PubMed · 11026375
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H Morita, R Nagai. 2000. [Heart failure].. https://pubmed.ncbi.nlm.nih.gov/11026375/
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BACKGROUND: Heart failure (HF) progression is closely linked to oxidative stress. 5-Oxoproline (5-OP), a product of glutathione degradation, is normally metabolized by 5-oxoprolinase (OPLAH) but accumulates when the gamma-glutamyl cycle is disrupted. Here, we investigated the clinical characteristics of circulating 5-OP, its proteomic correlates, and the associations to outcome in HF. METHODS: In serum of 823 BIOSTAT-CHF patients, 5-OP was quantified by validated liquid chromatography-mass spectrometry and analyzed for associations with clinical outcomes. Proteomic correlates were identified across 355 OLINK proteins using stability selection with Minimax Concave Penalty regression. Mechanistic context was evaluated in a multi-comorbidity, large-animal cardio-kidney-metabolic (CKM) model with regional OPLAH assessment. RESULTS: Higher 5-OP was associated with worse renal function (eGFR declining across 5-OP tertiles, 67.9 to 60.2 mL/min/1.73 m2; p = 0.0012) and higher all-cause mortality (HR 1.55, 95% CI 1.11-2.17, p = 0.010). Per SD increase in log-5-OP, risk for the 2-year composite endpoint increased (HR 1.27, 95% CI 1.05-1.53), with broadly similar associations across CKD strata (interaction p = 0.63). TGF-α was the most robust proteomic correlate (π = 0.70; empirical permutation p = 0.001). In CKM swine, circulating 5-OP was elevated and renal cortical OPLAH protein, but not cardiac OPLAH, was selectively reduced, consistent with a renal contribution to systemic 5-OP elevation. CONCLUSION: Circulating 5-OP identifies HF patients at higher risk and is robustly associated with TGF-α. In a translational swine model, selective loss of renal cortical OPLAH provides tissue context supporting a renal contribution to systemic 5-OP elevation in cardiorenal syndrome.
Evolving statistical concepts and innovative trial designs for heart failure (HF) clinical trials seek to improve the conduct, efficiency, and likelihood of meaningful evidence generation crucial for advancing therapeutic development and optimizing patient care. HF trials with conventional statistical frameworks often require large sample sizes, long follow-up times, and high cost to generate sufficient evidence. Novel statistical methodologies would be of interest if they could address these issues while retaining or enhancing the clinical relevance and reliability of results. The HFC (Heart Failure Collaboratory), comprising clinical investigators, clinicians, statisticians, patients, government representatives, payors, and industry collaborators, leads efforts to improve HF research methodologies. HFC discussions have included statistical concepts such as the estimand framework, HR drift, and analytic methods, including the win ratio and restricted mean survival time, that have not been used frequently in HF trials. The estimand framework encourages precise definition and alignment of trial objectives with trial design. The win ratio method attempts to incorporate and prioritize multiple clinically meaningful outcomes by using a hierarchy of clinical importance. The restricted mean survival time provides an alternative to the HR as a measure of therapeutic effect by quantifying the mean time gained or lost during a fixed time after randomization. This paper provides a critical review of some evolving HF trial design methodologies and statistical concepts for the HF community as discussed within the HFC. Our goal is to foster collaboration among diverse stakeholders and advance the development of effective treatments and improve patient care outcomes.
OBJECTIVE: To determine the effect of time since onset of risk factors on the modeling of risk factors for ischemic stroke. METHODS: The resources of the Rochester Epidemiology Project allowed identification of the 1,397 incident cases of ischemic stroke and age- and sex-matched control subjects from the population for 1970 through 1989. These cases and controls permitted the development of a multiple conditional logistic regression model to estimate the odds ratios of ischemic stroke for various risk factors. The time since onset variables for each risk factor were then added to the model to determine which were significant and to assess their impact on variables in the model. RESULTS: The time since onset variables for congestive heart failure and TIA were the only variables of this type included in the resultant model. Each showed the highest risk for stroke soon after the onset of the risk factor. In addition, the influence of congestive heart failure was higher at younger ages. Hypertension (with or without left ventricular hypertrophy) increases the risk for stroke but has a diminishing influence with increasing age. In addition, persons with left ventricular hypertrophy are at a higher risk than those with hypertension alone, although this difference also decreases with age. The time since onset variables pertaining to systolic hypertension at 140 to 159 mm Hg, 160 to 179 mm Hg, and > or =180 mm Hg were not significant in any analysis. CONCLUSIONS: TIA and congestive heart failure were the only risk factors for stroke for which time since onset was significant in the model for predicting ischemic stroke.