Non-Cognitive Predictors of Student Success: A Predictive Validity Comparison Between Domestic and International Students Heart rate variability helps predict paroxysmal sympathetic hyperactivity after traumatic brain injury Non-Cognitive Predictors of Student Success: A Predictive Validity Comparison Between Domestic and International Students INTRO • Paroxysmal sympathetic hyperactivity (PSH) occurs in a subset of TBI patients • Diagnosed clinically; likely under-recognized • Associated with worse outcomes • Represents an imbalance between sympathetic and parasympathetic nervous systems • We sought to evaluate whether acute physiologic changes in markers of sympathetic and parasympathetic function may aid in the identification of PSH prior to its clinical expression in TBI patients METHODS 1. Case-control study design identified PSH cases matched by ICU admission GCS and age to non- PSH TBI controls (Figure 1, Table 1) 2. ECG data was assessed for time-frequency heart rate variability and waveform analysis over 5- minute epochs for the first 36 hours of admission 3. A generalized estimating equation (GEE) using autoregressive correlation was used to identify features associated with PSH Early changes in heart rate variability are associated with PSH after TBI Independent predictors of PSH Epidemiologic Non-white race Non-penetrating TBI Anatomical injury pattern a DAI Cisternal compression IVH/SAH Absence of contusion Physiologic Higher admission SBP LF:HF ratio DFA alpha1 RESULTS • Heart rate variability features differ over time between cases and controls (Fig 2) • PSH was diagnosed on hospital day 7 ±4, on average 5 days after physiologic analysis. • PSH cases have worse neurologic outcomes than age- and severity-matched controls (Fig 3) CONCLUSIONS • Quantitative measurement of autonomic nervous system function using continuous physiologic data to model HRV features may aid in the early identification of PSH in TBI patients. Figure 1: Patient inclusion flow diagram Figure 2: HRV parameters over time Figure 3: Discharge neurologic outcomes Table 1: Demographic and clinical characteristics of PSH cases vs controls Jamie Podell, Serenity Miller, Shiming Yang, Rao Gullapalli, Gunjan Parikh, Peter Hu, Neeraj Badjatia Program in Trauma, Departments of Neurology, Anesthesiology, University of Maryland School of Medicine a Based on initial Head CT Cases Controls p-value N=78 N=78 Age a 40.1 (14) 40.9 (14) 0.73 Female a 10 (13) 19 (24) 0.064 Race a 0.15 -- Asian 3 (4) 0 -- Black 34 (44) 30 (39) -- White 34 (44) 42 (54) -- Other/Unknown 7 (9) 6 (8) Penetrating injury a 1 (1) 10 (13) 0.012 Brain AIS b 4 (3,5) 4 (3,5) 0.28 ISS c 27.5 (11) 28.4 (12) 0.63 TRISS c 0.71 (0.23) 0.71 (0.28) 0.97 ICU admission GCS b 7 (5,8) 7 (5,9) 0.95 Craniotomy a 23 (30) 22 (28) 0.70 ICP monitor a <0.001 -- None 19 (24) 50 (64) -- Intraparenchymal 22 (28) 4 (5) -- Intraventricular 37 (47) 24 (31) Tracheostomy a 51 (65) 27 (35) <0.001 Gastrostomy a 55 (71) 39 (50) 0.009 a N(%); b Median(IQR); c Mean(SD) [email protected] Saatman, et al. J Neurotrauma 2008

Figure 1: Early changes in heart rate variability are associated ......Jamie Podell, Serenity Miller, ShimingYang, Rao Gullapalli, Gunjan Parikh, Peter Hu, Neeraj Badjatia Program

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Page 1: Figure 1: Early changes in heart rate variability are associated ......Jamie Podell, Serenity Miller, ShimingYang, Rao Gullapalli, Gunjan Parikh, Peter Hu, Neeraj Badjatia Program

Non-Cognitive Predictors of Student Success:A Predictive Validity Comparison Between Domestic and International Students

Heart rate variability helps predict

paroxysmal sympathetic hyperactivity

after traumatic brain injury

Non-Cognitive Predictors of Student Success:A Predictive Validity Comparison Between Domestic and International Students

INTRO

• Paroxysmal sympathetic hyperactivity (PSH) occurs in a subset of TBI patients

• Diagnosed clinically; likely under-recognized• Associated with worse outcomes• Represents an imbalance between sympathetic

and parasympathetic nervous systems• We sought to evaluate whether acute physiologic

changes in markers of sympathetic and parasympathetic function may aid in the identification of PSH prior to its clinical expression in TBI patients

METHODS

1. Case-control study design identified PSH cases matched by ICU admission GCS and age to non-PSH TBI controls (Figure 1, Table 1)

2. ECG data was assessed for time-frequency heart rate variability and waveform analysis over 5-minute epochs for the first 36 hours of admission

3. A generalized estimating equation (GEE) using autoregressive correlation was used to identify features associated with PSH

Early changes in heart rate variability are associated with PSH after TBI

Independent predictors of PSHEpidemiologic Non-white race

Non-penetrating TBIAnatomical injury patterna

DAICisternal compressionIVH/SAHAbsence of contusion

Physiologic Higher admission SBPLF:HF ratioDFA alpha1

RESULTS

• Heart rate variability features differ over time between cases and controls (Fig 2)

• PSH was diagnosed on hospital day 7 ±4, on average 5 days after physiologic analysis.

• PSH cases have worse neurologic outcomes than age- and severity-matched controls (Fig 3)

CONCLUSIONS• Quantitative measurement of autonomic nervous

system function using continuous physiologic data to model HRV features may aid in the early identification of PSH in TBI patients.

Figure 1: Patient inclusion flow diagram

Figure 2: HRV parameters over time

Figure 3: Discharge neurologic outcomes

Table 1: Demographic and clinical characteristics of PSH cases vs controls

Jamie Podell, Serenity Miller, Shiming Yang, Rao Gullapalli, Gunjan Parikh, Peter Hu, Neeraj Badjatia

Program in Trauma, Departments of Neurology, Anesthesiology, University of Maryland School of Medicine

aBased on initial Head CT

Cases Controls p-value N=78 N=78

Agea 40.1 (14) 40.9 (14) 0.73 Femalea 10 (13) 19 (24) 0.064 Racea 0.15 -- Asian 3 (4) 0

-- Black 34 (44) 30 (39) -- White 34 (44) 42 (54)

-- Other/Unknown 7 (9) 6 (8) Penetrating injurya 1 (1) 10 (13) 0.012 Brain AISb 4 (3,5) 4 (3,5) 0.28 ISSc 27.5 (11) 28.4 (12) 0.63 TRISSc 0.71 (0.23) 0.71 (0.28) 0.97 ICU admission GCSb 7 (5,8) 7 (5,9) 0.95 Craniotomya 23 (30) 22 (28) 0.70 ICP monitora <0.001 -- None 19 (24) 50 (64) -- Intraparenchymal 22 (28) 4 (5) -- Intraventricular 37 (47) 24 (31) Tracheostomya 51 (65) 27 (35) <0.001 Gastrostomya 55 (71) 39 (50) 0.009 aN(%); bMedian(IQR); cMean(SD)

[email protected]

Saatman, et al. J Neurotrauma 2008