Limb loading measurements serve as an objective evaluation of asymmetrical weight bearing in the lower limb. Digital weighing scales (DWSs) could be used in clinical settings for measurement of static limb loading. However, ambiguity exists whether limb loading measurements of DWSs are comparable with a standard tool such as MatScan. A cross-sectional study composed of 33 nondisabled participants was conducted to investigate the reliability, agreement, and validity of DWSs with MatScan in static standing. Amounts of weight distribution and plantar pressure on the individual lower limb were measured using two DWSs (A, B) and MatScan during eyes open (EO) and eyes closed (EC) conditions. The results showed that intra- and interrater reliability (3, 1) were excellent (0.94-0.97) within and between DWS A and B. Bland-Altman plot revealed good agreement between DWS and MatScan in EO and EC conditions. The area under the receiver operating characteristic curve was significant and identified as 0.68 (p = 0.01). The measurements obtained with DWSs are valid and in agreement with MatScan measurements. Hence, DWSs could be used interchangeably with MatScan and could provide clinicians an objective measurement of limb loading suitable for clinical settings.
Matched MeSH terms: Weights and Measures/instrumentation*
Accurate values are a must in medicine. An important parameter in determining the quality of a medical instrument is agreement with a gold standard. Various statistical methods have been used to test for agreement. Some of these methods have been shown to be inappropriate. This can result in misleading conclusions about the validity of an instrument. The Bland-Altman method is the most popular method judging by the many citations of the article proposing this method. However, the number of citations does not necessarily mean that this method has been applied in agreement research. No previous study has been conducted to look into this. This is the first systematic review to identify statistical methods used to test for agreement of medical instruments. The proportion of various statistical methods found in this review will also reflect the proportion of medical instruments that have been validated using those particular methods in current clinical practice.
Matched MeSH terms: Weights and Measures/instrumentation
Monitoring clinical activity at the bedside in the intensive care unit (ICU) can provide useful information to evaluate nursing care and patient recovery. However, it is labour intensive to quantify these activities and there is a need for an automated method to record and quantify these activities. This paper presents an automated system, Clinical Activity Tracking System (CATS), to monitor and evaluate clinical activity at the patient's bedside. The CATS uses four Microsoft Kinect infrared sensors to track bedside nursing interventions. The system was tested in a simulated environment where test candidates performed different motion paths in the detection area. Two metrics, 'Distance' and 'Dwell time', were developed to evaluate interventions or workload in the detection area. Results showed that the system can accurately track the intervention performed by individual or multiple subjects. The results of a 30-day, 24-hour preliminary study in an ICU bed space matched clinical expectations. It was found that the average 24-hour intervention is 22.0minutes/hour. The average intervention during the day time (7am-11pm) is 23.6minutes/hour, 1.4 times higher than 11pm-7am, 16.8minutes/hour. This system provides a unique approach to automatically collect and evaluate nursing interventions that can be used to evaluate patient acuity and workload demand.
Matched MeSH terms: Weights and Measures/instrumentation*