Preoperative Point-of-Care Ultrasound to Identify Frailty and Predict Postoperative Outcomes: A Diagnostic Accuracy Study

2021 ◽  
Author(s):  
Cecilia Canales ◽  
Einat Mazor ◽  
Heidi Coy ◽  
Tristan R. Grogan ◽  
Victor Duval ◽  
...  

Background Frailty is increasingly being recognized as a public health issue, straining healthcare resources and increasing costs to care for these patients. Frailty is the decline in physical and cognitive reserves leading to increased vulnerability to stressors such as surgery or disease states. The goal of this pilot diagnostic accuracy study was to identify whether point-of-care ultrasound measurements of the quadriceps and rectus femoris muscles can be used to discriminate between frail and not-frail patients and predict postoperative outcomes. This study hypothesized that ultrasound could discriminate between frail and not-frail patients before surgery. Methods Preoperative ultrasound measurements of the quadriceps and rectus femoris were obtained in patients with previous computed tomography scans. Using the computed tomography scans, psoas muscle area was measured in all patients for comparative purposes. Frailty was identified using the Fried phenotype assessment. Postoperative outcomes included unplanned intensive care unit admission, delirium, intensive care unit length of stay, hospital length of stay, unplanned skilled nursing facility admission, rehospitalization, falls within 30 days, and all-cause 30-day and 1-yr mortality. Results A total of 32 patients and 20 healthy volunteers were included. Frailty was identified in 18 of the 32 patients. Receiver operating characteristic curve analysis showed that quadriceps depth and psoas muscle area are able to identify frailty (area under the curve–receiver operating characteristic, 0.80 [95% CI, 0.64 to 0.97] and 0.88 [95% CI, 0.76 to 1.00], respectively), whereas the cross-sectional area of the rectus femoris is less promising (area under the curve–receiver operating characteristic, 0.70 [95% CI, 0.49 to 0.91]). Quadriceps depth was also associated with unplanned postoperative skilled nursing facility discharge disposition (area under the curve 0.81 [95% CI, 0.61 to 1.00]) and delirium (area under the curve 0.89 [95% CI, 0.77 to 1.00]). Conclusions Similar to computed tomography measurements of psoas muscle area, preoperative ultrasound measurements of quadriceps depth shows promise in discriminating between frail and not-frail patients before surgery. It was also associated with skilled nursing facility admission and postoperative delirium. Editor’s Perspective What We Already Know about This Topic What This Article Tells Us That Is New

1999 ◽  
Vol 27 (2) ◽  
pp. 203-203
Author(s):  
Kendra Carlson

The Supreme Court of California held, in Delaney v. Baker, 82 Cal. Rptr. 2d 610 (1999), that the heightened remedies available under the Elder Abuse Act (Act), Cal. Welf. & Inst. Code, §§ 15657,15657.2 (West 1998), apply to health care providers who engage in reckless neglect of an elder adult. The court interpreted two sections of the Act: (1) section 15657, which provides for enhanced remedies for reckless neglect; and (2) section 15657.2, which limits recovery for actions based on “professional negligence.” The court held that reckless neglect is distinct from professional negligence and therefore the restrictions on remedies against health care providers for professional negligence are inapplicable.Kay Delaney sued Meadowood, a skilled nursing facility (SNF), after a resident, her mother, died. Evidence at trial indicated that Rose Wallien, the decedent, was left lying in her own urine and feces for extended periods of time and had stage I11 and IV pressure sores on her ankles, feet, and buttocks at the time of her death.


2020 ◽  
Author(s):  
Wenhao Zhang ◽  
Ramin Ramezani ◽  
Zhuoer Xie ◽  
John Shen ◽  
David Elashoff ◽  
...  

BACKGROUND The availability of low cost ubiquitous wearable sensors has enabled researchers, in recent years, to collect a large volume of data in various domains including healthcare. The goal has been to harness wearables to further investigate human activity, physiology and functional patterns. As such, on-body sensors have been primarily used in healthcare domain to help predict adverse outcomes such as hospitalizations or fall, thereby enabling clinicians to develop better intervention guidelines and personalized models of care to prevent harmful outcomes. In the previous studies [9,10] and the patent application [11], we introduced a generic framework (Sensing At-Risk Population) that draws on the classification of human movements using a 3-axial accelerometer and extraction of indoor localization using BLE beacons, in concert. This work is to address the longitudinal analyses of a particular cohort using the introduced framework in a skilled nursing facility. OBJECTIVE (a) To observe longitudinal changes of physical activity and indoor localization features of rehabilitation-dwelling patients, (b) to assess if such changes can be used at early stages during the rehabilitation period to discriminate between patients that will be re-hospitalized versus the ones that will be discharged to a community setting and (c) to investigate if the sensor based longitudinal changes can imitate patients changes captured by therapist assessments over the course of rehabilitation. METHODS Pearson correlation was used to compare occupational therapy (OT) and physical therapy (PT) assessments with sensor-based features. Generalized Linear Mixed Model was used to find associations between functional measures with sensor based features. RESULTS Energy intensity at therapy room was positively associated with transfer general (β=0.22;SE=0.08;p<.05). Similarly, sitting energy intensity showed positive association with transfer general (β=0.16;SE=0.07;p<.05). Laying down energy intensity was negatively associated with hygiene grooming (β=-0.27;SE=0.14;p<.05). The interaction of sitting energy intensity with time (β=-0.13;SE=.06;p<.05) was associated with toileting general. Dressing lower body was strongly correlated with overall energy intensity (r = 0.66), standing energy intensity (r = 0.61), and laying down energy intensity (r = 0.72) on the first clinical assessment session. CONCLUSIONS This study demonstrates that a combination of indoor localization and physical activity tracking produces a series of features, a subset of which can provide crucial information on the storyline of daily and longitudinal activity patterns of rehabilitation-dwelling patients.


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