Reliability of videotaped observational gait analysis in patients with orthopedic impairments

BACKGROUND: In clinical practice, visual gait observation is often used to determine gait disorders and to evaluate treatment. Several reliability studies on observational gait analysis have been described in the literature and generally showed moderate reliability. However, patients with orthopedic disorders have received little attention. The objective of this study is to determine the reliability levels of visual observation of gait in patients with orthopedic disorders. METHODS: The gait of thirty patients referred to a physical therapist for gait treatment was videotaped. Ten raters, 4 experienced, 4 inexperienced and 2 experts, individually evaluated these videotaped gait patterns of the patients twice, by using a structured gait analysis form. Reliability levels were established by calculating the Intraclass Correlation Coefficient (ICC), using a two-way random design and based on absolute agreement. RESULTS: The inter-rater reliability among experienced raters (ICC = 0.42; 95%CI: 0.38–0.46) was comparable to that of the inexperienced raters (ICC = 0.40; 95%CI: 0.36–0.44). The expert raters reached a higher inter-rater reliability level (ICC = 0.54; 95%CI: 0.48–0.60). The average intra-rater reliability of the experienced raters was 0.63 (ICCs ranging from 0.57 to 0.70). The inexperienced raters reached an average intra-rater reliability of 0.57 (ICCs ranging from 0.52 to 0.62). The two expert raters attained ICC values of 0.70 and 0.74 respectively. CONCLUSION: Structured visual gait observation by use of a gait analysis form as described in this study was found to be moderately reliable. Clinical experience appears to increase the reliability of visual gait analysis

Newport Transect 02, Image 10

This still image was captured from a video transect in Newport, Oregon. Researchers are able to use this image to quantify relative abundance and diversity of benthic (i.e. bottom-dwelling) organisms.https://digitalcommons.linfield.edu/biol_transects_photos/1019/thumbnail.jp

Is etoricoxib effective in preventing heterotopic ossification after primary total hip arthroplasty?

Item does not contain fulltextPURPOSE: Heterotopic ossification is a common complication after total hip arthroplasty. Non-steroidal anti-inflammatory drugs (NSAIDs) are known to prevent heterotopic ossifications effectively, however gastrointestinal complaints are reported frequently. In this study, we investigated whether etoricoxib, a selective cyclo-oxygenase-2 (COX-2) inhibitor that produces fewer gastrointestinal side effects, is an effective alternative for the prevention of heterotopic ossification. METHODS: We investigated the effectiveness of oral etoricoxib 90 mg for seven days in a prospective two-stage study design for phase-2 clinical trials in a small sample of patients (n = 42). A cemented primary total hip arthroplasty was implanted for osteoarthritis. Six months after surgery, heterotopic ossification was determined on anteroposterior pelvic radiographs using the Brooker classification. RESULTS: No heterotopic ossification was found in 62 % of the patients that took etoricoxib; 31 % of the patients had Brooker grade 1 and 7 % Brooker grade 2 ossification. CONCLUSIONS: Etoricoxib seems effective in preventing heterotopic ossification after total hip arthroplasty. This finding further supports the use of COX-2 inhibitors for the prevention of heterotopic ossification following total hip arthroplasty

Risk factors for adverse outcomes during mechanical ventilation of 1152 COVID-19 patients: a multicenter machine learning study with highly granular data from the Dutch Data Warehouse

Background: The identification of risk factors for adverse outcomes and prolonged intensive care unit (ICU) stay in COVID-19 patients is essential for prognostication, determining treatment intensity, and resource allocation. Previous studies have determined risk factors on admission only, and included a limited number of predictors. Therefore, using data from the highly granular and multicenter Dutch Data Warehouse, we developed machine learning models to identify risk factors for ICU mortality, ventilator-free days and ICU-free days during the course of invasive mechanical ventilation (IMV) in COVID-19 patients. Methods: The DDW is a growing electronic health record database of critically ill COVID-19 patients in the Netherlands. All adult ICU patients on IMV were eligible for inclusion. Transfers, patients admitted for less than 24 h, and patients still admitted at time of data extraction were excluded. Predictors were selected based on the literature, and included medication dosage and fluid balance. Multiple algorithms were trained and validated on up to three sets of observations per patient on day 1, 7, and 14 using fivefold nested cross-validation, keeping observations from an individual patient in the same split. Results: A total of 1152 patients were included in the model. XGBoost models performed best for all outcomes and were used to calculate predictor importance. Using Shapley additive explanations (SHAP), age was the most important demographic risk factor for the outcomes upon start of IMV and throughout its course. The relative probability of death across age values is visualized in Partial Dependence Plots (PDPs), with an increase starting at 54 years. Besides age, acidaemia, low P/F-ratios and high driving pressures demonstrated a higher probability of death. The PDP for driving pressure showed a relative probability increase starting at 12 cmH2O. Conclusion: Age is the most important demographic risk factor of ICU mortality, ICU-free days and ventilator-free days throughout the course of invasive mechanical ventilation in critically ill COVID-19 patients. pH, P/F ratio, and driving pressure should be monitored closely over the course of mechanical ventilation as risk factors predictive of these outcomes