Functional status and prevalence of falls and fractures in population-based sample of postmenopausal women from the RAC-OST-POL Study

Impaired Functional Status Increases Fracture Incidence in 10-year Follow-Up: The Results from RAC-OST-POL Study

INTRODUCTION

The aim of study was to establish the influence of baseline functional status on fracture incidence.

METHODOLOGY

In a prospective 10-years observation in epidemiological sample of postmenopausal women from RAC-OST-POL Study a thesis that affected functional status enhance fracture incidence was verified. At baseline, data were collected in 978 women at mean age 66.48±7.6 years and after 10 years of follow-up 640 subjects at mean age 75.04±6.95 years remained in the study. Functional status at baseline was established using Stand up and Go test (SAG) and Activity of Daily Living (IADL). Afterwards, annually data on fracture incidence were collected by phone interviews.

RESULTS

In the period of observation 190 low-energy fractures in 129 women were noted. The whole group was divided into subgroups: without fracture (n=511), with one fracture (n=91) and those ones who had more than one fracture (n=38). In fractured and unfractured subgroup mean SAG results were 11.36±4.28 and 10.36±2.76, respectively and differed significantly (p<0.01). With increasing number of fractures the SAG time was longer - it was 11.15±4.49 in one fracture subgroup and 11.87±3.73 in multiple fractures subgroup, with both values significantly higher than in no fracture subjects. The mean value of IADL was 23.56±1.60. In 576 (90%) women IADL reached maximal value of 24 points. In the rest of them (n=64) IADL score was between 11 and 23 points. Mean value of IADL in fractured and unfractured subgroup were 23.27±1.97 and 23.64±1.47, respectively and differed significantly (p<0.01).

CONCLUSION

The measures of functional status predict fractures in a prospective observation of representative epidemiological female sample.

Five-year fracture risk assessment in postmenopausal women, using both the POL-RISK calculator and the Garvan nomogram: the Silesia Osteo Active Study

The study project was designed to assess the concordance of clinical results in the assessment of 5-year fracture risk of any fracture, carried out by two methods: the Garvan algorithm and the POL-RISK model. The study group included 389 postmenopausal women of Caucasian race. The concordance of results, obtained by those two models, turned out to be moderate, and the threshold for high fracture risk group was 11% in the POL-RISK model.

PURPOSE

The goal of the study was to evaluate the concordance of results in fracture risk assessments between the Garvan Fracture Risk Calculator and POL-RISK, a new Polish algorithm, and to define an optimal threshold for intervention.

METHODS

The study was a part of the Silesia Osteo Active Study. A group of 389 postmenopausal women, aged 65.2±6.9 years (mean ± SD), was randomly selected from the general population of Zabrze, Poland. All the participants had bone densitometry examination to assess the bone mineral density of the femoral neck. The mean femoral neck T-score was (-0.99) ± 1.05 SD. 6.4% of the women revealed osteoporosis. Five-year risk of any fracture was assessed, using the Garvan and POL-RISK calculators. The performance of each model was evaluated by the area under the receiver operating characteristic curve (AUC).

RESULTS

The median 5-year risk of any fracture was 7% (range 1-54%) in the Garvan model and 8.8% (range 1.1-45.5%) in the POL-RISK algorithm. There was a significant correlation between the results obtained by both methods (r=0.6, p<0.005). For the thresholds, assumed at 8% and 13% (according to recommendation derived from Garvan tool), the rates of concordance of results between both calculators were 76% and 84%, respectively. In ROC analysis for the POL-RISK method, performed with reference to the Garvan method at two different cut-offs, assumed to be high fracture risk indicators (8% and 13%), the AUC values were 0.865 and 0.884, respectively. The optimal threshold for high fracture risk in the POL-RISK algorithm was ≥ 11%, which yielded a sensitivity of 0.94 and a specificity of 0.71.

CONCLUSION

The obtained data demonstrate a moderate concordance of results between the POL-RISK algorithm and the Garvan model, illustrated by low and high fracture risk cut-offs, established in ROC analysis. In addition, the threshold of 11% in the POL-RISK method was the optimal level for "high risk".

Identification of risk factors for falls in postmenopausal women: a systematic review and meta-analysis

The purpose of this study was to identify risk factors for falls in postmenopausal women and provide evidence for the primary prevention of falls in postmenopausal women. The protocol for this meta-analysis is registered with PROSPERO (CRD42020170927). We searched PubMed, the Cochrane Library and EMBASE for observational studies on the risk factors for falls in postmenopausal women. Review Manager 5.3 was used to calculate the relative risk (RR) or weighted mean difference (WMD) of potential risk factors related to falls. STATA 14.0 was used for the quantitative evaluation of publication bias. Eleven studies with 42,429 patients from 7 countries were included. The main risk factors for falls in postmenopausal women were patient sociodemographic risk factors (age: WMD = 0.37, 95% CI 0.07 to 0.68; body weight: WMD = 0.88, 95% CI 0.56 to 1.12; BMI: WMD = 0.34, 95% CI 0.21 to 0.46; exercise: RR = 0.97, 95% CI 0.94 to 0.99; and FES-I: WMD = 6.60, 95% CI 0.72 to 12.47) and medical risk factors (dietary calcium intake: WMD = - 16.91, 95% CI - 25.80 to - 8.01; previous fracture history: RR = 1.21, 95% CI 1.13 to 1.29; previous falls: RR = 2.02, 95% CI 1.91 to 2.14; number of diseases, ˃ 2: RR = 1.17, 95% CI 1.11 to 1.23; and number of reported chronic health disorders: WMD = 0.30, 95% CI 0.10 to 0.49). Knowledge of the many risk factors associated with falls in postmenopausal women can aid in fall prevention. However, we cannot rule out some additional potential risk factors (age at the onset of menopause, years since last menstruation, hormone therapy and BMD) that need further clinical research.

Risk Factors for Fractures Identified in the Algorithm Developed in 5-Year Follow-Up of Postmenopausal Women From RAC-OST-POL Study

The aim of the study was to establish factors with an impact on fracture risk and to develop an algorithm to predict osteoporotic fracture. A total of 978 postmenopausal women from the epidemiological, population-based RAC-OST-POL study with a mean age of 65.7 ± 7.3 years were enrolled. At baseline, bone mineral density at hip and clinical risk factors for fracture were collected. Afterward, each person was asked annually on fracture incidence in the 5-year follow-up. Finally, data for complete 5-year observation were gathered for the group of 802 patients. During the follow-up, 92 osteoporotic fractures occurred in 78 women. The most common fracture site was the forearm (n = 45). The following baseline factors were found as significant for fracture incidence: femoral neck bone mineral density, prior fractures, steroid use, falls within previous 12 months, and height. Fracture risk was predicted by the following formula: Riskoffractureincidence=11+e^{-(-9.899+1.077∗STEROIDS+0.681∗PRIORFALLS+0.611∗PRIORFRACTURES-0.483∗FNTscore+0.042∗HEIGHT)}. In our current longitudinal study, an algorithm predicting fracture occurrence over a period of 5 years was developed. It may find application in daily medical practice.

Relationship between visual status and functional status and the risk of falls in women. The RAC-OST-POL study

INTRODUCTION

Falls in elderly women producing fractures are a public health problem that could be largely preventable. The aim of this study was to determine the effect of visual impairment on functional status, falls and fractures in women.

MATERIAL AND METHODS

We examined 623 women aged ≥ 55 years in order to assess the association between visual status and functional status and the risk of falls and fractures. Distance, near visual acuity, and depth perception were examined. Functional status was assessed using the Instrumental Activities of Daily Living (IADL) and Timed Up and Go (TUG) tests. The history of falls in the last 12 months and prior osteoporotic fractures were recorded.

RESULTS

The mean age of participants was 66.01 ±7.76 years. Distance visual acuity was correlated (r = -0.13, p < 0.0001) with an increased number of falls. The most prognostic fall factor was IADL (Z = 3.19, p < 0.05), which showed a significant association with distance acuity (r = 0.27, p < 0.0001). The TUG test time significantly increased with diminishing visual acuity: 10.6 ±3.1 s for good, 12.8 ±6.1 s for moderate and 15.3 ±8.8 s for poor visual acuity (p < 0.0001, ANOVA 24.4). The IADL also differs significantly (p < 0.0001) in subgroups divided according to visual acuity (23.6 ±1.5, 22.6 ±2.9, 21.2 ±4.8 points, respectively). In multivariate logistic regression on probability of falls including IADL, TUG and visual acuity, IADL was found to be an independent prognostic factor (p = 0.025). The data revealed no association of refractive correction, depth perception, or near visual acuity with fall incidence or history of fractures.

CONCLUSIONS

Visual acuity influences functional status and number of falls in women aged over 55 years.

A validation study of a smartphone application for functional mobility assessment of the elderly

Background

To minimize the reaction time and position judgment error using stopwatch-timed measures, we developed a smartphone application to measure performance in the five-time sit-to-stand (FTSTS) and timed up-and-go (TUG) tests.

Objective

This study aimed to validate this smartphone application by comparing its measurement with a laboratory-based reference condition.

Methods

Thirty-two healthy elderly people were asked to perform the FTSTS and TUG tests in a randomized sequence. During the tests, their performance was concurrently measured by the smartphone application and a force sensor installed in the backrest of a chair. The intraclass correlation coefficient [ICC_(2,1)] and Bland-Altman analysis were used to calculate the measurement consistency and agreement, respectively, between these two methods.

Results

The smartphone application demonstrated excellent measurement consistency with the lab-based reference condition for the FTSTS test [ICC_(2,1) = 0.988] and TUG test [ICC_(2,1) = 0.946]. We observed a positive bias of 0.27 seconds (95% limits of agreement, -1.22 to 1.76 seconds) for the FTSTS test and 0.48 seconds (95% limits of agreement, -1.66 to 2.63 seconds) for the TUG test.

Conclusion

We cross-validated the newly developed smartphone application with the laboratory-based reference condition during the examination of FTSTS and TUG test performance in healthy elderly.

High fracture probability predicts fractures in a 4-year follow-up in women from the RAC-OST-POL study

In 770 postmenopausal women, the fracture incidence during a 4-year follow-up was analyzed in relation to the fracture probability (FRAX risk assessment tool) and risk (Garvan risk calculator) predicted at baseline. Incident fractures occurred in 62 subjects with a higher prevalence in high-risk subgroups. Prior fracture, rheumatoid arthritis, femoral neck T-score and falls increased independent of fracture incidence.

INTRODUCTION

The aim of the study was to analyze the incidence of fractures during a 4-year follow-up in relation to the baseline fracture probability and risk.

METHODS

Enrolled in the study were 770 postmenopausal women with a mean age of 65.7 ± 7.3 years. Bone mineral density (BMD) at the proximal femur, clinical data, and fracture probability using the FRAX tool and risk using the Garvan calculator were determined. Each subject was asked yearly by phone call about the incidence of fracture during the follow-up period.

RESULTS

Of the 770 women, 62 had a fracture during follow-up, and 46 had a major fracture. At baseline, BMD was significantly lower, and fracture probability and fracture risk were significantly higher in women who had a fracture. Among women with a major fracture, the percentage with a high baseline fracture probability (>10 %) was significantly higher than among those without a fracture (p < 0.01). Fracture incidence during follow-up was significantly higher among women with a high baseline fracture probability (12.7 % vs. 5.2 %) and a high fracture risk (9.2 vs. 5.3 %) so that the "fracture-free survival" curves were significantly different (p < 0.05). The number of clinical risk factors noted at baseline was significantly associated with fracture incidence (chi-squared = 20.82, p < 0.01). Prior fracture, rheumatoid arthritis, and femoral neck T-score were identified as significant risk factors for major fractures (for any fractures, the influence of falls was also significant).

CONCLUSIONS

During follow-up, fracture incidence was predicted by baseline fracture probability (FRAX risk assessment tool) and risk (Garvan risk calculator). A number of clinical risk factors and a prior fracture, rheumatoid arthritis, femoral neck T-score, and falls were independently associated with an increased incidence of fractures. [Corrected]

Injury patterns, severity and outcomes among older adults who sustained brain injury following a same level fall: a retrospective analysis

INTRODUCTION

The objectives of this study were to: identify the incidence and types of brain injuries; classify brain injury severity; identify additional injuries; and identify predictors of length of stay, mortality and trauma center admission.

METHODS

This secondary analysis used the NY State Inpatient Databases Healthcare Cost and Utilization Project. Inclusion criteria were: age 65 years and older, admitted to a hospital following a same level fall, primary hospital discharge diagnosis of traumatic brain injury. Descriptive and regression analyses were performed.

RESULTS

3331 patient records were analyzed. Intracranial hemorrhage accounted for 70% of the brain injuries. Younger age, higher household income, insurance status, ethnicity, patient location, increasing number of chronic diseases and diagnoses predicted trauma center admission. Age, trauma center admission, comorbidities, and brain injury severity predicted mortality. Age, race, major surgery, and number of diagnoses predicted length of stay.

DISCUSSION

Brain injuries are common sequelae from falls among older adults. Additional research is needed to understand sociodemographic factors that are associated with trauma center admission.