Predicting in-hospital mortality for dementia patients after hip fracture surgery - A comparison between the Charlson Comorbidity Index (CCI) and the Elixhauser Comorbidity Index

Association between surgical delays for femoral neck fractures and early postoperative complications in young and middle-aged adults: A study based on the national inpatient sample database

BACKGROUND

Femoral neck fractures (FNF) in young and middle-aged adults are primarily caused by high-energy injuries in traffic accidents. Surgical delays often occur due to transportation issues, preoperative evaluations, and economic burdens.

METHODS

A retrospective analysis was conducted on young and middle-aged FNF patients undergoing reduction and internal fixation surgeries from 2010 to 2019 with the use of the National Inpatient Sample database. Logistic regression analysis was used to assess the relationship between surgical delays and complications, and the independent risk factors contributing to delays. Categorical variables were investigated via a chi-square test, while continuous variables including Elixhauser Comorbidity Index (ECI) scores, length of hospital stay (LOS), and total medical costs were analyzed via t-test or rank-sum test.

RESULTS

9,204 patients undergoing reduction and internal fixation surgeries were included. In the delayed group, patients had higher ECI scores, longer hospital stays, higher expenses, and increased inpatient mortality (1.61% vs. 0.28 %, P < 0.0001). Longer surgical delays were associated with higher risks of complications, including femoral head osteonecrosis, internal fixation loosening and breakage, and respiratory complications. Fluid and electrolyte disorders, metastatic cancer, pulmonary circulation disorders, and renal failure were identified as independent risk factors for surgical delays. Except for anemia (OR=2.37, P < 0.0001), no significant differences in early postoperative complications were found between open-reduction and closed-reduction internal fixation (ORIF/CRIF) surgeries.

CONCLUSION

Early surgical intervention, within a 2-days period after injury, seems to be crucial for young adults with FNF. If CRIF is challenging in some cases, ORIF can be another choice.

Validation of the Charlson Comorbidity Index for the prediction of 30-day and 1-year mortality among patients who underwent hip fracture surgery

INTRODUCTION

The aim of our study was to validate the original Charlson Comorbidity Index (1987) (CCI) and adjusted CCI (2011) as a prediction model for 30-day and 1-year mortality after hip fracture surgery. The secondary aim of this study was to verify each variable of the CCI as a factor associated with 30-day and 1-year mortality.

METHODS

A prospective database of two-level II trauma teaching hospitals in the Netherlands was used. The original CCI from 1987 and the adjusted CCI were calculated based on medical history. To validate the original CCI and the adjusted CCI, the CCI was plotted against the observed 30-day and 1-year mortality, and the area under the curve (AUC) was calculated.

RESULTS

A total of 3523 patients were included in this cohort study. The mean of the original CCI in this cohort was 5.1 (SD ± 2.0) and 4.6 (SD ± 1.9) for the adjusted CCI. The AUCs of the prediction models were 0.674 and 0.696 for 30-day mortality for the original and adjusted CCIs, respectively. The AUCs for 1-year mortality were 0.705 and 0.717 for the original and adjusted CCIs, respectively.

CONCLUSIONS

A higher original and adjusted CCI is associated with a higher mortality rate. The AUC was relatively low for 30-day and 1-year mortality for both the original and adjusted CCIs compared to other prediction models for hip fracture patients in our cohort. The CCI is not recommended for the prediction of 30-day and 1-year mortality in hip fracture patients.

Study protocol for the development and validation of a clinical prediction tool to estimate the risk of 1-year mortality among hospitalized patients with dementia

BACKGROUND

Patients with dementia and their caregivers could benefit from advance care planning though may not be having these discussions in a timely manner or at all. A prognostic tool could serve as a prompt to healthcare providers to initiate advance care planning among patients and their caregivers, which could increase the receipt of care that is concordant with their goals. Existing prognostic tools have limitations. We seek to develop and validate a clinical prediction tool to estimate the risk of 1-year mortality among hospitalized patients with dementia.

METHODS

The derivation cohort will include approximately 235,000 patients with dementia, who were admitted to hospital in Ontario from April 1st, 2009, to December 31st, 2017. Predictor variables will be fully prespecified based on a literature review of etiological studies and existing prognostic tools, and on subject-matter expertise; they will be categorized as follows: sociodemographic factors, comorbidities, previous interventions, functional status, nutritional status, admission information, previous health care utilization. Data-driven selection of predictors will be avoided. Continuous predictors will be modelled as restricted cubic splines. The outcome variable will be mortality within 1 year of admission, which will be modelled as a binary variable, such that a logistic regression model will be estimated. Predictor and outcome variables will be derived from linked population-level healthcare administrative databases. The validation cohort will comprise about 63,000 dementia patients, who were admitted to hospital in Ontario from January 1st, 2018, to March 31st, 2019. Model performance, measured by predictive accuracy, discrimination, and calibration, will be assessed using internal (temporal) validation. Calibration will be evaluated in the total validation cohort and in subgroups of importance to clinicians and policymakers. The final model will be based on the full cohort.

DISCUSSION

We seek to develop and validate a clinical prediction tool to estimate the risk of 1-year mortality among hospitalized patients with dementia. The model would be integrated into the electronic medical records of hospitals to automatically output 1-year mortality risk upon hospitalization. The tool could serve as a trigger for advance care planning and inform access to specialist palliative care services with prognosis-based eligibility criteria. Before implementation, the tool will require external validation and study of its potential impact on clinical decision-making and patient outcomes.

TRIAL REGISTRATION

NCT05371782.

Association of polypharmacy scores with the long-term survival of patients with intact aortoiliac aneurysms and indication for repair

OBJECTIVE/BACKGROUND

Our study analyzed the relationship between two polypharmacy scores (addition of chronic prescribed drugs [ACPDs] and Rx-Risk Comorbidity Index) and survival in patients with an intact abdominal aortic and/or common iliac aneurysm (AAA).

METHODS

Consecutive retrospective, single-center cohort of patients attended for an intact AAA with indication for repair from 2008 to 2021. Demographic data, Charlson Comorbidity Index, AAA treatment, ACPD, and Rx-Risk polypharmacy scores were recorded at baseline. Main outcomes were the 5-year and long-term survival rates. The statistical analysis included Cox regression, area under the curve, and continuous net reclassification index.

RESULTS

A total of 424 patients with AAA were evaluated (median age: 76 years; 92.2% male, median Charlson index 2), of whom 314 (74.1%) underwent intervention (80% endovascular and 20% open) and 110 (25.9%) did not. During follow-up (mean 4.6 years), 245 patients (57.8%) died, with 1-month, 1-year, and 5-year survival rates of 98.1%, 86.3%, and 52.7%, respectively. ACPD and Rx-Risk indices (median [interquartile range]: 6 [4-9] and 3 [0-5], respectively) were significantly and linearly associated (P < .001) with survival, with the best cutoff points at 5 and 0, respectively. An ACPD >5 (patients with >5 chronically prescribed drugs at baseline) and an Rx-Risk >0 were associated with a 45.2% (P = .038) and 102% (P = .002) increase in 5-year mortality, respectively, after adjustment for age, sex, Charlson index, and type of AAA treatment. Both polypharmacy indices improved significantly the discriminative power of the Charlson Comorbidity Index in predicting survival.

CONCLUSIONS

Both ACPD and Rx-Risk polypharmacy scores are independently related to survival among patients with an intact AAA and indication for repair. Their behavior is similar, so the simple ACPD >5 appears to be sufficient to identify patients with lower survival rates.

Predictive Value of Machine Learning Models in Postoperative Mortality of Older Adults Patients with Hip Fracture: A Systematic Review and Meta-analysis

BACKGROUND

Some researchers have used machine learning to predict mortality in old patients with hip fracture, but its application value lacks an evidence-based basis. Hence, we conducted this meta-analysis to explore the predictive accuracy of machine learning for mortality in old patients with hip fracture.

METHODS

We systematically retrieved PubMed, Cochrane, Embase, and Web of Science for relevant studies published before July 15, 2022. The PROBAST assessment tool was used to assess the risk of bias in the included studies. A random-effects model was used for the meta-analysis of C-index, whereas a bivariate mixed-effects model was used for the meta-analysis of sensitivity and specificity. The meta-analysis was performed on R and Stata.

RESULTS

Eighteen studies were included, involving 8 machine learning models and 398,422 old patients undergoing hip joint surgery, of whom 60,457 died. According to the meta-analysis, the pooled C-index for machine learning models was 0.762 (95% CI: 0.691 ∼ 0.833) in the training set and 0.838 (95% CI: 0.783 ∼ 0.892) in the validation set, which is better than the C-index of the main clinical scale (Nottingham Hip Fracture Score), that is, 0.702 (95% CI: 0.681 ∼ 0.723). Among different machine learning models, ANN and Bayesian belief network had the best predictive performance.

CONCLUSION

Machine learning models are more accurate in predicting mortality in old patients after hip joint surgery than current mainstream clinical scoring systems. Subsequent research could focus on updating clinical scoring systems and improving their predictive performance by relying on machine learning models.

Mortality rate and its determinants among people with dementia receiving home healthcare: a nationwide cohort study

People with dementia (PwD) who receive home healthcare (HHC) may have distressing symptoms, complex care needs and high mortality rates. However, there are few studies investigating the determinants of mortality in HHC recipients. To identify end-of-life care needs and tailor individualized care goals, we aim to explore the mortality rate and its determinants among PwD receiving HHC. We conducted a retrospective cohort study using a Taiwanese national population database. People with new dementia diagnosis in 2007-2016 who received HHC were included. We calculated the accumulative mortality rate and applied Poisson regression model to estimate the risk of mortality for each variable (adjusted risk ratios, aRR) with a 95% confidence interval (CI). We included 95,831 PwD and 57,036 (59.5%) of them died during the follow-up period (30.5% died in the first-year). Among comorbidities, cirrhosis was associated with the highest mortality risks (aRR 1.65, 95% CI 1.49-1.83). Among HHC-related factors, higher visit frequency of HHC (> 2 versus ≦1 times/month, aRR 3.52, 95% CI 3.39-3.66) and higher level of resource utilization group (RUG, RUG 4 versus 1, aRR = 1.38, 95% CI 1.25-1.51) were risk factor of mortality risk. Meanwhile, HHC provided by physician and nurse was related to reduced mortality risk (aRR 0.79, 95% CI 0.77-0.81) compared to those provided by nurse only. Anticipatory care planning and timely end-of life care should be integrated in light of the high mortality rate among PwD receiving HHC. Determinants associated with increased mortality risk facilitate the identification of high risk group and tailoring the appropriate care goals. Trial registration number: ClinicalTrials.gov Identifier is NCT04250103 which has been registered on 31st January 2020.

Prediction of 3-Year Survival in Patients with Cognitive Impairment Based on Demographics, Neuropsychological Data, and Comorbidities: A Prospective Cohort Study

OBJECTIVES

Based on readily available demographic data, neuropsychological assessment results, and comorbidity data, we aimed to develop and validate a 3-year survival prediction model for patients with cognitive impairment.

METHODS

In this prospective cohort study, 616 patients with cognitive impairment were included. Demographic information, data on comorbidities, and scores of the Mini-Mental State Examination (MMSE), Instrumental Activities of Daily Living (IADL) scale, and Neuropsychiatric Inventory Questionnaire were collected. Survival status was determined via telephone interviews and further verified in the official death register in the third year. A 7:3 ratio was used to divide patients into the training and validation sets. Variables with statistical significance (p < 0.05) in the single-factor analysis were incorporated into the binary logistic regression model. A nomogram was constructed according to multivariate analysis and validated.

RESULTS

The final cohort included 587 patients, of whom 525 (89.44%) survived and 62 (10.56%) died. Younger age, higher MMSE score, lower IADL score, absence of disinhibition, and Charlson comorbidity index score ≤ 1 were all associated with 3-year survival. These predictors yielded good discrimination with C-indices of 0.80 (0.73-0.87) and 0.85 (0.77-0.94) in the training and validation cohorts, respectively. According to the Hosmer-Lemeshow test results, neither cohort displayed any statistical significance, and calibration curves displayed a good match between predictions and results.

CONCLUSIONS

Our study provided further insight into the factors contributing to the survival of patients with cognitive impairment.

CLINICAL IMPLICATIONS

Our model showed good accuracy and discrimination ability, and it can be used at community hospitals or primary care facilities that lack sophisticated equipment.

Comorbidity among inpatients with dementia: a preliminary cross-sectional study in West China

OBJECTIVE

To investigate comorbidities among hospitalized patients with dementia.

METHOD

Data were extracted from the discharge records in our hospital. Comorbidities based on ICD-10 were selected from the Charlson Comorbidity Index (CCI) and Elixhauser Comorbidity Index (ECI). The distributions of these comorbidities were described in dementia inpatients and age- and sex-matched nondementia controls, as well as in inpatients with Alzheimer's disease and vascular dementia. A logistic regression model was applied to identify dementia-specific morbid conditions.

RESULTS

A total of 3355 patients with dementia were included, with a majority of 1503 (44.8%) having Alzheimer's disease, 395 (11.8%) with vascular dementia, and 441 (13.1%) with mixed dementia. The mean number of comorbidities was 3.8 in dementia patients (vs. 2.9 in controls). The most prevalent comorbidities in inpatients with dementia compared with those without dementia were cerebral vascular disease (73.0% vs. 35.9%), hypertension (62.8% vs. 56.2%), and peripheral vascular disease (53.7% vs. 31.2%). Comorbidities associated with dementia included epilepsy (OR 4.8, 95% CI 3.5-6.8), cerebral vascular disease (OR 4.1, 95% CI 3.7-4.5), depression (OR 4.0, 95% CI 3.2-5.0), uncomplicated diabetes (OR 1.5, 95% CI 1.4-1.7), peripheral vascular disease (OR 1.8, 95% CI 1.6-2.0), rheumatoid arthritis collagen vascular disease (OR 1.7, 95% CI 1.3-2.3), and anemia (OR 1.2, 95% CI 1.04-1.3). Some comorbidities suggested a protective effect against dementia. They were hypertension (OR 0.8, 95% CI 0.7-0.9), COPD (OR 0.6, 95% CI 0.5-0.6), and solid tumor without metastasis (OR 0.4, 95% CI 0.3-0.4). Vascular dementia has more cardiovascular and cerebrovascular comorbidities than Alzheimer's disease.

CONCLUSION

Patients with dementia coexisted with more comorbidities than those without dementia. Comorbidities (esp. cardio-cerebral vascular risks) in patients with vascular dementia were more than those in patients with AD. Specifically, vascular and circulatory diseases, epilepsy, diabetes and depression increased the risk of dementia.

Modeling acute care utilization: practical implications for insomnia patients

Machine learning models can help improve health care services. However, they need to be practical to gain wide-adoption. In this study, we investigate the practical utility of different data modalities and cohort segmentation strategies when designing models for emergency department (ED) and inpatient hospital (IH) visits. The data modalities include socio-demographics, diagnosis and medications. Segmentation compares a cohort of insomnia patients to a cohort of general non-insomnia patients under varying age and disease severity criteria. Transfer testing between the two cohorts is introduced to demonstrate that an insomnia-specific model is not necessary when predicting future ED visits, but may have merit when predicting IH visits especially for patients with an insomnia diagnosis. The results also indicate that using both diagnosis and medications as a source of data does not generally improve model performance and may increase its overhead. Based on these findings, the proposed evaluation methodologies are recommended to ascertain the utility of disease-specific models in addition to the traditional intra-cohort testing.

Efficacy of Neutrophil-to-Lymphocyte Ratio for Cancer-Specific Survival in Elderly Patients with Localized Colon Cancer: A Single Center Propensity Score-Matched Analysis

Purpose

The prognostic value of neutrophil-to-lymphocyte ratio (NLR) has been studied for colorectal cancer. Elderly patients in general tend to have comorbidities and decreased organ function that potentially influence the NLR score. The aim of this study was to investigate the relationship between NLR and cancer-specific survival in elderly patients with colon cancer, using a propensity score-matched analysis.

Patients and Methods

A total of 203 patients aged over 75 years who underwent curative resection for colon cancer and were diagnosed pathologically with stage II/III disease were eligible for entry to the study. Patients were divided into two groups according to NLR score: NLR-High (NLR≥4.5) group (NLR-H, n=60) and NLR-Low (NLR<4.5) group (NLR-L, n=143). After propensity score matching, 57 patients in each group were matched.

Results

Before matching, Charlson comorbidity index was significantly higher in the NLR-H group (4 vs 2, p<0.001). After matching, all factors were similar between the groups. The median follow-up period was 43 months (range, 1-160 months). Five-year relapse-free-survival (69.8% vs 87.3%, p=0.030) and cancer-specific survival (83.0% vs 96.0%, p=0.042) were significantly lower in the NLR-H group.

Conclusion

NLR appears to be a cancer-specific prognostic marker in elderly patients with colon cancer.

Age-adjusted Charlson comorbidity index predicts postoperative mortality in elderly patients with hip fracture: A prospective cohort

Background

This study aimed to evaluate the clinical association between the age-adjusted Charlson comorbidity index (aCCI) and postoperative mortality in elderly patients.

Materials and methods

Elderly patients with hip fractures were screened from January 2015 to September 2019. After demographic and clinical characteristics were collected, linear and non-linear multivariate Cox regression models were used to identify the association between the aCCI and mortality. All analyses were performed using EmpowerStats and R software.

Results

A total of 2,657 patients were included in the study, and the mean follow-up duration was of 38.97 months. The mean aCCI score was 4.24 ± 1.09, and 977 (34.14%) died of all-cause mortality. The fully-adjusted linear multivariate Cox regression models showed the aCCI to be associated with mortality [hazard ratio (HR) = 1.31, 95% confidence interval (CI):1.21-1.41, P < 0.0001]. Patients in Q2 showed greater mortality (HR = 1.60, 95% CI: 1.23-2.09; P = 0.0005) than those in Q1; patients in Q3 showed greater mortality (HR = 2.18, 95% CI: 1.66-2.87; P < 0.001) than those in Q1. In addition, the P-value for the trend also showed a linear association in the three models (P < 0.0001). In the sensitivity analysis, propensity score matching was used, and the results were stable.

Conclusion

The mortality risk of hip fractures increased by 31% when the aCCI increased by one unit. aCCI score was shown to be a good predictor of three-year mortality following hip fracture.

Clinical trial registration

http://www.chictr.org.cn/showproj.aspx?proj=152919, identifier ChiCTR2200057323.

Comparison of Prognostic Value of 10 Biochemical Indices at Admission for Prediction Postoperative Myocardial Injury and Hospital Mortality in Patients with Osteoporotic Hip Fracture

Aim: To evaluate the prognostic impact at admission of 10 biochemical indices for prediction postoperative myocardial injury (PMI) and/or hospital death in hip fracture (HF) patients. Methods: In 1273 consecutive patients with HF (mean age 82.9 ± 8.7 years, 73.5% women), clinical and laboratory parameters were collected prospectively, and outcomes were recorded. Multiple logistic regression and receiver-operating characteristic analyses (the area under the curve, AUC) were preformed, the number needed to predict (NNP) outcome was calculated. Results: Age ≥ 80 years and IHD were the most prominent clinical factors associated with both PMI (with cardiac troponin I rise) and in-hospital death. PMI occurred in 555 (43.6%) patients and contributed to 80.3% (49/61) of all deaths (mortality rate 8.8% vs. 1.9% in non-PMI patients). The most accurate biochemical predictive markers were parathyroid hormone > 6.8 pmol/L, urea > 7.5 mmol/L, 25(OH)vitamin D < 25 nmol/L, albumin < 33 g/L, and ratios gamma-glutamyl transferase (GGT) to alanine aminotransferase > 2.5, urea/albumin ≥ 2.0 and GGT/albumin ≥ 7.0; the AUC for developing PMI ranged between 0.782 and 0.742 (NNP: 1.84−2.13), the AUC for fatal outcome ranged from 0.803 to 0.722, (NNP: 3.77−9.52). Conclusions: In HF patients, easily accessible biochemical indices at admission substantially improve prediction of hospital outcomes, especially in the aged >80 years with IHD.

Femoral and Lateral Femoral Cutaneous Nerve Block as Anesthesia for High-Risk Intertrochanteric Fracture Repair Patients

Introduction. Intertrochanteric fracture (IF) is a common injury among the elderly. Due to significant comorbidities, anesthesia for IF repair may be challenging. The authors propose femoral nerve block together with a lateral femoral cutaneous nerve block and sedation as an anesthetic technique for most severe cases of IF with contraindications to spinal anesthesia. Methods. In total, 61 patients were enrolled prospectively in a study, 19 received general anesthesia (GA group), 22 spinal anesthesia (SA group), and 20 nerve blocks with sedation (PNB group). Results. Groups were comparable in terms of age, gender, independence, and several comorbidities: diabetes, obesity, underweight, cardiovascular, and cerebrovascular incidents in the past, dementia, chronic obstructive pulmonary disease, and frailty. Heart failure (p = 0.033), hemoglobin < 10 g/dL (p = 0.001) and eGFR < 30 mL/min (p = 0.039) were more frequent in PNB group. PNB group had higher American Society of Anesthesiologists (ASA) (p < 0.001), Nottingham Hip Fracture Score (NHFS) (p < 0.001), and Charlson Comorbidity Index (CCI) (p = 0.002) scales scores, and lower probability of 10-year survival according to CCI (p = 0.012). GA group had more frequent active malignancy (p = 0.041). GA and PNB groups had a higher frequency of hemostasis disorder (p < 0.001). Surgery was completed under the scheduled anesthesia technique. Survival, frequency of cardio and cerebrovascular incidents after surgery, loss of independence, and postoperative delirium were comparable between groups, as well as the length of postoperative stay. Conclusions. Surgical repair of intertrochanteric fracture with intramedullary nailing system among elderly, frail, and sick patients can be conducted under peripheral nerve block. FNB and LFCNB in the combination is a viable option for IT fracture repair.

Charlson Comorbidity Index: A Critical Review of Clinimetric Properties

The present critical review was conducted to evaluate the clinimetric properties of the Charlson Comorbidity Index (CCI), an assessment tool designed specifically to predict long-term mortality, with regard to its reliability, concurrent validity, sensitivity, incremental and predictive validity. The original version of the CCI has been adapted for use with different sources of data, ICD-9 and ICD-10 codes. The inter-rater reliability of the CCI was found to be excellent, with extremely high agreement between self-report and medical charts. The CCI has also been shown either to have concurrent validity with a number of other prognostic scales or to result in concordant predictions. Importantly, the clinimetric sensitivity of the CCI has been demonstrated in a variety of medical conditions, with stepwise increases in the CCI associated with stepwise increases in mortality. The CCI is also characterized by the clinimetric property of incremental validity, whereby adding the CCI to other measures increases the overall predictive accuracy. It has been shown to predict long-term mortality in different clinical populations, including medical, surgical, intensive care unit (ICU), trauma, and cancer patients. It may also predict in-hospital mortality, although in some instances, such as ICU or trauma patients, the CCI did not perform as well as other instruments designed specifically for that purpose. The CCI thus appears to be clinically useful not only to provide a valid assessment of the patient's unique clinical situation, but also to demarcate major diagnostic and prognostic differences among subgroups of patients sharing the same medical diagnosis.

The factors associated with nosocomial infection in elderly hip fracture patients: gender, age, and comorbidity

PURPOSE

This is a retrospective case-control study to ascertain the factors influencing nosocomial infection (NI) in elderly patients with hip fractures.

METHODS

A total of 80,174 patients (≥ 60 years) who suffered hip fractures between 2006 and 2017 were identified through a national inquiry of 94 hospitals. The patients were divided into an NI group and control group according to the occurrence or lack of occurrence of NI within 48 hours after surgery, respectively. Age, gender, hip fracture pattern, whether to operate, surgical treatments, and comorbidities were recorded as variables.

RESULTS

A total of 9806 elderly hip fracture patients (60 years) were included, 1977 of whom were patients diagnosed with NI. The control group consisted of randomly drawn cases from the 9806 patients from different hospitals with a rate of one NI patient: four patients without NI. Patient gender, age, and in particular the number of comorbidities were associated with occurrence of NI. Using regression models to predict infection outcomes based on the number of comorbidities had an area under the curve (AUC) of 0.714, while using the Charlson comorbidity index (CCI) yielded a smaller value of 0.694. The most common comorbidities of this elderly cohort were chronic respiratory disease, hypertension, diabetes mellitus, cerebrovascular disease, and coronary heart disease.

CONCLUSIONS

Older age, male gender, and greater number of comorbidities were found to be associated with the occurrence of NI. In particular, the number of comorbidities was the most accurate predictor of NI occurrence, and when used to build a regression model, it had greater predictive capability than CCI to predict NI in elderly hip fracture patients. Additionally, the common diseases of the elderly should be primarily considered when investigating the relationship between comorbidities and NI in older patients.

Treatment-Emergent Co-Morbidities and Survival in Patients With Metastatic Castration-Resistant Prostate Cancer Receiving Abiraterone or Enzalutamide

Secondary hormone therapy, abiraterone and enzalutamide, has improved outcomes for metastatic castration-resistant prostate cancer (mCRPC) and prolonged patients' lives significantly. Various studies have compared the cancer-related outcomes, adverse effects, and drug-induced comorbidities in patients with mCRPC who are treated with abiraterone or enzalutamide. However, few studies have explored associations between survival and comorbidities or comprehensive analyzed newly developed comorbidities during and after secondary hormone therapy. We attempted to clarify whether the Charlson comorbidity index (CCI) overall or itemized is predictive for overall survival, and we compared newly developed comorbidities between abiraterone and enzalutamide groups. We extracted data about expenses and comorbidities for patients who have mCRPC, received abiraterone and enzalutamide and met pre-examination operation criteria between September 2016 and December 2017 from the Taiwan National Health Insurance database. A total of 1153 patients with mCRPC who received abiraterone (n = 782) or enzalutamide (n = 371) with or without previous chemotherapy were included. We used the propensity score to match confounding factors, including age, pre-existing comorbidities, and precipitating factors for comorbidity (e.g., hypertension, hyperlipidemia), to eliminate selection bias in the comparison of newly developed comorbidities. Cox regression analysis was used for overall survival. We found that enzalutamide is superior to abiraterone with regard to overall survival. Our study revealed that there is no statistically significant difference in development of new comorbidities between abiraterone and enzalutamide group. Moreover, the CCI score, rather than any single item of the CCI, was a statistically significant predictor for overall survival.

Secular trends of patients hospitalized for major osteoporotic fractures based on a national claims database

There was a reduction in the hospitalization rate for major osteoporotic fractures. As per our analysis, hospitalization for site-specific fractures showed a declining trend for hip and vertebral fractures for both the sexes. However, an increasing trend was noted in women regarding hospitalization for forearm fracture.

PURPOSE

Major osteoporotic fractures (MOFs) constitute a large proportion of the total expenditures for public healthcare. Knowing the secular trends of MOF will allow for more efficient use of healthcare resources, but such data are insufficient for the current population of Taiwan. Therefore, we investigated the epidemiological data of MOF hospitalization from adults 50 years of age or older in Taiwan during the period 2000-2015.

METHODS

The data analyzed were acquired from the Taiwan National Health Insurance Research Database (NHIRD) entries between 2000 and 2015. All study subjects were 50 years of age or older at the time of admission and diagnosed as having MOF.

RESULTS

A general decline was observed in the incidence rate (IR) of MOF hospitalization for the whole population, from 74.52 per 10,000 person-years (PYs) in 2000 to 55.19 in 2015. Females aged ≥65 years had the highest rates of hospitalization for MOF among the subgroups analyzed. Apart from the wrist fracture hospitalization rates in both sexes, which remained steady, all other site-specific fracture hospitalization rates exponentially increased with age. Among men, the IRs of all MOF hospitalization were steady, except for a slight decrease in hip and vertebral fracture hospitalizations. In women, hip and vertebral fracture hospitalization rates gradually decreased, humerus and wrist fracture hospitalization remained steady, and forearm fracture hospitalization increased.

CONCLUSIONS

Hospitalization rates of MOF decreased. The trend of site-specific fracture hospitalization analysis showed that hip and vertebral fractures decreased for both sexes. However, an increasing trend in forearm fracture hospitalization was noticed among females.

Predicting 30-Day and 180-Day Mortality in Elderly Proximal Hip Fracture Patients: Evaluation of 4 Risk Prediction Scores at a Level I Trauma Center

This study evaluated the use of risk prediction models in estimating short- and mid-term mortality following proximal hip fracture in an elderly Austrian population. Data from 1101 patients who sustained a proximal hip fracture were retrospectively analyzed and applied to four models of interest: Physiological and Operative Severity Score for the enUmeration of Mortality and Morbidity (POSSUM), Charlson Comorbidity Index, Portsmouth-POSSUM and the American College of Surgeons National Surgical Quality Improvement Program (ACS-NSQIP^®) Risk Score. The performance of these models according to the risk prediction of short- and mid-term mortality was assessed with a receiver operating characteristic curve (ROC). The median age of participants was 83 years, and 69% were women. Six point one percent of patients were deceased by 30 days and 15.2% by 180 days postoperatively. There was no significant difference between the models; the ACS-NSQIP had the largest area under the receiver operating characteristic curve for within 30-day and 180-day mortality. Age, male gender, and hemoglobin (Hb) levels at admission <12.0 g/dL were identified as significant risk factors associated with a shorter time to death at 30 and 180 days postoperative (p < 0.001). Among the four scores, the ACS-NSQIP score could be best-suited clinically and showed the highest discriminative performance, although it was not specifically designed for the hip fracture population.