Hypoperfusion-Shock Continuum in Acute Decompensated Heart Failure

Abstract

Acute decompensated heart failure is a clinical syndrome characterized by upregulation of neurohormonal compensatory mechanisms that, while intended to preserve organ perfusion as a response to reduced cardiac output, progressively exacerbate systemic congestion. Perfusion, defined by adequate oxygen delivery to the tissues, is more complex than simple cardiac output and arterial inflow, and is also significantly influenced by venous backpressure, as well as microcirculatory autoregulation. Therefore, as venous pressures continue to rise, these may ultimately contribute to hypoperfusion and, therefore, cardiogenic shock (CS). Other mechanisms, such as inflammation and increased organ capsular pressure, can contribute to further impairments in tissue oxygenation. This gradual and often clinically unrecognized deterioration from acute decompensated heart failure to heart failure–related CS (HF-CS) contrasts with acute myocardial infarction–related CS, where underlying compensatory mechanisms are more limited. Furthermore, prolonged and unrecognized hypoperfusion may further worsen HF-CS through progressive microcirculatory dysfunction with subsequent uncoupling of macrocirculation and microcirculation. At this point, normalization of macrocirculatory parameters may no longer restore tissue oxygenation. Early identification of hypoperfusion is, therefore, critical so that interventions targeting systemic hemodynamics may still improve tissue perfusion and reverse circulatory collapse. This review (1) outlines the pathophysiology of hypoperfusion in HF-CS; (2) summarizes invasive, biochemical, and imaging parameters to detect hypoperfusion; (3) phenotypes HF-CS profiles; and (4) proposes a monitoring framework for hypoperfusion in HF-CS.

Acute heart failure (HF) is a serious condition and the leading cause for hospitalization. Up to 10% of the patients die during their admission, and once discharged, 30% die within 1 year following hospitalization.¹ Acute decompensated HF (ADHF) represents the most common manifestation of acute HF, accounting for up to 70% of cases.²

ADHF is primarily characterized by systemic congestion, which develops over days to weeks before symptoms become severe enough for patients to seek medical attention.³ The gradual onset is important to acknowledge, as, during this time, neurohormonal compensatory mechanisms are activated to maintain perfusion of tissues and vital organs. Conversely, these compensatory mechanisms may mask worsening hemodynamics, resulting in hypoperfusion that is not readily detected through clinical assessment or basic hemodynamic measures alone. Without timely intervention, this can ultimately lead to HF-related cardiogenic shock (HF-CS), a state of critical circulatory failure. The insidious progression of ADHF to HF-CS contrasts the pathophysiology of acute myocardial infarction–related cardiogenic shock (AMI-CS), where acute ventricular failure lacks such compensatory mechanisms and is, therefore, more easily recognized. Although the relative risk of death is higher in AMI-CS, HF-CS carries a substantial short-term mortality, with reported rates of 25% to 51%.^4,5 A comprehensive overview of the differences between AMI-CS and HF-CS is shown in Table 1.

Table 1.

Differences Between AMI-CS and HF-CS

In this article, we first examine the mechanisms underlying hypoperfusion in HF-CS. We then review invasive, biochemical, and imaging modalities for their detection and subsequent profiling of HF-CS phenotypes. Finally, we discuss a clinical decision framework tailored to hypoperfusion in HF-CS.

Hypoperfusion in ADHF

Pathophysiology of ADHF

Figure 1 depicts the vicious cycle by which HF deteriorates into ADHF. In summary, ADHF develops due to increasing cardiac filling pressures and reduced cardiac output (CO), often triggered by a (cardiac) event. The neurohormonal axis, initially activated to preserve perfusion of vital organs, ultimately leads to increasing systemic congestion. Sympathetic stimulation induces vasoconstriction, increasing the stressed blood volume by recruiting blood from the unstressed volume (largely in the splanchnic venous reservoir), increasing venous return and filling pressures.⁶

Figure 1.

Acute decompensated heart failure pathophysiology. (1) ↓ Cardiac output; (2) ↓ forward blood flow; (3) sympathetic vasoconstriction; (4) recruitment of stressed blood volume; (5) ↑ central venous pressure (CVP) via ↑ venous return; (6) renal autoregulation (afferent constriction); (7) renin-angiotensin-aldosterone system (RAAS) activation; (8) angiotensin II release; (9) efferent constriction; (10) aldosterone secretion; (11) vasopressin release; (12) ↑ proximal Na⁺/H₂O reabsorption; (13) ↑ renal venous pressure; (14) ↓ filtration gradient; (15) reinforced Na⁺/H₂O retention; (16) further ↑ CVP; and (17) cardiac remodeling.

At the renal level, reduced forward flow combined with increased central venous pressure (CVP) leads to a decline in renal blood flow.⁷ Intrarenal autoregulation, including both the myogenic response and tubuloglomerular feedback, initially preserves glomerular hydrostatic pressure and stabilizes glomerular filtration rate despite falling renal blood flow. Tubuloglomerular feedback, by sensing reduced chloride delivery to the macula densa, modulates afferent arteriole tone to maintain sodium balance and triggers renin release. This compensation, however, occurs at the expense of an increased filtration fraction, which enhances proximal tubular reabsorption of sodium and water. Concurrently, elevated renal venous and interstitial pressures increase back pressure on the glomerular capillaries, diminishing net starling forces and, thereby, reducing the effective transglomerular filtration gradient despite autoregulatory efforts. The resultant reduction in distal sodium chloride delivery further stimulates renin release and systemic activation of the renin-angiotensin-aldosterone system. Angiotensin II, the principal effector of renin-angiotensin-aldosterone system, preferentially constricts the efferent arteriole to preserve glomerular filtration pressure despite reduced renal perfusion, further increasing proximal tubular sodium and water reabsorption. In addition, angiotensin II stimulates aldosterone secretion, which enhances distal tubular sodium retention and potassium excretion. Finally, elevated angiotensin II levels, together with baroreceptor-mediated nonosmotic pathways, augment vasopressin secretion, further promoting free water retention. Collectively, these mechanisms drive sodium and water retention, diuretic resistance, and progressive volume overload, thereby exacerbating cardiac filling pressures to promote pathological cardiac remodeling, inflammation, and a self-reinforcing cycle of worsening HF and renal dysfunction referred to as the cardiorenal syndrome. The Ronco classification describes several subtypes of cardiorenal syndrome, with type 1 being most common, up to 50%, in ADHF and reflecting impaired renal perfusion due to acute cardiac dysfunction, whereas type 2 refers to chronic kidney disease secondary to chronic HF. However, the reverse interaction, cardiac dysfunction due to acute or chronic renal failure, also occurs.⁸

Clinical Risk Factors of ADHF

Various patient-specific factors contribute to increased susceptibility to hemodynamic deterioration in ADHF. A severely reduced left ventricular (LV) ejection fraction is associated with increased mortality in ADHF.⁹ However, it should be noted that it does not necessarily guide immediate clinical management in ADHF, and unlike AMI-related cardiogenic shock (CS),¹⁰ its short-term prognostic value in HF-CS remains unclear. When accompanied by right ventricular (RV) dysfunction, the risk of systemic congestion and multiorgan involvement rises substantially.¹¹ A history of HF hospitalizations signals progressive disease.¹² Episodes of ventricular arrhythmias or shocks from an implantable cardioverter defibrillator reflect an unstable trajectory.¹³ The discontinuation of guideline-directed medical therapy due to hypotension or worsening renal function marks an advanced stage of HF.¹⁴ Persistence of volume overload despite escalating doses of diuretics, suggesting diuretic resistance and impaired renal perfusion, serves as an early marker of a downward hemodynamic trend in ADHF.¹⁵ Finally, risk profiles differ between acute-on-chronic and de novo HF: de novo patients may decline rapidly with initially preserved organ function and greater hemodynamic instability, while acute-on-chronic patients typically have more structural heart disease, chronic neurohormonal activation, and organ dysfunction, leading to reduced compensatory capacity and higher mortality.⁴

These high-risk features, categorized as low risk, intermediate risk, and high risk, are displayed in Table 2. Patients with high-risk features are prone to rapid clinical deterioration and progression to HF-CS and should be recognized early to warrant intensified monitoring.

Table 2.

Risk Features in ADHF

HF-CS Diagnosis

The scientific expert panel from the Shock Academic Research Consortium defines CS as a cardiac disorder resulting in both clinical and biochemical evidence of sustained tissue hypoperfusion, irrespective of underlying blood pressure (BP).¹⁶ Specifically, they define HF-CS as related to primary myocardial dysfunction in patients who do not meet criteria for AMI-CS. This definition excludes causes such as severe valvular disease, pericardial disease, pulmonary embolism, ongoing arrhythmia, or patients post-cardiotomy.

Building on this framework, the Society for Cardiovascular Angiography and Interventions (SCAI) classification has become a widely adopted tool for staging CS, guiding therapeutic decisions, and serving as a framework for clinical research. The classification stratifies patients according to shock severity, ranging from stage A (at risk) to stage E (refractory or extreme shock). Although developed as a staging tool and shown to perform well in that role,⁵ the SCAI classification has nonetheless been applied as a diagnostic instrument in clinical trials of HF-CS.¹⁷ However, prior studies have shown that patients in stage B at diagnosis may experience mortality rates similar to those in stage C,⁵ and that up to one-third of patients categorized as stage A required vasoactive or inotropic support despite lacking overt hypotension or hypoperfusion classified by the SCAI criteria.¹⁸ Thus, while the SCAI classification appears well suited for its intended role as a staging framework, its diagnostic utility in HF-CS is limited, and clinicians should rely on physiological evidence of hypoperfusion to guide early hemodynamic intervention rather than await advancement through the SCAI stages.

Hypoperfusion in HF-CS

The Role of BP

The relationship between BP and CO is dictated by systemic vascular resistance. Although hypotension in HF-CS is strongly associated with mortality, it does not necessarily reflect the degree of hypoperfusion.⁵ Mortality is higher in patients with HF-CS with normotensive shock than in patients with isolated hypotension and only marginally lower than in those with classical CS.¹⁹ In HF-CS, many patients exhibit normotensive hypoperfusion before progressing to classic shock because the aforementioned compensatory mechanisms can increase systemic vascular resistance to maintain an acceptable BP. This contrasts with AMI-CS, in which hypotension often presents early when these mechanisms are less upregulated. On the other hand, patients with ADHF frequently exhibit baseline hypotension (without hypoperfusion) due to inherent characteristics of the condition and its treatment. Therefore, reliance on hypotension alone as a diagnostic criterion is hazardous, potentially delaying recognition and initiation of appropriate therapy.

The Role of CO

Organ perfusion is primarily regulated by arterial inflow (CO and vascular resistance), but venous backpressure, closing pressure, and the microcirculation are also of considerable importance, especially in ADHF.²⁰ A common misconception is that hypoperfusion is synonymous with low CO. Although the 2 may coexist and low CO may precipitate hypoperfusion, the latter is dictated by the interplay between the macrocirculation, microcirculation, and the individual needs of the tissues, meaning that a single threshold value for CO does not exist. In AMI-CS, where acute pump failure is the predominant pathophysiologic mechanism and underlying adaptation is minimal, CO may serve as a surrogate for tissue perfusion, at least during the initial phase. However, in HF-CS, where multifactorial hemodynamic and cellular derangements contribute to the lack of tissue oxygen delivery, the diagnostic value of CO as a marker is limited,²¹ and it is the trend rather than the absolute value that is important. Moreover, oxygen delivery to the tissues is determined not only by CO but also by the arterial oxygen content.²² Arterial oxygen content is primarily determined by hemoglobin concentration and its oxygen saturation. Therefore, optimizing both arterial oxygen content and CO is essential for effective arterial oxygen delivery. Finally, the relative contribution of CO to hypoperfusion is substantiated by the observation that normalization of CO alone appears insufficient, as shown in a CS cohort, where nearly half of the patients who died had achieved a restored CO at the time of death.²³

The Importance of Congestion

Because capillaries are considered a low-pressure compartment, the effect of congestion as a backpressure to microcirculatory flow is substantial in HF-CS.²⁴ Beyond intravascular hemodynamics, edema of surrounding anatomic structures may exert external pressure on the venous system, further aggravating tissue congestion. This phenomenon is particularly relevant to the kidneys, as described by the renal tamponade hypothesis.²⁵ Although the kidney is especially vulnerable to this mechanism, elevated global intra-abdominal pressure, commonly increased in ADHF, can similarly impair other organs through pressure-congestion interactions.²⁶ An often underrecognized contributor to congestion in ADHF is impaired clearance of interstitial fluid (edema) by the lymphatic system. Rises in CVP hinder lymphatic drainage by reducing the necessary pressure gradient for fluid return to the venous circulation.²⁷ Subsequently, congestion further impairs lymphatic vessel integrity and compliance, diminishing their clearance capacity.²⁸ Disturbed lymphatic drainage is a critical factor in ADHF, as it is the primary mechanism through which interstitial edema is relieved.

Venous Volume-Pressure-Flow Relationship

An important consideration in HF-CS is the relationship between venous volume, pressure, and flow. CVP does not rise linearly with volume because most venous blood is unstressed volume that fills the system without generating pressure; only a smaller stressed portion contributes to pressure.²⁹ Owing to the high venous capacitance, large volume shifts may occur without measurable pressure changes, meaning that congestion can be present despite normal pressures. This is clinically relevant because the pulmonary artery catheter (PAC) measures pressures and derived flows, not the underlying venous blood volume. Also, CVP does not reflect preload but rather the backpressure for venous return to the heart. An increase in CVP will lead to a decrease in venous return and CO instead of an increase, unless it is accompanied by an even larger increase in mean systemic filling pressure.³⁰

The Microcirculation

While restoration of macrocirculatory parameters may lead to disease regression in preshock states (SCAI A/B), this is often ineffective in advanced HF-CS trajectories.⁵ In critically ill patients, improvement of the macrocirculation does not always result in parallel improvement of the microcirculation, a phenomenon referred to as hemodynamic incoherence, or uncoupling of the macrocirculation and microcirculation.²⁰ The relationship between arterial flow, venous congestion, and microcirculatory dysfunction in ADHF is depicted in Figure 2. The microcirculation is responsible for delivering oxygen to the parenchymal cells by transportation of red blood cells and their exchange of oxygen and nutrients, therefore serving as a critical link between the heart and the tissue. Endothelial dysfunction, metabolic disturbances, and the systemic inflammatory response syndrome caused by prolonged hypoperfusion each result in a compromised systemic autoregulation of the microcirculation.³¹ Importantly, intestinal hypoperfusion and venous congestion damage the oxygen-sensitive gut villi, increasing mucosal permeability and endotoxin translocation, which trigger inflammation and worsen microcirculatory dysfunction.³²

Figure 2.

Mechanisms underlying circulatory hypoperfusion. Tissue hypoperfusion arises from both low arterial inflow and high venous pressures, which may be compounded by external compressive forces. The resulting net reduction in tissue perfusion leads to microcirculatory dysfunction through mechanisms including endothelial dysfunction (*), metabolic disturbances (†), and inflammatory pathways (‡).

Finally, patients with ADHF more often receive chronic guideline-directed medical therapy compared with patients presenting with AMI. Long-term angiotensin-converting enzyme inhibitor or angiotensin receptor blocker therapy may contribute to vasodilatory tendencies and lower systemic vascular tone at the time of ADHF. Chronic β-blocker therapy, which reduces heart rate and sympathetic activity, has well-established long-term cardioprotective effects. However, in the acute setting of HF-CS, particularly in patients with limited cardiac reserve, β-blockade may blunt the compensatory tachycardic response needed to maintain perfusion.

Diagnostic Markers of Hypoperfusion in HF-CS

In the following sections, we examine each parameter used in routine clinical practice to assess hypoperfusion. Together, these domains form the complementary components of HF-CS diagnosis, summarized in Figure 3.

Figure 3.

Global and organ hypoperfusion parameters. Global hypoperfusion is evaluated through physical signs, right heart catheterization measurements, and blood gas analysis. Organ hypoperfusion is indicated by markers of liver dysfunction and kidney dysfunction. ALT indicates alanine aminotransferase; API, aortic pulsatility index; CI, cardiac index; CO, cardiac output; CPO, cardiac power output; CRT, capillary refill time; CVP, central venous pressure; RAP, right atrial pressure; and SvO₂, venous oxygen saturation.

Physical Examination

Physical examination remains the cornerstone of bedside assessment for hypoperfusion.

The hemodynamic profiles clinically adapted by Nohria et al³³ classify patients by perfusion (warm versus cold) and congestion (dry versus wet), with HF-CS typically presenting as a cold-wet phenotype. In ADHF, 17% to 20% presents with a cold-wet profile at admission, and this subgroup has the highest mortality risk.^2,33 However, caution is warranted, as a substantial proportion of patients with CS may present without overt signs of congestion, and the absence of such findings does not preclude a cardiac cause of shock.³⁴ Specifically, both a prolonged capillary refill time (>3 seconds) and mottling serve as simple and readily available markers of skin hypoperfusion and early predictors of mortality in CS and are strongly correlated with the presence of microcirculatory dysfunction.²⁰ Prolonged capillary refill time (>3 seconds) is the more robust of these 2 markers, providing an objective and reproducible measure of skin hypoperfusion rather than a subjective clinical finding.³⁵ Moreover, prolonged capillary refill time was closely associated with elevated lactate levels and reduced urine output (UO) but not with systolic BP, heart rate, or cardiac index.³⁵ Altered mental status is an independent predictor of short-term mortality in patients with CS. Interestingly, a higher prevalence was seen in AMI-CS than in HF-CS, owing to compensatory mechanisms.³⁶ The classical cold-wet profile is a hallmark of advanced shock but may have limited utility in early stage or normotensive HF-CS when patients often remain classified as warm-wet. This diagnostic ambiguity underscores a critical limitation of the traditional bedside profiles, which may delay recognition and timely intervention in these patients. Therefore, while routine daily physical examination remains a practical and accessible tool in managing ADHF and HF-CS, its sensitivity and specificity for detecting early hypoperfusion are suboptimal.

Venous Oxygen Saturation and Central Venous-to-Arterial Carbon Dioxide Difference

In a state of hypoperfusion, tissues compensate by increasing oxygen extraction, leading to a decline in venous oxygen saturation (SvO₂). Theoretically, SvO₂ provides a more comprehensive indicator of hypoperfusion than CO or CVP alone, as it reflects the net effect of reduced CO, systemic autoregulation, and venous congestion on the ability of the tissue to extract oxygen.³⁷ SvO₂ has been consistently linked to short-term mortality in patients with HF-CS, with levels below 60% commonly indicating systemic hypoperfusion.³⁸ With respect to outcomes, the change in SvO₂ during early treatment in HF-CS appears to be of greater prognostic significance than its absolute value at presentation. In one study, no difference in SvO₂ at admission was observed between patients with and without major adverse cardiovascular events; however, improvement in SvO₂ following inotropic therapy was associated with a lower incidence of such events.³⁸ Notably, this improvement correlated predominantly with effective decongestion, evidenced by UO and reduced inferior vena cava diameter, rather than changes in CO. Therapeutically, monitoring SvO₂ allows detection of a prehypoperfusion state when oxygen extraction is increasing, but overt hypoperfusion is not yet apparent. It can identify patients at risk of progressing to shock earlier than conventional parameters, enabling timely intervention to prevent further deterioration. In ADHF, a decline in SvO₂ typically reflects macrocirculatory failure rather than microcirculatory dysfunction.³⁹ However, while a low SvO₂ is the result of a mismatch between CO (macrocirculation) and cellular needs, microcirculatory dysfunction, for example during a systemic inflammatory response syndrome reaction, can disturb this supply/demand relationship. It does so by decreasing local delivery of oxygen to the cells in certain regions of the tissues, decreasing the ability to extract oxygen in these regions, creating a shunt effect to other regions, and falsely increasing SvO₂.⁴⁰ The central venous-to-arterial carbon dioxide difference (pCO₂ gap) helps to accurately interpret elevations in SvO2 in these cases. It is defined as the difference between the partial pressure of CO₂ in venous and arterial blood. Because CO₂ production remains relatively constant and its diffusion is highly efficient regardless of blood flow, elevations in the pCO₂ gap primarily reflect impaired washout (ie, circulatory failure) and are largely unaffected by tissue hypoxia.⁴¹ Therefore, the pCO₂ gap retains diagnostic value even in an uncoupled microcirculation. True mixed SvO₂ and the pCO₂ gap can only be measured in the pulmonary artery, where blood from the superior and inferior vena cava and coronary sinus fully mix, hence requiring a PAC. In routine practice, these measurements are often measured via a central venous catheter that reflects superior vena cava flow only. In stable cardiac patients, they correlate reasonably well, but, during hemodynamic deterioration, preferential perfusion of vital organs and reduced splanchnic circulation further widen the discrepancy.⁴² Therefore, mixed SvO₂ outperforms centrally measured SvO₂ for the diagnosis of HF-CS, but central venous catheter–determined SvO₂ may be used as a surrogate for assessing therapeutic responsiveness. With regard to the pCO₂ gap, the traditional cutoff of >6 mm Hg, indicative of persistent shock, applies only when CO₂ is sampled from the pulmonary artery. When measured from the superior vena cava, a higher threshold of 9 mm Hg should be used, as it more accurately predicts outcomes.^39,43

Lactate and Acid-Base Disturbances

Systemic hypoperfusion impairs oxygen delivery to tissues, prompting a shift in mitochondrial metabolism toward the anaerobic pathway and resulting in excess lactate production via lactate dehydrogenase, widely considered the principal driver of hyperlactatemia in CS. Although often within the normal range, elevated lactate levels are observed in a subset of patients admitted with ADHF, even in the absence of hypotension or overt signs of hypoperfusion.⁴⁴ Elevated lactate levels may result from various other mechanisms in ADHF: mitochondrial dysfunction impairs oxidative phosphorylation, increasing lactate production⁴⁵; heightened sympathetic activity and exogenous catecholamines stimulate glycolysis⁴⁵; and last, hepatic and renal dysfunction reduce lactate clearance, which is increasingly recognized in HF-CS. The mechanism underlying lactate elevation in patients with ADHF who appear well-perfused remains incompletely understood but may be the result of a combination of factors as previously described.⁴⁴ Regardless of its cause, hyperlactatemia has been identified as an independent predictor of both in-hospital and 1-year mortality.⁴⁴ Lactate is, therefore, among the most commonly used parameters to evaluate tissue hypoperfusion and is included in the latest proposed SCAI classification.⁴⁶ Lactate clearance may be an even stronger predictor of mortality, with prognostic value evident as early as 8 hours after initiation of therapy.⁴⁷ β-Blocker therapy may result in lactate not infrequently being a late manifestation of hypoperfusion in HF-CS. By attenuating β-adrenergic–mediated lactate generation, β-blockers can blunt the rise in lactate during shock, potentially leading to underestimation of its severity.⁴⁸ Indeed, studies show that patients on β-blockers present with lower initial lactate levels and are less likely to exhibit marked hyperlactatemia in septic shock.⁴⁹ Finally, lactate measurements obtained from either venous or arterial blood have been shown to yield comparable results, thereby providing a readily accessible tool for its assessment.⁵⁰ Assessment of acid-base imbalances provides prognostic information complementary to lactate levels.^44,51 Unlike lactate, acid-base disturbances reflect both respiratory compensation and buffer system effectiveness. In HF-CS, metabolic acidosis from systemic hypoperfusion predicts mortality, whereas respiratory acidosis in acute pulmonary edema has not been associated with adverse outcomes.^44,51 Profound acidosis (pH <7.2) has been incorporated into the SCAI classification to identify patients at greatest risk of death.⁴⁶

Microcirculatory Assessment

Ideally, direct assessment of the microcirculation would allow for more precise identification of hypoperfusion. Several techniques have been developed for this purpose, with sublingual microcirculatory assessment being among the most extensively studied.^52,53 Although studies have established its independent prognostic value in AMI-CS,⁵² randomized trial data in a mixed shock population have failed to demonstrate a clinical benefit.⁵³ Moreover, real-time bedside applicability remains challenging due to technical and interpretative limitations. Given the lack of widespread clinical adoption, direct microcirculatory assessment falls beyond the scope of this review and has been comprehensively discussed elsewhere.⁵⁴

Organ Hypoperfusion

Acute renal dysfunction occurs in up to half of patients hospitalized with ADHF (113). Although serum creatinine and estimated glomerular filtration rate are widely used as indices of renal function, they primarily reflect glomerular filtration pressure rather than renal blood flow. Consequently, modest rises in creatinine following initiation of renin-angiotensin system inhibition or volume depletion are often hemodynamically mediated, resulting from altered autoregulatory tone rather than tubular ischemia. In such settings, transient reductions in glomerular filtration rate do not necessarily portend adverse outcomes, unless the underlying cause is true hypoperfusion. This distinction underscores the importance of differentiating hemodynamic from ischemic mechanisms when interpreting changes in kidney function. Growing evidence implicates venous congestion as a key driver,⁵⁵ and CO becomes relevant when autoregulatory thresholds are exceeded.⁵⁶ The kidney is highly sensitive to congestion, as previously described in the renal tamponade hypothesis.²⁵ Congestion at baseline correlates with renal impairment and mortality,^55,57,58 but baseline congestion does not reliably predict worsening renal function during treatment.^57,58 Moreover, worsening renal function during therapy, especially with a good diuretic response, may not reflect true hypoxia of the tissues and has been associated with better outcomes.^15,59 In the context of HF-CS, acute kidney injury occurs in up to 80% of patients, with 21% requiring renal replacement therapy, a finding that is strongly associated with increased mortality.^60,61 In contrast to ADHF, kidney failure in HF-CS likely stems from the combined effects of severe hypoperfusion and congestion. Standard acute kidney injury definitions (risk, injury, failure, loss of kidney function, and end-stage kidney disease, Acute Kidney Injury Network, and Kidney Disease: Improving Global Outcomes), which include UO, outperform worsening renal function criteria in prognostic accuracy though interpretation of UO must account for confounders such as diuretic-induced polyuria.⁶² A UO of ≥0.5 mL/kg per hour is generally recommended to indicate adequate perfusion in ADHF.⁶³ In summary, while estimated glomerular filtration rate and UO offer diagnostic and prognostic value in HF-CS, their use for diagnosing hypoperfusion in ADHF remains challenging. Novel biomarkers such as cystatin C, less influenced by muscle mass, may offer earlier and more accurate detection of renal dysfunction than creatinine in critically ill patients.⁶⁴ Urinary sodium excretion is also a valuable tool during decongestive treatment, providing information on renin-angiotensin-aldosterone system activity, renal blood flow, and diuretic resistance. Current guidelines recommend its use to assess initial diuretic response after the start of diuretic therapy.⁶⁵

Liver function test abnormalities are common in ADHF,^66,67 reflecting either cholestasis or hepatic necrosis. Cholestasis, marked by elevated alkaline phosphatase, gamma-glutamyl transferase, and bilirubin, suggests congestive hepatopathy,⁶⁶ driven by elevated venous and sinusoidal pressure, but does not represent tissue hypoxia. Hepatic necrosis is reflected by elevations in ALT (alanine aminotransferase) and aspartate aminotransferase, with ALT being more liver-specific. In CS, 2 hypoperfusion-related liver injury patterns are recognized: hypoxic liver injury and congestive hepatopathy. Hypoxic liver injury typically occurs when hepatic congestion is compounded by a second hit, such as prolonged hypotension, respiratory failure, and sepsis, often in a multifactorial context.⁶⁸ It is characterized by 10- to 20-fold increases in aminotransferases, carrying a high mortality rate up to 60%.⁶⁹ Congestive hepatopathy is typically associated with more modest elevations in transaminases, although associated with mortality, remaining inconsistent.^66,67 The SCAI criteria define ALT ≥200 U/L as a marker of hypoperfusion and mortality in CS⁴⁶ but found no such association in HF-CS.⁵ Reliance on ALT in HF-CS is, therefore, generally not recommended, unless hypoxic liver injury is suspected.

Finally, elevations in troponins reflect myocardial ischemia and are associated with mortality in HF-CS.⁷⁰ Because these elevations do not reflect peripheral hypoperfusion and, therefore, do not contribute directly to the diagnosis of shock, this topic lies outside the scope of the present review.

Phenotyping HF-CS

If the diagnosis of HF-CS is established, it is of major (clinical) importance to determine its phenotype. Cardiac failure may present as predominant LV failure, RV failure, or biventricular failure, each with distinct pathophysiologic and clinical characteristics essential for recognition and treatment of hypoperfusion. LV failure, characterized by low CO and pulmonary congestion, represents the predominant phenotype in CS care.⁵ Its early identification as a cause of hypoperfusion is critical for timely diagnosis and treatment, as therapies aimed at augmenting CO, including inotropes and mechanical circulatory support, may be crucial for patient salvage. Moreover, pulmonary congestion further compromises alveolar gas exchange, reducing oxygen uptake and perpetuating tissue hypoperfusion. RV failure, characterized by systemic venous congestion, may occur in isolation in conditions such as pulmonary arterial hypertension but more commonly develops secondary to LV failure in the setting of HF-CS, resulting in biventricular dysfunction. Biventricular failure is frequent in HF-CS, occurring in up to 62% of patients.⁷¹ Its presence is particularly deleterious, as adverse interventricular interactions amplify hemodynamic compromise: leftward septal shift, increased RV afterload from pulmonary congestion, and the dependence of 40% to 60% of RV mechanical work on LV contraction together create a vicious cycle of progressive biventricular dysfunction.⁷² Interestingly, recent machine learning–based phenotyping of CS has revealed distinct patterns of hypoperfusion markers depending on whether left or RV dysfunction predominates, underscoring the mechanistic and clinical heterogeneity of hypoperfusion.⁷³

Hemodynamic Profiling

The PAC and transthoracic echocardiography are complementary tools for hemodynamic profiling in HF-CS. Use of the PAC declined after the ESCAPE trial, which showed no clinical benefit in patients with advanced ADHF; however, that study failed to include many patients with severe CS.⁷⁴ This shift led to increased reliance on noninvasive echocardiographic estimates of CO and filling pressures. Although transthoracic echocardiography provides general estimates of ventricular function, CO, and filling pressures, it is especially inaccurate for assessing left-sided filling pressures.⁷⁵

Recently, the application of the PAC has been rising as complete hemodynamic profiling was shown to be associated with improved mortality in CS, especially in advanced stages of CS.⁷⁶ The PAC also permits measurement of SvO₂, enabling direct monitoring of tissue hypoperfusion; combined with hemodynamic and biochemical profiling, it may identify patients in a preshock state before overt hypoxia develops. In the setting of established HF-CS, the use of a PAC may facilitate informed decisions about escalation or deescalation of CS therapy. The PAC in CS is currently investigated in the PACCS trial (Pulmonary Artery Catheter in Cardiogenic Shock; Unique identifier: NCT05485376).

Figure 4 summarizes the echocardiographic and invasive parameters used for hemodynamic profiling of the LV and RV, including normal reference ranges.^77–79 In the next sections, we examine every parameter in detail.

Figure 4.

Hemodynamic profiling in right vs left ventricular failures.^77–79 Parameters for invasive and echocardiographic assessment are shown for right ventricular and left ventricular dysfunctions. API indicates aorta pulsatility index; CPO, cardiac power output; CVP, central venous pressure; dPAP, diastolic pulmonary artery pressure; eRVsystolic pressure, estimated right ventricular systolic pressure; IVC, inferior vena cava; LVOT-VTI, left ventricle outflow tract-velocity time integral; mPAP, mean arterial pressure; PACa, pulmonary arterial capacitance; PAOP, pulmonary artery occlusion pressure; PAPI, pulmonary arterial pulsatility index; PVR, pulmonary vascular resistance; RAP, right atrial pressure; RVOT-VTI, right ventricle outflow tract-velocity time integral; RVSWI, right ventricular stroke work index; sPAP, systolic pulmonary artery pressure; SVR, systemic vascular resistance; TAPSE, tricuspid annular plane systolic excursion; and VExUS, venous excess ultrasound score.

Left-Sided Assessment

Cardiac Output

In the care of patients with HF-CS, CO is most often measured by thermodilution with PAC, whereas the direct Fick method remains the gold standard but is seldom used given its complexity. Patients with advanced HF may have chronically low output yet remain stable in the absence of hypoperfusion.²¹ Serial trends, however, remain informative for assessing therapy and guiding fluid management. Cardiac power output, calculated as (mean arterial pressure [MAP]−right atrial pressure [RAP])×CO/451, integrates flow and pressure and has been shown to predict in-hospital mortality more accurately than CO alone.⁸⁰ As a noninvasive alternative, LV outflow tract-velocity time integral on echocardiography serves as a surrogate of CO and correlates closely with invasive measurements.⁷⁵

Pulmonary Artery Occlusion Pressure

Pulmonary arterial occlusion pressure (PAOP), measured invasively via balloon occlusion of the pulmonary artery, is widely used as a surrogate for left-sided filling pressures. In the case of persistently elevated PAOP in HF-CS despite vasoactive-inotropic treatment, escalation to unloading devices should be considered. In recent years, the aortic pulsatility index has been introduced, defined as the ratio of pulse pressure to PAOP (aortic pulsatility index=[systolic BP−diastolic BP]/PAOP). Because cardiac power output mainly reflects the energy invested in generating flow, it performs more poorly in HF-CS, compared with AMI-CS, where the compensatory mechanism maintains stroke volume but at the price of lower energetic efficiency.⁸¹ Aortic pulsatility index, mainly reflecting cardiac efficiency, therefore better accounts for these compensatory mechanisms (volume and pressure overload) and, therefore, seems to outperform cardiac index and cardiac power output in the risk stratification across the ADHF spectrum.^82,83 Finally, a novel 2-step echocardiographic algorithm was proposed to estimate LV filling pressures, incorporating e′, the E/e′ ratio, and systolic pulmonary artery pressure, with further evaluation by left atrial strain, left atrial volume index, isovolumic relaxation time, and pulmonary venous flow when results are discordant. This approach demonstrated greater accuracy than previous methods though its performance in HF-CS remains to be determined.⁸⁴

Right-Sided Assessment

Systemic Congestion

Although invasive measurement of CVP and RAP is considered the gold standard for assessing right-sided congestion, echocardiographic measurement of the inferior vena cava diameter and collapse during respiration is often used as a surrogate. Although this parameter correlates reasonably well with invasive measurements,⁷⁵ it has significant limitations in certain critical care contexts, including high positive-pressure ventilation, asthma/chronic obstructive pulmonary disease, chronic RV dysfunction, and pulmonary hypertension.⁸⁵ Moreover, it does not necessarily reflect venous backpressure on organs and tissues. For this purpose, the venous excess ultrasound score has been developed, offering a systematic Doppler-based approach through assessment of the inferior vena cava, portal vein, hepatic vein, and intrarenal veins. Elevated venous excess ultrasound scores have been associated with an increased risk of acute kidney injury, highlighting its clinical utility, particularly in the context of renal vulnerability to elevated venous pressures.²⁵

RV Function and Pulmonary Circulation

Assessment of the RV is complex due to its geometry, dependence on before and after load, and interventricular interactions. Echocardiographic parameters, such as tricuspid annular plane systolic excursion and tricuspid annular systolic wall motion velocity, are commonly used, yet tricuspid annular plane systolic excursion and RV outflow tract-velocity time integral both show modest correlations with invasive stroke volume measurements.⁸⁶ Most RV imaging parameters are load-dependent and do not measure RV intrinsic contractility. During end-stage RV failure, RAP increases, and systolic pulmonary artery pressure decreases, a relationship exploited in the pulmonary arterial pulsatility index, calculated as pulmonary pulse pressure divided by RAP. Pulmonary arterial pulsatility index, initially developed to predict RV failure after left ventricular assist device implantation, is a strong predictor of mortality and the need for mechanical circulatory support following heart transplantation.^87,88 Invasive alternatives include RV stroke work index and the RAP/PAOP ratio, which are associated with outcomes,⁸⁸ though pulmonary arterial pulsatility index appears superior for detecting intrinsic RV myocardial dysfunction in advanced HF.⁸⁹

Because RV function is highly load-dependent, assessment of the pulmonary circulation in ADHF and HF-CS is important for full hemodynamic appreciation. An invasively measured mean PAP marks the diagnosis of pulmonary hypertension⁷⁵ but does not signify RV afterload. RV afterload consists of 3 components: the pulmonary vascular resistance representing the static component, compliance representing the pulsatile component, and impedance reflecting the opposition of pulmonary vessels to pulsatile blood flow. Pulmonary vascular resistance, calculated as the gradient between mean PAP and left atrial pressure divided by CO, is commonly used to assess RV afterload.⁹⁰ Pulmonary arterial capacitance, defined as stroke volume divided by pulmonary pulse pressure, incorporates the pulsatile component, which is essential in patients with LV failure and pulmonary hypertension.⁹¹

Organ Perfusion Pressure

True arterial perfusion pressure represents the difference between MAP and the critical closing pressure, in accordance with the vascular waterfall principle. The prognostic relevance of congestion has been underscored by studies evaluating organ perfusion pressure (OPP; defined as MAP minus CVP). Low OPP on admission was significantly associated with higher in-hospital mortality, whereas MAP only was not.⁹² After adjustment for age and sequential organ failure assessment score, OPP remained an independent predictor of mortality. This finding was most pronounced among patients with HF-CS, whereas no significant association was observed in AMI-CS. Compared with AMI-CS, patients with ADHF-CS exhibited lower MAP, OPP, and lactate levels but higher CVP. Collectively, these findings indicate that OPP, rather than MAP, more accurately reflects the hemodynamic compromise underlying adverse outcomes in HF-CS.

Clinical Decision Framework

The often subclinical presentation of early HF-CS necessitates a structured diagnostic approach, both at baseline and throughout serial assessments, which is outlined in Figure 5. As previously discussed, various parameters may be used to assess hypoperfusion and characterize the underlying phenotype of CS. In patients with ADHF or HF-CS, the diagnostic value of each parameter must be weighed against the invasiveness of its measurement, with the choice guided by the patient’s clinical trajectory. Given the often insidious course of HF-CS, we do propose standardized baseline screening for hypoperfusion in all patients with ADHF or HF-CS, accompanied by early echocardiographic assessment. This screening should consist of a combination of noninvasive parameters: physical examination, vitals, and echocardiographic assessment, and biochemical assessment: lactate, pH, kidney function, ALT, urine sodium, and body weight. In hospitalized patients, UO should be collected when available, and in those with a central venous catheter, measurement of SvO₂ should be performed. In this context, baseline should be interpreted broadly, encompassing the time of hospital admission, interhospital transfer, or escalation to a higher level of care such as an intensive care unit or cardiac care unit.

Figure 5.

Diagnostic recommendations in acute decompensated heart failure (ADHF) and heart failure–related cardiogenic shock (HF-CS). *As defined by the Shock Academic Research Consortium (SHARC) expert consensus.¹⁶ †Complete hemodynamic profiling: right atrial pressure (RAP) or central venous pressure (CVP), pulmonary artery pressure (PAP), pulmonary artery pulsatility index (PAPI), right ventricular stroke work index (RVSWI), RAP/pulmonary artery occlusion pressure (PAOP) ratio, pulmonary vascular resistance (PVR), PAOP, arterial pulsatility index (API), cardiac index (CI), and cardiac power output (CPO); partial hemodynamic profiling: CVP, PAP, PAOP, API, CI, CPO, and systemic vascular resistance (SVR). ‡Kidney function: creatinine or cystatin C–derived estimated glomerular filtration rate (eGFR). ALT indicates alanine aminotransferase; HD, hemodynamic; Spo₂, peripheral capillary oxygen saturation; and SvO₂, venous oxygen saturation.

Following this baseline hypoperfusion screening, patients may be categorized into 2 groups: those with hypoperfusion where diagnosis of HF-CS can be confirmed, and those without evidence of hypoperfusion. In patients without hypoperfusion, further risk stratification is required based on the presence or absence of high-risk features, as summarized in Table 1. Although desirable, current evidence provides guidance rather than definitive criteria for stratifying patients as low or high risk. Once a patient is adjudicated as high or low risk, the intensity and modality of subsequent daily diagnostic evaluation should be individualized according to the patient’s risk profile and evolving clinical course.

In patients with established low-risk ADHF, routine invasive hemodynamic monitoring is not necessary. Instead, physical examination, vitals, and serial assessment of kidney function and body weight are generally sufficient to monitor the evolution of ADHF. It remains important to monitor for any clinical changes that may suggest progression to high-risk ADHF or HF-CS, at which point a more intensive screening strategy should be initiated.

High-risk patients may derive benefit from a single invasive hemodynamic assessment using right heart catheterization; however, continuous invasive monitoring may be utilized to further aid medical optimization by tracking changes in filling pressures and CO. At a minimum, patients with high-risk ADHF should receive an arterial line to enable intensive monitoring of BP and arterial blood gas. Hypoperfusion screening should include serial measurement of pH, lactate, and either central or mixed SvO₂ every 6 to 8 hours, along with continuous monitoring of UO and urinary sodium excretion in patients in whom cardiorenal interaction limits decongestion. For high-risk patients who are not monitored invasively with right heart catheterization, daily, and at least weekly, echocardiographic hemodynamic assessment should be strongly considered.

In patients with confirmed HF-CS, a more comprehensive approach (including a PAC) is warranted, in which daily full hemodynamic profiling is recommended. Hereafter, invasive hemodynamic indices, pH, lactate, and SvO₂ should be repeated every 2 to 6 hours to monitor the disease trajectory and therapeutic responsiveness. In cases of RV failure, the use of a PAC with a separate RV port might be interesting although we currently lack the data to recommend its use. Subsequently, in HF-CS, reassessment every 2 to 6 hours is advised for hour-sensitive biomarkers, with daily comprehensive evaluation of organ function to support timely clinical decision-making.

Future Perspectives

Ideally, restoration of hemodynamics would occur before the onset of overt hypoperfusion, as hypoperfusion might result in an irreversible vicious cycle leading to multiorgan failure and death. Nevertheless, early intervention strategies have often failed to yield the expected benefit. For example, continuous PAC use in ADHF and the use of inotropic agents in ADHF have both been associated with excess mortality and adverse events.^74,93 For this reason, we contend that aggressive therapy, including vasoactive-inotropic support and mechanical circulatory support, should be reserved for cases in which overt hypoperfusion is present. The objective, therefore, becomes to diagnose hypoperfusion as soon as it emerges. For example, perfusion pressure (MAP-CVP) has been shown to outperform both MAP and serum lactate in predicting outcomes in CS.⁹² Understanding how SvO₂ and perfusion pressure interact could yield novel insights and improve diagnostic accuracy.

Emerging biomarkers hold promise for improving risk stratification and enabling earlier detection of hypoperfusion. DPP3 (dipeptidyl peptidase 3) is a cytosolic enzyme released into the circulation following cellular injury.⁹⁴ In CS, persistently elevated DPP3 levels have been associated with 10-fold increased mortality, and may enhance existing risk scores while also predicting CS onset.⁹⁵

ADM (adrenomedullin) is a vasoactive peptide elevated in response to hemodynamic stress, hypoxia, and inflammation.⁹⁶ ADM reflects microcirculatory dysfunction and has been associated with mortality in CS.⁹⁶ It retains prognostic value beyond lactate normalization and correlates with biventricular pressures and end-organ injury.^96,97

Finally, inflammation, manifesting as systemic inflammatory response syndrome, is increasingly recognized as a central feature of CS, contributing to microcirculatory dysfunction, vasodilation, and adverse outcomes,³¹ and shown to play a role in HF progression as well.⁹⁸ Recent evidence even suggests that patients with HF-CS exhibit a distinct inflammatory profile compared with those with ADHF without shock, even before clinical deterioration occurs.⁹⁹ This raises the possibility of inflammatory profiling for early risk stratification and disease staging. Biomarkers such as angiopoietin-2, soluble urokinase-type plasminogen activator receptor, and interleukin-6 have shown prognostic value in CS.¹⁰⁰ Further research is needed to define the role of these emerging biomarkers in HF-CS.

Conclusions

In patients with ADHF and HF-CS, diagnosis of hypoperfusion remains challenging, as individual parameters may appear deceptively normal. As both high-risk ADHF and early HF-CS are associated with increased mortality, timely diagnosis is crucial. A multifaceted approach, anchored in appropriate risk stratification, is, therefore, essential for timely recognition. The degree and intensity of diagnostic assessment, including the use of invasive monitoring, should be tailored to the patient’s risk profile. In this context, the PAC holds particular value, offering detailed insights into hemodynamic and biochemical disturbances that precede overt hypoperfusion. Future strategies should focus on integrating hemodynamic data with both established and emerging biomarkers to identify hypoperfusion at its earliest and still reversible stage.

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