RESUMO
Purpose: To assess the utility of a validated wearable device (VWD) in examining preoperative and postoperative sleep patterns and how these data compare to patient-reported outcomes (PROs) after rotator cuff repair (RCR) or total shoulder arthroplasty (TSA). Methods: Male and female adult patients undergoing either RCR or TSA were followed up from 34 days preoperatively to 6 weeks postoperatively. Sleep metrics were collected using a VWD in an unsupervised setting. PROs were assessed using the following validated outcome measures: Patient-Reported Outcomes Measurement Information System (PROMIS) Physical Function questionnaire; American Shoulder and Elbow Surgeons self-evaluation questionnaire; visual analog scale assessing pain; and Disabilities of the Arm, Shoulder and Hand questionnaire. Data were analyzed preoperatively and at 2-week intervals postoperatively with χ2 analysis to evaluate device compliance. Sleep metrics and PROs were evaluated at each interval relative to preoperative values within each surgery type with an analysis of variance repeated on time point. The relation between sleep metrics and PROs was assessed with correlation analysis. Results: A total of 57 patients were included, 37 in the RCR group and 20 in the TSA group. The rate of device compliance in the RCR group decreased from 84% at surgery to 46% by 6 weeks postoperatively (P < .001). Similarly, the rate of device compliance in the TSA group decreased from 81% to 52% (P < .001). Deep sleep decreased in RCR patients at 2 to 4 weeks (decrease by 10.99 ± 3.96 minutes, P = .021) and 4 to 6 weeks postoperatively (decrease by 13.37 ± 4.08 minutes, P = .008). TSA patients showed decreased deep sleep at 0 to 2 weeks postoperatively (decrease by 12.91 ± 5.62 minutes, P = .045) and increased rapid eye movement sleep at 2 to 4 weeks postoperatively (increase by 26.91 ± 10.70 minutes, P = .031). Rapid eye movement sleep in the RCR group and total sleep in the TSA group were positively correlated with more favorable PROs (P < .05). Conclusions: VWDs allow for monitoring components of sleep that offer insight into potential targets for improving postoperative fatigue, pain, and overall recovery after shoulder surgery. However, population demographic factors and ease of device use are barriers to optimized patient compliance during data collection. Level of Evidence: Level IV, diagnostic case series.
RESUMO
Fractures are costly to treat and can significantly increase morbidity. Although dual-energy x-ray absorptiometry (DEXA) is used to screen at risk people with low bone mineral density (BMD), not all areas have access to one. We sought to create a readily accessible, inexpensive, high-throughput prediction tool for BMD that may identify people at risk of fracture for further evaluation. Anthropometric and demographic data were collected from 492 volunteers (â275, â217; [44 â± â20] years; Body Mass Index (BMI) = [27.6 â± â6.0] kg/m2) in addition to total body bone mineral content (BMC, kg) and BMD measurements of the spine, pelvis, arms, legs and total body. Multiple-linear-regression with step-wise removal was used to develop a two-step prediction model for BMC followed by BMC. Model selection was determined by the highest adjusted R2, lowest error of estimate, and lowest level of variance inflation (α â= â0.05). Height (HTcm), age (years), sexm=1, f=0, %body fat (%fat), fat free mass (FFMkg), fat mass (FMkg), leg length (LLcm), shoulder width (SHWDTHcm), trunk length (TRNKLcm), and pelvis width (PWDTHcm) were observed to be significant predictors in the following two-step model (p â< â0.05). Step1: BMC (kg) = (0.006 3 × HT) â+ â(-0.002 4 × AGE) â+ â(0.171 2 × SEXm=1, f=0) â+ â(0.031 4 × FFM) â+ â(0.001 × FM) â+ â(0.008 9 × SHWDTH) â+ â(-0.014 5 × TRNKL) â+ â(-0.027 8 × PWDTH) - 0.507 3; R2 â= â0.819, SE â± â0.301. Step2: Total body BMD (g/cm2) = (-0.002 8 × HT) â+ â(-0.043 7 × SEXm=1, f=0) â+ â(0.000 8 × %FAT) â+ â(0.297 0 × BMC) â+ â(-0.002 3 × LL) â+ â(0.002 3 × SHWDTH) â+ â(-0.002 5 × TRNKL) â+ â(-0.011 3 × PWDTH) â+ â1.379; R2 â= â0.89, SE â± â0.054. Similar models were also developed to predict leg, arm, spine, and pelvis BMD (R2 â= â0.796-0.864, p â< â0.05). The equations developed here represent promising tools for identifying individuals with low BMD at risk of fracture who would benefit from further evaluation, especially in the resource or time restricted setting.
RESUMO
Accurate assessment of blood thrombosis and antithrombotic therapy is essential for the management of patients in a variety of clinical conditions, including surgery and on extracorporeal life support. However, current monitoring devices do not measure the effects of hemodynamic forces that contribute significantly to coagulation, platelet function and fibrin formation. This limits the extent to which current assays can predict clotting status in patients. Here, we demonstrate that a biomimetic microfluidic device consisting stenosed and tortuous arteriolar vessels would analyze blood clotting under flow, while requiring a small blood volume. When the device is connected to an inline pressure sensor a clotting time analysis is applied, allowing for the accurate measurement of coagulation, platelets and fibrin content. Furthermore, this device detects a prolonged clotting time in clinical blood samples drawn from pediatric patients on extracorporeal membrane oxygenation receiving anticoagulant therapy. Thus, this tortuosity activated microfluidic device could lead to a more quantitative and rapid assessment of clotting disorders and their treatment.
