Heart Rate Variability Is an Independent Predictor of Morbidity and Mortality in Hemodynamically Stable Trauma Patients

Ryan, Mark L.; Ogilvie, Michael P.; Pereira, Bruno M.; Gómez-Rodríguez, Juan Carlos; Manning, Ronald J.; Vargas, Paola A.; Duncan, Robert C.; Proctor, Kenneth G.

doi:10.1097/ta.0b013e31821858e6

Cited by 61 publications

(42 citation statements)

References 32 publications

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“…Evidence of reduced HRV after TBI implies reduced parasympathetic tone (Baguley et al, 2006). With TBI, HRV has been shown to predict brain death and cerebrovascular dysregulation (Ryan et al, 2011), and HRV is associated with autonomic dysfunction in multiple other pathological states including sepsis, shock, and adrenal insufficiency (Morris et al, 2007; Werdan et al, 2009), each of which can co-occur in TBI. Further work suggests that HRV can be an effective mortality predictor, among hemodynamically stable patients with TBI (Ryan et al, 2011).…”

Section: Discussionmentioning

confidence: 99%

“…With TBI, HRV has been shown to predict brain death and cerebrovascular dysregulation (Ryan et al, 2011), and HRV is associated with autonomic dysfunction in multiple other pathological states including sepsis, shock, and adrenal insufficiency (Morris et al, 2007; Werdan et al, 2009), each of which can co-occur in TBI. Further work suggests that HRV can be an effective mortality predictor, among hemodynamically stable patients with TBI (Ryan et al, 2011). Importantly, there is evidence that BDNF levels (Pal et al, 2014), BDNF genetic variability (Yang et al, 2010), and cortisol levels (Pal et al, 2014) are associated with HRV, making autonomic instability a plausible mechanism by which cortisol regulation of BDNF affects mortality risk.…”

Section: Discussionmentioning

confidence: 99%

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Cerebrospinal Fluid Cortisol Mediates Brain-Derived Neurotrophic Factor Relationships to Mortality after Severe TBI: A Prospective Cohort Study

Munoz

Kumar

et al. 2017

Front. Mol. Neurosci.

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Distinct regulatory signaling mechanisms exist between cortisol and brain derived neurotrophic factor (BDNF) that may influence secondary injury cascades associated with traumatic brain injury (TBI) and predict outcome. We investigated concurrent CSF BDNF and cortisol relationships in 117 patients sampled days 0–6 after severe TBI while accounting for BDNF genetics and age. We also determined associations between CSF BDNF and cortisol with 6-month mortality. BDNF variants, rs6265 and rs7124442, were used to create a gene risk score (GRS) in reference to previously published hypothesized risk for mortality in “younger patients” (<48 years) and hypothesized BDNF production/secretion capacity with these variants. Group based trajectory analysis (TRAJ) was used to create two cortisol groups (high and low trajectories). A Bayesian estimation approach informed the mediation models. Results show CSF BDNF predicted patient cortisol TRAJ group (P = 0.001). Also, GRS moderated BDNF associations with cortisol TRAJ group. Additionally, cortisol TRAJ predicted 6-month mortality (P = 0.001). In a mediation analysis, BDNF predicted mortality, with cortisol acting as the mediator (P = 0.011), yielding a mediation percentage of 29.92%. Mediation effects increased to 45.45% among younger patients. A BDNF*GRS interaction predicted mortality in younger patients (P = 0.004). Thus, we conclude 6-month mortality after severe TBI can be predicted through a mediation model with CSF cortisol and BDNF, suggesting a regulatory role for cortisol with BDNF's contribution to TBI pathophysiology and mortality, particularly among younger individuals with severe TBI. Based on the literature, cortisol modulated BDNF effects on mortality after TBI may be related to known hormone and neurotrophin relationships to neurological injury severity and autonomic nervous system imbalance.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Cerebrospinal Fluid Cortisol Mediates Brain-Derived Neurotrophic Factor Relationships to Mortality after Severe TBI: A Prospective Cohort Study

Munoz

Kumar

et al. 2017

Front. Mol. Neurosci.

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“…3 HRV is increasingly gaining popularity as a predictor of outcome in a variety of clinical environments, including trauma patients, 12 critically ill emergency department 4 patients, 13 septic patients on admission to ED, 14 and the haemodynamically stable trauma patient. 15 It has also been used to predict outcomes such as hypotension during obstetric spinal hypotension. 16,17 Its use in ICU and anaesthesia has been extensively reviewed elsewhere.…”

Section: Discussionmentioning

confidence: 99%

Heart rate variability predicts 30-day all-cause mortality in intensive care units

Bishop

Wise

Lee

et al. 2016

Southern African Journal of Anaesthesia and Analgesia

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Background: Autonomic nervous function, as quantified by heart rate variability (HRV), has shown promise in predicting clinically important outcomes in the critical care setting; however, there is debate concerning its utility. HRV analysis was assessed as a practical tool for outcome prediction in two South African hospitals and compared with Acute Physiology and Chronic Health Evaluation II (APACHE II) scoring. Method: In a dual centre, prospective, observational cohort study of patients admitted to the intensive care units (ICU) of two hospitals in KwaZulu-Natal, South Africa frequency domain HRV parameters were explored as predictors of: all-cause mortality at 30 days after admission; ICU stay duration; the need for invasive ventilation; the need for inotrope/vasopressor therapy; and the need for renal replacement therapy. The predictive ability of HRV parameters against the APACHE II score for the study outcomes was also compared. Results: A total of 55 patients were included in the study. Very low frequency power (VLF) was shown to predict 30-day mortality in ICU (odds ratio 0.6; 95% confidence interval 0.396-0.911). When compared with APACHE II, VLF remained a significant predictor of outcome, suggesting that it adds a unique component of prediction. No HRV parameters were predictive for the other secondary outcomes. Conclusion: This study found that VLF independently predicted all-cause mortality at 30 days after ICU admission. VLF provided additional predictive ability above that of the APACHE II score. As suggested by this exploratory analysis larger multi-centre studies seem warranted.

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“…6,8,14 For example, a recent report demonstrated that reduced HRV was an independent predictor of morbidity and mortality in 216 hemodynamically stable trauma patients with evidence of traumatic brain injury upon hospital arrival. 6 Importantly, however, the aforementioned study acknowledges that HRV analysis was completed a few hours to 3 days after initial measurement, which limits usefulness for clinical decision making. Similarly, Cancio et al 4 noted that analysis of HRV parameters required long processing times, which limits clinical utility.…”

Section: Discussionmentioning

confidence: 99%

Real-time heart rate entropy predicts the need for lifesaving interventions in trauma activation patients

Mejaddam

Birkhan

Sideris

et al. 2013

Journal of Trauma and Acute Care Surgery

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Heart Rate Variability Is an Independent Predictor of Morbidity and Mortality in Hemodynamically Stable Trauma Patients

Cited by 61 publications

References 32 publications

Cerebrospinal Fluid Cortisol Mediates Brain-Derived Neurotrophic Factor Relationships to Mortality after Severe TBI: A Prospective Cohort Study

Cerebrospinal Fluid Cortisol Mediates Brain-Derived Neurotrophic Factor Relationships to Mortality after Severe TBI: A Prospective Cohort Study

Heart rate variability predicts 30-day all-cause mortality in intensive care units

Real-time heart rate entropy predicts the need for lifesaving interventions in trauma activation patients

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