From Prognostic Determinants to Trajectory-Based Risk Stratification in Pediatric Dilated Cardiomyopathy: Clinical Implications for Therapeutic Decision-Making — A Narrative Review

A. Clinical and Demographic Prognostic Fac-tors

Age at diagnosis has always been an important prognos-tic factor for pediatric DCM patients from a clinical per-spective.⁵ Later childhood/adolescence at presenta-tion usually exhibits worse transplant-free survival than younger children among several cohorts.^2,3 Older age at diagnosis in the PCMR (for instance, above 6 years) was still a risk factor for death or heart transplantation independently of the other confounding factors.² Sev-eral series have considered young age as a positive prog-nostic factor possibly due to a higher proportion of re-versible conditions at early ages (such as myocarditis) and an ability to recuperate for those who survive the initial very risky period.^5,2 Nevertheless, infant-onset DCM (< 1 year) is not always protective; some groups find that infants have a higher short-term mortality rate, which is probably due to the disease progressing so quickly that there is no time to get advanced support.⁴ This is in line with the idea that age, risk relationship is non-linear, with the highest risk being at the extremes of age (very early infancy and older childhood) rather than a simple linear effect.⁴ From a clinical perspective, adolescent-onset DCM is a case for a higher level of risk alert, whereas the age factor should be considered in combination with etiology and severity at presentation.^2,4,9

In pediatric DCM, etiology serves as the main “risk con-text” since it determines how severity markers (EF, LV dila-tion, MR, and biomarkers) are to be interpreted.² Data from the registry era reveal a large variation in the out-come depending on the cause, with significantly better scenarios in the categories of potentially reversible versus primary/genetic phenotypes.² Different studies show that myocarditis-associated DCM is more likely to recover function and have fewer death/HTx events than idio-pathic DCM, which is in line with an acute inflammatory injury that may be facilitated by early support.^2,10 By contrast, idiopathic DCM, which is largely accounted for genetic cardiomyopathy cases in modern cohorts, has been associated with lower transplant-free survival and a more deteriorating progression of the disease.^2,11 Familial/genetic disease could be at a higher risk in some cases, and the family history can be a convenient bedside indicator for increased monitoring; for instance, a single-center cohort study found family history as a risk fac-tor in time-to-event analysis.¹² Neuromuscular DCM (e.g., dystrophinopathies) is also typically linked to worse prognosis, which is influenced by the presence of sys-temic comorbidities and, in some cases, limited advanced-therapy candidacy.² Importantly, new data have con-nected the words “etiology” and “genotype”: in a study involving children who had their myocarditis confirmed through biopsy and showed a DCM phenotype, it was found that pathogenic/likely pathogenic cardiomyopathy variants were highly present and that event-free survival was significantly lower in those that had such variants, thus indicating that myocarditis may reveal an inherited substrate.^10,13 Therefore, the etiologic classification should be clear when talking prognostics, as it not only changes the baseline risk but also how genetic testing can further refine the risk even within presentations labeled as myocarditis.^2,10,13

Severity of HF at diagnosis is strongly indicative of a near-term prognosis in pediatric DCM. Children manifesting advanced symptoms (Ross/NYHA III, IV) are found to be at a notably greater risk of death/HTx as compared to those with less severe presentations.¹⁴ In a signifi-cant group of children, the researchers created a nomo-gram and a simple bedside score. They found that an advanced functional class not just predicted the outcome but was also the factor with the greatest weight, which is in agreement with the idea that severe heart failure is a highly indicative marker of immediate danger.¹⁴ Markers of critical illness, such as admission to the ICU, being on inotropes for a longer period, and the need for MCS, are mainly seen in children very close to cardiogenic shock and thus, these markers are highly correlated with early death or very quick progression to HTx.¹⁵ Besides baseline visual acuity being a starting point, prognosis is not static: analysis of registry data shows that the greatest risk of death or heart transplant is right after the diagno-sis, and those who stabilize continue to have an improv-ing conditional prognosis with recovery patterns varying according to the cause and treatment response.^2,16 On the clinical side, when a patient is in a critical condi-tion (for example, low blood pressure, which keeps get-ting worse, needing increasing doses of vasoactive drugs, ventilatory support, or consideration of ECMO/MCS), it is advisable to seek the help of advanced HF/transplant services immediately.^15,14 Severity scores are also useful; for instance, elevated NYU-PHFI scores have been linked with greater chances of death/HTx in pediatric DCM populations.¹⁷

Arrhythmias in pediatric DCM patients can be complica-tions as well as signs of the existence of a more malignant myocardial substrate. Although atrial arrhythmias and conduction disease usually are signs of an advanced or arrhythmogenic phenotype, sustained VT and advanced AV block are directly relevant to the risk of sudden death.⁵ Previously, reviews showed inconsistent relation-ships between heart rhythm disorders and results, prob-ably because of different definitions and small numbers of events in cohorts.⁵ Current evidence from the reg-istry era confirms that physicians should classify as “high-concern” cardiac arrest or life-threatening ventricular ar-rhythmias and severe conduction abnormalities on ECG, notably when there is also severe LV dysfunction or the presence of adverse remodeling.¹⁸ Sudden cardiac death (SCD) is a smaller, but still significant, part of the total mortality in DCM (3% at 5 years). Hence, prag-matic stratification tools have been suggested that can be used to identify children who might be monitored more closely for their heart rhythm or even considered for de-vice therapy.¹⁸ For example, in one model, it was demonstrated that the majority of SCD events occurred in children who at one point fulfilled the triad criteria (severe LV dilation, age below a certain threshold, and LV wall thinning), which is in line with a thin-walled, heavily remodeled ventricle that is vulnerable to malig-nant arrhythmias.¹⁸ ECG phenotypes might provide additional prognostic information that is independent of other factors: lowvoltage QRS was independently asso-ciated with death/HTx in a contemporary pediatric risk score,¹⁴ probably indicating diffuse myocardial disease or fibrosis burden.¹⁴ In addition, conduction disease may indicate the presence of high-risk genotypes; LMNA-related DCM is typically accompanied by conduction ab-normalities and malignant ventricular arrhythmias, which justifies rhythm surveillance and escalation planning from a very early stage.¹⁹ A similar example would be SCN5A-related phenotypes, which may present a mixture of conduction disorder/arrhythmias, together with struc-tural DCM, thus emphasizing the idea that “electrical red flags” might be an indicator of genotype-related risk.²⁰ In a real-world scenario, a patient with sustained VT, a high number of ectopy/NSVT together with adverse re-modeling, or major conduction disease should be consid-ered for a more intensive follow-up and the involvement of an electrophysiologist, while decisions about the device should be individualized.^18,19,20

The knowledge of cardiomyopathy or sudden cardiac death in a family is medically very significant as it can be used as a proxy for the presence of hereditary dis-eases. Therefore, it is common that this evidence leads to early genetic testing and cascade screening.²¹ On the other hand, the majority of studies show that family his-tory alone has no clear effect on the outcomes of pediatric DCM. The variations in definition, referral patterns, and genetic testing intensity among cohorts might have con-tributed to the different evidence obtained.²² A single-center cohort found a positive family history of DCM to be significantly associated with mortality in Cox regression.¹² On the other hand, a registry-based comparison of familial DCM versus idiopathic DCM in children revealed a broadly similar transplant-free survival, and the family history of sudden death was not an independent predic-tor of death/HTx.²² Similarly, in the context of SCD-centric modeling, family history has not always been ob-served as a standalone predictor.¹⁸ Thus, family his-tory should ideally be handled less as a statistical risk-enhancing factor and more as a very effective prompt for obtaining a more comprehensive etiologic understanding, especially genetic testing and rhythm monitoring, since the actual risk is frequently determined by the genotype-associated malignant phenotypes rather than by family history itself.^21,22

While the occurrence rates differ between sexes, sex, however, has not ultimately been identified as a stable independent predictor of death/HTx when the pheno-type and severity are taken into account.^2,22 Un-der competing-risk models, male sex has failed to demon-strate a strong correlation with the combined outcome of death or transplantation, thereby implying that the dif-ference seen is usually a result of the severity, etiologic mix, or care pathways factors.²² For example, sex-related disparities in advanced-therapy treatments rather than in the biology of intrinsic DCM could be more pro-nounced; transplant-era analyses, for instance, have doc-umented differences in pediatric waitlist survival by sex while the transplantation rates were the same.²³ In comparison, growth and nutritional status are indicative of the overall whole-child severity. Stunting (low height-for-age z-score) has been linked in PCMR studies to a higher risk of death (even more than the risk of trans-plantation), which is in line with the understanding that growth failure reflects the chronic burden of heart fail-ure and the child’s susceptibility to decompensation.⁵ From a clinical standpoint, failure to thrive or malnutri-tion can be considered effective warning signs that ne-cessitate increased monitoring and supportive treatment when combined with adverse cardiac indicators.^2,5

Resource setting has a major impact on the outcomes ob-served in pediatric DCM, mainly through access to ad-vanced HF therapies such as HTx and durable VAD sup-port.²⁴ In LMICs, these options may be limited, and outcomes often reflect what can be achieved with med-ical therapy and supportive care alone; a prospective study conducted in Khartoum state (Sudan) has shown very high mortality rates, thus emphasizing the suffer-ing of the very ill patients without the availability of scal-ing up treatments.²⁵ Other LMIC cohorts also report similar high event rates and persistent severe dysfunc-tion, which is in line with delayed presentation and lim-ited longitudinal HF infrastructures that exacerbate early risk.²⁶ LMIC studies also uncover modifiable factors. For instance, an Ethiopian decade-experience series first linked malnutrition to bad outcomes and then enalapril use to better outcomes, implying that basic HF optimiza-tion in these patients can still bring significant improve-ments even when HTx is not available.²⁷ On the other hand, in transplant-capable systems, HTx and durable support have the potential to change the paths of the pa-tients from death to survival with advanced intervention, thereby making the use of the composite endpoint “death or HTx” complicated for comparisons.²⁴ Experience in the United States shows that using durable VADs as a bridge to transplant for a longer period can result in greater success of bridging to transplantation when com-pared with the use of extracorporeal support. This is an example of how the healthcare system’s ability to man-age a case can change what was initially a fatal course into a survival after transplantation.²⁸ Through the years, registry studies have also revealed enhanced sur-vival without the need for a transplant, indicating that HF treatment improvements have been made in general and not just in the areas of transplant volume.⁷ Hence, prognostic understanding must deliberately recognize re-source context; a given clinical severity, therefore, may result in different actual risks based on whether and how quickly advanced therapies are available.^24,25 The major clinical and demographic predictors, together with representative supporting evidence, are summarized in Table 1.

B. Echocardiographic and Imaging Predictors

Since DCM basically is ventricular dilatation and dysfunc-tion, one should not be surprised that quantitation of the cardiac size and function by various imaging techniques have very powerful prognostic significance. Echocardio-graphy is the first interventional tool and a number of studies have tested ejection fraction, fractional shortening and ventricular dimensions as predictors of outcome. Re-cently, different advanced imaging parameters like strain from speckle-tracking echocardiography or fibrosis detec-tion by cardiac MRI have been investigated. A systematic review and meta-analysis focusing on childhood imaging risk factors in DCM by Street-de-Palma et al. (2025) con-firmed EF, LV size, and MR to be the top three most consistently associated parameters (refer to Table 2 for pooled effect estimates).⁸

LVEF is still one of the most consistent and reliable imag-ing markers for pediatric DCM. It has been able con-sistently to distinguish between higher- and lower-risk groups not only in individual observational cohorts but also pooled analyses.^5,8 Fractional shortening (FS), which is commonly used in pediatrics, gives a supplemental prognostic indicator; initial FS (and its standardized z-score) has been associated with death/HTx risk, and, clin-ically important, serial absence of FS improvement identi-fies children with continuously high risk even when base-line values are similar ( Table 2).²⁹ In fact, EF/FS can be regarded as severity anchors that provide the bound-aries for the rest of the prognostic assessment and thus should not be seen as standalone “yes/no” predictors.⁵

Besides it being merely a baseline severity, the early re-modeling trajectory typically determines the fate. Se-rial PCMR analyses reveal that, at the point of one year, the majority of children who are alive without a trans-plant have their LV systolic function and chamber size im-proved. However, the cases where the function remains impaired or the dilation progresses in the first few months of the disease are marked as a high-risk pathway.³⁰ This notion of “dynamic risk” is in line with shifting from a single time-point interpretation (baseline EF/FS) to-wards a trajectory-based interpretation (response vs non-response) in consultation with families and making deci-sions on the timing of escalation.^2,16,30 Besides, it is necessary to integrate trajectory with other domains; for instance, a longitudinal study might find that imaging measures (such as GLS) were significant predictors in the univariate analyses, however, NT-proBNP was identified as the strongest independent predictor in the multivari-ate analysis, meaning that remodeling parameters usu-ally reflect the same heart failure biological process that biomarkers detect (and not that they are substitutes for biomarkers).³¹

LV dilation that is usually measured as LVEDD z-score is the second main imaging predictor of pediatric DCM and has been consistently negatively associated in pooled ev-idence ( Table 2).⁸ Longitudinal modeling highlights that changes over time may even represent a larger risk factor than baseline measurements. LV size at baseline is important, but if the size keeps getting worse in se-rial measurements (particularly enlargement of systolic dimensions), it usually reflects an unfavorable remodel-ing process and increased risk of events.³² At the bed-side stratification, simple threshold-based methods have been suggested to help in identifying high-risk pheno-types (e.g., CART-derived cutoffs combining LV size and EF). These methods confirm that the combination of “very large LV + severe dysfunction” is widely recognized as the most dangerous pattern across datasets.³³

Functional mitral regurgitation is common in children with idiopathic DCM and is a direct consequence of ge-ometric changes (annular dilation and papillary muscle displacement) occurring together with a deterioration of hemodynamics. Whereas some of the older studies dis-agreed, a collection of up-to-date evidence now indi-cates that moderate-to-severe MR is an important nega-tive prognostic marker ( Table 2).⁸ Actually, this idea has also made its way into prognosis tools; e.g., latest pe-diatric risk models use MR grade as a significant compo-nent to determine the risk of death/HTx, which is in line with MR being both a marker and a booster of remodel-ing (volume overload and reduced forward output).¹⁴ From a clinical standpoint, the level of MR provides the most valuable information when it is combined with LV size and systolic function, and also when it is monitored over time as the remodeling changes continue.^8,14

Even though the strongest predictors in prognostic mod-els are typically those related to the LV, the presence of RV dysfunction frequently signifies a progressed biventricu-lar disease and can challenge the management as well as the planning of advanced therapies. Serial studies on chil-dren have revealed that intact RV function (for instance, greater TAPSE or RV fractional area change) is linked to a lower risk, which is in line with the clinical view of RV reserve being protective ( Table 2).³² Hence, measures of RV function should mainly be considered as a potential additional source of risk information, especially when one is thinking about the timing and suitability for therapy es-calation.³²

Speckle-tracking GLS is a technique that analyses myocar-dial deformation, which means that it is able to uncover dysfunctions that EF cannot detect. In children, GLS has been a significant prognostic factor in univariate analyses of repeated-measures cohorts, but its incremental inde-pendence may be compromised when powerful biomark-ers of HF (especially NT-proBNP) are added to the model, thus thereby partially sharing the signals of global HF severity.³¹ Anyway, GLS remains an absolutely valid clinical instrument for profiling phenotypes and is highly sensitive for the detection of subtle systolic impairment; in the case, control pediatric data, GLS was found to be greatly impaired in DCM compared to normal controls, thus depicting the magnitude of deformation loss in the disease condition.³⁴ Today, GLS mainly serves as a secondary marker, for instance, in cases where EF is bor-derline or when the initial phases of the disease are being tracked, while waiting for a large pediatric dataset to help quantify the additional prognostic benefit over EF/LV size and biomarkers.^31,34

CMR offers additional tissue characterization, such as LGE which is used as a fingerprint of fibrosis/scar. LGE is a very well-known negative marker in adult DCM but prog-nostic evidence in the pediatric population is still scarce. According to the 2025 meta-analysis, only a few pediatric studies on LGE were found and a statistically strong cor-relation with outcomes was not shown, thus highlighting the limited power and heterogeneity of the present pe-diatric CMR literature ( Table 2).⁸ Therefore, CMR is typically very helpful in children mainly for clarifying the cause of a disease (for example, patterns of myocarditis or infiltrative diseases) rather than for final risk assessment, however, in practice, widespread fibrosis is still generally considered worrying.⁸

Several additional echo measures, particularly diastolic indices, show emerging albeit inconsistent evidence in pe-diatrics. In longitudinal prediction studies, certain dias-tolic surrogates and their serial changes were linked to the lowering of risk, thus they supported the idea that di-astolic remodeling patterns could, in certain phenotypes, contain clinically relevant information.³² Smaller ret-rospective analyses have also indicated a strong correla-tion of very low transmittal E-wave velocity with mor-tality, possibly due to severely reduced forward flow or advanced dysfunction in certain children.¹² Older global size surrogates (e.g. CTR on chest radiography) in essence are a mirror of the echo derived cardiomegaly and have been reported as adverse in some earlier contexts, however, echo has essentially taken over CTR for current risk quantification.⁹ Pulmonary hypertension (PH) de-tected by echocardiography (e.g., high estimated RV sys-tolic pressure from TR jet) is an extra prognostic factor as it mostly indicates that the LV filling pressures have been elevated for a long time and the disease is at an advanced stage. Among the pediatric DCM group reported by Wang et al., PH (defined by PASP ≥30 mmHg) was a frequently observed clinical condition and it was even more numeri-cally common among non-survivors, However, PH did not turn out to be an independent predictor when multivari-able modeling was done. This is just one example of how PH might be a severity correlate instead of an indepen-dent signal in different datasets.³⁵ From a clinical per-spective, one of the key factors that can lead to the accel-eration of referral and escalation planning (including ad-vanced HF/transplant assessment) is the demonstration of persistently elevated pulmonary pressures despite op-timized therapy, as this could potentially limit the options and also increase the risk during the peri-transplant pe-riod.³⁶

C. Biomarkers and Neurohormonal Indicators

Circulating biomarkers add objective, repeatable signals of hemodynamic stress, neurohormonal activation, and systemic response that complement clinical and imag-ing assessment in pediatric DCM.^31,37 Natriuretic peptides are the most extensively validated for progno-sis among the various laboratory biomarkers available, whereas inflammatory indices that are derived from CBC and abnormalities in routine chemistry are probably best regarded as adjuncts, with very limited pediatric evidence at present ( Table 3).^12,31,37

1) NT-proBNP/BNP

2) Inflammatory Markers (Neutrophil-to-Lymphocyte Ratio (NLR) and Systemic In-flammatory Index (SII)):

3) Other Biomarkers and Routine Laboratory In-dicators:

D. Genetic Factors and Genotype-Phenotype Correlations

Genetic testing has fundamentally changed our understanding of the causes and outcomes of pediatric DCM. Today, an increasingly standard part of care is compre-hensive genomic testing, mainly because it can (i) iden-tify the cause of the disease, (ii) facilitate family mem-bers’ testing through cascade screening, and (iii) pro-vide risk assessment if the genotype, outcome associations are known in pediatric populations.^11,39 Diagnostic yield varies among cohorts because of different pheno-type definitions (isolated vs. syndromic DCM), age com-position, and sequencing/interpretation pipelines. How-ever, various studies have demonstrated that a signifi-cant portion of children initially diagnosed as “idiopathic” cases, are eventually discovered to have a genetic basis for their condition when thoroughly examined.^11,39 Studies of contemporary pediatric DCM cohorts show that the yield varies considerably between identifying genetic causes, and pediatric outcome data now reveal that the “gene-positive” status can have prognostic implications, i.e., it is not solely diagnostic. Genome sequencing of a nationwide Dutch pediatric DCM cohort (2010, 2017) un-covered LP/P variants in more than one-third of the chil-dren tested, and the carriers of the variants had a signif-icantly worse transplant-free survival, with a greater risk (hazard) of death/HTx during the follow-up period.¹¹ One of the things that most clearly reveals the usefulness of clinical utility is a lot of sequencing work done in stud-ies of pediatric cardiomyopathy. For instance, the exome-based work in a large pediatric cohort found a molecular diagnosis in about a third of patients overall. The study also showed that the yield depended on the age and was lower in infants. This therefore supports the notion that the yield from a cohort is determined by its make-up and the risk interpretation given afterwards.^40,41

i. Gene spectra and age-dependent patterns

One’s genetic background may be physiologically differ-ent at different ages and thus can be very useful for diag-nosis. The research group from the Netherlands found that the profile of the spectrum varies among the different age groups. At a very early stage, even since birth-onset cases of sarcomeric/cytoskeletal genes (e.g., MYH7 and others) dominated. Whereas, the children of older/adolescent groups generally had the involvement of more genes such as TTN and RBM20 in that pattern.¹¹ Clinically, it also helps to calibrate the pre-test probability and also guides as to what to tell the patient: for in-stance, if the patient comes very early the doctor may start thinking of certain sarcomeric etiologies, but if the ven-tricular dysfunction develops during the teenage years, the genetic cause will be suspected to be one that leads to severe remodeling of the heart and increases the risk of arrhythmias as is generally known from the DCM ge-netics literature.^11,39

ii. Presence of a pathogenic variant: prognosis is not purely “baseline DCM,” and genetics can modify “acquired” triggers

Identification of an LP/P variant offers a major cardiomy-opathic substrate which, at a population level, seems less capable of completely reversal than a truly tran-sient injury. The pediatric outcome data give direct backing to this: in the Dutch nationwide cohort, dur-ing follow-up, the variant carrier children had a signifi-cantly higher risk of death/HTx than the variant-negative children.¹¹ In fact, the role of genetics also opens up new perspectives on the so-called “acquired” trig-gers, as it is a predisposition/second-hit model. A very good example that supports this notion comes from pe-diatric biopsy-proven myocarditis. In a cohort study, gene variants of cardiomyopathy were not uncommon; on the contrary, they were more frequent among those children who had a DCM phenotype, and thus, a signif-icantly worse event-free survival was found in children with gene variants. Therefore, part of the “myocarditis” presentation may be due to inherited susceptibility espe-cially when myocarditis is combined with DCM-like re-modeling.¹⁰ Convergent evidences drawn from adult population-based samples also demonstrate a higher fre-quency of rare cardiomyopathy-gene variants in acute my-ocarditis patients versus controls, hence genetically pre-disposed to be revealed by exposure to environmental or inflammatory stressors.⁴² It is always safe to be cau-tious about directly applying the generalizations made about adults to children, however, these signals give more weight to the argument that genomics should be evalu-ated early in cases of myocarditis complicated by the pres-ence of prominent DCM features or an atypical trajectory.^10,42

iii. Specific genes and genotypes associated with poorer prognosis or “arrhythmic DCM” be-havior

While pediatric genotype, outcome datasets in DCM are inherently smaller than those of adults, modern pediatric cohorts and guidelines meta-analysis endorse the exis-tence of “arrhythmic” or higher-risk DCM genotypes (typ-ically including LMNA, FLNC, PLN, RBM20, and several others) that require an accelerated rhythm surveillance and individualized preventive strategy.^11,39 Since pediatric quantification is limited in extent, it is most rea-sonable to accept that risk estimation is usually based on adult cohorts, whereas pediatric studies are now show-ing similar patterns, occasionally even early-onset severe disease.

iv. Genetic vs non-genetic DCM: recovery and risk-stratification implications

One practical combination which fits well with the current evidence is the idea that genotype status may explain to some extent why kids with the same baseline echocar-diography follow different paths. Disease-positive vari-ants may be less prone to continued reverse remodeling after the first injury, whereas negative-variant/idiopathic groups may even show a partial recovery in some cases, although there are exceptions and the cause of the dis-ease is still the main factor.^43,11 Genotype can be seen as one of the factors influencing the decision of in-creasing the management intensity: it can serve to de-cide the necessity of more frequent follow-up visits, the implementation of more intensified rhythm monitoring, and referral to advanced heart failure programs at lower severity levels in high-risk/arrhythmic substrates cases, whereas, the choices of pediatric devices should be kept individualized and aligned with the guidelines.^11,39 Finally, family screening becomes an urgent clinical out-come after the discovery of an LP/P variant. It allows for the identification of asymptomatic relatives and leads to better management of familial risk.^11,39 Several pediatric DCM genotypes may produce phenotypes with a higher arrhythmic burden than others, and this vul-nerability is not fully captured by LVEF alone; therefore, genotype-informed rhythm surveillance appears more ap-propriate than relying on a single functional threshold. Table 4 picks out a few genes and the associated pheno-types/outcomes for easier reference: