating Disorder Examination Questionnaire scores at baseline, runners with disordered eating at baseline reported fewer menstrual cycles/year (6.4 ± 4.5 vs. 10.5 ± 2.8, p = .005), more years of amenorrhea (1.6 ± 1.4 vs. 0.3 ± 0.5, p = .03), and a higher proportion of menstrual irregularity (75.0% vs. 31.3%, p = .02) and failed to increase lumbar spine or total hip bone mineral density at the 3-year follow-up. In a multivariate model including body mass index and menstrual cycles in the past year at baseline, baseline shape concern score (B = -0.57, p value = .001) was inversely related to the annual number of menstrual cycles between assessments. Weight concern score (B = -0.40, p value = .005) was inversely associated with lumbar spine bone mineral density Z-score change between assessments according to a multivariate model adjusting for age and body mass index. These finding support associations between disordered eating at baseline and future menstrual irregularities or reduced accrual of lumbar spine bone mass in female adolescent endurance runners.

Hidradenitis Suppurativa: Proposal of Classification in Two Endotypes with Two-Step Cluster Analysis

Introduction: Hidradenitis suppurativa (HS) is a chronic, inflammatory, recurrent disorder of the pilosebaceous unit. Currently, several attempts have been made to classify this disease according to its pathogenesis and clinical manifestations. We attempted at classifying 103 patients using two-step cluster analysis. Methods: The final model included body mass index, C-reactive protein (CRP), and serum concentrations of IL-1, IL-6, IL-17, and IL-10 as continuous variables, and sex, later/early onset, anterior/posterior lesion sites, presence/absence of sinus tracts, nodules and abscesses, positive/negative history of pilonidal sinus, and presence/absence of mutations in gamma-secretase subunits (APH1A, APH1B, MEFV, NCSTN, PSEN1, PSEN2, PSENEN, PSTPIP1) as qualitative variables. Results: The resultant model defined two groupings or clusters: cluster 1 (64.9% of patients) characterized by nonobese males, with nodular lesions in posterior sites, early-onset HS, higher IL-10, presence of gamma-secretase mutations, and history of pilonidal sinus; and cluster 2 (35.1% of patients) characterized by obese females or males, with lesions in anterior sites, more presence of sinus tracts and abscesses and less nodules, later-onset HS, and higher concentrations of IL-1, CRP, IL-17, and IL-6. Severity measures (Hurley, HS-PGA, and IHS4) and tobacco use were discarded because the analysis found them to be less relevant for clustering. Conclusion: Our resultant model confirms the clinical impression that HS is a disease spectrum with two pathogenic poles defining two clusters or endotypes. The probability of having severe disease was equally distributed in the two clusters. The variable with the highest predictive value for clustering was involvement of typical anterior sites (axillae, submammary) or atypical posterior sites (back, gluteal). Serum concentrations of interleukins, tobacco use, and sex had a lower predictive power for clustering.

Adherence to the MIND Diet and Risk of Breast Cancer: A Case-control Study

IntroductionNo data are available on the association between adherence to the Mediterranean-DASH Intervention for Neurodegenerative Delay (MIND) diet and breast cancer. Materials and MethodsThis population-based case-control study was conducted among women aged ≥ 30 years, who were residing in Isfahan, Iran. The study included 350 patients with newly diagnosed stage I to IV breast cancer, for whom in situ or invasive status of breast cancer was confirmed by physical examination, mammography, and pathologic verification. Controls were 700 age-matched apparently healthy individuals who were randomly selected from the general population. Dietary data were collected using a validated 106-item Willett-format, semi-quantitative dish-based food frequency questionnaire. ResultsAfter adjustment for age and energy intake, women in the top tertile of the MIND diet score had 60% lower odds of breast cancer than women in the bottom tertile (odds ratio [OR], 0.40; 95% confidence interval [CI], 0.29-0.55). In the fully adjusted model including body mass index, those with the greatest MIND diet scores had 50% lower chance of breast cancer (OR, 0.50; 95% CI, 0.34-0.72) than those with the lowest adherence to the MIND diet. Postmenopausal women with the greatest adherence to the MIND diet were less likely to have breast cancer than those in the bottom tertile (OR, 0.45; 95% CI, 0.30-0.66). In addition, we found a significant inverse association between adherence to the MIND diet and odds of breast cancer among normal-weight women (OR, 0.39; 95% CI, 0.25-0.60). ConclusionAdherence to the MIND diet was associated with a reduced chance of breast cancer in this case-control study.

Development and Validation of a Model for Predicting Urethral Recurrence in Male Patients with Muscular Invasive Bladder Cancer After Radical Cystectomy Combined with Urinary Diversion.

PurposeRadical cystectomy (RC) is the primary treatment strategy for patients with muscular invasive bladder cancer (MIBC). However, the prognosis is poor and tumor recurrence is not rare, in particular, urethral recurrence (UR) in male patients who underwent RC combined with urinary diversion. Here, we have developed and validated a model for predicting UR in these patients.Patients and MethodsThe development cohort comprised 310 patients who underwent RC combined with urinary diversion at our center between 1 January 2007 and 31 December 2015. Clinicopathologic data of patients were comprehensively recorded. Multivariate Cox proportional hazard regression was used for building a predictive model with regression coefficients and backward stepwise selection applied by utilizing the likelihood ratio test with Akaike’s information criterion as the stopping rule. An independent cohort consisting of 131 consecutive patients treated from 1 January 2016 to 31 December 2017 was used for validation. The performance of this predictive model was assessed with respect to discrimination, calibration, and clinical usefulness.ResultsThe predictors of this model included body mass index, history of transurethral resection of bladder tumor, tumor grade, tumor stage, and concomitant carcinoma in situ. In the validation cohort, the model showed good discrimination with a concordance index of 0.777 (95% CI, 0.618 to 0.937) and calibration. Decision curve analysis also demonstrated the clinical utility of the model.ConclusionThe predictive model facilitated postoperative individualized prediction of UR in male patients with MIBC after RC combined with urinary diversion and it may therefore serve to improve follow-up strategies.

Differential blood count as triage tool in evaluation of pelvic masses

ObjectiveTriaging patients with presumptive ovarian cancer to the appropriate specialist may improve survival. Therefore, there is increasing interest in complementary diagnostic markers to the standard serum CA125. In patients with...

Development and validation of a prediction model for incident hand osteoarthritis in the HUNT study

To develop and externally validate prediction models for incident hand osteoarthritis (OA) in a large population-based cohort of middle aged and older men and women. We included 17,153 men and 18,682 women from a population-based cohort, aged 35-70yearsat baseline (1995-1997). Incident hand OA were obtained from diagnostic codes in the Norwegian National Patient Register (1995-2018). We studied whether a range of self-reported and clinically measured predictors could predict hand OA, using the Area Under the receiver-operating Curve (AUC) from logistic regression. External validation of an existing prediction model for male hand OA was tested on discrimination in a sample of men. Bootstrapping was used to avoid overfitting. The model for men showed modest discriminatory ability (AUC=0.67, 95% CI 0.62-0.71). Adding a genetic risk score did not improve prediction. Similar discrimination was observed in the model for women (AUC=0.62, 95% CI 0.59-0.64). Prediction was not improved by adding a genetic risk score or hormonal and reproductive factors. Applying external validation, similar results were observed among men in HUNT (The Nord-Trøndelag Health Study) as in the developmental sample (AUC=0.62, 95% CI 0.57-0.65). We developed prediction models for incident hand OA in men and women. For women, the model included body mass index (BMI), heavy physical work, high physical activity and perceived poor health. The model showed moderate discrimination. For men, we have shown that a prediction model including BMI, education and information on sleep can predict incident hand OA in several populations with moderate discriminative ability.

An association between echocardiographic left ventricle longitudinal strain and hypertension in general population depending on blood pressure control

Background . Ultrasound assessment of myocardial strain allows non-invasive identification of early stages of heart failure with preserved ventricular ejection fraction. A decline of the left ventricle (LV) global longitudinal strain in hypertension (HT) accompanied by LV hypertrophy (LVH) was reported in clinical samples with manifest HT. Data on the relationship between longitudinal strain and blood pressure (BP) and HT in general population is lacking. Objective . We studied the relationship between LV peak systolic global longitudinal strain ( GLS ) and strain rate ( GSR ) in subjects with high and controlled BP from a general population sample aged over 55 years. Design and methods . The cross-sectional study was based on a population cohort (HAPIEE, Novosibirsk). In a random sample (n = 416, aged 55–84 years old) we performed echocardiography and evaluated GLS and GSR of LV by speckle tracking technique. ANOVA multivariable models were applied. Results. In the studied sample, the prevalence of HT comprised 78,9 %. The mean GLS value was –18,7 ± 3,79 %, and it was lower in men than in women (–18,2 ± 3,85 % vs –19,2 ± 3,66 %, p = 0,005). The mean GSR value was –0,84 ± 0,17s –1 , and did not differ by sex. The absolute value of GLS in HT was lower than in normotensives: –18,5 ± 3,73 % vs –19,9 ± 3,42 %, p = 0,003; this difference was independent of age, sex and LV myocardial mass index (IMM), p = 0,011; but it was attenuated in a multivariable-adjusted model including body mass index (BMI). In HT groups, the GLS was the lowest among those “treated ineffectively” and significantly lower than in normotensives independently of age, sex and myocardium mass index (p = 0,008). The absolute value of GSR in HT was lower than in normotensives: –0,90 ± 0,17 s –1 vs –0,83 ± 0,17s –1 , p < 0,001; and persisted in multivariable models. GSR was the lowest among those “treated ineffectively” and significantly lower than in normotensives in multivariable models independently of age, sex, BMI and myocardial mass index (p = 0,017; 0,002). The average values of LV ejection fraction (Simpson) in all groups were above 50 % without significant inter-group differences (p = 0,904). conclusions. In the studied population sample, GLS and GSR of LV were associated with HT; however, the association between GLS and HT was largely explained by BMI. In hypertensives, the lowest GLS and GSR , as well as higher extent of LVH, were found among those treated ineffectively, which might point at the initial reduction of systolic ventricular function in HT with inadequate BP control.

Polycystic Ovary Syndrome Signs and Metabolic Syndrome in Premenopausal Hispanic/Latina Women: the HCHS/SOL Study.

Polycystic ovary syndrome (PCOS), a condition of androgen excess in women, is associated with cardiometabolic risk factors; however, this association is not fully characterized in a population-based sample of premenopausal women and high-risk groups such as Hispanics/Latinas. We examined the association of PCOS signs and metabolic syndrome (MetS) in premenopausal Hispanic/Latina women. This cross-sectional analysis includes 1427 women age 24 to 44 years from the Hispanic Community Health Study/Study of Latinos. PCOS signs included menstrual cycle greater than 35 days or irregular, self-reported PCOS, and oral contraceptive use to regulate periods or acne, and a composite of 1 or more PCOS signs. We calculated odds ratios (OR) and 95% CI for MetS, accounting for sociodemographic factors and the complex survey design; an additional model included body mass index (BMI). The mean age was 34 years and 30% reported any PCOS sign. The odds of MetS were higher in women reporting cycles greater than 35 days or irregular (OR 1.63; CI: 1.07-2.49) vs cycles 24 to 35 days, self-reported PCOS (OR 2.49; CI: 1.38-4.50) vs no PCOS, and any PCOS sign (OR 1.58; CI: 1.10-2.26) vs none. We found no association between OC use to regulate periods or acne and MetS (OR 1.1; CI: 0.6-1.8). When adjusting for BMI, only the association of self-reported PCOS and MetS was attenuated (OR 1.78; CI: 0.92-3.44). In Hispanic/Latina women, irregular menstrual cycles, self-reported PCOS, and any PCOS sign were associated with MetS and could indicate women at metabolic disease risk.

Development and validation of a clinical model to predict intraoperative hemodynamic instability in patients with pheochromocytomas surgery.

Although currently the primary strategy for the treatment of pheochromocytomas is surgery, it is associated with a high risk of intraoperative hemodynamic instability (IHD), even with adequate preoperative medical preparation, which may result in life-threatening situations. The aim of this study was to develop and validate a nomogram for preoperative prediction of IHD related to pheochromocytoma surgery. The development cohort consisted of 283 patients with pheochromocytoma who underwent unilateral laparoscopic or open adrenaletomy at our center between January 1, 2007 and December 31, 2016. The clinicopathological characteristics of each patient were recorded. The least absolute shrinkage and selection operator binary logistic regression model was used for data dimension reduction and feature selection, while multivariable logistic regression analysis was used to develop the prediction model. An independent cohort consisting of 119 consecutive patients from January 1, 2017 to December 31, 2018 was used for validation. The performance of the prediction model was assessed in regards to discrimination, calibration, and clinical usefulness. The predictors of this model included body mass index, coronary heart disease, tumor size, and preoperative use of crystal/colloid fluid. For the validation cohort, the model showed good discrimination with an area under the receiver operating characteristic of 0.767 (95% CI, 0.667-0.857) and good calibration (unreliability test, p = 0.852; Hosmer-Lemeshow test, p = 0.9309). Decision curve analysis demonstrated that the model was clinically useful. This nomogram to facilitate preoperative individualized prediction of IHD in patients with pheochromocytoma may help to improve the perioperative strategy and treatment outcome.

Development and validation of a predictive model for predicting cardiovascular morbidity in patients after pheochromocytoma surgery.

Although surgical resection is the primary treatment method for pheochromocytoma, it carries a high risk of morbidity, especially cardiovascular-related morbidity. There are no models for predicting cardiovascular morbidity after pheochromocytoma surgery. Thus, we developed and validated a model for the preoperative prediction of cardiovascular morbidity after pheochromocytoma surgery. The development cohort consisted of 262 patients who underwent unilateral laparoscopic or open pheochromocytoma surgery at our centre between 1 January 2007 and 31 December 2016. Patient's clinicopathologic data were recorded. The LASSO regression was used for data dimension reduction and feature selection; then, multivariable logistic regression analysis was used to develop the prediction model. An independent cohort consisting of 112 consecutive patients from 1 January 2017 and 31 December 2018 was used for validation. The performance of this prediction model was assessed with respect to discrimination, calibration and clinical usefulness. The predictors in this prediction model included body mass index, history of coronary heart disease, tumour size, intraoperative hemodynamic instability and use of crystal/colloid fluids preoperatively. In the validation cohort, the model showed good discrimination with an AUROC of 0.869 (95% CI, 0.797, 0.940) and good calibration (unreliability test, P=.852). Decision curve analysis demonstrated that the model was also clinically useful. This study presented a good nomogram that could facilitate the preoperative individualized prediction of cardiovascular morbidity after pheochromocytoma surgery, which may help improve perioperative strategy and good treatment outcomes.

Predicting the Risk of Weight Loss After Esophageal Cancer Surgery

BackgroundMalnutrition after esophageal cancer surgery is associated with reduced health-related qualify of life. Therefore, a prediction model identifying patients at risk for severe weight loss after surgery was developed.MethodsData from a Swedish population-based cohort study, including 616 patients undergoing esophageal cancer surgery in 2001–2005, was used. Candidate predictors included risk factors available before and immediately after surgery. Severe weight loss was defined as ≥ 15% loss of body weight between the time of surgery and 6 months postoperatively. The prediction model was developed using multivariable models. The accuracy of the model was measured by the area under the receiver operating characteristics curve (AUC) with bootstrap validation. The model was externally validated in a hospital-based cohort of 91 surgically treated esophageal cancer patients in the United Kingdom in 2011–2016. Each predictor in the final model was assigned a corresponding risk score. The sum of risk scores was equivalent to an estimated probability for severe weight loss.ResultsAmong the 351 patients with 6 months follow-up data, 125 (36%) suffered from severe postoperative weight loss. The final prediction model included body mass index at diagnosis, preoperative weight loss, and neoadjuvant therapy. The AUC for the model was 0.78 (95% CI 0.74–0.83). In the validation cohort, the AUC was 0.76. A clinical risk assessment guide was derived from the prediction model.ConclusionsThis prediction model can preoperatively identify individuals with high risk of severe weight loss after esophageal cancer surgery. Intensive nutritional interventions for these patients are recommended.

Predicting stress urinary incontinence during pregnancy: combination of pelvic floor ultrasound parameters and clinical factors.

The aim of this study was to develop and validate a predictive tool that combines pelvic floor ultrasound parameters and clinical factors for stress urinary incontinence during pregnancy. A total of 535 women in the first or second trimester of pregnancy were included for an interview and transperineal ultrasound assessment from two hospitals. Imaging data sets were analyzed offline to assess for bladder neck vertical position, urethra angles (α, β and γ angles), hiatal area and bladder neck funneling. All significant continuous variables at univariable analysis were analyzed by receiver operating characteristics. Three multivariable logistic models were built on clinical factors, and combined with ultrasound parameters. The final predictive model with best performance and fewest variables was selected to establish a nomogram. Internal and external validation of the nomogram was performed by both discrimination represented by C-index and calibration measured by Hosmer-Lemeshow test. A decision curve analysis was conducted to determine the clinical utility of the nomogram. After excluding 14 women with invalid data, 521 women were analyzed. β angle, γ angle and hiatal area had limited predictive value for stress urinary incontinence during pregnancy, with area under curves of 0.558-0.648. The final predictive model included body mass index gain since pregnancy, constipation, previous delivery mode, β angle at rest, and bladder neck funneling. The nomogram based on the final model showed good discrimination with a C-index of 0.789 and satisfactory calibration (p=0.828), both of which were supported by external validation. Decision curve analysis showed that the nomogram was clinically useful. The nomogram incorporating both the pelvic floor ultrasound parameters and clinical factors has been validated to show good discrimination and calibration, and could be an important tool for stress urinary incontinence risk prediction at an early stage of pregnancy.

Insulin Resistance and In Vivo Lipolytic Rate Are Positively Associated with Body Iron Stores in Obese Women

High body iron stores are positively related to insulin resistance in humans, but the underlying mechanisms remain unresolved. Iron stimulates lipolysis in murine adipocytes in vitro, but the influence of iron stores on lipolytic rate in vivo is unknown. Our aim was to determine if body iron stores are associated with lipolytic rate and whole-body insulin sensitivity in obese, pre-menopausal women. We studied 20 subjects with clinically-normal (20-200 ng/mL) plasma [ferritin], an index of body iron stores. Fatty acid rate of appearance into systemic circulation (FA Ra) was assessed by 13C-palmitate isotope dilution, insulin resistance was assessed by hyperinsulinemic-euglycemic clamp, and abdominal subcutaneous adipose tissue protein expression was assessed via immunoblot. [Ferritin] was significantly (p &amp;lt; 0.01), positively correlated with FA Ra (r2 = 0.42), adipose hormone sensitive lipaseser660 phosphorylation (p-HSLser660, a marker of lipolytic activation in adipose tissue; r2 = 0.41), and whole-body insulin resistance (r2 = 0.33). Importantly, [ferritin] remained a significant, independent predictor for these parameters in multiple regression models including body mass index, plasma [adiponectin], and plasma [CRP] as covariates. We stratified subjects into tertiles based on [ferritin] to compare high-normal and low-normal [ferritin] groups (138 ± 30 vs. 40 ± 15 ng/mL). Compared with the low-normal [ferritin] group, the high-normal [ferritin] group had significantly (p &amp;lt; 0.02) higher FA Ra (15.6 ± 5.5 vs. 8.8 ± 2.4 µmol/kg fat mass/min), adipose p-HSLser660 (1.3 ± 0.4 vs. 0.6 ± 0.2 AU) and whole-body insulin resistance (glucose infusion rate 9.2 ± 2.3 vs. 14.3 ± 3.5 mg/kg fat free mass/min). There were no between-group differences in anthropometric characteristics, plasma [adiponectin], or plasma [CRP]. Our findings suggest that iron-mediated activation of adipose lipolysis may be a mechanism linking body iron stores and insulin resistance in obese humans. Disclosure B.J. Ryan: None. D.W. Van Pelt: None. L.M. Guth: None. A. Ludzki: None. R.A. Gioscia-Ryan: None. C. Ahn: None. J.F. Horowitz: None.