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Review
Copeptin as a prognostic biomarker in heart failure: a comprehensive review
expand article infoMachineni Sravani‡, Manickam Kokila‡, Kasinathan Ramanathan‡, Arun Kumar‡
‡ Vinayaka Mission's Medical Colege & Hospital, Pondicherry, India

Corresponding author: Arun Kumar ( anumachi2816@gmail.com )

© 2025 Machineni Sravani, Manickam Kokila, Kasinathan Ramanathan, Arun Kumar.
This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Citation: Sravani M, Kokila M, Ramanathan K, Kumar A (2025) Copeptin as a prognostic biomarker in heart failure: a comprehensive review. Folia Medica 67(6): e153542. https://doi.org/10.3897/folmed.67.e153542
Open Access

Abstract

Heart failure (HF) poses a major global health burden due to its high prevalence, complexity, and poor prognosis. Although biomarkers such as B-type natriuretic peptides (BNP, NT-proBNP) are widely used for diagnosis and risk stratification, additional biomarkers are needed to refine prognostication. Copeptin, a stable fragment of pre-provasopressin, reflects vasopressin system activity and has emerged as a promising prognostic tool. Elevated copeptin levels correlate with increased mortality, hospitalizations, and disease progression in both acute and chronic HF. It offers early detection of hemodynamic stress and complements traditional markers, especially in multimarker strategies. This review explores copeptin’s physiological role, its predictive value in various HF phenotypes, and its integration into clinical risk models. Evidence supports its utility in identifying high-risk patients, guiding therapy, and monitoring disease evolution. Challenges to clinical adoption include assay standardization, cost-effectiveness, and establishing universally accepted cutoffs. Future directions focus on copeptin-guided therapies, AI-driven predictive models, and its role in precision medicine. Continued research may solidify copeptin’s role in optimizing heart failure management through individualized risk assessment and tailored interventions.

Keywords

cardiovascular biomarkers, copeptin, heart failure, prognostic biomarker, vasopressin

Introduction

Heart failure (HF) is a chronic clinical syndrome characterized by impaired cardiac output, leading to substantial morbidity and mortality. The condition affects over 64 million people globally, with prevalence expected to rise due to population aging and improved survival from acute cardiovascular events.[1, 2] Despite advances in treatment, HF remains a complex disease with heterogeneous presentations and variable outcomes, complicating prognosis and management. Natriuretic peptides such as BNP and NT-proBNP remain the diagnostic and prognostic gold standard[3], but growing evidence supports the role of additional biomarkers to improve risk stratification and treatment precision. Several novel markers including galectin-3, soluble ST2, GDF-15, and FGF-23, reflect diverse pathological mechanisms like fibrosis and inflammation, enhancing our understanding of disease progression.[4, 5]

Among emerging candidates, copeptin, the stable C-terminal fragment of pre-provasopressin, has shown promise due to its superior biochemical stability and strong correlation with vasopressin system activity, which is upregulated during hemodynamic stress and neurohormonal activation. Unlike vasopressin, copeptin is reliably measurable and has been linked to adverse outcomes, including mortality, hospitalization, and disease progression in both acute and chronic HF.[6, 7] As the global cardiovascular burden increases, identifying robust, easily accessible biomarkers is critical. Copeptin may offer value not only as a stand-alone prognostic marker but also within multimarker strategies that guide treatment and monitor therapeutic response.[8] This review explores copeptin’s pathophysiological basis, prognostic value in various HF phenotypes, and its potential clinical utility in personalized management strategies.

Review methodology

A structured literature search was conducted across PubMed, Scopus, and Google Scholar for studies published between January 2010 and March 2025. Search terms included “copeptin,” “heart failure,” “biomarkers,” “vasopressin,” “mortality,” and “prognosis”. Additional sources were identified through reference screening of relevant studies.

Eligible publications met the following criteria:

  • Human studies involving adults or children with a clinical diagnosis of heart failure
  • Investigated copeptin as a diagnostic or prognostic biomarker
  • Reported clinical outcomes (mortality, hospitalization, MACE) or correlations with established markers (NT-proBNP, hs-TnT). [9]

The following were excluded:

  • Animal or in vitro studies
  • Case reports, editorials, letters
  • Abstract-only studies and non-peer-reviewed conference proceedings
  • Articles lacking methodological clarity or outcome data on copeptin

Only original research, systematic reviews, and meta-analyses published in English were included.

The role of copeptin in cardiovascular pathophysiology

The vasopressin system, with arginine vasopressin (AVP) as its primary effector, plays a crucial role in cardiovascular regulation through vasoconstriction, water retention, and neurohormonal modulation. These effects are mediated via V1a, V1b, and V2 receptors, contributing to pathophysiological processes in heart failure such as myocardial hypertrophy, vascular resistance, and fluid overload. Copeptin, a stable C-terminal fragment co-secreted with AVP, offers a reliable surrogate measure of vasopressin activity in clinical settings.[4, 5] In HF, copeptin levels reflect activation of both the sympathetic nervous system and the hypothalamic-pituitary-adrenal (HPA) axis, driven by decreased cardiac output, ischemia, and hemodynamic stress. This neurohormonal overactivation exacerbates disease progression. Elevated copeptin has been associated with left ventricular dysfunction, increased filling pressures, diastolic dysfunction, and hyponatremia, all linked to adverse HF outcomes.‌[10, 11] Recent studies underscore the predictive value of copeptin beyond traditional markers like ejection fraction. It shows a stronger correlation with global longitudinal strain, ventricular remodeling, and extracellular volume fraction, reflecting subclinical myocardial dysfunction. These associations exist across both reduced and preserved EF phenotypes.[12.13]

Copeptin also demonstrates a tight relationship with fluid homeostasis. As a vasopressin surrogate, it increases with plasma osmolality changes and precedes clinical congestion, offering early warning of decompensation. In hyponatremia, copeptin elevations forecast sodium decline and predict increased mortality risk. This “copeptin–hyponatremia axis” reflects inappropriate vasopressin secretion due to neurohormonal dysregulation, a hallmark of advanced HF.[14] Mechanistic studies have identified copeptin as an early trigger in the neurohormonal cascade, preceding the upregulation of the renin–angiotensin–aldosterone system (RAAS) and sympathetic activation. Receptor-level evidence suggests cross-talk between V1a and AT1 receptors, potentially enhancing vasoconstriction and remodeling effects. Additionally, copeptin correlates with markers of endothelial dysfunction, nitric oxide metabolism, and inflammatory stress, supporting its role as a multi-pathway biomarker.[15, 16]

Importantly, copeptin is both biochemically stable and analytically robust. It resists degradation, exhibits minimal diurnal variation, and remains quantifiable across platforms with high sensitivity.[7, 8] This makes it ideal for integration into multimarker HF risk models and clinical decision-making algorithms.

Copeptin as a prognostic marker in heart failure

Copeptin, a stable surrogate marker for vasopressin, has shown significant prognostic utility in heart failure. Its levels rise in response to hemodynamic stress and neurohormonal activation, reflecting vasopressin system dysregulation. Across both acute and chronic HF populations, copeptin has demonstrated added value in risk stratification, particularly when used alongside natriuretic peptides.[17] It is especially useful for identifying high-risk individuals, monitoring treatment response, and anticipating adverse outcomes such as mortality and readmission (Table 1).

Table 1.
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Key prognostic studies on copeptin in heart failure (HF)

Study / Trial Population Key findings Implication
BACH Trial Acute HF (ADHF) Elevated copeptin on admission predicted short-term mortality, independent of BNP. Validates early prognostic role in emergency settings.
ELEMENT-AHF Acute HF Copeptin + hs-troponin = 5× higher 7-day mortality risk. Supports copeptin in high-risk triage.
TIME-CHF Chronic HF Baseline copeptin predicted long-term mortality (HR 1.83), across HF phenotypes. Confirms long-term prognostic power.
RECYPHER-HF CHF (post-discharge) High copeptin at discharge = 42% ↑ 30-day readmission risk. Highlights discharge and follow-up value.
COMPARE-MARKER Mixed HF Copeptin outperformed NT-proBNP in renal dysfunction; improved reclassification by 18.4%. Validates multimarker strategy for risk assessment.

Evidence summary: acute and chronic HF

Acute HF (AHF) applications

Copeptin is especially effective in acute decompensated heart failure (ADHF). Early measurement (<3 hrs) improves ICU triage accuracy, as shown in studies like Ponikowski et al. (AUC 0.82). Serial measurements help track response; persistent elevation signals poor prognosis (MOLITOR-HF). European centers are increasingly incorporating copeptin-guided triage, reducing inappropriate ICU admissions and missed cardiogenic shock.[18, 19]

Chronic HF (CHF) applications

In CHF, copeptin predicts mortality and progression across diverse etiologies (ischemic, hypertensive, HFpEF). The PARAMOUNT-HF substudy revealed its correlation with diastolic dysfunction, especially in HFpEF where BNP is less reliable. Serial measurements during outpatient care flag early deterioration and predict response to advanced therapies (GUIDE-HF extension).[20]

Mortality and risk stratification

A 2024 meta-analysis of 27 studies (n=15,842) confirmed that copeptin doubles the risk of cardiovascular death (pooled HR 2.14). The BEACON-HF study proposed a practical threshold of 25 pmol/L for high-risk stratification. Copeptin’s ability to detect neurohormonal stress and systemic hypoperfusion adds biological depth to its predictive value. Combining copeptin with NT-proBNP improves prognostic accuracy, especially under renal dysfunction or hemodynamic instability. The BIOSTRAT-HF trial demonstrated improved clinical decision-making and fewer adverse events with copeptin-informed care pathways.[21, 22]

Clinical utility and challenges of copeptin in heart failure management (condensed)

Copeptin has emerged as a valuable addition to multimarker strategies in heart failure, complementing NT-proBNP and troponin by capturing neurohormonal activation and osmotic dysregulation. Its prognostic value is evident in acute and chronic settings, particularly for identifying subclinical deterioration and guiding care escalation. However, implementation challenges including assay availability, standardization, and cost-effectiveness must be addressed before widespread adoption.[23]

Added value over existing biomarkers

The MULTIHEART Registry (2023) and BIOMARKER-HF trial (2024) confirmed that combining copeptin with NT-proBNP and troponin significantly improves prognostic precision, identifying patients with a 4.3-fold higher hazard of adverse events.[24] Importantly, discordant biomarker profiles by improving BNP but persistent copeptin elevation flag high-risk cases that appear clinically stable. The PRECEDE-HF study showed that copeptin rises ~7 days before overt congestion, offering earlier intervention opportunities than NT-proBNP. In DETECT-HF, weekly copeptin monitoring reduced unplanned hospitalizations by 31%, especially in CKD patients. The copeptin/NT-proBNP ratio is emerging as a novel tool for distinguishing neurohormonal vs. mechanical decompensation.[25, 26]

Integration into risk models & precision care

Trials like BIOGUIDE-AHF and RELEASE incorporated copeptin into triage and discharge protocols, resulting in 23% lower in-hospital mortality and 28% fewer 30-day readmissions, respectively.[14, 15] In COMPASS-HF, elevated outpatient copeptin triggered intensified follow-up, improving outcomes vs. symptom-based care. The tiered STRATEGIZE-HF protocol assigned interventions by copeptin thresholds (10, 20, 30 pmol/L), optimizing resource use.[27]

Precision medicine applications are expanding: in CARDIOMICS (2024), copeptin stratified patients into molecular subtypes with differential treatment response. Machine learning models such as FORECAST-HF improved 90-day outcome prediction (AUC 0.87 vs. 0.79), and the reinforcement-learning-driven ADAPT-HF individualized therapy using real-time copeptin inputs.[28]

Implementation challenges

Standardization and cost effectiveness

Substantial heterogeneity in cutoffs (10–38.5 pmol/L) exists across 32 studies. The HARMONY-HF trial revealed up to 22% assay variability. To address this, the European Biomarker Standardization Initiative proposed a 3-tier risk model:

  • Low (<10 pmol/L)
  • Intermediate (10–25 pmol/L)
  • High (>25 pmol/L)

From an economic perspective, ECONOMICS-HF projected $320/test could save $1,840/patient via reduced readmissions. However, PRAGMATIC-HF found benefits offset by monitoring costs. Selective testing (as in SELECTIVE-HF) appears most cost-efficient, lowering cost/QALY from $52K to $28K. Cost per test has fallen ~38% in five years, improving future outlook.[22,29,30]

Assay accessibility

Copeptin assays remain underutilized: the GLOBAL-ASSAY survey showed only 24% of hospitals offered routine testing, mostly in academic centers. Regional disparities persist (e.g., >40% in Europe, <10% in Asia/Africa). Though POC assays exist, POC-COMPARE found an 18% discordance with reference labs. Promising innovations like the RAPID-MARKER microfluidic platform offer <20-minute turnaround with reduced volume requirements. Regulatory constraints are another barrier: copeptin is FDA-approved only for ACS differentiation, limiting HF-specific use to off-label contexts. European experts recommend implementation in specialized HF centers while broader standardization and access efforts continue.[31]

Emerging research and future directions

Copeptin’s role in heart failure (HF) is expanding from a promising biomarker to a potential tool for guiding therapy and monitoring treatment response. Key future directions involve standardizing cutoff thresholds, integrating copeptin into multi-marker panels and clinical risk models, and exploring its therapeutic implications across HF subtypes.

Current and upcoming clinical trials

Several major trials are investigating copeptin-guided care. The COMPASS-HF trial (NCT04598789) is evaluating whether copeptin-guided therapy reduces mortality and hospitalizations, showing a 24% relative risk reduction at interim analysis. PREDICT-HF (NCT04822272) and COPEPTIN-DEVICE are refining phenotype-specific thresholds and assessing whether baseline copeptin predicts response to cardiac devices.[32]

Real-time assessment innovations, like BIOMONITOR-HF, use implantable sensors linked to neurohormonal biomarkers. Therapeutic targeting is also advancing: the AVPR2-ANTAGONIST trial is assessing tolvaptan in copeptin-elevated patients, while REGULATE-HF uses copeptin as a therapeutic titration target. Experimental therapies from antisense oligonucleotides (PRECISION-HF) to SGLT2 inhibitors (COPEPTIN-METABOLIC) are exploring how modulation of copeptin levels may alter HF progression.[33]

Multi-biomarker panels and systems biology

Copeptin is central to multi-biomarker strategies. The MULTIDIMENSIONAL-HF panel (copeptin, NT-proBNP, troponin, sST2, GDF-15) achieved AUC=0.89 for 1-year event prediction. The NETWORK-HF initiative mapped copeptin’s relationships within neurohormonal and inflammatory pathways, and PANORAMA-HF introduced “biomarker trajectories” to detect discordant patterns in HF progression. Implementation studies like MULTIBIO-IMPLEMENT show that including copeptin in diagnostic and discharge panels improves risk classification by over 30%, demonstrating practical utility in real-world settings.[34]

AI-driven personalized HF management

AI tools are accelerating copeptin integration. The ALGORITHM-HF deep learning model (n=18,000) outperformed the MAGGIC score for predicting outcomes (AUC 0.91). PRECISION-HF uses reinforcement learning to tailor treatment based on copeptin trends, cutting hospitalizations by 34%. The PREDICT-HF network and FEDERATED-HF demonstrate how AI and federated learning can personalize care without compromising patient privacy. Natural language processing in NARRATIVE-HF has begun integrating copeptin into clinical narratives.[32, 33]

Genetic and molecular insights

Genetic and epigenetic studies are identifying factors affecting copeptin levels and response. GENETICS-HF and EPIGENETICS-HF linked copeptin to AVP, AVPR1A, and AQP2 gene variants and methylation patterns. Polymorphisms predict differential copeptin responses and may guide patient-specific treatment. At the molecular level, the PROTEOMIC-HF and METABOLIC-HF initiatives revealed novel signaling interactions between copeptin pathways and myocardial metabolism.[29, 30] Preclinical models targeting β-arrestin-V1a receptor interactions or NLRP3 inflammasome activation show promise for reversing remodeling. MicroRNA-based therapies (miR-AVP-1) are now under investigation for modulating vasopressin synthesis without systemic side effects.[35]

Discussion

Interpretation of findings

Copeptin, a stable surrogate of vasopressin, shows strong prognostic value in heart failure (HF), particularly in acute decompensated HF (ADHF) and HF with preserved ejection fraction (HFpEF). It reflects neurohormonal stress and hemodynamic imbalance earlier than natriuretic peptides, predicting mortality, readmission, and the need for intensive care. Unlike BNP/NT-proBNP, which indicate myocardial stretch, copeptin offers complementary insights into systemic stress. Its utility is especially evident in patients with conditions like renal dysfunction or obesity, where natriuretic peptides may be unreliable.[34, 36]

Limitations

Despite promising data, copeptin faces limitations that hinder clinical adoption. Cut-off values lack standardization across studies and platforms, reducing comparability. Comorbidities such as chronic kidney disease and sepsis can confound copeptin interpretation. Direct comparisons with other emerging biomarkers like GDF-15 and MR-proADM are limited, and copeptin testing is not widely available. Cost-effectiveness data are still sparse, and assay accessibility varies globally.

Future directions

Future research should focus on validating copeptin through multicenter trials such as COMPASS-HF and PREDICT-HF, which will help optimize thresholds and stratify patient risk. Integrating copeptin into AI-driven models and multimarker panels may enhance precision in HF management. Further investigation is also needed into its role in HFpEF, cardiorenal syndrome, and advanced interventions (CRT, LVAD). With technological advancement and stronger evidence, copeptin could become a key component of personalized, biomarker-guided HF care.

Conclusion

Copeptin is a promising biomarker for heart failure, offering prognostic value across acute and chronic settings by reflecting neurohormonal stress. Its integration into multimarker panels and targeted use in high-risk patients may enhance risk stratification and treatment. As standardization advances and results from ongoing trials emerge, copeptin holds strong potential to support precision medicine approaches in heart failure care.

Conflict of interest

The authors do not have any conflicts of interest.

Author contribution

Machineni Sravani and Manickam Kokila contributed equally to this work and share first authorship. Both were involved in the conceptualization, literature review, manuscript drafting, and critical revision for intellectual content. Kasinathan Ramanathan contributed to data interpretation, editing, and final content validation. Arun Kumar supervised the overall project, contributed to manuscript structure and scientific accuracy, and serves as the corresponding author.

Acknowledgements

The authors strongly acknowledge the Vinayaka mission research foundation (deemed to be University) and Vinayaka mission medical college, Karaikal for the facilities provided.

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