Background Assessing pediatric patients for insulin resistance is one way to identify those who are at a high risk of developing type 2 diabetes mellitus. The homoeostasis model assessment (HOMA) is a measure of insulin resistance based on fasting blood glucose and insulin levels. Although this measure is widely used in research, cutoff values for pediatric populations have not been established. Objective To assess the validity of HOMA cutoff values used in pediatric studies published in peer-reviewed journals. Methods Studies published from January 2010 to December 2015 were identified through MEDLINE. Initial screening of abstracts was done to select studies that were conducted in pediatric populations and used HOMA to assess insulin resistance. Subsequent full-text review narrowed the list to only those studies that used a specific HOMA score to diagnose insulin resistance. Each study was classified as using a predetermined fixed HOMA cutoff value or a cutoff that was a percentile specific to that population. For studies that used a predetermined cutoff value, the references cited to provide evidence in support of that cutoff were evaluated. Results In the 298 articles analyzed, 51 different HOMA cutoff values were used to classify patients as having insulin resistance. Two hundred fifty-five studies (85.6%) used a predetermined fixed cutoff value, but only 72 (28.2%) of those studies provided a reference that supported its use. One hundred ten studies (43%) that used a fixed cutoff either cited a study that did not mention HOMA or provided no reference at all. Tracing of citation history indicated that the most commonly used cutoff values were ultimately based on studies that did not validate their use for defining insulin resistance. Conclusion Little evidence exists to support HOMA cutoff values commonly used to define insulin resistance in pediatric studies. These findings highlight the importance of validating study design elements when training medical students and novice investigators. Using available data to generate population ranges for HOMA would improve its clinical utility.

West Virginia is a rural state with an aging population that may experience barriers to accessing nutritional and lifestyle counseling. This study examined feasibility of an online personalized nutrition tracking application, Good Measures (GM), with patients at seven health care clinics throughout the state. Fourteen healthcare providers and 64 patients 18 years or older with a Body Mass Index (BMI) greater than or equal to 30 and access to the Internet were recruited for this 12-week feasibility study. Patient participants logged meals and exercise into the GM application via smart phone, tablet, or computer and virtually engaged with a Registered Dietitian Nutritionist (RDN) in one-on-one sessions. The primary endpoint was to examine feasibility of the program by usage of the application and feedback questions regarding the benefits and challenges of the application. Participants were predominately white (92%) and female (76%). Minimal improvements in weight and systolic blood pressure were found. Participant attitude survey data declined from 4-weeks to 12-weeks of the intervention. Interestingly though, patients in a rural clinic had lesser declines in attitudes than peri-urban participants. Qualitative feedback data identified participants predominately had a positive overall feeling toward the approach. Participants expressed favorability of RDN access, the variety of foods, but did give suggestions for in-person meetings and more updating of the application. Implementing a technology approach to nutrition in rural areas of West Virginia using a mobile application with RDN access may be one strategy to address public health issues such as obesity.

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Background Studies have suggested that triglyceride to HDL-cholesterol ratio (TRG/HDL) is a surrogate marker of insulin resistance (IR), but information regarding its use in pediatric patients is limited. Objective This study investigated the ability of TRG/HDL ratio to assess IR in obese and overweight children. Subjects The sample consisted of de-identified electronic medical records of patients aged 10–17 years (n = 223). Materials and methods Logistic regression was performed using TRG/HDL ratio as a predictor of hyperinsulinemia or IR defined using homeostasis model assessment score. Results TRG/HDL ratio had limited ability to predict hyperinsulinemia (AUROC 0.71) or IR (AUROC 0.72). Although females had higher insulin levels, male patients were significantly more likely to have hypertriglyceridemia and impaired fasting glucose. Conclusions TRG/HDL ratio was not adequate for predicting IR in this population. Gender differences in the development of obesity-related metabolic abnormalities may impact the choice of screening studies in pediatric patients.

PurposeThe impact of intrauterine exposure of opioids and other addictive substances on pediatric patients is concerning for health care providers in rural WV.  NAS patients must be identified, screened, and treated during the pediatric years to facilitate improved outcomes. The purpose of this research was to evaluate the ability of rural providers to use EHRs to identify, describe, and monitor aspects of NAS across the pediatric health span.  MethodsThe research team used de-identified data of patients that had the NAS diagnosis from a rural clinic. One hundred fifty-five charts were evaluated.  Demographics, clinical characteristics, and developmental milestone status were extracted from charts. ResultsThere were differences in characteristics across age groups. Reported secondhand smoke was higher among the 0-3 year olds. Normal BMI percentile was highest among 4-5 year olds.  The Ages and Stages Developmental screening was abnormal more in those aged 6-19 years. Foster care was highest among the ages 0-3 years. The 4-12 age groups highest amount of no show visits.  Respiratory illness was the most frequent diagnosis and was highest in the 4-5 age group.  Eye and ear diagnosis were noted as a recurrent diagnosis in the 4-5 year old group. Diagnosis related to mental health were highest in the 6-18 age group.  DiscussionThe EHR can be used to describe and track special populations such as NAS in rural areas. Tagging and tacking patients with NAS can help primary care providers manage care and anticipate age related health care needs. Tracking high risk populations assures that the patient care is maintained. Tracking no show rates assists providers in assuring that patient’s caregivers are compliant in necessary treatments and referrals. Child Protection can also be involved if medical neglect is noted. EHRs are useful in identifying high risk populations such as NAS to facilitate treatments and continuity of care.  DOI:  http://doi.org/10.14574/ojrnhc.v20i2.625