Traditional Risk Indicators Research Articles

Galectin-3 Predicts Long-Term Risk of Cerebral Disability and Mortality in Out-of-Hospital Cardiac Arrest Survivors.

Out-of-hospital cardiac arrest (OHCA) is associated with high mortality and cerebral disability in survivors. Current models of risk prediction and survival are mainly based on resuscitation duration. We examined the prognostic value of circulating biomarkers in predicting mortality and severe cerebral disability for OHCA survivors, alongside traditional clinical risk indicators. Biomarkers including BNP, troponin I, and galectin-3 were measured at hospital admission in resuscitated OHCA patients. Prognostic significance for mortality and cerebral disability involving circulating biomarkers, resuscitation duration, demographics, and laboratory and clinical characteristics was examined via univariate and multivariate Cox proportional hazards regression models. The incremental prognostic value of the index covariates was examined through model diagnostics, focusing on the Akaike information criterion (AIC) and Harrell's concordance statistic (c-statistic). In a combinatorial analysis of 144 OHCA survivors (median follow-up 5.7 years (IQR 2.9-6.6)), BNP, galectin-3, arterial pH, and resuscitation time were significant predictors of all-cause death and severe cerebral disability, whereas troponin I levels were not. Multivariate regression, adjusting for BNP, arterial pH, and resuscitation time, identified galectin-3 as an independent predictor of long-term mortality. Multiple linear regression models also confirmed galectin-3 as the strongest predictor of cerebral disability. The incorporation of galectin-3 into models for predicting mortality and cerebral disability enhanced fit and discrimination, demonstrating the incremental value of galectin-3 beyond traditional risk predictors. Galectin-3 is a significant, independent long-term risk predictor of cerebral disability and mortality in OHCA survivors. Incorporating galectin-3 into current risk stratification models may enhance early prognostication and guide targeted clinical interventions.

Risk Assessment of Roundabout Scenarios in Virtual Testing Based on an Improved Driving Safety Field.

With the advancement of autonomous driving technology, scenario-based testing has become the mainstream testing method for intelligent vehicles. However, traditional risk indicators often fail in roundabout scenarios and cannot accurately define dangerous situations. To accurately quantify driving risks in roundabout scenarios, an improved driving safety field model is proposed in this paper. First, considering the unique traffic flow characteristics of roundabouts, the dynamic characteristics of vehicles during diverging or merging were taken into account, and the driving safety field model was improved to accurately quantify the driving risks in roundabout scenarios. Second, based on data from the rounD dataset, the model parameters were calibrated using the social force model. Finally, a DENCLUE-like method was used to extract collision systems, calculate vehicle risk degree, and analyze these risks for both the temporal and the spatial dimensions, providing guidance for virtual testing. The proposed method significantly improves detection efficiency, increasing the number of identified dangerous scenarios by 175% compared to the Time to Collision (TTC) method. Moreover, this method can more accurately quantify driving risks in roundabout scenarios and enhance the efficiency of generating dangerous scenarios, contributing to promoting the safety of autonomous vehicles.

Cardiovascular Diseases and Adipokines: The Role of Visfatin in Coronary Atherosclerosis

Coronary artery disease (CAD) is a leading cause of cardiovascular disease-related mortality globally. Traditional risk indicators for CAD, such as age, gender, hypertension, and cholesterol levels, may not reliably predict the existence and severity of the disease in all individuals. Furthermore, these risk variables may not provide information regarding the long-term prognosis and survival of the patients with stable CAD. The limitations of present screening approaches suggest the need to develop novel prognostic biomarkers for the detection of coronary atherosclerosis (CA). This review focuses on the significance of adipokines in the pathophysiology of CA. The article discusses the role of various cytokines, focusing on visfatin in developing and progressing coronary atheroma and its potential to improve risk stratification, increase diagnostic accuracy, and guide therapy decisions. Clinical evidence supporting visfatin’s role as a diagnostic marker for CAD is already available, with elevated levels observed in patients with significant CA. However, the paper acknowledges certain limitations, such as the need for more extensive longitudinal studies to validate its potential use in clinical practice to improve early diagnosis and prognosis, ultimately enhancing strategies for preventing cardiovascular disease.

Effects of elevated remnant cholesterol on outcomes of acute ischemic stroke patients receiving mechanical thrombectomy.

Large cohort studies provided evidence that elevated remnant cholesterol (RC) was an important risk factor for ischemic stroke. However, the association between high RC and clinical outcomes in acute ischemic stroke (AIS) individuals was still undetermined. This retrospective study enrolled 165 AIS patients undergoing mechanical thrombectomy in one tertiary stroke center. We divided patients into two groups based on the median of their RC levels (0.49 mmol/L). The modified Rankin Scale (mRS) was used to evaluate the primary outcome 90 days after the onset of symptoms. The mRS scores ≤ 2 and ≤ 1 at 90 days were deemed as favorable and excellent outcomes, respectively. In the overall AIS patients undergoing mechanical thrombectomy, there was no obvious distinction between the high and low RC group at 90-day favorable outcome (41.0% vs. 47.1%, P = 0.431) or excellent outcome (23.1% vs. 31.0%, P = 0.252). In the subgroup analysis stratified by stroke etiology, non-large artery atherosclerosis (non-LAA) stroke patients yielded with less favorable or excellent prognosis in the high RC group (26.8% vs. 46.8%, adjusted OR = 0.31, 95%CI: 0.11-0.85, P = 0.023; or 12.2% vs. 29.0%, adjusted OR = 0.18, 95%CI: 0.04-0.80, P = 0.024, respectively.). Post hoc power analyses indicated that the power was sufficient for favorable outcome (80.38%) and excellent outcome (88.72%) in non-LAA stroke patients. Additionally, RC can enhance the risk prediction value of a poor outcome (mRS scores 3-6) based on traditional risk indicators (including age, initial NIHSS score, operative duration, and neutrophil-to-lymphocyte ratio) for non-LAA stroke patients (AUC = 0.86, 95%CI: 0.79-0.94, P < 0.001). In AIS patients undergoing mechanical thrombectomy, elevated RC was independently related to poor outcome for non-LAA stroke patients, but not to short-term prognosis of LAA stroke patients.

Deficit accumulation in relation to dementia and survival outcomes in residential care older adults

AbstractBackgroundAs people age, they are more likely to accumulate health deficits leading to an increased risk of adverse outcomes, including dementia. In community‐dwelling older adults, even combining only the deficits traditionally unrelated to dementia predicts dementia. Previously, we reported an association between deficit accumulation and dementia in residential care. Here, our objectives are to 1) understand the profiles of deficit accumulation and the relationships between traditional and non‐traditional dementia risk factors in older residents with or without dementia and 2) investigate the impact of deficit accumulation on dementia and survival outcomes in residential‐care older adults.MethodWe analyzed the first full‐assessment data of older adults in InterRAI Residential Care (RAI‐RC MDS2.0) who enrolled in facilities under the care of Fraser Health Canada between 2010 and 2019 (female = 63.8%, mean age = 84.6±8.0 years). Dementia diagnoses (n = 18169), including pure Alzheimer’s disease (AD), mixed AD, other dementia, and no dementia (n = 11,589), were recorded at annual assessments. Two indices were constructed as the mean of the coded deficits between 0 (absent) and 1 (present), employing the same descriptive levels as in the original assessment. One index contained 20 traditional dementia risk factors (e.g., cognition, hypertension, and heart disease); the other contained 20 non‐traditional ones (e.g., vision, hearing, arthritis, and continence). Participants were followed until 2021. Relationships between the indices and their impact on survival were tested. Incidental dementia outcome was examined for the non‐demented sub‐sample.ResultOver 92% of residents had at least one daily‐living dependency. The two indices were highly correlated (R = 0.59, p&lt;.001), and each positively related to mortality, regardless of dementia diagnoses. People with dementia accumulated more deficits and had a higher mean traditional risk index than those without dementia (F = 334.72, p&lt;.001), while the latter group accumulated more non‐traditional risk factors on average (F = 135.39, p&lt;.001). A higher level of the indices showed variable risks of incidental dementia at follow‐ups (p’s&lt;.05).ConclusionOlder residents without dementia are dominated by dependent living with a distinct deficit accumulation profile than those with dementia. Deficit accumulation has negative impact on both dementia and survival outcomes in residential care.

Survival and analysis of prognostic factors for primary malignant cardiac tumors based on the SEER database.

The purpose of this study was to use the Surveillance, Epidemiology, and End Results (SEER) database to evaluate the survival rate of primary malignant cardiac tumors (PMCTs), assess the risk factors affecting survival, and calculate the number of PMCT cases in recent years. SEER 22 registries were used to calculate the number of cases PMCT. Data on age, sex, race, marital status, tumor size, the American Joint Committee on Cancer (AJCC) stage, lymph node involvement, metastasis, treatment, and survival were collected to analyze the survival and prognostic factors of SEER 17 registries. Using the Kaplan-Meier estimation method, a survival curve was obtained according to the influencing factors, and a multivariable Cox regression model was established. In recent years, the average annual number of PMCT cases was 20.56 ± 7.12, significantly higher than the average before 2004 (P = 0.015; 95% CI 1.14-8.98). The 1-, 3-, and 5-year survival rates were 45.6%, 18.8%, and 11.2%, respectively. Multivariate analysis revealed that age (risk ratio [HR], 2.047; 95% CI 1.381-3.034), AJCC stage III (HR, 1.786; 95% CI 1.123-2.839), AJCC staging with distant metastasis (HR, 2.666; 95% CI 1.509-4.709), no chemotherapy (HR, 2.011; 95% CI 1.561-2.590), and tumor size larger than 99mm (HR, 1.766; 95% CI 1.132-2.756) were independent risk factors for poor prognosis. Only age over 76years and distant metastasis were independent risk factors for prognosis in the chemotherapy group. In recent years, the annual number of patients with PMCT has increased significantly. Due to developments in chemotherapy, we should re-evaluate the traditional tumor staging and prognostic risk indicators to improve clinical applications.

Predicting food crises using news streams.

Anticipating food crisis outbreaks is crucial to efficiently allocate emergency relief and reduce human suffering. However, existing predictive models rely on risk measures that are often delayed, outdated, or incomplete. Using the text of 11.2 million news articles focused on food-insecure countries and published between 1980 and 2020, we leverage recent advances in deep learning to extract high-frequency precursors to food crises that are both interpretable and validated by traditional risk indicators. We demonstrate that over the period from July 2009 to July 2020 and across 21 food-insecure countries, news indicators substantially improve the district-level predictions of food insecurity up to 12 months ahead relative to baseline models that do not include text information. These results could have profound implications on how humanitarian aid gets allocated and open previously unexplored avenues for machine learning to improve decision-making in data-scarce environments.

Cardiovascular risk indicators among depressed persons: A special case?

BackgroundTraditional cardiovascular risk indicators only partially explain cardiovascular risks in depressed persons. Depressed persons may exhibit a profile of cardiovascular risk indicators that goes beyond traditional cardiovascular risk indicators, such as symptom severity, insomnia, loneliness and neuroticism, yet research on the added value of these depression-related characteristics in predicting cardiovascular risks of depressed persons is scarce. MethodsData from N = 1028 depressed Dutch adults without prevalent CVD were derived from two longitudinal depression cohort studies. The outcome was medication-confirmed self-reported CVD. Fifteen depression-related clinical and psychological characteristics were included and tested against traditional cardiovascular risk indicators. Data were analysed using Cox regression models. Incremental values of these characteristics were calculated using c-statistics. ResultsAfter a median follow-up of 65.3 months, 12.7% of the participants developed CVD. Only anxiety and depressive symptom severity were associated with incident CVD beyond traditional cardiovascular risk indicators. The c-statistic of the model with traditional cardiovascular risk indicators was 85.47%. This increased with 0.56 or 0.33 percentage points after inclusion of anxiety or depression severity, respectively. LimitationsOther relevant depression-related characteristics were not available in the datasets used. ConclusionAnxiety and depressive symptom severity were indicative of an increased cardiovascular risk. Including these as additional risk indicators barely improved the ability to assess cardiovascular risks in depressed persons. Although traditional cardiovascular risk indicators performed well in depressed persons, existing risk prediction algorithms need to be validated in depressed persons.

Incremental value of PET primary lesion-based radiomics signature to conventional metabolic parameters and traditional risk factors for preoperative prediction of lymph node metastases in gastric cancer.

Precise preoperative prediction of lymph node metastasis (LNM) is crucial for optimal diagnosis and treatment in patients with gastric cancer (GC), in which existing imaging methods have certain limitations. We hypothesized that PET primary lesion-based radiomics signature could provide incremental value to conventional metabolic parameters and traditional risk indicators in predicting LNM in patients with GC. This retrospective study was performed in 127 patients with GC who underwent preoperative PET/CT. Basic clinical data and PET conventional metabolic parameters were collected. Radiomics signature was constructed by the least absolute shrinkage and selection operator algorithm (LASSO) logistic regression. Basedon the postoperative histological results, the patients were divided into LNM group and non-lymph node metastasis (NLNM) group. Receiver-operating characteristic (ROC) was used to evaluate the discriminatory ability of Radiomics score (Rad-score) for predicting LNM and determine whether adding Rad-score to PET conventional metabolic parameters and traditional risk factors could improve the predictive value in LNM. The Integrated discrimination improvement (IDI) and net reclassification improvement (NRI) were calculated to further confirm the incremental value of Rad-score for predicting LNM in GC. The LNM group had higher Rad-score than NLNM group [(0.35 (-0.13-0.85) vs. -0.61 (-1.92-0.18), P < 0 .001)]. After adjusted for gender, age, BMI, and FBG, multivariable logistic regression analysis illustrated that Rad-score (OR: 6.38, 95% CI: 2.73-14.91, P < 0.0001) was independent risk factors for LNM in GC. Adding PET conventional parameters to traditional risk factors increased the predictive value of LNM in GC (AUC 0.751 vs 0.651, P = 0.02). Additional inclusion of Rad-score to conventional metabolic parameters and traditional risk indicators significantly improved the AUC (0.882 vs 0.751; P = 0.006). Bootstrap resampling (times = 500) was used for internal verification, 95% confidence interval (CI) was 0.802-0.948, with the sensitivity equaled to 89.5%, and positive predictive value (PPV) was 93.5%. When Rad-score was added to conventional metabolic parameters and traditional risk indicators, net reclassification improvement (NRI) was 0.293 (P = 0.0040) and integrated discrimination improvement (IDI) was 0.293 (P = 0.0045). In GC patients, PET Radiomics signature of the primary lesion-based was significantly associated with LNM and could improve the prediction of LNM above PET conventional metabolic parameters and traditional risk factors, which could provide incremental value for individual diagnosis and treatment of GC.

Анализ возможности эскалации аварии в системе надземных многониточных газопроводов в условиях Арктики

Assessment of the risk of accidents for the pipelines in the multi-line corridors is very relevant, especially in the event of a possible escalation of an accident from one line to another. Methodological approach for assessing the conditional probability of an escalation of an accident on the multi-line above-ground gas pipelines located in the Arctic and intended for supplying fuel to certain regions is considered in the article. From the point of view of industrial safety, to describe the degree of danger of an accident during the operation of gas pipelines, the use of traditional risk indicators, such as individual, collective, and social risk, is not very informative, since the Arctic gas pipelines are laid in a sparsely populated area. Therefore, in this article it is proposed to use the conditional probability of an accident escalation, and, based on such an assessment, draw conclusions about the independence of gas supply along the individual lines. The calculations are made concerning the escalation of an accident to adjacent lines during depressurization of a typical above-ground multi-line main gas pipeline. The hazard of abnormal avalanche-like depressurization of a gas pipeline during its oscillations under the influence of reactive forces from outflowing jets is considered separately. Dependence is given related to the conditional probability of an accident escalation on the distance between the lines in the case of an avalanche-like destruction of an above-ground gas pipeline on the equipped supports. The method is developed to consider the specifics of the recipient gas pipeline when simulating its destruction under the influence of thermal radiation.

Assessment of Coronary Artery Disease With Computed Tomography Angiography and Inflammatory and Immune Activation Biomarkers Among Adults With HIV Eligible for Primary Cardiovascular Prevention

Cardiovascular disease (CVD) is increased among people with HIV (PWH), but little is known regarding the prevalence and extent of coronary artery disease (CAD) and associated biological factors in PWH with low to moderate traditional CVD risk. To determine unique factors associated with CVD in PWH and to assess CAD by coronary computed tomography angiography (CTA) and critical pathways of arterial inflammation and immune activation. This cohort study among male and female PWH, aged 40 to 75 years, without known CVD, receiving stable antiretroviral therapy, and with low to moderate atherosclerotic cardiovascular disease (ASCVD) risk according to the 2013 American College of Cardiology/American Heart Association pooled cohort equation, was part of the Randomized Trial to Prevent Vascular Events in HIV (REPRIEVE), a large, ongoing primary prevention trial of statin therapy among PWH conducted at 31 US sites. Participants were enrolled from May 2015 to February 2018. Data analysis was conducted from May to December 2020. HIV disease. The primary outcome was the prevalence and composition of CAD assessed by coronary CTA and, secondarily, the association of CAD with traditional risk indices and circulating biomarkers, including insulin, monocyte chemoattractant protein 1 (MCP-1), interleukin (IL) 6, soluble CD14 (sCD14), sCD163, lipoprotein-associated phospholipase A2 (LpPLA2), oxidized low-density lipoprotein (oxLDL), and high-sensitivity C-reactive protein (hsCRP). The sample included 755 participants, with a mean (SD) age of 51 (6) years, 124 (16%) female participants, 267 (35%) Black or African American participants, 182 (24%) Latinx participants, a low median (interquartile range) ASCVD risk (4.5% [2.6%-6.8%]), and well-controlled viremia. Overall, plaque was seen in 368 participants (49%), including among 52 of 175 participants (30%) with atherosclerotic CVD (ASCVD) risk of less than 2.5%. Luminal obstruction of at least 50% was rare (25 [3%]), but vulnerable plaque and high Leaman score (ie, >5) were more frequently observed (172 of 755 [23%] and 118 of 743 [16%], respectively). Overall, 251 of 718 participants (35%) demonstrated coronary artery calcium score scores greater than 0. IL-6, LpPLA2, oxLDL, and MCP-1 levels were higher in those with plaque compared with those without (eg, median [IQR] IL-6 level, 1.71 [1.05-3.04] pg/mL vs 1.45 [0.96-2.60] pg/mL; P = .008). LpPLA2 and IL-6 levels were associated with plaque in adjusted modeling, independent of traditional risk indices and HIV parameters (eg, IL-6: adjusted odds ratio, 1.07; 95% CI, 1.02-1.12; P = .01). In this study of a large primary prevention cohort of individuals with well-controlled HIV and low to moderate ASCVD risk, CAD, including noncalcified, nonobstructive, and vulnerable plaque, was highly prevalent. Participants with plaque demonstrated higher levels of immune activation and arterial inflammation, independent of traditional ASCVD risk and HIV parameters.

Impaired Peripheral Microvascular Function and Risk of Major Adverse Cardiovascular Events in Patients With Coronary Artery Disease.

[Figure: see text].

Predicting cardiac risk in noncardiac surgery: a narrative review.

Risk stratification endeavors to categorize patients into groups based on the level of risk for each group. Improved perioperative screening tests using more sensitive cardiac biomarkers have revealed that about 68% of perioperative myocardial infarctions (MI) are asymptomatic and may only be detected by routine postoperative screening with troponin measurements. This is important since myocardial injury not meeting criteria for myocardial infarction is associated with increased risk of 30-day mortality (Botto et al. in Anesthesiology 120:564-578, 2014). Traditional risk indices including the revised cardiac risk index (RCRI) and the myocardial infarction cardiac arrest (MICA) index were developed based on overt clinical signs of myocardial infarction and significantly underestimate adverse cardiac events. Recently, brain type natriuretic peptides (BNP) and its precursor n- terminal pro-brain type natriuretic peptide (nt-proBNP) have been shown to be powerful prognostic markers. Incorporating serum biomarkers into updated clinical risk indices is likely to improve their performance. Further studies are needed to determine appropriate clinical interventions to treat isolated elevations in cardiac troponin levels and further mitigate the increased risk of morbidity and mortality. The objective of this review is to summarize the current literature on the clinical diagnoses of perioperative myocardial injury in the setting of noncardiac surgery.

Topological data analysis in investment decisions

This article explores the applications of Topological Data Analysis (TDA) in the finance field, especially addressing the primordial problem of asset allocation. Firstly, we build a rationale on why TDA can be a better alternative to traditional risk indicators such as standard deviation using real data sets. We apply Takens embedding theorem to reconstruct the time series of returns in a high dimensional space. We adopt the sliding window approach to draw the time-dependent point cloud data sets and associate a topological space with them. We then apply the persistent homology to discover the topological patterns that appear in the multidimensional time series. The temporal changes in the persistence landscapes, which are the real-valued functions that encode the persistence of topological patterns, are captured via Lp norm. The time series of the Lp norms shows that it is better at measuring the dynamics of returns than the standard deviation.Inspired by our findings, we explore an application of TDA in Enhanced Indexing (EI) that aims to build a portfolio of fewer assets than that in the index to outperform the latter. We propose a two-step procedure to accomplish this task. In step one, we utilize the Lp norms of the assets to propose a filtration technique of selecting a few assets from a larger pool of assets. In step two, we propose an optimization model to construct an optimal portfolio from the class of filtered assets for EI. To test the efficiency of this enhanced algorithm, experiments are carried out on ten data sets from financial markets across the globe. Our extensive empirical analysis exhibits that the proposed strategy delivers superior performance on several measures, including excess mean returns from the benchmark index and tail reward-risk ratios than some of the existing models of EI in the literature. The proposed filtering strategy is also noted to be beneficial for both risk-seeking and risk-averse investors.

An Incremental-Variable-Based State Enumeration Method for Power System Operational Risk Assessment Considering Safety Margin

This paper proposes an incremental-variable-based state enumeration method (IVSE) for power system operation risk assessment and develops the risk indices considering the safety margin. Firstly, the traditional risk indices are modified to take into account the safety margin, which is defined as the virtual distance from the operational limits to the current normal operating point. Those indices can provide more potential risk information to operators for reasonable decision-making. Thereafter, an incremental- variable-based state enumeration is developed by utilizing the relationship between high order contingencies and low order contingencies. The proposed method is more efficient and accurate than traditional methods, which makes it more suitable for online application. Finally, case studies are performed on the IEEE-118 bus system. And results verify the accuracy and efficiency of the proposed method in various situations. In addition, it also can diagnose the weak points of the system, which can assist operators in online decision making.

Survival and analysis of prognostic factors for hepatoblastoma: based on SEER database.

The goal of this study is to assess the newest survival of hepatoblastoma (HB) and the risk factors which impacted on survival by using the Surveillance, Epidemiology and End Results (SEER) database, also calculate the incidence of HB in recent years. We calculate age-adjusted incidence of HB by using SEER 21 registries. Age, sex, race, tumor size, macrovascular involvement, multifocal tumor, distant metastasis, the way of treatment, and the survival were collected for survival and analysis of prognostic factors in SEER 18 registries. Survival curves, according to different factors, were obtained by Kaplan-Meier estimates. Multivariable Cox regression models were also built. The overall age-adjusted incidence of HB was 0.19 patients per 100,000 children with a statistically significant increase per year. Overall survival (OS) at 1-, 3- and 5-year for all patients were 89.3%, 84.6%, and 81.9%, respectively. Multivariate analysis showed tumor size >5 cm [hazard ratio (HR), 8.271; 95% confidence interval (CI), 1.134-60.310], multiple tumors (HR, 2.578; 95% CI, 1.424-4.668) and no-surgery treatment (HR, 7.520; 95% CI, 4.121-13.724) were independent indicators of poor prognosis. Only the age ≥2-year-old (HR, 3.240; 95% CI, 1.433-7.326) and multiple tumors (HR, 2.395; 95% CI, 1.057-5.430) were the risk factors for the surgical treatment group. The survival of patients with HB has been greatly improved in the recent years, and at the same time, due to the application of better chemotherapy, we should re-evaluate the traditional risk indicators of prognosis in order to better apply to the clinical.

Frailty as a predictor of complications after radical cystectomy: A prospective study of various preoperative assessments

PurposeFrailty has been correlated with worse postoperative outcomes. Prospective studies examining frailty and bladder cancer are lacking. We aimed to determine whether a prospective frailty assessment or traditional risk indices can identify patients undergoing radical cystectomy (RC) at risk for complications. Materials and methodsPatients ≥65 years undergoing RC were preoperatively assessed using Fried Frailty Criteria (FFC; grip strength, gait speed, exhaustion, physical activity, shrinking), Charlson Comorbidity Index, American Society of Anesthesiologists score, Katz Index of Independence in Activities of Daily Living, Karnofsky Performance Scale, Eastern Cooperative Oncology Group performance status, and Center for Epidemiological Studies Depression scale. Thirty-day and 90-day postoperative complications were recorded. Univariate and multivariate analyses were performed. ResultsOne hundred and twenty three patients were assessed with median age of 74 years. Fifty-nine patients (48.0%) had ≥1 complication within 30 days and 72 (58.5%) within 90 days. Center for Epidemiological Studies Depression scale (odds ratio [OR] 1.08, 95% confidence interval [CI] 1.01–1.17, P = 0.027) and shrinking (OR 3.79, 95% CI 1.64–9.26, P = 0.0024) were significant for any 30-day complication, while physical activity was protective (OR 0.84, 95% CI 0.69–1.00, P = 0.072) for any 90-day complication. Being intermediately frail or frail was associated with high-grade 30-day (OR 4.87, 95% CI 1.39–22.77, P = 0.022) and 90-day complications (OR 3.01, 95% CI 1.05–9.37, P = 0.045), along with Eastern Cooperative Oncology Group score ≥3 (OR 45.00, 95% CI 6.92–437.69, P = 0.0010 and OR 17.85, 95% CI 3.21–143.26, P = 0.0079, respectively). ConclusionsFried Frailty Criteria were predictive of high-grade complications, while individual components were predictive of having any complication. Elderly patients should be routinely assessed prior to RC to guide postoperative care.

A Simplified Frailty Index to Predict Outcomes After Radical Cystectomy

BackgroundTraditional surgical risk indices are notoriously inaccurate, especially for the elderly, so there has been a trend to evaluate frailty instead. ObjectiveTo describe a simplified five-item frailty index for evaluating radical cystectomy outcomes and compare its predictive ability with other risk assessment tools for a total patient cohort and a subgroup of patients aged ≥65yr. Design, setting, and participantsThe National Surgical Quality Improvement Program (NSQIP) database from 2007 to 2015 was queried for radical cystectomy cases for bladder cancer. A simplified five-item frailty index (sFI) was created based on previously described measures of frailty. Outcome measurement and statistical analysisCorrelation of the sFI with postoperative outcomes was investigated using multivariate logistic regression analyses. The predictive ability of the sFI was compared to the extended 11-item frailty index, NSQIP risk calculator, and the American Society of Anesthesiologists (ASA) score by comparing the area under the receiver operating characteristic curve. Subgroup analysis was performed for those aged ≥65 yr to evaluate the accuracy of the index in the older age group, for which traditional risk indices are notoriously inaccurate. Results and limitationsOf 5516 cases identified, 10.7% experienced a Clavien grade ≥3 complication within 30 d of surgery. Individuals with an sFI of 3+ had a greater likelihood of experiencing a major complication (odds ratio 3.22, 95% confidence interval 2.01–5.17). The sFI outperformed the ASA score in predicting major complications and had a similar predictive ability to the more complex 11-item index and NSQIP risk calculator. There was also a significant correlation between the sFI and discharge destination. These relationships were consistent in the subgroup of patients aged ≥65yr. The study is limited by the database, which only records 30-d outcomes and does not allow evaluation of long-term sequelae. ConclusionsThere is a strong correlation between frailty assessed via the sFI and radical cystectomy outcomes, including in the elderly. This tool can be used in the clinical setting to counsel patients and aid decision-making. Patient summaryThis study demonstrated that a simple five-item frailty index can be used to assess preoperative risk in patients undergoing radical cystectomy.

A county-level cross-sectional analysis of positive deviance to assess multiple population health outcomes in Indiana

ObjectiveTo test a positive deviance method to identify counties that are performing better than statistical expectations on a set of population health indicators.DesignQuantitative, cross-sectional county-level secondary analysis of risk variables...

An Accumulated Deficits Model Predicts Perioperative and Long-term Adverse Events after Carotid Endarterectomy

There is increasing recognition that decreased reserve in multiple organ systems, known as accumulated deficits (AD), may better stratify perioperative risk than traditional risk indices. We hypothesized that an AD model would predict both perioperative adverse events and long-term survival after carotid endarterectomy (CEA), particularly important in asymptomatic patients. Consecutive patients undergoing CEA between 1st January 2000 and 31st December 2010 were retrospectively identified. Seven of the deficit items from the Canadian Study of Health and Aging-frailty index (coronary disease, renal insufficiency, pulmonary disease, peripheral vascular disease, heart failure, hypertension, and diabetes) were tabulated for each patient. Predictors of perioperative and long-term outcomes were evaluated using regression analysis. About 1,782 CEAs in 1,496 patients (mean age: 71.3±9.3years, 56.3% male, 35.4% symptomatic) were included. The risk of major adverse events (stroke, death, or myocardial infarction) at 30days for patients with ≤3 deficits was 2.53% vs. 8.81% for patients with ≥4 deficits (P<0.001). For patients with ≥5 deficits, the risk was 15.18%. Each additional deficit increased the odds of a 30-day major adverse event and hospital stay >2days by 1.64 (P<0.001) and 1.15 (P<0.001), respectively. In multivariate analysis, the presence of ≥4 deficits was more predictive of perioperative major adverse events (odds ratio [OR] = 3.62, P<0.001) than symptomatology within 6months (OR = 1.57, P=0.08) or octogenarian status (OR=2.00, P=0.02). Kaplan-Meier analysis showed significantly decreased survival over time with accumulating deficits (P<0.001). Patients with ≥4 deficits have a hazards ratio for death of 2.6 compared to patients with ≤3 deficits (P<0.001). Overall survival is estimated at 79.5% (95% confidence interval [CI]: 0.77-0.82) at 5 years in patients with ≤3 deficits versus 52.4% (95% CI: 0.46-0.58) in patients with ≥4 deficits, respectively. In subgroup analysis of asymptomatic patients, 5-year survival for octogenarian male patients with ≥4 deficits was only 26.8%. For asymptomatic males aged 70-79 years with ≥4 deficits, 5-year survival was 59.9%. An AD model is more predictive of perioperative adverse events after CEA than age or symptomatic status. This model remains predictive of long-term survival. In asymptomatic male octogenarians with 4 or more AD, 5-year survival is severely limited.