Estimating early and long-term functional outcomes is not a one-size-fits-all process but rather a dynamic synthesis of multiple factors. These include the nature of acute brain injury, the patient’s premorbid state, insights from clinical status and findings from neuroprognostic tests, and ethical considerations, with each factor weighed differently depending on the individual case. The complexity of neuroprognostication following HIBI is further compounded by the significant variability and lack of standardization in current practices despite many different available guidelines. ^,,,,, While current guidelines outline the evidence supporting the recommendation of each prognostic tool and highlight their pitfalls, they do not prioritize one over another or specify a recommended sequence of use. Table 1 summarizes the 3 most referenced neuroprognostication guidelines for HIBI; note that American Heart Association 2025 updated version is expected to replace 2020 when published. In practice, clinicians are often faced with the challenge of reconciling conflicting recommendations across existing guidelines and determining how best to apply them to the specific scenario at hand. Even when presented with the same clinical scenario, experts might not agree on their interpretation for the recovery potential and in their final prognostic impressions. Each guideline has their own process for selecting, reviewing, appraising, and synthesizing evidence into a set of recommendations, which include specific norms and boundaries. Most guidelines have limited generalizability, as they are rarely applicable to every possible scenario; their recommendations must remain grounded to the boundaries of available evidence, even while recognizing the disconnect between controlled study conditions and real-world clinical practice. A central practical challenge lies in aligning patient’s values regarding acceptable levels of disability with the interpretation of the findings from neuroprognostic tools, as guided by existing recommendations. While the patient’s values ultimately define what constitutes a favorable outcome or meaningful recovery—for example, what level of disability is personally considered unacceptable, and thus, a poor outcome ?—guidelines lack the nuance to accommodate individualized interpretations on a case-by-case basis. Being confined to the available evidence, the meaning behind “poor,” “unfavorable,” “good,” “favorable,” “meaningful” in guidelines is derived from the approach chosen by investigators conducting studies that informed practice guidelines. The required pragmatic definitions for analyses, often dichotomizing outcomes from functional scales into “good” and “poor” outcomes, are agnostic of individual premorbid status, preferences, and values. In most neuroprognostic studies, a “favorable” functional outcome is defined by the ability to achieve independence (ie, Glasgow-Pittsburgh Cerebral Performance Category, CPC, scores 1–2 or modified Rankin Scale, mRS, scores 0–3), although some studies have lower thresholds characterized by recovery of consciousness (ie, CPC 1–3 or mRS 0–4). For a cardiac arrest survivor whose premorbid baseline included dependence on others for advanced activities of daily living for the last 2 decades, returning to that baseline state might be a meaningful recovery—yet, without this personalized nuance, this individual is automatically allocated to a category of “poor” outcome in most studies (CPC 3). It is, therefore, essential to recognize this practical limitation when applying recommendations in clinical practice—especially during discussions with surrogates. Rather than focusing solely on the binary question, “ Will this patient survive neurologically intact? ,” clinicians should be asking instead: “ How long will recovery take, and to what extent will specific functions be regained? ” and “ What level of disability would be considered meaningful or acceptable for this individual? .” This shift in perspective is particularly important when navigating prognostic uncertainty and reflect the bias of attribute substitution, when using a simpler, related question when trying to tackle a complex problem.

While integrating multiple predictive modalities improves prognostic accuracy and reduces uncertainty, it also increases complexity and the risk of cognitive biases driven by heuristics. Neuroprognostication is fraught with uncertainty, from limitations of current prognostic tools, methodology used in neuroprognostic studies, and cognitive biases underlying systematic errors inherent to the process of outcome prediction. Most patients who remain comatose after cardiac arrest ultimately die from neurologic causes: approximately 10% to 20% progress to brain death, ^,, while the remaining 80% die following withdrawal of life support based on the perceived poor neurologic prognosis. ^, Even in the context of clinical trials, deaths related to withdrawal of life support occur prematurely within 72 hours from ROSC. ^,

The self-fulfilling prophecy bias is pervasive in neuroprognostic studies, perpetuating the overinflated prediction performance of tools being investigated, when the findings from such tools are used in clinical practice to inform end-of-life decisions. ^, Acknowledging the role of heuristic judgment is critical in outcome prediction, as withdrawing life support based on an inaccurately perceived poor prognosis can lead to irreversible consequences. Health care providers are better at predicting 6-month mortality than neurologic outcomes ; this can also reflect self-fulfilling prophecy bias, reinforced heuristic judgment, and attribute substitution bias.

The predictive performance of various tools for estimating favorable or unfavorable outcomes varies widely. ^, Ideally, neuroprognostication should incorporate several modalities of tests; however, this is far from the reality: in a study utilizing administrative data, fewer than 10% of patients had at least one and only 2% had at least 2 prognostic tests. A great threat to neuroprognostication is the limited access to recommended tools, which in turn leads to reduced familiarity and potential discomfort with their use and interpretation of findings creating a vicious cycle. The limited access to these tools, coupled with variability in how each provider conducts and interprets the available tests, presents significant risks that must be carefully considered. Future guidelines should account for variations in access to these modalities and provide alternative approaches to ensure equitable and reliable prognostication.

Another important challenge is the variability in the timing of assessments and prognostic conclusions. The timing of testing for neuroprognostic tools depends on each tool and on the intent for maximizing its yield; this is determined often by avoiding the effect of confounding (eg, temperature and sedatives effect) or neurophysiologic stunning from anoxic depolarizations. The ideal timing for testing also hinges on the intent for each specific tool: If capturing the impact of early injury from primary insults (thus, early timing for testing) or capturing the overall burden of HIBI after the cascade of secondary injury is completed (ie, delayed after 48–72 hours from cardiac arrest). Providers report favoring accuracy of predictors over timeliness of prognostic impressions; in fact, the highest false positive rate deemed acceptable among practitioners who perform neuroprognostication in hypoxic-ischemic encephalopathy is just 0.1%. Conversely, there is a concerning trend of clinicians disclosing premature prognostic impressions in practice—often before the guideline-recommended minimum of 72 hours ^,,, —and relying on tools that carry an unacceptably high false positive rates (FPR; anchoring effect) or are used outside their optimal time window.

Many threats to the accuracy of neuroprognostication may coexist and have a compounding effect—patients for whom prognostic impressions were premature, are also less likely to have more than one prediction tool used, or the involvement of a neurology consultant. ^, These findings reinforce the importance of providers anchoring their practices on evidence-based guidelines and refraining from overinflating the value of anecdotal experiences and ingrained clinical practices. Avoiding overconfidence and identifying knowledge gaps is crucial in mitigating biases and improving neuroprognostication accuracy.