Intravenous iron therapy for heart failure and iron deficiency: An updated meta-analysis of randomized clinical trials.

Heart failure (HF) patients frequently exhibit iron deficiency, which is associated with a poor prognosis. Although various trials have been conducted, it is uncertain if intravenous (IV) iron replenishment improves clinical outcomes in HF patients with iron deficiency. A comprehensive literature search was conducted using PubMed/MEDLINE, Embase, and the Cochrane Library from inception till 15 September 2023 to retrieve randomized controlled trials (RCTs) that compared IV iron therapy with placebo or standard of care in patients with HF and iron deficiency. Clinical outcomes were assessed by generating forest plots using the random-effects model and pooling odds ratios (ORs) or weighted mean differences (WMDs). Fourteen RCTs with 6651 patients were included. IV iron therapy showed a significantly reduced incidence of the composite of first heart failure hospitalization (HHF) or cardiovascular (CV) mortality as compared with the control group (OR = 0.73, 95% CI: 0.58 to 0.92). The IV iron therapy resulted in a trend towards lower CV mortality (OR = 0.88, 95% CI: 0.76 to 1.01), 1-year all-cause mortality (OR = 0.85, 95% CI: 0.71 to 1.02), and first HHF (OR = 0.73, 95% CI: 0.51 to 1.05), and an improved left ventricular ejection fraction (LVEF) (MD = 4.54, 95% CI: -0.13 to 9.21). Meta-regression showed a significant inverse moderating effect of baseline LVEF on the first HHF or CV death. In patients with HF and iron deficiency, IV iron therapy reduced the incidence of composite of first HHF or CV mortality. There was a trend of lower overall CV and 1-year all-cause mortality, first HHF, and improved LVEF with IV iron therapy.

Trends in direct health care costs among US adults with atherosclerotic cardiovascular disease with and without diabetes.

OBJECTIVE: Population-based national data on the trends in expenditures related to coexisting atherosclerotic cardiovascular diseases (ASCVD) and diabetes is scarce. We assessed the trends in direct health care expenditures for ASCVD among individuals with and without diabetes, which can help to better define the burden of the co-occurrence of diabetes and ASCVD. METHODS: We used 12-year data (2008-2019) from the US national Medical Expenditure Panel Survey including 28,144 U.S individuals aged ≥ 18 years. Using a two-part model (adjusting for demographics, comorbidities and time), we estimated mean and adjusted incremental medical expenditures by diabetes status among individuals with ASCVD. The costs were direct total health care expenditures (out-of-pocket payments and payments by private insurance, Medicaid, Medicare, and other sources) from various sources (office-based visits, hospital outpatient, emergency room, inpatient hospital, pharmacy, home health care, and other medical expenditures). RESULTS: The total direct expenditures for individuals with ASCVD increased continuously by 30% from $14,713 (95% confidence interval (CI): $13,808-$15,619) in 2008-2009 to $19,145 (95% CI: $17,988-$20,301) in 2008-2019. Individuals with diabetes had a 1.5-fold higher mean expenditure that those without diabetes. A key driver of the observed increase in direct costs was prescription drug costs, which increased by 37% among all individuals with ASCVD. The increase in prescription drug costs was more pronounced among individuals with ASCVD and diabetes, in whom a 45% increase in costs was observed, from $5184 (95% CI: $4721-$5646) in 2008-2009 to $7501 (95% CI: $6678-$8325) in 2018-2019. Individuals with ASCVD and diabetes had $5563 (95% CI: $4643-$6483) higher direct incremental expenditures compared with those without diabetes, after adjusting for demographics and comorbidities. Among US adults with ASCVD, the estimated adjusted total direct excess medical expenditures were $42 billion per year among those with diabetes vs. those without diabetes. CONCLUSIONS: In the setting of ASCVD, diabetes is associated with significantly increased health care costs, an increase that was driven by marked increase in medication costs.

Association between SGLT2 Inhibitors and Risk of Dementia and Parkinson's Disease: A Meta-Analysis of 12 Randomized Controlled Trials.

BACKGROUND: Sodium-glucose cotransporter 2 inhibitors (SGLT2i) have demonstrated to reduce the risk of hospitalizations from heart failure and cardiovascular mortality. However, SGLT2i therapy's potential effects on the risks of dementia and Parkinson's disease are not well established, with conflicting results based on observational studies. Hence, we sought to evaluate the association between SGLT2i and the risk of dementia and Parkinson's disease in patients with type 2 diabetes mellitus, heart failure, or chronic kidney disease. METHODS: We performed a systematic literature search on PubMed, and Clinicaltrial.gov for relevant randomized controlled trials (RCTs) from inception until March 2024 without any language restrictions. Odds ratios (OR) and 95% confidence intervals (CI) were pooled using a random-effect model. RESULTS: A total of 12 RCTs with 74, 442 patients (40,784 in the SGLT2i group and 33,658 in the control group) were included in the analysis. The mean age of patients in SGLT2i and control was 65.3 and 65.2 years respectively. Pooled analysis showed that there is no significant association between SGLT2i and the risk of dementia (OR, 1.37 (95%CI: 0.70-2.69), P=0.36), dementia Alzheimer's type (OR, 1.99 (95%CI: 0.59-6.71), P=0.27), vascular dementia (OR, O.40 (95%CI: 0.09-1.85), P=0.24), and Parkinson's Disease (OR, 0.63 (95%CI: 0.25-1.61), P=0.33) was comparable between SGLT2i and control groups. CONCLUSION: Our study suggests that there is no significant association between SGLT2i and the risk of dementia, its subtypes, and Parkinson's Disease.

Examining Heart Failure Outcomes Amidst Housing Insecurity.

BACKGROUND: How housing insecurity might affect patients with heart failure (HF) is not well characterized. Housing insecurity increases risks related to both communicable and non-communicable diseases. For patients with HF, housing insecurity likely increases the risk for worse outcomes and rehospitalizations. METHODS AND RESULTS: We analyzed U.S. HF hospitalizations using the 2020 National Inpatient Sample (NIS) and Nationwide Readmissions Database (NRD) to evaluate the impacts of housing insecurity on HF outcomes and hospital utilization. Individuals were identified as having housing insecurity using diagnostic ICD-10 codes. Demographics and comorbidities were compared between HF patients with and without housing insecurity. An adjusted logistic regression was performed to evaluate the relationships between housing insecurity and socioeconomic status on in-hospital mortality. Using a Cox proportional hazards model, HF patients with and without housing insecurity were evaluated for the risk of all-cause and HF-specific readmissions over time. Of the 1,003,270 hospitalizations for HF in the U.S. in 2020, 16,150 were identified as having housing insecurity (1.6%) and 987,120 were identified as having no housing insecurity (98.4%). The median age of patients with housing insecurity hospitalized for HF was 57, as compared to 73 in the population with no housing insecurity. A higher proportion of patients in the housing insecurity group were Black (35% vs 20.1%) or Hispanic (11.1% vs 7.3%). Patients with housing insecurity were more likely to carry a diagnosis of alcohol use disorder (15.2% vs 3.3%) or substance use disorder (70.2% vs 17.8%), but were less likely to use tobacco (18.3% vs 28.7%). Patients with housing insecurity were over 4.5 times more likely to have Medicaid (52.4% vs 11.3%). Median length of stay did not differ between patients with housing insecurity versus those without. Patients with housing insecurity were more likely to discharge Against Medical Advice (11.4% vs 2.03%). After adjusting for patient characteristics, housing insecurity was associated with lower in-hospital mortality (OR 0.60, 95% CI 0.39 - 0.92). Housing insecurity was associated with a higher risk of all-cause readmissions at 180 days (HR 1.13, 95% CI 1.12 - 1.14). However, there was no significant difference in the risk of HF-specific readmissions at 180 days (HR 1.07, 95% CI 0.998 - 1.14) CONCLUSIONS: Patients with HF and housing insecurity have distinct demographic characteristics. They are also more likely to be readmitted after their initial hospitalization when compared to those without housing insecurity. Identifying and addressing specific comorbid conditions for patients with housing insecurity who are hospitalized for HF may allow clinicians to provide more focused care, with the goal of preventing morbidity, mortality, and unnecessary readmissions.

Health Care Expenditure among US Adults with Heart Failure with and without Diabetes.

The health costs for heart failure (HF) among individuals with and without diabetes can help understand the conjoint burden of diabetes and HF. Using the 2008-2019 US national Medical Expenditure Panel Survey data including 2,019 adults with HF and a 2-part adjusted model, we estimated mean and adjusted incremental direct medical expenditures related to diabetes. The total direct expenditures for individuals with HF increased by 27%: $24,725 (95% confidence interval [CI]: $20,457-$28,993) in 2008-2009 to $31,426 (95% CI: $25,705-$37,147) in 2018-2019. The expenditures rose by 34% among those with diabetes. Inpatient costs represented the highest fraction of costs ∼ 43.3 % and were 8% higher among those with diabetes vs. those without diabetes. The drug costs accounted for 24% of all costs, increased by 44%, and were 86% higher among HF patients with diabetes vs. those without diabetes. The adjusted excess costs among individuals with HF and diabetes vs. HF without diabetes was $6,818 (95% CI: 2,241-11,395); the corresponding excess costs for drugs and medical costs other than drugs were $3,297 (95% CI: 2,168-4,426) and $3,554 (95% CI: -777-7,886). Among US adults with HF, the estimated adjusted total direct excess costs were $5.2 billion per year higher among individuals with diabetes vs. those without diabetes. In conclusion, diabetes is associated with substantially increased health care costs among patients with HF, suggesting the need for an integrated management of diabetes and HF.

Advancements in Incident Heart Failure Risk Prediction & Screening Tools.

Heart Failure (HF) is a major cause of mortality and morbidity in the United States that carries substantial healthcare costs. Multiple risk prediction models and strategies have been developed over the past 30-years with the aim to identify those at high risk of developing HF and implement preventive therapies effectively. This review highlights recent developments in HF risk prediction tools including emerging risk factors, innovative risk prediction models, and novel screening strategies from AI to biomarkers. These developments allow for more accurate prediction but their impact on clinical outcomes remain to be investigated. Implementation of these risk models into clinical practice is a considerable challenge, but HF risk prediction tools offer a promising opportunity to improve outcomes while maintaining value.

Association of Medication Adherence and Health Status in Heart Failure With Reduced Ejection Fraction: Insights From the CHAMP-HF Registry.

BACKGROUND: The foundation for managing heart failure with reduced ejection fraction (HFrEF) is adherence to guideline-directed medical therapy. Finding an association between medication adherence and patients' health status (their symptoms, function, and quality of life) can be used to underscore its importance to patients. METHODS: The association of self-reported medication adherence in US outpatients with HFrEF enrolled in the Change the Management of Patients with Heart Failure registry from 2015 to 2017 was compared with their health status at baseline and 12 months later. A secondary analysis of changes in adherence between baseline and 6 months with 6-month health status was also performed. Medication adherence was assessed with the self-reported 4-item Morisky-Green-Levine Medication Adherence Scale, with scores ≥1 classified as nonadherent. The primary health status outcome was the disease-specific 12-item Kansas City Cardiomyopathy Questionnaire Overall Summary Score (KCCQ-OS; range, 0-100; higher is better). Robust linear regression models adjusted for confounders were used. RESULTS: After excluding those who died (n=316) or did not provide 12-month KCCQ (n=1285), 3495 outpatients with HFrEF were included, of whom 1108 (31.7%) reported being nonadherent. Nonadherent participants were younger, had significantly worse baseline health status (-5.83-point difference; P<0.001), and showed less improvement at 12 months (-1.7-point difference in mean change; P=0.017) than adherent participants. Among nonadherent patients at baseline, those whose adherence improved trended toward greater 6-month health status improvements than those remaining nonadherent (fully adjusted difference of 2.52 points; P=0.054). CONCLUSIONS: In HFrEF, medication nonadherence was associated with worse health status and less improvement over the following year. Improvements in adherence were associated with better health status than remaining nonadherent, underscoring the importance of supporting adherence with guideline-directed medical therapy in patients with HFrEF.

DCRM 2.0: Multispecialty practice recommendations for the management of diabetes, cardiorenal, and metabolic diseases.

The spectrum of cardiorenal and metabolic diseases comprises many disorders, including obesity, type 2 diabetes (T2D), chronic kidney disease (CKD), atherosclerotic cardiovascular disease (ASCVD), heart failure (HF), dyslipidemias, hypertension, and associated comorbidities such as pulmonary diseases and metabolism dysfunction-associated steatotic liver disease and metabolism dysfunction-associated steatohepatitis (MASLD and MASH, respectively, formerly known as nonalcoholic fatty liver disease and nonalcoholic steatohepatitis [NAFLD and NASH]). Because cardiorenal and metabolic diseases share pathophysiologic pathways, two or more are often present in the same individual. Findings from recent outcome trials have demonstrated benefits of various treatments across a range of conditions, suggesting a need for practice recommendations that will guide clinicians to better manage complex conditions involving diabetes, cardiorenal, and/or metabolic (DCRM) diseases. To meet this need, we formed an international volunteer task force comprising leading cardiologists, nephrologists, endocrinologists, and primary care physicians to develop the DCRM 2.0 Practice Recommendations, an updated and expanded revision of a previously published multispecialty consensus on the comprehensive management of persons living with DCRM. The recommendations are presented as 22 separate graphics covering the essentials of management to improve general health, control cardiorenal risk factors, and manage cardiorenal and metabolic comorbidities, leading to improved patient outcomes.

Time to Benefit and Harm of Direct Oral Anticoagulants in Device-Detected Atrial Fibrillation: A Pooled Analysis of the NOAH-AFNET 6 and ARTESiA Trials.

BACKGROUND: Direct oral anticoagulants (DOACs) reduce stroke risk in patients with device-detected atrial fibrillation (DD-AFib) but increase major bleeding risk. The time to benefit (TTB) and time to harm (TTH) are not well quantified. OBJECTIVE: To determine TTB and TTH in DOACs-treated DD-AFib patients. METHODS: Studies were identified from PubMed searching until November 2023. The primary efficacy outcome was the time to first stroke event, and the primary safety outcome was the time to the first major bleeding event. Pooled hazard ratio (HR) and its confidence interval (CI) were calculated through reconstructed patient-level data and study-level data. Weibull model and Markov chain Monte Carlo simulation were applied to determine time to specific absolute risk change thresholds. RESULTS: Two trials involving DOACs, NOAH-AFNET 6 and ARTESiA, were identified, which randomized 6,548 adults with mean age over 75 and a median atrial high-rate episode duration ranging from 1.5 to 2.8 hours. DOACs decreased the risk of stroke (HR 0.67, 95% CI: 0.50 to 0.90) but increased the risk of major bleeding (HR 1.57, 95% CI: 1.21 to 2.04). A TTB of 2.67 years was needed to prevent one stroke per 100 DOACs-treated patients, while a TTH of 1.67 years was needed to observe one major bleeding. CONCLUSIONS: In elderly patients with low durations of DD-AFib, DOACs result in a delayed and restricted stroke-preventive benefit while posing an early-onset bleeding risk. Our findings offer new insights into the risk-benefit profile and provide clinicians an additional dimension to facilitate shared decision-making discussions with patients.

Artificial intelligence approaches for phenotyping heart failure in U.S. Veterans Health Administration electronic health record.

AIMS: Heart failure (HF) is a clinical syndrome with no definitive diagnostic tests. HF registries are often based on manual reviews of medical records of hospitalized HF patients identified using International Classification of Diseases (ICD) codes. However, most HF patients are not hospitalized, and manual review of big electronic health record (EHR) data is not practical. The US Department of Veterans Affairs (VA) has the largest integrated healthcare system in the nation, and an estimated 1.5 million patients have ICD codes for HF (HF ICD-code universe) in their VA EHR. The objective of our study was to develop artificial intelligence (AI) models to phenotype HF in these patients. METHODS AND RESULTS: The model development cohort (n = 20 000: training, 16 000; validation 2000; testing, 2000) included 10 000 patients with HF and 10 000 without HF who were matched by age, sex, race, inpatient/outpatient status, hospital, and encounter date (within 60 days). HF status was ascertained by manual chart reviews in VA's External Peer Review Program for HF (EPRP-HF) and non-HF status was ascertained by the absence of ICD codes for HF in VA EHR. Two clinicians annotated 1000 random snippets with HF-related keywords and labelled 436 as HF, which was then used to train and test a natural language processing (NLP) model to classify HF (positive predictive value or PPV, 0.81; sensitivity, 0.77). A machine learning (ML) model using linear support vector machine architecture was trained and tested to classify HF using EPRP-HF as cases (PPV, 0.86; sensitivity, 0.86). From the 'HF ICD-code universe', we randomly selected 200 patients (gold standard cohort) and two clinicians manually adjudicated HF (gold standard HF) in 145 of those patients by chart reviews. We calculated NLP, ML, and NLP + ML scores and used weighted F scores to derive their optimal threshold values for HF classification, which resulted in PPVs of 0.83, 0.77, and 0.85 and sensitivities of 0.86, 0.88, and 0.83, respectively. HF patients classified by the NLP + ML model were characteristically and prognostically similar to those with gold standard HF. All three models performed better than ICD code approaches: one principal hospital discharge diagnosis code for HF (PPV, 0.97; sensitivity, 0.21) or two primary outpatient encounter diagnosis codes for HF (PPV, 0.88; sensitivity, 0.54). CONCLUSIONS: These findings suggest that NLP and ML models are efficient AI tools to phenotype HF in big EHR data to create contemporary HF registries for clinical studies of effectiveness, quality improvement, and hypothesis generation.

Ongoing and Future Clinical Trials of Pharmacotherapy for Heart Failure.

Increasing knowledge of the processes leading to heart failure (HF) has allowed significant developments in therapies for HF over the past few decades. Despite the evolution of HF treatment, it still places a large burden on patients and health care systems across the world.We used clinicaltrials.gov to gather information about clinical trials as of August 2023 studying pharmacotherapy for HF. We included interventional trials that were "active, not recruiting", "recruiting", or looking for participants but "not yet recruiting". In total, 119 studies met our criteria of ongoing clinical trials studying novel as well as currently approved HF pharmacotherapies. The major interventions were novel medications/already approved medications for other diseases 29 % (34 trials), sodium-glucose co-transporter inhibitors 21 % (25 trials), angiotensin receptor blocker-neprilysin inhibitors 10 % (12 trials), diuretics 14 % (17 trials) and mineralocorticoid receptor antagonists 5 % (6 trials). Ongoing research will aid in reducing the impact of HF and we summarize clinical trials leading the way to better HF treatment in this review.

Mapping the Ecological Terrain of Stroke Prehospital Delay: A Nationwide Registry Study.

BACKGROUND: Delays in hospital presentation limit access to acute stroke treatments. While prior research has focused on patient-level factors, broader ecological and social determinants have not been well studied. We aimed to create a geospatial map of prehospital delay and examine the role of community-level social vulnerability. METHODS: We studied patients with ischemic stroke who arrived by emergency medical services in 2015 to 2017 from the American Heart Association Get With The Guidelines-Stroke registry. The primary outcome was time to hospital arrival after stroke (in minutes), beginning at last known well in most cases. Using Geographic Information System mapping, we displayed the geography of delay. We then used Cox proportional hazard models to study the relationship between community-level factors and arrival time (adjusted hazard ratios [aHR] <1.0 indicate delay). The primary exposure was the social vulnerability index (SVI), a metric of social vulnerability for every ZIP Code Tabulation Area ranging from 0.0 to 1.0. RESULTS: Of 750 336 patients, 149 145 met inclusion criteria. The mean age was 73 years, and 51% were female. The median time to hospital arrival was 140 minutes (Q1: 60 minutes, Q3: 458 minutes). The geospatial map revealed that many zones of delay overlapped with socially vulnerable areas (https://harvard-cga.maps.arcgis.com/apps/webappviewer/index.html?id=08f6e885c71b457f83cefc71013bcaa7). Cox models (aHR, 95% CI) confirmed that higher SVI, including quartiles 3 (aHR, 0.96 [95% CI, 0.93-0.98]) and 4 (aHR, 0.93 [95% CI, 0.91-0.95]), was associated with delay. Patients from SVI quartile 4 neighborhoods arrived 15.6 minutes [15-16.2] slower than patients from SVI quartile 1. Specific SVI themes associated with delay were a community's socioeconomic status (aHR, 0.80 [95% CI, 0.74-0.85]) and housing type and transportation (aHR, 0.89 [95% CI, 0.84-0.94]). CONCLUSIONS: This map of acute stroke presentation times shows areas with a high incidence of delay. Increased social vulnerability characterizes these areas. Such places should be systematically targeted to improve population-level stroke presentation times.

Cause-Specific Health Care Costs Following Hospitalization for Heart Failure and Cost Offset With SGLT2i Therapy.

BACKGROUND: Little is known regarding differences in cause-specific costs between heart failure (HF) with ejection fraction (EF) ≤40% vs >40%, and potential cost implications of sodium glucose co-transporter 2 inhibitor (SGLT2i) therapy. OBJECTIVES: This study sought to compare cause-specific health care costs following hospitalization for HF with EF ≤40% vs >40% and estimate the cost offset with implementation of SGLT2i therapy. METHODS: This study examined Medicare beneficiaries hospitalized for HF in the Get With The Guidelines-Heart Failure registry from 2016 to 2020. Mean per-patient total (excluding drug costs) and cause-specific costs from discharge through 1-year follow-up were calculated and compared between EF ≤40% vs >40%. Next, risk reductions on total all-cause and HF hospitalizations were estimated in a trial-level meta-analysis of 5 pivotal trials of SGLT2is in HF. Finally, these relative treatment effects were applied to Medicare beneficiaries eligible for SGLT2i therapy to estimate the projected cost offset with implementation of SGLT2i, excluding drug costs. RESULTS: Among 146,003 patients, 50,598 (34.7%) had EF ≤40% and 95,405 (65.3%) had EF >40%. Mean total cost through 1 year was $40,557. Total costs were similar between EF groups overall but were higher for EF ≤40% among patients surviving the 1-year follow-up period. Patients with EF >40% had higher costs caused by non-HF and noncardiovascular hospitalizations, and skilled nursing facilities (all P < 0.001). Trial-level meta-analysis of the 5 SGLT2i clinical trials estimated 11% (rate ratio: 0.89; 95% CI: 0.84-0.93; P < 0.001) and 29% (rate ratio: 0.71; 95% CI: 0.66-0.76; P < 0.001) relative reductions in rates of total all-cause and HF hospitalizations, respectively, regardless of EF. Reductions in all-cause and HF hospitalizations were projected to reduce annual costs of readmission by $2,451 to $2,668 per patient with EF ≤40% and $1,439 to $2,410 per patient with EF >40%. CONCLUSIONS: In this large cohort of older U.S. adults hospitalized for HF, cause-specific costs of care differed among patients with EF ≤40% vs >40%. SGLT2i significantly reduced the rate of HF and all-cause hospitalizations irrespective of EF in clinical trials, and implementation of SGLT2i therapy in clinical practice is projected to reduce costs by $1,439 to $2,668 per patient over the 1 year post-discharge, excluding drug costs.

Generalizable Approach to Quantifying Guideline-Directed Medical Therapy.

BACKGROUND: Quantifying guideline-directed medical therapy (GDMT) intensity is foundational for improving heart failure (HF) care. Existing measures discount dose intensity or use inconsistent weighting. METHODS: The Kansas City Medical Optimization (KCMO) score is the average of total daily to target dose percentages for eligible GDMT, reflecting the percentage of optimal GDMT prescribed (range, 0-100). In Change the Management of Patients With HF, we computed KCMO, HF collaboratory (0-7), and modified HF Collaboratory (0-100) scores for each patient at baseline and for 1-year change in established GDMT at the time (mineralocorticoid receptor antagonist, ß-blocker, ACE [angiotensin-converting enzyme] inhibitor/angiotensin receptor blocker/angiotensin receptor neprilysin inhibitor). We compared baseline and 1-year change distributions and the coefficient of variation (SD/mean) across scores. RESULTS: Among 4532 patients at baseline, mean KCMO, HF collaboratory, and modified HF Collaboratory scores were 38.8 (SD, 25.7), 3.4 (1.7), and 42.2 (22.2), respectively. The mean 1-year change (n=4061) for KCMO was -1.94 (17.8); HF collaborator, -0.11 (1.32); and modified HF Collaboratory, -1.35 (19.8). KCMO had the highest coefficient of variation (0.66), indicating greater variability around the mean than the HF collaboratory (0.49) and modified HF Collaboratory (0.53) scores, reflecting higher resolution of the variability in GDMT intensity across patients. CONCLUSIONS: KCMO measures GDMT intensity by incorporating dosing and treatment eligibility, provides more granularity than existing methods, is easily interpretable (percentage of ideal GDMT), and can be adapted as performance measures evolve. Further study of its association with outcomes and its usefulness for quality assessment and improvement is needed.

Time to benefit of colchicine in patients with cardiovascular disease: A pooled analysis of randomized controlled trials.

Background: Low-dose colchicine has been shown to lower major adverse cardiovascular events (MACE) among those with cardiovascular disease (CVD). It remains unclear how long a CVD patient needs to live to potentially benefit from colchicine. Our study aimed to determine the time to benefit (TTB) of colchicine in individuals with CVD. Methods: Literature searches were performed in PubMed for the cardiovascular outcome trial of colchicine in patients with CVD until October 12, 2023. The primary outcome measured was MACE. Reconstructed individual participant data (IPD) and the stratified Cox proportional hazards model were used to calculate the hazard ratio (HR) and 95 % confidence interval (CI) to estimate the efficacy of colchicine, and Weibull survival curves were fitted to estimate TTB for specific absolute risk reduction (ARR) thresholds (0.002, 0.005, and 0.01). Results: Four trials randomizing 11,594 adults aged between 59.8 and 66.5 years were included (follow-up duration: 12-28.6 months). Compared with placebo, colchicine reduced the risk of MACE (HR 0.68, 95 % CI: 0.60 to 0.78) but had no impact on cardiovascular and all-cause mortality. A TTB of 11.0 months (95 % CI: 0.59 to 21.3) was estimated to be needed to prevent 1 MACE in 100-colchicine-treated patients. The TTB for acute coronary syndrome was similar compared to stable coronary artery disease (10.7 vs. 11.2 months for ARR = 0.010). Conclusions: By using reconstructed IPD, this pooled analysis demonstrated that colchicine was associated with reduced nonfatal MACE, and the TTB was approximately 11.0 months to prevent 1 MACE per 100 patients.

Prognostic implications of heart failure stages among Chinese community populations: insight from a nationwide population-based study.

Background: In light of high burden of heart failure (HF) in China, studies of prognostic implication of HF stages are important. We aimed to evaluate the relationship between HF stages and mortality risk in Chinese community populations. Methods: Nationwide representative populations aged ≥35 years (n = 23,284, mean age 56.9 years, women 53.2%) were enrolled from 2012 to 2016. According to the international HF guidelines, participants were divided into stage A, B and C, and those who did not qualify these stages were categorized as apparently-healthy group. Association between HF stages and all-cause, cardiovascular [CV] and non-CV death was evaluated using multivariable-adjusted Cox proportional regression analysis. Findings: During a median follow-up of 4.7 years (109,902.8 person-years), 1314 deaths occurred. Age-adjusted incidence rate of all-cause death was 5.3 in apparently-healthy, 7.8 in stage A, 8.6 in stage B and 24.6 in stage C groups per 1000 person-years. In reference to apparently-healthy group, adjusted hazard ratio for all-cause death was 1.90 (95% CI: 1.47-2.45), 2.43 (95% CI: 1.89-3.13) and 6.40 (95% CI: 4.56-8.99) for stage A, B and C. Advancing HF stages were associated with increasing risks for all-cause, CV and non-CV death (P-trend <0.05). For all-cause death, population attributable fraction due to stage A, B and C were 21.2%, 33.4% and 4.9%, accounting for 1,933,385, 3,045,993 and 446,867 deaths in China in 2018. Interpretation: Advancing HF stages were associated with increasing risk mortality. Development and implementation of early screening and targeted interventions are urgently needed to reduce HF burdens in China. Funding: This work was supported by the Chinese Academy of Medical Sciences Innovation Fund for Medical Sciences (grant 2017-I2M-1-004), the Projects in the Chinese National Science & Technology Pillar Program during the Twelfth Five-year Plan Period (No.: 2011BAI11B01), and the Project Entrusted by the National Health Commission of the People's Republic of China (NHC2020-609).

Cost-Effectiveness of Medical Therapy for Heart Failure With Mildly Reduced and Preserved Ejection Fraction.

BACKGROUND: Three medications are now guideline-recommended treatments for heart failure with mildly reduced or preserved ejection fraction (HFmrEF/HFpEF), however, the cost-effectiveness of these agents in combination has yet to be established. OBJECTIVES: The purpose of this study was to determine the cost-effectiveness of mineralocorticoid receptor antagonists (MRA), angiotensin receptor-neprilysin inhibitors (ARNIs), and sodium glucose co-transporter 2 inhibitors (SGLT2is) in individuals with HFmrEF/HFpEF. METHODS: Using a 3-state Markov model, we performed a cost-effectiveness study using simulated cohorts of 1,000 patients with HFmrEF and HFpEF. Treatment with 1-, 2-, and 3-drug combinations was modeled. Based on a United States health care sector perspective, outcome data was used to calculate incremental cost-effectiveness ratios (ICERs) in 2023 United States dollars based on a 30-year time horizon. RESULTS: Treatment with MRA, MRA+SGLT2i, and MRA+SGLT2i+ARNI therapy resulted in an increase in life years of 1.04, 1.58, and 1.80 in the HFmrEF subgroup, respectively, and 0.99, 1.54, and 1.77 in the HFpEF subgroup, respectively, compared with placebo. At a yearly cost of $18, MRA therapy resulted in ICERs of $10,000 per quality-adjusted life year (QALY) in both subgroups. The ICER for the addition of SGLT2i therapy ($4,962 per year) was $113,000 per QALY in the HFmrEF subgroup and $141,000 in the HFpEF subgroup. The addition of ARNI therapy ($5,504 per year) resulted in ICERs >$250,000 per QALY in both subgroups. If SGLT2i and ARNI were available at generic pricing the ICERs become <$10,000 per QALY in both EF subgroups. Outcomes were highly sensitive to assumed benefit in cardiovascular death. CONCLUSIONS: For patients with heart failure, MRA was of high value, SGLT2i was of intermediate value, and ARNI was of low value in both HFmrEF and HFpEF subgroups. For patients with HFmrEF/HFpEF increased use of MRA and SGLT2i therapies should be encouraged and be accompanied with efforts to lower the cost of SGLT2i and ARNI therapies.

Prediction of Large Vessel Occlusion Stroke Using Clinical Registries for Research.

OBJECTIVES: A reliable method of predicting large vessel occlusion (LVO) stroke in data sets without neuroimaging could be retrospectively applied to expand research efforts. METHODS: We conducted a retrospective, cross-sectional cohort analysis of the Get With The Guidelines (GWTG)-Stroke registry. We included adult patients with a final diagnosis of ischemic stroke from 2016 to 2021 who had brain and vascular imaging and excluded those with missing data or posterior circulation stroke. RESULTS: We included 416,022 patients of which 125,381 (30.1%) had LVO. The mean age was 71 years, and 48.2% were female. The area under the receiver operating curve (AUC) for the final model, including age, sex, hypertension, dyslipidemia, atrial fibrillation, diabetes, TOAST stroke mechanism, and NIH Stroke Scale (NIHSS), was 0.79 (95% CI 0.79-0.80). Without TOAST mechanism, the AUC was 0.74. The specificity did not exceed 0.5 using different cut points for the NIHSS. DISCUSSION: We found that 30% of adult acute ischemic stroke patients in GWTG-Stroke have LVO and that the combination of clinical covariates and NIHSS is only moderately predictive of LVO status. These results are consistent with previous studies and suggest it may not be possible to retrospectively predict LVO with high accuracy in data sets without vascular neuroimaging.

Identification and outcomes of KDIGO-defined chronic kidney disease in 1.4 million U.S. Veterans with heart failure.

AIMS: According to the Kidney Disease: Improving Global Outcomes (KDIGO) guideline, the definition of chronic kidney disease (CKD) requires the presence of abnormal kidney structure or function for >3 months with implications for health. CKD in patients with heart failure (HF) has not been defined using this definition, and less is known about the true health implications of CKD in these patients. The objective of the current study was to identify patients with HF who met KDIGO criteria for CKD and examine their outcomes. METHODS AND RESULTS: Of the 1 419 729 Veterans with HF not receiving kidney replacement therapy, 828 744 had data on ≥2 ambulatory serum creatinine >90 days apart. CKD was defined as estimated glomerular filtration rate (eGFR) <60 ml/min/1.73 m2 (n = 185 821) or urinary albumin-to-creatinine ratio (uACR) >30 mg/g (n = 32 730) present twice >3 months apart. Normal kidney function (NKF) was defined as eGFR ≥60 ml/min/1.73 m2, present for >3 months, without any uACR >30 mg/g (n = 365 963). Patients with eGFR <60 ml/min/1.73 m2 were categorized into four stages: 45-59 (n = 72 606), 30-44 (n = 74 812), 15-29 (n = 32 077), and <15 (n = 6326) ml/min/1.73 m2. Five-year all-cause mortality occurred in 40.4%, 57.8%, 65.6%, 73.3%, 69.7%, and 47.5% of patients with NKF, four eGFR stages, and uACR >30mg/g (albuminuria), respectively. Compared with NKF, hazard ratios (HR) (95% confidence intervals [CI]) for all-cause mortality associated with the four eGFR stages and albuminuria were 1.63 (1.62-1.65), 2.00 (1.98-2.02), 2.49 (2.45-2.52), 2.28 (2.21-2.35), and 1.22 (1.20-1.24), respectively. Respective age-adjusted HRs (95% CIs) were 1.13 (1.12-1.14), 1.36 (1.34-1.37), 1.87 (1.84-1.89), 2.24 (2.18-2.31) and 1.19 (1.17-1.21), and multivariable-adjusted HRs (95% CIs) were 1.11 (1.10-1.12), 1.24 (1.22-1.25), 1.46 (1.43-1.48), 1.42 (1.38-1.47), and 1.13 (1.11-1.16). Similar patterns were observed for associations with hospitalizations. CONCLUSION: Data needed to define CKD using KDIGO criteria were available in six out of ten patients, and CKD could be defined in seven out of ten patients with data. HF patients with KDIGO-defined CKD had higher risks for poor outcomes, most of which was not explained by abnormal kidney structure or function. Future studies need to examine whether CKD defined using a single eGFR is characteristically and prognostically different from CKD defined using KDIGO criteria.

Twenty Years of Get With The Guidelines-Stroke: Celebrating Past Successes, Lessons Learned, and Future Challenges.

The Get With The Guidelines-Stroke program which, began 20 years ago, is one of the largest and most important nationally representative disease registries in the United States. Its importance to the stroke community can be gauged by its sustained growth and widespread dissemination of findings that demonstrate sustained increases in both the quality of care and patient outcomes over time. The objectives of this narrative review are to provide a brief history of Get With The Guidelines-Stroke, summarize its major successes and impact, and highlight lessons learned. Looking to the next 20 years, we discuss potential challenges and opportunities for the program.