Loss of Ambulatory Level and Activities of Daily Living at 1 Year Following Hip Fracture: Can We Identify Patients at Risk?

Can we predict 1-year functional outcomes and mortality following hip fracture in middle-aged and geriatric patients at time of admission?

This study's purpose is to determine if patients treated for hip fracture at highest risk for poor functional outcomes, shorter time to death, and death within 1-year can be predicted at the time of admission. We hypothesized that the Score for Trauma Triage in the Geriatric and Middle-Aged (STTGMA) tool can be used to predict risk of these variables. Between February 2019-July 2020, 544 patients ≥ 55-years-old were treated for hip fracture [AO/OTA 31A/B, 32A/C]. Each patient's demographics, functional status, and injury details were used to calculate their respective risk (STTGMA) score at time of admission. Patients were divided into risk quartiles by STTGMA score. Patients were contacted by phone to complete EuroQol-5 Dimension (EQ5D-3L) questionnaires on functional status. Comparative analyses were conducted on outcomes and EQ5D-3L questionnaire results. 439 patients (80.7%) had at least 1-year follow-up. 82 patients (18.7%) died within 1-year after hospitalization. Mean STTGMA score was 1.67% ± 4.49%. The highest-risk cohort experienced a 42x (p < 0.01) and 2.5x (p = 0.01) increased rate of 1-year mortality compared to the minimal- and low-risk groups respectively. The highest-risk cohort had the shortest time to death (p = 0.015). The highest-risk cohort had the lowest EQ5D index (p < 0.01) and VAS scores (p < 0.01) along with the highest rate of 30 day readmission (p < 0.01) and the longest length of stay (p < 0.01). The STTGMA tool provides important prognostic information for middle-aged and geriatric hip fracture patients that can help modulate care levels. This information is useful when counseling patients, their families, and caregivers on expected outcomes.

Association between Caregivers' Fear of Post-fracture Patients Falling and a Decline in Patients' Activities

Objectives

To evaluate caregivers' fear of post-fracture patients falling, we previously developed the Caregivers' Fear of Falling Index (CFFI). In this study, we investigated the relationship between patient performance in activities of daily living (ADLs) and CFFI.

Methods

We surveyed 55 patients receiving home-visit rehabilitation after fall-related fracture and their primary caregivers. Participants (patient and caregiver pair) were divided into two groups based on patient performance in basic ADLs (BADLs) and instrumental ADLs (IADLs). ROC analysis was conducted to assess the usefulness of CFFI and Falls Efficacy Scale-International (FES-I) in determining declines in performance in BADLs and IADLs. Multivariate logistic regression analysis was performed to examine the association between CFFI and declining performance in BADLs and IADLs.

Results

ROC analysis showed that CFFI exhibited a higher accuracy than FES-I (AUC: 0.73 in BADLs, 0.77 in IADLs) as an indicator of reduced ADL performance. Multivariate logistic analysis adjusted for age, sex, and physical function showed that CFFI was associated with a decline in patients' performance in IADLs (odds ratio, 0.92; 95% confidence interval, 0.85-0.99).

Conclusions

Caregivers' fear of post-fracture patients falling was associated with a decline in patients' performance in IADLs. These findings may serve as a guide for supporting caregivers of post-fracture patients.

Diagnostic Accuracy of a Trauma Risk Assessment Tool Among Geriatric Patients With Crash Injuries

ABSTRACT

The Score for Trauma Triage in the Geriatric and Middle-Aged (STTGMA) is a risk stratification tool. We evaluated the STTGMA's accuracy in predicting 30-day mortality and the odds of unfavorable clinical trajectories among crash-related trauma patients. This retrospective cohort study (n = 912) pooled adults aged 55 years and older from a single institutional trauma database. The data were split into training and test data sets (70:30 ratio) for the receiver operating curve analysis and internal validation, respectively. The outcome variables were 30-day mortality and measures of clinical trajectory. The predictor variable was the high-energy STTGMA score (STTGMAHE). We adjusted for the American Society of Anesthesiologists Physical Status. Using the training and test data sets, STTGMAHE exhibited 82% (95% CI: 65.5-98.3) and 96% (90.7-100.0) accuracies in predicting 30-day mortality, respectively. The STTGMA risk categories significantly stratified the proportions of orthopedic trauma patients who required intensive care unit (ICU) admissions, major and minor complications, and the length of stay (LOS). The odds of ICU admissions, major and minor complications, and the median difference in the LOS increased across the risk categories in a dose-response pattern. STTGMAHE exhibited an excellent level of accuracy in identifying middle-aged and geriatric trauma patients at risk of 30-day mortality and unfavorable clinical trajectories.

Pre-fracture ambulation capacity, Charlson comorbidity index, and dementia as predictors of functional impairment after bipolar hemiarthroplasty for unstable intertrochanteric fracture. A retrospective analysis in 158 octogenarian patients

Background: the primary purpose of this study was to assess the ambulatory capacity 12 months after surgery in patients that underwent bipolar hemiarthroplasty (BH) due to unstable intertrochanteric fractures (UITF). Secondly, to identify which preoperative variables influenced these modifications.

Methods

We retrospectively analyzed a consecutive series of patients older than 80 years with UITF treated with BH between 2010 and 2019. Ambulatory capacity was assessed before surgery, at 3 and 12 months postoperatively, using Koval's classification and the modified Harris Hip Score (mHHS). The registered variables were: gender, age, osteoporosis, Charlson comorbidity index (CCI), ASA classification, body mass index (BMI), and dementia. The identification of variables that impaired postoperative functionality was performed by uni- and multivariate analysis.

Results

158 patients were included with a median age of 87 (range 80-102) years and a follow-up of 29.2 (range 12-56) months. The 1-year overall ambulatory capacity impairment was 28.5% and significantly affected pre-fracture community walkers (p = 0.001). A CCI >4 (OR 2.72; p = 0.044), dementia (OR 14.13; p = 0.0001), and a Koval 2-3 (OR 12.84; p = 0.001) were identified as risk factors for this impairment.

Conclusion

Ambulation impairment at one year was 28.5%. The predictive characteristics found in this study help to identify patients with a greater risk of ambulation impairment and to focus rehabilitation plans to reduce this impact.

Assessment of gait and posture characteristics using a smartphone wearable system for persons with osteoporosis with and without falls

We used smartphone technology to differentiate the gait characteristics of older adults with osteoporosis with falls from those without falls. We assessed gait mannerism and obtained activities of daily living (ADLs) with wearable sensor systems (smartphones and inertial measurement units [IMUs]) to identify fall-risk characteristics. We recruited 49 persons with osteoporosis: 14 who had a fall within a year before recruitment and 35 without falls. IMU sensor signals were sampled at 50 Hz using a customized smartphone app (Lockhart Monitor) attached at the pelvic region. Longitudinal data was collected using MoveMonitor+ (DynaPort) IMU over three consecutive days. Given the close association between serum calcium, albumin, PTH, Vitamin D, and musculoskeletal health, we compared these markers in individuals with history of falls as compared to nonfallers. For the biochemical parameters fall group had significantly lower calcium (P = 0.01*) and albumin (P = 0.05*) and higher parathyroid hormone levels (P = 0.002**) than nonfall group. In addition, persons with falls had higher sway area (P = 0.031*), lower dynamic stability (P < 0.001***), gait velocity (P = 0.012*), and were less able to perform ADLs (P = 0.002**). Thus, persons with osteoporosis with a history of falls can be differentiated by using dynamic real-time measurements that can be easily captured by a smartphone app, thus avoiding traditional postural sway and gait measures that require individuals to be tested in a laboratory setting.