Abstract
To the Editor: We appreciate the insightful response by Kerezoudis et al1 to our article2 and agree with a number of points that they make regarding the role of neurosurgical intervention in the care of elderly patients with traumatic brain injury (TBI). We commend their previous work in this area.3 Longer life expectancies and a growing elderly population make the care of elderly patients with TBI a critical topic. As Kerezoudis et al1 mentioned, we believe that it is crucial to identify and risk stratify subgroups of elderly patients with TBI based on baseline patient health (underlying comorbidities, anticoagulation use, functional status, etc.), the pathologic characteristics of their TBI, and any advance care planning.4 The accurate risk stratification and identification of clinically meaningful patient subgroups requires detailed data on patient clinical characteristics, hospital course, and outcomes. Unfortunately, few big administrative data sets, such as the National Trauma Data Bank, include long-term outcomes relevant to TBI, such as 6-month, 1-year, and 2-year Glasgow Outcome Scale-Extended scores. A significant amount of recovery occurs outside of the initial hospitalization, especially for those patients with lower presenting Glasgow Coma Scale. Most information pertaining to functional recovery is, therefore, lost when postacute, longer-term outcomes are not measured. Including long-term outcomes is especially critical in elderly patients with TBI who have been shown to have a slower recovery than younger patients.4 Finally, current measures of long-term TBI outcomes are not designed for elderly patients and may not capture clinically significant improvements. As a result, measured outcomes in elderly patients can be artificially depressed and contribute to the nihilism surrounding elderly TBI. This limitation highlights the need for additional research into long-term outcome measures specific to TBI in elderly patients.4 An additional downside of large data sets such as the National Trauma Data Bank are that they lack insight into socioeconomic status, home support systems, and other factors in the bio-psycho-socio-ecological framework that encompasses the variety of factors which influence TBI recovery.5 Although this limitation highlights the need for additional research using data sets with more granular clinical data, it also calls attention to the need for caution in interpreting any results from observational data. Neurosurgical researchers need to avoid the McNamara fallacy, in which available quantitative data are assumed to be adequate and are used for the exclusion of other observations to formulate conclusions.6 Further investigation into the preoperative evaluation and risk stratification of elderly patients and underlying patient protoplasm is also required. The concept of a dissociation between chronological age and risk of adverse outcome (ie frailty) has been suggested since the 1970s.7,8 Previous studies in patients with general trauma have highlighted the superiority of frailty over age in predicting outcomes.9 In fact, a recent study by Galimberti et al10 demonstrated a strong relationship between frailty and outcomes after TBI in a large multicenter study. Interestingly, they also showed that elderly patients with low frailty had better outcomes than those with higher frailty, agreeing with previous reports of robust recovery in low frailty elderly patients11 and further demonstrating the importance of using frailty to risk stratify elderly patients. Despite the value of frailty in predicting outcomes, no standard method to measure frailty exists. In addition, many measures of frailty require a detailed clinical history which might not be available to clinicians or researchers. Ongoing research into additional biomarkers/predictors of frailty, such as genetic mutations, epigenetics, and metabolomics, may help to provide a less bias and more accurate measure of frailty which can be used to potentially inform surgical decision making in the future.7,12-15 There is a general need for additional investigation into elderly TBI to improve surgical and medical decision making for this growing patient population. The use of large granular data sets with extended follow-up data will undoubtedly play a role in furthering our understanding and care of elderly patients with TBI.16 In addition, frailty measures and novel prognostic biomarkers may help to identify clinically relevant subgroups and potentially guide elderly TBI-specific interventions that modify or reduce the impact of frailty on outcomes.
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