Bilateral Atypical Femur Fractures as a Presenting Manifestation of Unrecognized Hypophosphatasia

Introduction: Hypophosphatasia (HPP) is a rare inherited disorder of the ALPL gene which leads to decreased alkaline phosphatase (ALP) activity. Though severe symptoms are seen in childhood, adult HPP is milder and often asymptomatic except for low bone density, thus frequently escapes diagnosis. Hallmarks of adult HPP include decreased ALP, non-traumatic fractures or pseudo-fractures, and premature loss of teeth. Case: A 56 year old previously healthy man presented for evaluation of bilateral atypical femur fractures. He experienced a soft impact slip-and-fall in September 2019 sustaining left mid-shaft displaced femur fracture. Twelve weeks later he stepped oddly while walking and felt pain in right his thigh resulting in fall; x-ray showed a non-traumatic, mid-shaft non-displaced transverse right femur fracture. He had no prior history of fractures, osteoporosis, bisphosphonate use, or any predisposing factors for osteoporosis. On review of laboratory results, it was noted that he had decreased levels of ALP for at least 9 years. After the two recent fractures, his ALP was inappropriately low-normal. Discussion: Review of the literature suggests that initial presenting symptoms of adult HPP are usually bone pain related to pseudo-fractures or premature loss of teeth. Atypical femur fractures (AFF) have been reported in the setting of previously undiagnosed HPP and concurrent bisphosphonate therapy, which is a known independent risk factor for AFF. However, our case is unusual in that bilateral AFF were the only presenting manifestations of an underlying undiagnosed adult onset HPP in an otherwise healthy individual not taking bisphosphonates.https://scholarlycommons.henryford.com/merf2020caserpt/1109/thumbnail.jp

Intra‐Amniotic Administration of HMGB1 Induces Spontaneous Preterm Labor and Birth

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/116331/1/aji12443_am.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/116331/2/aji12443.pd

EHR Visual Overlay Promises to Improve Hypertension Guideline Implementation

Background: Primary care management of essential hypertension (HTN) has become increasingly challenging since recently published guidelines integrate atherosclerotic cardiovascular disease (ASCVD) risk stratification into decision making. Our objective was to measure whether overlay of visualdecision support (VDS) with standard electronic health record (EHR) platform improves guideline-based treatment, and reduces time burden associated with EHR use, in management of essential HTN. Methods: This was a quality improvement project. We interviewed primary care physicians and tasked each with two simulated patient encounters for HTN: (1) using standard EHR to guide treatment, and (2) using VDS to guide treatment. The VDS included graphical blood pressure (BP) trends, target BP with recommended interventions, ASCVD risk score, and information on the patient’s social determinants of health. We assessed whether treatment selection was congruent with guidelines and tracked time physicians consulted the EHR. Results: We evaluated 70 case simulations in total. Use of VDS compared to usual EHR was associated with: higher proportion of correct guideline prescribing (94% vs. 60%, p\u3c0.01), more ASCVD risk determination (100% vs. 23, p\u3c0.01), and more correct BP target identification (97% vs. 60%, p\u3c0.01). Time clinicians spent consulting the EHR fell an average of 121 seconds with use of VDS (p\u3c0.01). On a 10-point scale, clinicians rated the VDS 9.2 vs. 5.9 (p\u3c0.01) for ease of gathering necessary information to treat HTN. Conclusions: The integration video decision support tools to standard EHR can reduce physician time spent per patient encounter, while increasing adherence to guidelines and improving patient outcomes. Further testing in clinical practice is indicated.https://scholarlycommons.henryford.com/merf2019qi/1009/thumbnail.jp

Visual Analytics Dashboard Promises to Improve Hypertension Guideline Implementation

BACKGROUND: Primary care management of hypertension under new guidelines incorporates assessment of cardiovascular disease risk and commonly requires review of electronic health record (EHR) data. Visual analytics can streamline the review of complex data and may lessen the burden clinicians face using the EHR. This study sought to assess the utility of a visual analytics dashboard in addition to EHR in managing hypertension in a primary care setting. METHODS: Primary care physicians within an urban, academic internal medicine clinic were tasked with performing two simulated patient encounters for HTN management: the first using standard EHR, and the second using EHR paired with a visual dashboard. The dashboard included graphical blood pressure trends with guideline-directed targets, calculated ASCVD risk score, and relevant medications. Guideline-appropriate antihypertensive prescribing, correct target blood pressure goal, and total encounter time were assessed. RESULTS: We evaluated 70 case simulations. Use of the dashboard with the EHR compared to use of the EHR alone was associated with greater adherence to prescribing guidelines (95% vs. 62%, p\u3c0.001) and more correct identification of BP target (95% vs. 57%, p\u3c0.01). Total encounter time fell an average of 121 seconds (95% CI 69 - 157 seconds, p\u3c0.001) in encounters that used the dashboard combined with the EHR. CONCLUSIONS: The integration of a hypertension-specific visual analytics dashboard with EHR demonstrates the potential to reduce time and improve hypertension guideline implementation. Further widespread testing in clinical practice is warranted

Predictors of Major Adverse Cardiac Events in Asymptomatic Low Gradient Aortic Stenosis with Preserved Ejection

Background: Patients with low mean pressure gradient (\u3c40mmHg) severe aortic stenosis (Aortic valve area \u3c1.0 cm2) despite preserved ejection fraction (≥50%) have had varying outcomes in prior studies. We sought to evaluate what clinical and echocardiographic parameters would help predict major adverse cardiac events (MACE) in these patients. Methods: A retrospective data review of patients with asymptomatic low gradient aortic stenosis with preserved ejection fraction was performed. Patients with prior valvuloplasty, surgical aortic valve replacement (SAVR), or transcatheter aortic valve replacement (TAVR) were excluded. Comprehensive demographic, clinical, echocardiographic parameters of 287 patients from January 2014 till December 2015 were obtained. Left ventricular global longitudinal strain (GLS) was able to be measured in 94 patients by using speckle tracking imaging. Composite MACE included congestive heart failure, myocardial infarction, SAVR, TAVR, or death were obtained after the initial echocardiogram date. Results: The average age of our studied population is 79.4 years (SD: 13.6). Of them, 67% (n=63) are females. Nineteen patients (20%) have atrial fibrillation, 77 patients have hypertension (82%), and 40 patients (43%) have history of coronary artery disease. Baseline echocardiographic parameters include mean aortic valve area of 0.8 cm2 (SD: 0.2) with indexed aortic valve area of 0.5 cm2/m2 (SD: 0.1). The average of mean pressure gradient is 27.8 mmHg (SD: 12.6) and the average stroke volume index (SVi) is 38.6 mL/m2 (SD: 11.5). Sixty-three patients had normal-flow low-gradient severe aortic stenosis (SVi ≥34mL/m2), while 31 patients had paradoxical low-flow low-gradient aortic stenosis (SVi \u3c34mL/m2). Composite outcomes of MACE developed in 58.5% (n=55) of the studied population (n=94). Independent univariate predictors of MACE were atrial fibrillation (OR, 4.9; 95% CI, 1.3-18.3; p=0.0174). Using a multivariate logistic regression, there were higher odds of having MACE among patients with higher mean gradient across aortic valve (OR, 1.1; 95% CI, 1.0-1.1; p=0.0025), with lower SVi (OR, 0.9; 95% CI, 0.9-1.0; p=0.0061), and with history of atrial fibrillation (OR, 5.3; 95% CI, 1.4-20.6; p=0.0163). Valvuloarterial impedance or GLS did not add any independent predictive value for MACE. Conclusion: Our single center study of low gradient aortic stenosis patients suggests that commonly used indices such as SVi, mean pressure gradient, and history of atrial fibrillation could best help predict MACE. Larger studies are necessary for further assessment