Integrating TCGA and single-cell sequencing data for colorectal cancer: a 10-gene prognostic risk assessment model.

Colorectal cancer represents a significant health threat, yet a standardized method for early clinical assessment and prognosis remains elusive. This study sought to address this gap by using the Seurat package to analyze a single-cell sequencing dataset (GSE178318) of colorectal cancer, thereby identifying distinctive marker genes characterizing various cell subpopulations. Through CIBERSORT analysis of colorectal cancer data within The Cancer Genome Atlas (TCGA) database, significant differences existed in both cell subpopulations and prognostic values. Employing WGCNA, we pinpointed modules exhibiting strong correlations with these subpopulations, subsequently utilizing the survival package coxph to isolate genes within these modules. Further stratification of TCGA dataset based on these selected genes brought to light notable variations between subtypes. The prognostic relevance of these differentially expressed genes was rigorously assessed through survival analysis, with LASSO regression employed for modeling prognostic factors. Our resulting model, anchored by a 10-gene signature originating from these differentially expressed genes and LASSO regression, proved adept at accurately predicting clinical prognoses, even when tested against external datasets. Specifically, natural killer cells from the C7 subpopulation were found to bear significant associations with colorectal cancer survival and prognosis, as observed within the TCGA database. These findings underscore the promise of an integrated 10-gene signature prognostic risk assessment model, harmonizing single-cell sequencing insights with TCGA data, for effectively estimating the risk associated with colorectal cancer.

Distributed State Estimation for Mixed Delays System Over Sensor Networks With Multichannel Random Attacks and Markov Switching Topology.

This article deals with the distributed state estimation for mixed delays system under unknown attacks. A new multichannel random attack model is established for the first time, where network attacks are considered to exist in three channels: the target-to-sensor channel, the senor-to-sensor channel, and the sensor-to-estimator channel. In the above model, transmitted packets are allowed to be attacked multiple times simultaneously, and when they are successfully attacked, the transmitted information is modified. Besides, the topology of the sensor network is considered to change dynamically according to the Markov chain. Based on the newly established distributed estimation model, the estimation error system is proven to be asymptotically mean-square stable under a given H∞ antidisturbance index by using a Lyapunov theory and a stochastic analysis technique; then, the estimator parameter matrices are solved utilizing a linearization method. Finally, several simulation examples are listed to testify the effectiveness of the designed algorithm.

A Review of Incident Prediction, Resource Allocation, and Dispatch Models for Emergency Management.

In the last fifty years, researchers have developed statistical, data-driven, analytical, and algorithmic approaches for designing and improving emergency response management (ERM) systems. The problem has been noted as inherently difficult and constitutes spatio-temporal decision making under uncertainty, which has been addressed in the literature with varying assumptions and approaches. This survey provides a detailed review of these approaches, focusing on the key challenges and issues regarding four sub-processes: (a) incident prediction, (b) incident detection, (c) resource allocation, and (c) computer-aided dispatch for emergency response. We highlight the strengths and weaknesses of prior work in this domain and explore the similarities and differences between different modeling paradigms. We conclude by illustrating open challenges and opportunities for future research in this complex domain.

Race-ethnicity and COVID-19 Vaccination Beliefs and Intentions: A Cross-Sectional Study among the General Population in the San Francisco Bay Area.

OBJECTIVE: The study was designed to compare intentions to receive COVID-19 vaccination by race-ethnicity, to identify beliefs that may mediate the association between race-ethnicity and intention to receive the vaccine and to identify the demographic factors and beliefs most strongly predictive of intention to receive a vaccine. DESIGN: Cross-sectional survey conducted from November 2020 to January 2021, nested within a longitudinal cohort study of the prevalence and incidence of SARS-CoV-2 among a general population-based sample of adults in six San Francisco Bay Area counties (called TrackCOVID). Study Cohort: In total, 3161 participants among the 3935 in the TrackCOVID parent cohort responded. RESULTS: Rates of high vaccine willingness were significantly lower among Black (41%), Latinx (55%), Asian (58%), Multi-racial (59%), and Other race (58%) respondents than among White respondents (72%). Black, Latinx, and Asian respondents were significantly more likely than White respondents to endorse lack of trust of government and health agencies as a reason not to get vaccinated. Participants' motivations and concerns about COVID-19 vaccination only partially explained racial-ethnic differences in vaccination willingness. Concerns about a rushed government vaccine approval process and potential bad reactions to the vaccine were the two most important factors predicting vaccination intention. CONCLUSIONS: Vaccine outreach campaigns must ensure that the disproportionate toll of COVID-19 on historically marginalized racial-ethnic communities is not compounded by inequities in vaccination. Efforts must emphasize messages that speak to the motivations and concerns of groups suffering most from health inequities to earn their trust to support informed decision making.

Implantable Cardioverter Defibrillator Utilization and Mortality Among Patients ≥65 Years of Age With a Low Ejection Fraction After Coronary Revascularization.

The purpose of this analysis was to assess implantable cardioverter-defibrillator (ICD) utilization and its association with mortality among patients ≥65 years of age after coronary revascularization. Patients in the National Cardiovascular Database Registry Chest Pain-Myocardial Infarction (MI) Registry who presented with MI from January 2, 2009 to December 31, 2016, had a left ventricular ejection fraction ≤35% and underwent in-hospital revascularization (10,014 percutaneous coronary intervention (PCI) and 1,647 coronary artery bypass grafting (CABG)) were linked with Medicare claims to determine rates of 1-year ICD implantation. The association between ICD implantation and 2-year mortality was assessed. Of 11,661 included patients, an ICD was implanted in 1,234 (10.6%) within 1 year of revascularization (1,063 (10.6%) PCI and 171 (10.4%) CABG). Among PCI-treated patients, in-hospital ventricular arrhythmia (adjusted hazard ratio [aHR] 1.60, 95% confidence interval [CI] 1.34 to 1.92), 2-week cardiology follow-up (aHR 1.48, 95% CI 1.29 to 1.70), readmission for heart failure (aHR 3.21, 95% CI 2.73 to 3.79), and readmission for MI (aHR 2.18, 95% CI 1.66 to 2.85) were positively associated with ICD implantation. Among CABG-treated patients, in-hospital ventricular arrhythmia (aHR 2.33, 95% CI 1.39 to 3.91), and heart failure readmission (aHR 3.14, 95% CI 1.96 to 5.04) were positively associated with ICD implantation. Women were less likely to receive an ICD, regardless of the revascularization strategy. ICD implantation was associated with lower 2-year all-cause mortality (aHR 0.74, 95% CI 0.63 to 0.86). In conclusion, only 1 in 10 Medicare patients with low ejection fraction received an ICD within 1 year after revascularization. Contact with the healthcare system after discharge was associated with higher likelihood of ICD implantation. ICD implantation was associated with lower mortality following revascularization for MI.

Facilitating the identification of patients hospitalized for acute myocardial infarction and heart failure and the assessment of their readmission risk through the Patient Navigator Program.

BACKGROUND: Optimal transition care mitigates early hospital readmission risk. Given limited resources, hospitals need to identify patients with high readmission risk. This article examines whether a coordinated quality improvement campaign can help achieve this objective. METHODS: The American College of Cardiology Patient Navigator Program, a 2-year quality improvement campaign, sought to assess the impact of transition care interventions on 30-day readmission rates for patients with acute myocardial infarction (AMI) or heart failure (HF) at 35 hospitals. This article examines the change in 2 of the 36 performance metrics the campaign tracked: the number of AMI and HF patients identified predischarge and those whose readmission risk was assessed. RESULTS: The number of facilities identifying AMI and HF patients predischarge increased from 24 (68.6%) and 28 (80.0%), respectively, at baseline, to 34 (97.1%) (P = .0016) and 34 (97.1%) (P = .014), respectively, at 2 years. The number of facilities assessing the readmission risk of AMI and HF patients risk increased from 9 (25.7%) and 11 (31.4%), respectively, at baseline, to 32 (91.4%) (P < .0001) and 33 (94.5%) (P < .0001), respectively, at 2 years. Importantly, baseline reporting of performance for both metrics was poor, with >25% of the hospitals missing data. CONCLUSIONS: Implementation of a coordinated quality improvement campaign may increase the number of facilities identifying AMI and HF patients predischarge and assessing their readmission risk. Further research is needed to determine if increased identification reduces 30-day readmission or facilitates improvement in other important clinical outcomes.

Temporal Trends in Racial Differences in 30-Day Readmission and Mortality Rates After Acute Myocardial Infarction Among Medicare Beneficiaries.

Importance: The association of the Hospital Readmission Reduction Program (HRRP) with reductions in racial disparities in 30-day outcomes for myocardial infarction (MI), is unknown, including whether this varies by HRRP hospital penalty status. Objective: To assess temporal trends in 30-day readmission and mortality rates among black and nonblack patients discharged after hospitalization for acute MI at low-performing and high-performing hospitals, as defined by readmission penalty status after HRRP implementation. Design, Setting, and Participants: This observational cohort analysis used data from the multicenter National Cardiovascular Data Registry Chest Pain-MI Registry centers that were subject to the first cycle of HRRP, between January 1, 2008, and November 30, 2016. All patients hospitalized with MI who were included in National Cardiovascular Data Registry Chest Pain-MI Registry were included in the analysis. Data were analyzed from April 2018 to September 2019. Exposures: Hospital performance category and race (black compared with nonblack patients). Centers were classified as high performing or low performing based on the excess readmission ratio (predicted to expected 30-day risk adjusted readmission rate) for MI during the first HRRP cycle (in October 2012). Main Outcomes and Measures: Thirty-day all-cause readmission and mortality rates. Results: Among 753 hospitals that treated 155 397 patients with acute MI (of whom 11 280 [7.3%] were black), 399 hospitals (53.0%) were high performing. Thirty-day readmission rates declined over time in both black and nonblack patients (annualized 30-day readmission rate: 17.9% vs 20.8%). Black (compared with nonblack) race was associated with higher unadjusted odds of 30-day readmission in both low-performing and high-performing centers (odds ratios: before HRRP: low-performing hospitals, 1.14 [95% CI, 1.03-1.26]; P = .01; high-performing hospitals, 1.17 [95% CI, 1.04-1.32]; P = .01; after HRRP: low-performing hospitals, 1.23 [95% CI, 1.13-1.34]; P < .001; high-performing hospitals, 1.25 [95% CI, 1.12-1.39]; P < .001). However, these racial differences were not significant after adjustment for patient characteristics. The 30-day mortality rates declined significantly over time in nonblack patients, with stable (nonsignificant) temporal trends among black patients. Adjusted associations between race and 30-day mortality showed that 30-day mortality rates were significantly lower among black (compared with nonblack) patients in the low-performing hospitals (odds ratios: pre-HRRP, 0.79 [95% CI, 0.63-0.97]; P = .03; post-HRRP, 0.80 [95% CI, 0.68-0.95]; P = .01) but not in high-performing hospitals. Finally, the association between race and 30-day outcomes did not vary after the HRRP period began in either high-performing or low-performing hospitals. Conclusions and Relevance: In this analysis, 30-day readmission rates among patients with MI declined over time for both black and nonblack patients. Differences in race-specific 30-day readmission rates persisted but appeared to be attributable to patient-level factors. The 30-day mortality rates have declined for nonblack patients and remained stable among black patients. Implementation of the HRRP was not associated with improvement or worsening of racial disparities in readmission and mortality rates.

Association of State Medicaid Expansion With Quality of Care and Outcomes for Low-Income Patients Hospitalized With Acute Myocardial Infarction.

Importance: Lack of insurance is associated with worse care and outcomes among adults hospitalized for acute myocardial infarction (AMI). It is unclear whether states' decision to expand Medicaid eligibility under the Patient Protection and Affordable Care Act in 2014 were associated with improved quality of care and outcomes among low-income patients hospitalized with AMI. Objective: To investigate whether rates of uninsurance, quality of care, and outcomes changed among patients hospitalized for AMI 3 years after states elected to expand Medicaid compared with nonexpansion states. Design, Setting, and Participants: Retrospective cohort study completed at hospitals participating in National Cardiovascular Data Registry Acute Coronary Treatment and Intervention Outcomes Network Registry. Participants were patients younger than 65 years hospitalized for AMI from January 1, 2012, to December 31, 2016. Exposures: State Medicaid expansion in 2014. Main Outcomes and Measures: Rates of uninsured and Medicaid-insured hospitalizations for AMI in states that expanded Medicaid vs those that did not. Comparison of in-hospital care quality, procedure use, and mortality between expansion and nonexpansion states for the years prior to and after Medicaid expansion. Hierarchical logistic regressions models were used to assess the association between Medicaid expansion and outcomes. Results: The initial cohort included 325 343 patients. Uninsured AMI hospitalizations declined in expansion states (18.0% [4395 of 24 358 hospitalizations] to 8.4% [2638 of 31 382 hospitalizations]) and more modestly in nonexpansion states (25.6% [7963 of 31 137 hospitalizations] to 21.1% [8668 of 41 120 hospitalizations]) from 2012 to 2016 (P < .001 difference in trend expansion vs nonexpansion). Medicaid coverage increased from 7.5% (1818 of 24 358 hospitalizations) to 14.4% (4502 of 31 382 hospitalizations) in expansion states and 6.2% (1924 of 31 137 hospitalizations) to 6.6% (2717 of 41 120 hospitalizations) in nonexpansion states (P < .001). The low-income cohort included 55 737 patients across 765 sites. In expansion states, low-income adults' odds of receipt of defect-free care increased (76.3% to 75.9%, adjusted odds ratio 1.11; 95% CI, 1.02-1.21) but to a lesser degree than in nonexpansion states (72.8% to 74.5%, adjusted odds ratio, 1.38; 95% CI, 1.30-1.47; P for interaction < .001). There was no change in use of most procedures (ie, percutaneous coronary intervention for non-ST-segment elevation myocardial infarction) in expansion compared with nonexpansion states. Improvement in in-hospital mortality was similar between expansion and nonexpansion states (3.2% to 2.8%, adjusted odds ratio, 0.93; 95% CI, 0.77-1.12 vs 3.3% to 3.0%, adjusted odds ratio, 0.85; 95% CI, 0.73-0.99; P for interaction = .48). Conclusions and Relevance: Medicaid expansion was associated with a significant reduction in rates of uninsurance among patients hospitalized with AMI. Quality of care and outcomes did not improve among low-income adults in expansion compared with nonexpansion states. Hospital care for AMI may be less sensitive to insurance than has been recognized in the past.

Association Between Hospital Volume, Processes of Care, and Outcomes in Patients Admitted With Heart Failure: Insights From Get With The Guidelines-Heart Failure.

BACKGROUND: Hospital volume is frequently used as a structural metric for assessing quality of care, but its utility in patients admitted with acute heart failure (HF) is not well characterized. Accordingly, we sought to determine the relationship between admission volume, process-of-care metrics, and short- and long-term outcomes in patients admitted with acute HF. METHODS: Patients enrolled in the Get With The Guidelines-HF registry with linked Medicare inpatient data at 342 hospitals were assessed. Volume was assessed both as a continuous variable, and quartiles based on the admitting hospital annual HF case volume, as well: 5 to 38 (quartile 1), 39 to 77 (quartile 2), 78 to 122 (quartile 3), 123 to 457 (quartile 4). The main outcome measures were (1) process measures at discharge (achievement of HF achievement, quality, reporting, and composite metrics); (2) 30-day mortality and hospital readmission; and (3) 6-month mortality and hospital readmission. Adjusted logistic and Cox proportional hazards models were used to study these associations with hospital volume. RESULTS: A total of 125 595 patients with HF were included. Patients admitted to high-volume hospitals had a higher burden of comorbidities. On multivariable modeling, lower-volume hospitals were significantly less likely to be adherent to HF process measures than higher-volume hospitals. Higher hospital volume was not associated with a difference in in-hospital (odds ratio, 0.99; 95% confidence interval [CI], 0.94-1.05; P=0.78) or 30-day mortality (hazard ratio, 0.99; 95% CI, 0.97-1.01; P=0.26), or 30-day readmissions (hazard ratio, 0.99; 95% CI, 0.97-1.00; P=0.10). There was a weak association of higher volumes with lower 6-month mortality (hazard ratio, 0.98; 95% CI, 0.97-0.99; P=0.001) and lower 6-month all-cause readmissions (hazard ratio, 0.98; 95%, CI 0.97-1.00; P=0.025). CONCLUSIONS: Our analysis of a large contemporary prospective national quality improvement registry of older patients with HF indicates that hospital volume as a structural metric correlates with process measures, but not with 30-day outcomes, and only marginally with outcomes up to 6 months of follow-up. Hospital profiling should focus on participation in systems of care, adherence to process metrics, and risk-standardized outcomes rather than on hospital volume itself.

Area disparity in children's perceptions of access to tobacco and cigarette purchasing experiences in Taiwan.

BACKGROUND: Adolescents who perceive easy access to tobacco are more likely to acquire cigarettes and experience smoking. This study assesses area disparities in perceptions of access to tobacco and cigarette purchasing experiences among schoolchildren. METHODS: Data on children's tobacco-related variables were obtained from the Control of School-Aged Children Smoking Study Survey in Taiwan. A stratified random sample of 65 primary schools was included. Polytomous logistic regression analyzed factors associated with tobacco accessibility and purchasing experiences. RESULTS: More than half of the children reported that tobacco retailers often or always sold cigarettes to them. Rural and mountainous children were more likely to have access to cigarettes (adjusted odds ratio [AOR] = 2.01 and 3.01, respectively) and have cigarette purchasing experiences (AOR = 3.06 and 13.76, respectively). Cigarette purchasing from retailers (AOR = 1.84) was significantly associated with children's perceptions of access to tobacco. The factors associated with cigarette purchasing experiences were families smoking (AOR = 8.90), peers smoking (AOR = 2.22), frequent exposure to entertainer smoking on TV and in films (AOR = 2.15), and perceived access to tobacco (AOR = 1.51). CONCLUSIONS: The health department should strictly enforce laws regarding retailers selling tobacco to underage, particularly in remote areas. Schools can reinforce tobacco-use prevention messages.