Saint Francis University

About: Saint Francis University is a education organization based out in Loretto, Pennsylvania, United States. It is known for research contribution in the topics: Population & Osteoblast. The organization has 1694 authors who have published 2038 publications receiving 87149 citations.

Objective moderate-to-vigorous physical activity in 1064 patients with COPD after stratification for gender, FEV1 and BMI

Abstract: Background: Physical inactivity in COPD is associated with poor outcomes. Therefore, it is important to understand the determinants of moderate-to-vigorous physical activity (MVPA) in COPD. We aimed to assess the mean level of MVPA after stratification for gender, forced expiratory volume in the first second (FEV1) and body-mass index (BMI). Methods: In 1064 COPD subjects (716 men; age: 67±8 years; BMI: 27±6 kg• m-2; FEV1: 50±21 % predicted) from 14 centers, MVPA time was assessed using the SenseWear Armband activity monitor for ≥4 days. Gender, FEV1 and BMI were used for stratification. Results: In total, 6300 days with MVPA data were obtained, with a median (IQR) MVPA time of 27 (11-59) min• day-1. 47% of the subjects had a MVPA time ≥30 min• day-1. Men had a higher MVPA time than women (29 (12-63) versus 24 (9-52) min• day-1, respectively; p=0.002). Figure 1 presents the mean time in MVPA after stratification for GOLD classes and BMI in men (A) and women (B). ![Figure][1] Conclusions: This multicenter study showed that MVPA time generally is BMI-dependent (higher BMI results in lower MVPA) and GOLD-dependent (higher GOLD results in lower MVPA) in men and women with COPD. [1]: pending:yes

Using machine learning for prediction of poor clinical outcomes in adult patients hospitalized with COVID-19

Abstract: Background: As the ongoing COVID-19 pandemic develops, there is a need for prediction rules to guide clinical decisions Previous reports have identified risk factors using statistical inference model The primary goal of these models is to characterize the relationship between variables and outcomes, not to make predictions In contrast, the primary purpose of machine learning is obtaining a model that can make repeatable predictions The objective of this study is to develop decision rules tailored to our patient population to predict ICU admissions and death in patients with COVID-19 Methods: We used a de-identified dataset of hospitalized adults with COVID- 19 admitted to our community hospital between March 2020 and June 2020 We used a Random Forest algorithm to build the prediction models for ICU admissions and death Random Forest is one of the most powerful machine learning algorithms;it leverages the power of multiple decision trees, randomly created, for making decisions Results: 313 patients were included;237 patients were used to train each model, 26 were used for testing, and 50 for validation A total of 16 variables, selected according to their availability in the Emergency Department, were fit into the models For the survival model, the combination of age >57 years, the presence of altered mental status, procalcitonin ≥3 0 ng/mL, a respiratory rate >22, and a blood urea nitrogen >32 mg/dL resulted in a decision rule with an accuracy of 98 7% in the training model, 73 1% in the testing model, and 70% in the validation model (Table 1, Figure 1) For the ICU admission model, the combination of age 591 IU/L, and a lactic acid >1 5 mmol/L resulted in a decision rule with an accuracy of 99 6% in the training model, 80 8% in the testing model, and 82% in the validation model (Table 2, Figure 2) Conclusion: We created decision rules using machine learning to predict ICU admission or death in patients with COVID-19 Although there are variables previously described with statistical inference, these decision rules are customized to our patient population;furthermore, we can continue to train the models fitting more data with new patients to create even more accurate prediction rules (Table Presented)

Vulvar pain after spondylosyndesis procedure: a presentation of 2 cases.

Abstract: Vulvar pain can be a difficult and frustrating problem for patients and practitioners. Often, no specific etiology can be determined for these symptoms. Treatment can be long and difficult as well.Spondylosyndesis is a common surgical procedure where the vertebrae are fused to decrease motion. There are several indications for this procedure. We report 2 patients who developed vulvar pain postoperatively after a spondylosyndesis procedure. Neither patient had a history of vulvar pain before their procedure. Of note, both patients had had a previous spondylosyndesis procedure in the past.Damage to lumbar nerves during spondylosyndesis procedures may precipitate vulvar pain in some patients.

Overuse injuries of the foot: imaging presentations of common pathologies.

Abstract: Overuse injuries of the foot are common, resulting in frequent visits to the primary care physician and orthopaedic surgeon. Radiologic workup often ensues. Morton's neuroma, plantar fasciitis and Haglund's syndrome are three such entities with classic MRI appearances.