Incidence, risk factors and the healthcare cost of falls postdischarge after elective total hip and total knee replacement surgery: protocol for a prospective observational cohort study

The Feasibility and Performance of Total Hip Replacement Prediction Deep Learning Algorithm with Real World Data

(1) Background: Hip degenerative disorder is a common geriatric disease is the main causes to lead to total hip replacement (THR). The surgical timing of THR is crucial for post-operative recovery. Deep learning (DL) algorithms can be used to detect anomalies in medical images and predict the need for THR. The real world data (RWD) were used to validate the artificial intelligence and DL algorithm in medicine but there was no previous study to prove its function in THR prediction. (2) Methods: We designed a sequential two-stage hip replacement prediction deep learning algorithm to identify the possibility of THR in three months of hip joints by plain pelvic radiography (PXR). We also collected RWD to validate the performance of this algorithm. (3) Results: The RWD totally included 3766 PXRs from 2018 to 2019. The overall accuracy of the algorithm was 0.9633; sensitivity was 0.9450; specificity was 1.000 and the precision was 1.000. The negative predictive value was 0.9009, the false negative rate was 0.0550, and the F1 score was 0.9717. The area under curve was 0.972 with 95% confidence interval from 0.953 to 0.987. (4) Conclusions: In summary, this DL algorithm can provide an accurate and reliable method for detecting hip degeneration and predicting the need for further THR. RWD offered an alternative support of the algorithm and validated its function to save time and cost.

Incidence and Associated Risk Factors for Falls in Older Adults After Elective Total Knee Replacement Surgery: A Prospective Cohort Study

OBJECTIVE

The aim of the study was to determine the incidence and associated risk factors for falls in older adults in the 12 mos after elective, primary total knee replacement surgery.

DESIGN

A prospective observational cohort of older adults undergoing total knee replacement were followed. Baseline measurements included risk factors of history of falls, using a gait aid and number of medications. Falls data were recorded after discharge for 12 mos alongside patient reported outcomes (Oxford Knee Score). Analyses used logistic and negative binomial regression modeling.

RESULTS

There were 267 participants (mean age = 70 [6.7] yrs) enrolled. Participants who fell (n = 102 [40.6%]) reported 200 falls in the 12 mos after surgery. The incidence of falls was 2.4 falls per 1000 patient days in the 12 mos after surgery, with the highest incidence (2.6 falls per 1000 patient days) in month 1. Risk factors for falling were a history of falls (adjusted odds ratio = 2.41, 95% confidence interval = 1.35-4.31) and number of central nervous system acting medications taken before surgery (adjusted odds ratio = 1.66, 95% confidence interval = 1.25-2.21). Using a walking aid at baseline was associated with falls after discharge (adjusted incident rate ratio = 2.38, 95% confidence interval = 1.57-3.60).

CONCLUSIONS

Older adults experience a high incidence of falls after elective total knee replacement. Further research that investigates falls prevention after total knee replacement is required.

Risk Factors for Non-Resilient Outcomes in Older Adults after Total Knee Replacement in the FORCE-TJR Cohort

BACKGROUND

Total knee replacement (TKR) is a common procedure in older adults. Physical resilience may be a useful construct to explain variable outcomes. We sought to define a simple measure of physical resilience and identify risk factors for non-resilient patient outcomes.

METHODS

Secondary analysis of FORCE-TJR cohort study, a prospective registry of total joint replacement. Analysis included 7,239 adults ages 60 or older who underwent TKR between 2011- 2015. Measures included sociodemographic and health factors. Outcomes were categorized as physically resilient versus non-resilient based on the change from baseline to 1-year follow up for three patient-reported outcomes: the physical component summary (PCS), bodily pain (BP), and vitality (VT) from the Short Form-36 (SF-36) subcomponent scores, at pre-op and 1-year post-procedure. Associations were expressed as relative risk of physically non-resilient outcomes using generalized linear regression models, with Poisson distribution and log link.

RESULTS

Age, BMI, and Charlson Comorbidity Index (CCI) were associated with increased risk of physically non-resilient outcomes across PCS, BP, and VT: age, per 5-years for PCS (RR=1.18[1.12-1.23]), BP (RR=1.06[1.01-1.11), and VT (RR=1.09[1.06-1.12]); BMI, per 5 Kg/m 2, for PCS (RR=1.13[1.07-1.19]), BP (RR=1.06[1.00-1.11]), and VT (RR=1.08[1.04-1.11]); and CCI for PCS CCI=1 (RR=1.38[1.20-1.59]), CCI=2-5 (RR=1.59[1.35-1.88]), CCI>=6 (RR=1.55[1.31-1.83]. Household-income >$45,000 associated with lower risk for PCS (RR=0.81[0.70-0.93]), BP (RR=0.80[0.69-0.91],), and VT (RR=0.86[0.78-0.93]).

CONCLUSIONS

We operationalized physical resilience and identified factors predicting resilience after TKR. This approach may aid clinical risk stratification, guide further investigation of causes, and ultimately aid patients through the design of interventions to enhance physical resilience.

Incidence and Associated Risk Factors for Falls in Older Adults Postdischarge Who Undergo Elective Total Hip Replacement Surgery—A Prospective Cohort Study

Background

Hip replacement surgery improves health-related quality of life; however, it has been suggested that falls rates increase after hospital discharge. The aim of the study was to determine the incidence and associated risk factors for falls in older adults in the 12 months after undergoing elective total hip replacement surgery.

Methods

A prospective observational cohort study was conducted. Participants were adults aged 60 years or older who underwent primary elective total hip replacement surgery in a private tertiary hospital in Perth, Australia. Baseline data collected immediately prior to discharge included use of walking aids, medications, and functional level of independence (using Katz and Lawton scales). Falls data were collected for 12 months using calendars and monthly phone calls. Data were analyzed using logistic and negative binomial regression modeling.

Results

Participants’ ([n = 167], 54.4% female) mean age was 71.2 (±6.9) years. There were 51 (31%) participants who used a walking aid prior to surgery. There were 140 falls reported over 12 months by 67 (42%) participants, of which 90 (64.3%) were injurious (n = 9 fractures). The fall rate was 2.6 per 1000 patient-days. Age (adjusted odds ratio 1.10, 95% confidence interval 1.01–1.20) and hospital length of stay (adjusted odds ratio 1.24, 95% confidence interval 1.00–1.54).were significantly associated with sustaining multiple falls.

Conclusions

More than 40% of older adults fell in the 12 months after elective hip replacement surgery although the cohort had low fall risk prior to surgery. Rehabilitation after hip replacement surgery should consider fall prevention.