An observational study in Neurosurgical Patients, sponsored by National Institute of Mental Health and Neuro Sciences, India. Completed at 1 site in India. Open to participants aged 18 Years to 80 Years. Per ClinicalTrials.gov, last updated 2023-07-07.
Sponsored by National Institute of Mental Health and Neuro Sciences, India · Observational
The autonomic nervous system (ANS) is cardinal for maintaining systemic homeostasis and is pivotal for the baseline regulation and modulation of vital cardiovascular, hemodynamic, respiratory, gastrointestinal, and body temperature regulating functions. Pathological perturbations of the ANS leading to cardiac dysautonomia (CAD) affect one in 1000 population. Autonomic dysfunction can occur from a variety of pathological conditions such as ischemic heart disease, systemic hypertension, diabetes mellitus, neurological illnesses, neurotrauma, and cervical spine diseases. When patients with dysautonomia present for surgical procedures, they may manifest severe hemodynamic responses that may be less responsive to pharmacological interventions. Pre-existing autonomic dysfunction accentuates perioperative hemodynamic fluctuations during stressful events like direct laryngoscopy, endotracheal intubation, and extubation, and can result in major adverse cardiac events (MACE). The complications arising from CAD can prolong the duration of hospital stay and contribute to morbidity and mortality. Preoperative diagnosis of CAD helps in anticipation of and preparation for potentially severe adverse events in the perioperative period. Most neurosurgical patients are not candidates for detailed ANS examination in the supine and standing positions due to their underlying neurological condition. Real-time assessment of heart rate variability (HRV) using the ANSiscope equipment provides information on the sympathovagal balance during the immediate preoperative period and aids in the simple rapid bedside assessment of CAD. This study aims to examine the incidence of CAD through HRV assessment in neurosurgical patients, identify the potential risk factors for CAD in this population, and evaluate the impact of CAD on perioperative outcomes.
Demographic and baseline clinical data including comorbid conditions and medication history will be collected. Baseline hemodynamic parameters - heart rate (HR) and systolic, diastolic, and mean blood pressure (SBP, DBP, MAP), rate pressure product (RPP) calculated as the product of HR and SBP and ANSindex (which informs the degree of dysautonomia and is derived noninvasively from a recording of 572 R wave to R wave intervals on an electrocardiogram) will be recorded in the immediate preoperative period.
Assessment of risk factors for preoperative CAD The investigators will explore potential risk factors for CAD in neurosurgical patients. The investigators postulate some known factors such as anxiety which will be diagnosed using the Visual analog scale for anxiety (VAS-A), age, gender, neurosurgical pathology, site-specific surgery (high cervical pathology, structural brain lesions, brainstem lesion, etc.), pre-existing diabetes mellitus and hypertension, and medications used for their treatment, higher American Society of Anesthesiology (ASA) grade, etc. to be associated with CAD in neurosurgical patients.
The investigators will explore the association between CAD and perioperative outcomes. Major Adverse Cardiac Events during Intra and postoperative period, in-hospital mortality, and duration of postoperative ICU and hospital stay.
Anesthesia will be administered as per the existing practice. Hemodynamic parameters HR, SBP, DBP, MAP at following time points - before and 1 and 2 min after induction of general anesthesia, before and at 1, 3, and 5 mins after tracheal intubation, and before and at 1, 3, and 5 mins after skull pin application, where applicable. Adverse hemodynamic events - persistent hypotension, arrhythmias, myocardial ischemia, cardiac failure, cardiac arrest) during the early (after anesthetic induction and before surgical incision), late (surgical incision to surgical closure) intraoperative period, recovery period (end of anesthesia to discharge from the operating room), post-anesthesia care unit (PACU) period (from arrival to discharge from PACU) and early postoperative period (up to 72 hours after surgery), neurological status (Glasgow Coma Scale) at hospital discharge, and duration of ICU and hospital stay will be recorded. The core temperature will be monitored during the intraoperative period to detect hypothermia (\<35o C) or hyperthermia (>37.5 o C).
Sample size and statistical analysis Previous studies in the non-neurosurgical populations have determined the prevalence of CAD to vary from 25 to 73%. Considering an average prevalence of 50% in the neurosurgical population and a possible 5% margin of error, a sample size of 383 would be necessary for achieving a 95% confidence level. Hence the investigators plan to recruit 400 patients over a period of 1 year to account for potential dropouts from the study.
Data will be analyzed using Statistical Package for the Social Sciences (SPSS) or R software. Continuous variables will be compared by t-test, qualitative data by chi2 test, or Fisher exact test. Logistic regression will be used to identify the risk factors for cardiac autonomic dysfunction. A p \< 0.05 will be considered statistically significant.
Consenting patients scheduled for neurosurgical procedures at the National Institute of Mental Health and Neurosciences, Bengaluru will be recruited if they fulfill the study inclusion criteria during the period of study duration
Exclusion Criteria:
This is a prospective observational study
Also known as: No interventions
Prevalence of cardiac autonomic dysfunction in neurosurgical patients
To study the prevalence of cardiac autonomic dysfunction in neurosurgical patients
Time frame: Before anesthesia administration for surgery
Risk factors of cardiac autonomic dysfunction in neurosurgical patients
To identify risk factors of cardiac autonomic dysfunction in neurosurgical patients
Time frame: Baseline
Impact of cardiac autonomic dysfunction on hemodynamic stress response
To assess the impact of cardiac autonomic dysfunction on hemodynamic stress response to laryngoscopy and intubation, anesthetic induction, and tracheal extubation
Time frame: During anesthesia procedure for surgery
Impact of cardiac autonomic dysfunction on hemodynamic instability
To assess the impact of cardiac autonomic dysfunction on incidence, duration and severity of intraoperative hypotension and hypertension and requirement of pharmacological intervention
Time frame: During surgery
Impact of cardiac autonomic dysfunction on Major Adverse Cardiac Events
To assess the impact of cardiac autonomic dysfunction on Major Adverse Cardiac Events namely, new onset myocardial ischemia, congestive cardiac failure, cardiac arrhythmias, cardiac arrest requiring resuscitation
Time frame: During and after surgery till discharge from the hospital, an average of 1 week
Impact of cardiac autonomic dysfunction on temperature instability
To assess the impact of cardiac autonomic dysfunction on incidence of hypothermia and hyperthermia
Time frame: During surgery
Impact of cardiac autonomic dysfunction on duration of hospital stay
To assess the impact of cardiac autonomic dysfunction on duration of ICU and hospital stay
Time frame: After surgery till the time of discharge from the hospital, an average of 1 week
Impact of cardiac autonomic dysfunction on in-hospital mortality
To assess the impact of cardiac autonomic dysfunction on in-hospital mortality
Time frame: After surgery till the time of discharge from the hospital, an average of 1 week
Plan to share: Undecided — Individual participant data will be available with the Principal Investigator and shared with other researchers on request.
This study is completed, as verified in Jul 2023. You cannot join it, but the record below documents what was studied.
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Autonomic Nervous System Diseases→
National Institute of Mental Health and Neuro Sciences, India