Evaluating the performance of the Charlson Comorbidity Index (CCI) in fracture risk prediction and developing a new Charlson Fracture Index (CFI): a register-based cohort study

One-Year Survival and Postoperative Complications in Older Patients with Intertrochanteric Fractures: Association with Polypharmacy-A Multicenter Retrospective Cohort Study

INTRODUCTION

Polypharmacy is common in older patients and associated with adverse outcomes. However, the association with outcomes in patients with intertrochanteric fractures remains unclear. This study aimed to investigate associations between polypharmacy and 1-year survival (primary outcome) and postoperative complications (secondary outcome), in older patients undergoing surgical treatment for intertrochanteric fractures.

PATIENTS AND METHODS

This multicenter retrospective study initially identified 1864 patients who underwent surgical treatment for intertrochanteric fractures between 2016 and 2020. We excluded those aged < 65 years, with polytrauma, or with Charlson Comorbidity Index (CCI) > 3 or insufficient data. Patients were classified into polypharmacy (≥ 5 medications) and non-polypharmacy (< 5 medications) groups. We performed two analyses: (1) complete case analysis using 1:1 propensity score matching (498 pairs) with variables including age, sex, body mass index (BMI), CCI, residence before admission, fracture type, American Society of Anesthesiologists (ASA) physical status (PS), and Parker Mobility Score, followed by Kaplan-Meier survival analysis with log-rank test and chi-squared test for complications and (2) multivariate Cox regression analysis using multiple imputation (CART method, five imputed datasets) of the eligible cohort (N = 1608), adjusting for the same variables.

RESULTS

In the matched cohort, the 1-year survival rate was significantly lower in the polypharmacy group (91.3%; 95% CI 87.7-93.8) compared with the non-polypharmacy group (94.0%; 95% CI 90.9-96.1; P = 0.027). Postoperative complications showed no significant differences between groups. Cox regression analysis revealed that advanced age, male sex, ASA-PS, and polypharmacy were associated with decreased survival, while higher Parker Mobility Score and normal and higher BMI showed improved survival.

CONCLUSIONS

Polypharmacy was associated with lower postoperative survival in older patients with intertrochanteric fractures and few comorbidities. As a potentially modifiable factor, medication review through multidisciplinary collaboration might contribute to improved outcomes.

An electronic health record (EHR)-based risk calculator can predict fractures comparably to FRAX: a proof-of-concept study

Information in the electronic health record (EHR), such as diagnoses, vital signs, utilization, medications, and laboratory values, may predict fractures well without the need to verbally ascertain risk factors. In our study, as a proof of concept, we developed and internally validated a fracture risk calculator using only information in the EHR.

PURPOSE

Fracture risk calculators, such as the Fracture Risk Assessment Tool, or FRAX, typically lie outside the clinician workflow. Conversely, the electronic health record (EHR) is at the center of the clinical workflow, and many variables in the EHR could predict fractures without having to verbally ascertain FRAX risk factors. We sought to evaluate the utility of EHR variables to predict fractures and, as a proof of concept, to create an EHR-based fracture risk model.

METHODS

Routine clinical data from 24,189 subjects presenting to primary care from 2010 to 2018 was utilized. Major osteoporotic fractures (MOFs) were captured by physician diagnosis codes. Data was split into training (n = 18,141) and test sets (n = 6048). We fit Cox regression models for candidate risk factors in the training set, and then created a global model using a backward stepwise approach. We then applied the model to the test set and compared the discrimination and calibration to FRAX.

RESULTS

We found variables related to vital signs, utilization, diagnoses, medications, and laboratory values to be associated with incident MOF. Our final model included 19 variables, including age, BMI, Parkinson's disease, chronic kidney disease, and albumin levels. When applied to the test set, we found the discrimination (AUC 0.73 vs. 0.70, p = 0.08) and calibration were comparable to FRAX.

CONCLUSION

Routinely collected data in EHR systems can generate adequate fracture predictions without the need to verbally ascertain fracture risk factors. In the future, this could allow for automated fracture prediction at the point of care to improve osteoporosis screening and treatment rates.

Age-adjusted Charlson comorbidity index is associated with the risk of osteoporosis in older fall-prone men: a retrospective cohort study

BACKGROUND

There is growing evidence linking the age-adjusted Charlson comorbidity index (aCCI), an assessment tool for multimorbidity, to fragility fracture and fracture-related postoperative complications. However, the role of multimorbidity in osteoporosis has not yet been thoroughly evaluated. We aimed to investigate the association between aCCI and the risk of osteoporosis in older adults at moderate to high risk of falling.

METHODS

A total of 947 men were included from January 2015 to August 2022 in a hospital in Beijing, China. The aCCI was calculated by counting age and each comorbidity according to their weighted scores, and the participants were stratified into two groups by aCCI: low (aCCI < 5), and high (aCCI ≥5). The Kaplan Meier method was used to assess the cumulative incidence of osteoporosis by different levels of aCCI. The Cox proportional hazards regression model was used to estimate the association of aCCI with the risk of osteoporosis. Receiver operating characteristic (ROC) curve was adapted to assess the performance for aCCI in osteoporosis screening.

RESULTS

At baseline, the mean age of all patients was 75.7 years, the mean BMI was 24.8 kg/m2, and 531 (56.1%) patients had high aCCI while 416 (43.9%) were having low aCCI. During a median follow-up of 6.6 years, 296 participants developed osteoporosis. Kaplan-Meier survival curves showed that participants with high aCCI had significantly higher cumulative incidence of osteoporosis compared with those had low aCCI (log-rank test: P < 0.001). When aCCI was examined as a continuous variable, the multivariable-adjusted model showed that the osteoporosis risk increased by 12.1% (HR = 1.121, 95% CI 1.041-1.206, P = 0.002) as aCCI increased by one unit. When aCCI was changed to a categorical variable, the multivariable-adjusted hazard ratios associated with different levels of aCCI [low (reference group) and high] were 1.00 and 1.557 (95% CI 1.223-1.983) for osteoporosis (P <  0.001), respectively. The aCCI (cutoff ≥5) revealed an area under ROC curve (AUC) of 0.566 (95%CI 0.527-0.605, P = 0.001) in identifying osteoporosis in older fall-prone men, with sensitivity of 64.9% and specificity of 47.9%.

CONCLUSIONS

The current study indicated an association of higher aCCI with an increased risk of osteoporosis among older fall-prone men, supporting the possibility of aCCI as a marker of long-term skeletal-related adverse clinical outcomes.

Validity of Major Osteoporotic Fracture Diagnoses in the Danish National Patient Registry

Objective

To evaluate the validity of diagnosis codes for Major Osteoporotic Fracture (MOF) in the Danish National Patient Registry (NPR) and secondly to evaluate whether the fracture was incident/acute using register-based definitions including date criteria and procedural codes.

Methods

We identified a random sample of 2400 records with a diagnosis code for a MOF in the NPR with dates in the year of 2018. Diagnoses were coded with the 10th revision of the International Classification of Diseases (ICD-10). The sample included 2375 unique fracture patients from the Region of Southern Denmark. Medical records were retrieved for the study population and reviewed by an algorithmic search function and medical doctors to verify the MOF diagnoses. Register-based definitions of incident/acute MOF was evaluated in NPR data by applying date criteria and procedural codes.

Results

The PPV for MOF diagnoses overall was 0.99 (95% CI: 0.98;0.99) and PPV=0.99 for the four individual fracture sites, respectively. Further, analyses of incident/acute fractures applying date criteria, procedural codes and using patients' first contact in the NPR resulted in PPV=0.88 (95% CI: 0.84;0.91) for hip fractures, PPV=0.78 (95% CI: 0.74;0.83) for humerus fractures, PPV=0.78 (95% CI: 0.73;0.83) for clinical vertebral fractures and PPV=0.87 (95% CI: 0.83;0.90) for wrist fractures.

Conclusion

ICD-10 coded MOF diagnoses are valid in the NPR. Furthermore, a set of register-based criteria can be applied to qualify if the MOF fracture was incident/acute. Thus, the NPR is a valuable and reliable data source for epidemiological research on osteoporotic fractures.

General Comorbidity Indicators Contribute to Fracture Risk Independent of FRAX: Registry-Based Cohort Study

CONTEXT

FRAX® estimates 10-year fracture probability from osteoporosis-specific risk factors. Medical comorbidity indicators are associated with fracture risk but whether these are independent from those in FRAX is uncertain.

OBJECTIVE

We hypothesized Johns Hopkins Aggregated Diagnosis Groups (ADG®) score or recent hospitalization number may be independently associated with increased risk for fractures.

METHODS

This retrospective cohort study included women and men age ≥ 40 in the Manitoba BMD Registry (1996-2016) with at least 3 years prior health care data and used linked administrative databases to construct ADG scores along with number of hospitalizations for each individual. Incident Major Osteoporotic Fracture and Hip Fracture was ascertained during average follow-up of 9 years; Cox regression analysis determined the association between increasing ADG score or number of hospitalizations and fractures.

RESULTS

Separately, hospitalizations and ADG score independently increased the hazard ratio for fracture at all levels of comorbidity (hazard range 1.2-1.8, all P < 0.05), irrespective of adjustment for FRAX, BMD, and competing mortality. Taken together, there was still a higher than predicted rate of fracture at all levels of increased comorbidity, independent of FRAX and BMD but attenuated by competing mortality. Using an intervention threshold of major fracture risk >20%, application of the comorbidity hazard ratio multiplier to the patient population FRAX scores would increase the number of treatment candidates from 8.6% to 14.4%.

CONCLUSION

Both complex and simple measures of medical comorbidity may be used to modify FRAX-based risk estimates to capture the increased fracture risk associated with multiple comorbid conditions in older patients.