Effect of sarcopenia and frailty on outcomes among patients with brain metastases.

PURPOSE: Sarcopenia and frailty have been associated with increased mortality and duration of hospitalization in cancer. However, data investigating these effects in patients with brain metastases remain limited. This study aimed to investigate the effects of sarcopenia and frailty on clinical outcomes in patients with surgically treated brain metastases. METHODS: Patients who underwent surgical resection of brain metastases from 2011 to 2019 were included. Psoas cross-sectional area and temporalis thickness were measured by two independent radiologists (Cronbach's alpha > 0.98). Frailty was assessed using the Clinical Frailty Scale (CFS) pre-operatively and post-operatively. Overall mortality, recurrence, and duration of hospitalization were collected. Cox regression was performed for mortality and recurrence, and multiple linear regression for duration of hospitalization. RESULTS: 145 patients were included, with median age 60.0 years and 52.4% female. Psoas cross-sectional area was an independent risk factor for overall mortality (HR = 2.68, 95% CI 1.64-4.38, p < 0.001) and recurrence (HR = 2.31, 95% CI 1.14-4.65, p = 0.020), while post-operative CFS was an independent risk factor for overall mortality (HR = 1.88, 95% CI 1.14-3.09, p = 0.013). Post-operative CFS (ß = 15.69, 95% CI 7.67-23.72, p < 0.001) and increase in CFS (ß = 11.71, 95% CI 3.91-19.51, p = 0.004) were independently associated with increased duration of hospitalization. CONCLUSION: In patients with surgically treated brain metastases, psoas cross-sectional area was an independent risk factor for mortality and recurrence, while post-operative CFS was an independent risk factor for mortality. Post-operative frailty and increase in CFS significantly increased duration of hospitalization. Measurement of psoas cross-sectional area and CFS may aid in risk stratification of surgical candidates for brain metastases.

Cost-Effective Analysis of Dual-Energy Computed Tomography for the Diagnosis of Occult Hip Fractures Among Older Adults.

OBJECTIVE: Early and accurate diagnosis of hip fractures minimizes morbidity and mortality. Although current guidelines favor magnetic resonance imaging (MRI) for the diagnosis of occult hip fractures, a new technology called dual-energy computed tomography (DECT) seems an effective alternative. This article investigates a potentially cost-effective strategy for the diagnosis of occult hip fractures in older adults in Singapore. METHODS: A decision tree model was developed to compare costs from a payer's perspective and outcomes in terms of quality-adjusted life-years (QALYs) of different imaging strategies for diagnosing occult hip fracture, comparing MRI with DECT supplementing single-energy computed tomography (SECT) and SECT alone. Model inputs were obtained from local sources where available. Sensitivity analyses are performed to test the robustness of the results. RESULTS: The MRI strategy was dominated by the DECT strategy, whereas DECT supplementing SECT provided 0.30 more QALYs at an incremental cost of SGD106.41 with an incremental cost-effectiveness ratio of SGD352.52 per QALY relative to SECT alone. DECT seemed a cost-effective strategy at a willingness-to-pay threshold of SGD50 000 per QALY. CONCLUSION: DECT supplementing SECT is a cost-effective imaging strategy to diagnose occult hip fractures among older adults in Singapore and should be included in clinical pathways to expedite timely treatment and considered for reimbursement schemes.

Effect of psoas muscle index on early postoperative outcomes in surgically treated spinal tumours in an Asian population.

BACKGROUND: Sarcopenia has been purported to be a pre-operative risk factor that affects patient outcomes in oncological surgery, but no study as of yet has investigated the effect of sarcopenia in patients with spinal tumours. Psoas muscle measurements, including the psoas muscle index (PMI), are an objective way to determine sarcopenia. OBJECTIVES: We investigated if PMI could predict post-operative outcomes (length of hospital stay and post-operative complications) in surgically treated spinal tumour patients in a multi-ethnic Asian population. METHODS: We conducted a retrospective cohort study of patients with spinal tumours who underwent surgery at our tertiary institution from January 2016 to January 2020. PMI was measured on T2-weighted MRI sequences, at the middle of the L3 vertebral body and measurements were collected by 2 independent raters. The primary outcome was length of hospital stay (LOS), and the secondary outcome was post-operative complications. ROC curve was used to attain the cut-off value for PMI and the population was then stratified into 2 groups; sarcopenic if PMI was less than 1.22 and non-sarcopenic if the PMI value was more than or equal to 1.22. Multivariable linear regression was used for LOS, while multivariate logistic regression was used for complications. RESULTS: 57 patients were included with a mean length of stay of 17.8 days (SD 25.1) and the total number of patients with complications were 20 (35.1 %). Mean LOS was significantly higher in the sarcopenic group compared to the non-sarcopenic group. Univariate analysis confirmed the association of lower psoas muscle index corresponding with longer lengths of stay and this was corroborated in a multivariable linear regression model. There were no significant associations between PMI and postoperative complications. CONCLUSIONS: Lower PMI values were significantly associated with a longer LOS. PMI may be warranted for risk stratifying Asian spinal tumour patients undergoing surgery.

Prognostication of Outcomes in Spontaneous Intracerebral Hemorrhage: A Propensity Score-Matched Analysis with Support Vector Machine.

OBJECTIVE: The role of surgery in spontaneous intracerebral hemorrhage (SICH) remains controversial. We aimed to use explainable machine learning (ML) combined with propensity-score matching to investigate the effects of surgery and identify subgroups of patients with SICH who may benefit from surgery in an interpretable fashion. METHODS: We conducted a retrospective study of a cohort of 282 patients aged ≥21 years with SICH. ML models were developed to separately predict for surgery and surgical evacuation. SHapley Additive exPlanations (SHAP) values were calculated to interpret the predictions made by ML models. Propensity-score matching was performed to estimate the effect of surgery and surgical evacuation on 90-day poor functional outcomes (PFO). RESULTS: Ninety-two patients (32.6%) underwent surgery, and 57 patients (20.2%) underwent surgical evacuation. A total of 177 patients (62.8%) had 90-day PFO. The support vector machine achieved a c-statistic of 0.915 when predicting 90-day PFO for patients who underwent surgery and a c-statistic of 0.981 for patients who underwent surgical evacuation. The SHAP scores for the top 5 features were Glasgow Coma Scale score (0.367), age (0.214), volume of hematoma (0.258), location of hematoma (0.195), and ventricular extension (0.164). Surgery, but not surgical evacuation of the hematoma, was significantly associated with improved mortality at 90-day follow-up (odds ratio, 0.26; 95% confidence interval, 0.10-0.67; P = 0.006). CONCLUSIONS: Explainable ML approaches could elucidate how ML models predict outcomes in SICH and identify subgroups of patients who respond to surgery. Future research in SICH should focus on an explainable ML-based approach that can identify subgroups of patients who may benefit functionally from surgical intervention.