Association of Osteoporosis Self-Assessment Tool for Asians (OSTA) Score with Clinical Presentation and Expenditure in Hospitalized Trauma Patients with Femoral Fractures

Prevalence of osteoporosis and associated factors among people aged 50 years and older in the Madhesh province of Nepal: a community-based cross-sectional study

BACKGROUND

The high prevalence of osteoporosis has increased the economic burden on the health system globally. The burden of osteoporosis and its associated factors have not been adequately assessed in community settings in the Nepalese context thus far. Therefore, this study aimed to assess the prevalence of osteoporosis and its associated factors, lifestyle behaviors, and dietary calcium intake.

METHODS

A community-based cross-sectional study was conducted among 395 people aged 50 years and older in the Madhesh Province of Nepal between July 2022 and August 2023. The Osteoporosis Self-assessment Tools for Asians (OSTA) index was used to measure osteoporosis. A structured questionnaire was used to collect sociodemographic information, anthropometric data, lifestyle behavior, daily dietary calcium intake, and frequency of calcium-rich food consumption. A food frequency questionnaire and 24-hour recall methods were used to assess dietary intake. The chi-square test, binary logistic regression and Mann‒Whitney U test were applied to measure the association between predictors and the outcome of interest.

RESULTS

The prevalence of no risk, moderate risk and high risk of osteoporosis were 38.7%, 39%, and 22.3% respectively. The risk of osteoporosis was higher in females (aOR = 5.18, CI: 2.10-12.75, p < 0.001) and increased risk with advancing age (aOR = 32.49, CI: 14.02-75.28, p < 0.001). Similarly, underweight was associated with increased odds of having osteoporosis (aOR = 13.42, CI = 4.58-39.30, p < 0.001). The incidence of osteoporosis was strongly associated with daily calcium intake of 225 mg (100, 386).

CONCLUSION

This study revealed a high prevalence of osteoporosis among people aged 50 years and older due to the combined effect of being underweight and having inadequate calcium intake. Nutritional counselling services encourage people to consume sufficient calcium-rich food and adopt an appropriate lifestyle behaviours to maintain healthy body weight so that osteoporosis and osteoporotic fractures could be prevented. Further research can explore the impact of socioeconomic status and medical comorbidities on a large scale.

Application of Machine Learning Algorithms to Predict Osteoporotic Fractures in Women

BACKGROUND

Predicting the risk of osteoporotic fractures is vital for prevention. Traditional methods such as the Fracture Risk Assessment Tool (FRAX) model use clinical factors. This study examined the predictive power of the FRAX score and machine-learning algorithms trained on FRAX parameters.

METHODS

We analyzed the data of 2,147 female participants from the Ansan cohort study. The FRAX parameters employed in this study included age, sex (female), height and weight, current smoking status, excessive alcohol consumption (>3 units/d of alcohol), and diagnosis of rheumatoid arthritis. Osteoporotic fracture was defined as one or more fractures of the hip, spine, or wrist during a 10-year observation period. Machine-learning algorithms, such as gradient boosting, random forest, decision tree, and logistic regression, were employed to predict osteoporotic fractures with a 70:30 training-to-test set ratio. We evaluated the area under the receiver operating characteristic curve (AUROC) scores to assess and compare the performance of these algorithms with the FRAX score.

RESULTS

Of the 2,147 participants, 3.5% experienced osteoporotic fractures. Those with fractures were older, shorter in height, and had a higher prevalence of rheumatoid arthritis, as well as higher FRAX scores. The AUROC for the FRAX was 0.617. The machine-learning algorithms showed AUROC values of 0.662, 0.652, 0.648, and 0.637 for gradient boosting, logistic regression, decision tree, and random forest, respectively.

CONCLUSION

This study highlighted the immense potential of machine-learning algorithms to improve osteoporotic fracture risk prediction in women when complete FRAX parameter information is unavailable.

Cultural adaptation and validation of the Sinhala version of the Frail Non-disabled tool (FiND)

BACKGROUND

Frailty, a common geriatric syndrome of vulnerability, is associated with a decline in health and function. The most problematic expression of population ageing is associated with weakness, slowing, decreased energy, lower activity and when severe, unintended weight loss. Frailty is not consciously identified in clinical practice and is not widely studied in Sri Lanka. A validated tool for screening frailty in a busy clinical setting is therefore much needed. This study was done as a part of validating the Sinhala version of the Frail Non-Disabled (S-FiND) tool.

METHODS

The FiND tool was translated from English to Sinhala by two translators, blinded to each other. They were combined and translated back to the original language by two separate translators. After verifying the content validity, unambiguity and clarity of items in a focused group discussion, the pre-final version was piloted among 30 volunteers. After assessing the psychometric properties of the pre-final version, the final version was tested among 100 adults older than 65 years from the Colombo South Teaching Hospital. The tool was compared with Fried's frailty phenotype taken as the gold standard.

RESULTS

Data were analysed for the agreement with the reference standard, the Fried Phenotype. The mean (SD) age of subjects was 73.9 (7.8) years. The overall time taken to fill out the questionnaire was 2 min. The agreement (Kappa) between the S-FiND questionnaire and the Fried phenotype was 0.7 (P < 001). The sensitivity and specificity of FiND in detecting frailty were 92% and 74%, respectively. The agreements (Kappa) between the individual items of S-Find: involuntary loss of weight/ more than 4.5 kg over one year, the feeling of effort/ not getting going and level of physical activity, with the Fried phenotype, were 0.28 (p = 0.001), 0.06 (p = 0.045) and 0.339 (p < 0.001). respectively. When subjects were categorized frail and robust based on FiND, frail subjects reported a higher incidence of falls (50%) during the previous 12 months, compared to those robust (13%) (p < 0.001 for Chi stat).

CONCLUSION

The S-FiND is a reliable, valid and well-received tool that can be used in detecting the frailty of non-disabled Sinhala-speaking older adults.

Development and validation of a risk prediction model for osteoporosis in elderly patients with type 2 diabetes mellitus: a retrospective and multicenter study

BACKGROUND

This study aimed to construct a risk prediction model to estimate the odds of osteoporosis (OP) in elderly patients with type 2 diabetes mellitus (T2DM) and evaluate its prediction efficiency.

METHODS

This study included 21,070 elderly patients with T2DM who were hospitalized at six tertiary hospitals in Southwest China between 2012 and 2022. Univariate logistic regression analysis was used to screen for potential influencing factors of OP and least absolute shrinkage. Further, selection operator regression (LASSO) and multivariate logistic regression analyses were performed to select variables for developing a novel predictive model. The area under the receiver operating characteristic curve (AUROC), calibration curve, decision curve analysis (DCA), and clinical impact curve (CIC) were used to evaluate the performance and clinical utility of the model.

RESULTS

The incidence of OP in elderly patients with T2DM was 7.01% (1,476/21,070). Age, sex, hypertension, coronary heart disease, cerebral infarction, hyperlipidemia, and surgical history were the influencing factors. The seven-variable model displayed an AUROC of 0.713 (95% confidence interval [CI]:0.697-0.730) in the training set, 0.716 (95% CI: 0.691-0.740) in the internal validation set, and 0.694 (95% CI: 0.653-0.735) in the external validation set. The optimal decision probability cut-off value was 0.075. The calibration curve (bootstrap = 1,000) showed good calibration. In addition, the DCA and CIC demonstrated good clinical practicality. An operating interface on a webpage ( https://juntaotan.shinyapps.io/osteoporosis/ ) was developed to provide convenient access for users.

CONCLUSIONS

This study constructed a highly accurate model to predict OP in elderly patients with T2DM. This model incorporates demographic characteristics and clinical risk factors and may be easily used to facilitate individualized prediction.

Geriatric Nutritional Risk Index as a Screening Tool to Identify Patients with Malnutrition at a High Risk of In-Hospital Mortality among Elderly Patients with Femoral Fractures-A Retrospective Study in a Level I Trauma Center

BACKGROUND

Malnutrition is frequently underdiagnosed in geriatric patients and is considered to be a contributing factor for worse outcomes during hospitalization. In addition, elderly patients who undergo trauma are often malnourished at the time of incurring fractures. The geriatric nutritional risk index (GNRI), calculated based on the serum albumin level and the ratio of present body weight to ideal body weight, was proposed for the assessment of the nutritional status of elderly patients with various illnesses. This study aimed to investigate whether the GNRI has a prognostic value that links the nutritional status and mortality outcomes of elderly patients who have previously undergone trauma with femoral fractures.

METHODS

From January 1, 2009 to December 31, 2019, a total of 678 elderly patients with femoral fractures were categorized into four nutritional risk groups: a major-risk group (GNRI <82; group 1, n = 127), moderate-risk group (GNRI 82- <92; group 2, n = 179), low-risk group (GNRI 92-98; group 3, n = 123), and no-risk group (GNRI >98; group 4, n = 249). To minimize the confounding effects of sex, age, preexisting comorbidities, and injury severity of patients on outcome measurements, propensity score-matched patient cohorts were created to assess the impact of patients being in different nutritional risk groups on the in-hospital mortality outcomes against the no-risk group.

RESULTS

The patients in groups 1-3 were significantly older and presented a significantly lower body mass index and lower serum albumin levels than those in group 4. Compared with patients in group 4 (3.6%), a significantly higher mortality rate was found in the patients in group 1 (17.3%, p < 0.001), but not in those in group 2 (6.7%) or group 3 (2.4%). The study of propensity score-matched patient cohorts provided similar results; group 1 patients had significantly higher odds of mortality than group 4 patients (odds ratio, 6.3; 95% confidence interval, 1.34-29.37; p = 0.009), but there were no significant differences in mortality risks among patients in groups 2 and 3 compared with those in group 4.

CONCLUSIONS

This preliminary study suggested that the GNRI may be used as a screening tool to identify patients with malnutrition at a high risk of mortality among elderly patients with femoral fractures. A prospective study is needed to validate the suggestion.

The influence of ageing on the incidence and site of trauma femoral fractures: a cross-sectional analysis

BACKGROUND

This study aimed to determine the influence of ageing on the incidence and site of femoral fractures in trauma patients, by taking the sex, body weight, and trauma mechanisms into account.

METHODS

This retrospective study reviewed data from adult trauma patients aged ≥20 years who were admitted into a Level I trauma center, between January 1, 2009 and December 31, 2016. According to the femoral fracture locations, 3859 adult patients with 4011 fracture sites were grouped into five subgroups: proximal type A (n = 1359), proximal type B (n = 1487), proximal type C (n = 59), femoral shaft (n = 640), and distal femur (n = 466) groups. A multivariate logistic regression analysis was applied to identify independent effects of the univariate predictive variables on the occurrence of fracture at a specific site. A two-dimensional plot was presented visually with age and the propensity score accounts for the risk of a fracture at a specific femoral site.

RESULTS

This analysis revealed that older age was an independent variable that could positively predict the occurrence of proximal type A (OR [95%CI]: 1.03 [1.03-1.04], p < 0.001) and B fractures (1.02 [1.01-1.02], p < 0.001), and negatively predict the occurrence of proximal type C (0.96 [0.94-0.98], p < 0.001), shaft (0.95 [0.95-0.96], p < 0.001), and distal fractures (0.98 [0.98-0.99], p < 0.001).

DISCUSSION

Using the propensity scores which account for the risk of a fracture in a specific femoral site, this study revealed that the older patients were at a higher risk of developing proximal type A and type B fractures, while a lower risk of developing fractures in the shaft and distal femur. This incidence of fracture site can largely be explained by age-related factors, including a decrease in bone strength and falling being the most common mechanism of trauma in older patients.

CONCLUSIONS

This study revealed a difference in the involvement of age in the incidence of femoral fracture sites in the trauma patients.

Impact of Sexual Dimorphism on Trauma Patterns and Clinical Outcomes of Patients with a High-Risk Score of the Osteoporosis Self-Assessment Tool for Asians: A Propensity Score-Matched Analysis

The Osteoporosis Self-assessment Tool for Asians (OSTA) is a validated index based on age and weight to predict the risk of osteoporosis in women. This cross-sectional study was designed to evaluate the impact of sexual dimorphism on the trauma patterns and the clinical outcomes of patients with high-risk OSTA scores. Trauma data of patients with high-risk OSTA scores between 1 January 2009 and 31 December 2015 were retrieved from the trauma registry system of a level I trauma center. A total of 2248 patients including 1585 women and 663 men were included in this study. In-hospital mortality was assessed as the primary outcome in the propensity score-matched analyses of the female and male patients, which were created in a 1:1 ratio under the adjustment of potential confounders, including age, co-morbidity, mechanism and injury-severity score (ISS). Female patients with a high-risk OSTA score had significantly lower mortality rates than their male counterparts. Among the propensity score-matched population, female patients had lower odds of having cerebral contusion and pneumothorax, but higher odds of presenting with radial, ulnar and femoral fractures than male patients. In addition, the female patients still had significantly lower odds of mortality (odds ratio (OR), 0.5; 95% confidence interval (CI), 0.29-0.90; p = 0.019) than the male patients. However, no significant differences were noted in the length of stay (LOS) in hospital, intensive-care unit (ICU) admission, and LOS in the ICU between the sexes. Female patients with high-risk OSTA scores showed different injury patterns and significantly lower mortality rates than their male counterparts, even after controlling for potential confounding factors.

Mortality Rate Associated with Admission Hyperglycemia in Traumatic Femoral Fracture Patients Is Greater Than Non-Diabetic Normoglycemic Patients but Not Diabetic Normoglycemic Patients

Background: Admission hyperglycemia is associated with increased morbidity and mortality in trauma patients. However, admission hyperglycemia is not only associated with stress-induced hyperglycemia (SIH) but also with diabetic hyperglycemia (DH); furthermore, patients with normoglycemia may not only have non-diabetic normoglycemia (NDN) but also have a possibility of diabetic normoglycemia (DN), with the diabetes under control. This study aimed to assess the effects of SIH and DH on the mortality outcomes of traumatic femoral fracture patients with NDN and DN. Methods: Admission hyperglycemia was diagnosed as a serum glucose ≥200 mg/dL upon arrival at the emergency department. Diabetes mellitus (DM) was determined by patient history and/or admission HbA1c ≥ 6.5%. DH and SIH were diagnosed by admission hyperglycemia in patients with and without DM. DN and NDN were determined by absence of admission hyperglycemia in patients with and without DM. These patients were allocated into four groups: SIH (n = 75), DH (n = 280), DN (n = 309), and NDN (n = 1326), with detailed information retracted from the Trauma Registry System at a level I trauma center between 1 January 2009, and 31 December 2016. Patients with incomplete registered data were excluded. The adjusted odds ratios (AORs) and 95% confidence intervals (CIs) for mortality were estimated through a stepwise model selection of a multiple regression model that was adjusted by controlling the cofounding variables such age, sex, co-morbidities, and Injury Severity Score. Results: Compared to NDN, a 9.8-fold (95% CI 1.54–62.05; p = 0.016) and a 5.8-fold (95% CI 1.46–22.67; p = 0.012) increase in the adjusted mortality odds ratio of patients with SIH and DH, respectively, were found in this study. In addition, the adjusted odds of mortality between SIH (AOR = 0.3; 95% CI 0.03–2.99; p = 0.302) as well as DH patients (AOR = 0.6; 95% CI 0.20–1.89; p = 0.394) and DN patients had no significant difference. Conclusions: This study demonstrated that SIH and DH patients with traumatic femoral fractures had higher mortality when compared with NDN patients, but not when compared with DN patients, with or without adjustment of the differences in patient’s age, sex, co-morbidities, and injury severity.

Epidemiology of Bone Fracture in Female Trauma Patients Based on Risks of Osteoporosis Assessed using the Osteoporosis Self-Assessment Tool for Asians Score

Background: Osteoporotic fractures are defined as low-impact fractures resulting from low-level trauma. However, the exclusion of high-level trauma fractures may result in underestimation of the contribution of osteoporosis to fractures. In this study, we aimed to investigate the fracture patterns of female trauma patients with various risks of osteoporosis based on the Osteoporosis Self-Assessment Tool for Asians (OSTA) score. Methods: According to the data retrieved from the Trauma Registry System of a Level I trauma center between 1 January 2009 and 31 December 2015, a total of 6707 patients aged ≥40 years and hospitalized for the treatment of traumatic bone fracture were categorized as high-risk (OSTA < -4, n = 1585), medium-risk (-1 ≥ OSTA ≥ -4, n = 1985), and low-risk (OSTA > -1, n = 3137) patients. Two-sided Pearson's, chi-squared, or Fisher's exact tests were used to compare categorical data. Unpaired Student's t-test and Mann-Whitney U-test were used to analyze normally and non-normally distributed continuous data, respectively. Propensity-score matching in a 1:1 ratio was performed with injury mechanisms as adjusted variables to evaluate the effects of OSTA-related grouping on the fracture patterns. Results: High- and medium-risk patients were significantly older, had higher incidences of comorbidity, and were more frequently injured from a fall and bicycle accident than low-risk patients did. Compared to low-risk patients, high- and medium-risk patients had a higher injury severity and mortality. In the propensity-score matched population, the incidence of fractures was only different in the extremity regions between high- and low-risk patients as well as between medium- and low-risk patients. The incidences of femoral fractures were significantly higher in high-risk (odds ratio [OR], 3.4; 95% confidence interval [CI], 2.73-4.24; p < 0.001) and medium-risk patients (OR, 1.4; 95% CI, 1.24-1.54; p < 0.001) than in low-risk patients. In addition, high-risk patients had significantly lower odds of humeral, radial, patellar, and tibial fractures; however, such lower odds were not found in medium- risk than low-risk patients. Conclusions: The fracture patterns of female trauma patients with high- and medium-risk osteoporosis were different from that of low-risk patients exclusively in the extremity region.