Risk Factors for Delirium Following Cardiac Surgery

In order to understand the role of medication usage and/or cardiopulmonary bypass, the investigators propose to leverage the perioperative data warehouse (PDW), an IRB approved data registry, to retrospectively evaluate the subjects. All patient data available in the warehouse may be included in the review. At this time, there are approximately 750,000 patients in the PDW. All data will be accessed retrospectively after the patient has been seen for their care here at Vanderbilt.

The Vanderbilt Perioperative Information Management System (VPIMS) is part of an integrated system that covers the entire perioperative process including instrument \& supply management, scheduling, and status displays. Because of the extensive effort that has been put toward in-house intraoperative software development, the Vanderbilt Anesthesiology \& Perioperative Informatics Research (VAPIR) Division is able to benefit from the availability of thousands of historical intraoperative records, each containing detailed physiologic information. The PDW incorporates VPIMS and electronic healthcare records (EHR) to build its database. In addition to PDW, information from the Society for Thoracic Surgeons (STS) database will be used in our study.

The database uses algorithms created by programmers with the assistance clinicians to screen the data and assess for accuracy and completeness. Once the data is compounded and uploaded, each variable is screened for outliers by a clinician. Outliers will be assessed and validated by a clinician based on trends from the raw data. The data collected for this study includes an extensive data dictionary listed below:

variable teeid anescasenumber mrn date orintime orouttime age gender race hx_dialysis_vpec hx_dialysis_hemodialysis_vpec hx_dialysis_peritoneal_vpec hx_esrd creatinine_base creatinine_pod1 creatinine_pod2 creatinine_pod3 creatinine_pod4 creatinine_pod5 creatinine_pod6 creatinine_pod7 creatinine_pod8 creatinine_pod9 creatinine_pod10 hx_htn hx_mi ck_preop ckmb_preop troponin_preop hx_cabg hx_angioplasty hx_angina hx_chf hx_ef_less_35 hx_chf_recent_hospital hx_chf_stable hx_chf_currentsigns hx_afib hx_aflutter hx_carotid_disease_current hx_carotid_disease_past hx_dementia hx_depression hx_stroke hx_tia hx_claudication chol_base ldl_base hdl_base triglycerides_base hx_copd hx_emphysema hx_smoking_current hx_smoking_quitless3months hx_smoking_quitmore3months hx_osa hx_hypoxia_ra_sat_less92 hx_home_o2 diabetes hba1c charlson_index weight height bmi hct_base hb_base platelet_count_base hx_neoplasm statin_preopyesno clopidogrel_preop aspirin_preop betablocker_preop aceinhibitor_preop diuretic_preop preop_meds ph_intraop_first ph_intraop_last ph_intraop_min ph_intraop_max ph_intraop_median ph_intraop_count po2_intraop_first po2_intraop_last po2_intraop_min po2_intraop_max po2_intraop_median po2_intraop_count lactate_intraop_first lactate_intraop_last lactate_intraop_min lactate_intraop_max lactate_intraop_median lactate_intraop_count ebl_intraop hespan_intraop lr_intraop lr5dex_intraop ns_intraop plasmalyte_intraop input_intraop uop_intraop emergency_surgery procedure_cpt procedure_descriptor cabg_grafts cpb_on_time1 cpb_off_time1 cpb_on_time2 cpb_off_time2 cpb_on_time3 cpb_off_time3 cpb_on_time4 cpb_off_time4 cpb_on_time5 cpb_off_time5 cpb_duration cpb_duration_calculated cbp_recorded_matches_calculated ao_clamp_duration circ_arrest_duration ultrafiltration_volume pump_drugs uop_onpump prbc_intraop_ml prbc_intraop_unit ffp_intraop_ml ffp_intraop_unit platelets_intraop_ml platelets_intraop_unit cryo_intraop_ml cryo_intraop_unit prbc_postop ffp_postop platelets_postop cryo_postop ckmb_pod1 req_reop_24 req_reop_72 is_reop wbc_base wbc_pod1 wbc_pod2 wbc_pod3 wbc_pod4 wbc_pod5 wbc_pod6 wbc_pod7 wbc_pod8 wbc_pod9 wbc_pod10 ph_pod1 ph_pod2 ph_pod3 ph_pod4 ph_pod5 ph_pod6 ph_pod7 ph_pod8 ph_pod9 ph_pod10 lactate_pod1 lactate_pod2 lactate_pod3 lactate_pod4 lactate_pod5 lactate_pod6 lactate_pod7 lactate_pod8 lactate_pod9 lactate_pod10 pfratio_pod1 pfratio_pod2 pfratio_pod3 pfratio_pod4 pfratio_pod5 pfratio_pod6 pfratio_pod7 pfratio_pod8 pfratio_pod9 pfratio_pod10 creatinine_pod30 creatinine_pod60 creatinine_pod90 creatinine_pod365 dialysis_postop_predischarge dialysis_postop_pod30 dialysis_postop_pod60 dialysis_postop_pod90 dialysis_postop_pod365 cam_icu_pod1 cam_icu_pod2 cam_icu_pod3 cam_icu_pod4 cam_icu_pod5 cam_icu_pod6 cam_icu_pod7 cam_icu_pod8 cam_icu_pod9 cam_icu_pod10 rass_pod1 rass_pod2 rass_pod3 rass_pod4 rass_pod5 rass_pod6 rass_pod7 rass_pod8 rass_pod9 rass_pod10 los_icu los los_surgery_discharge death_inhospital death_date death_pod30 death_pod60 death_pod90 death_pod365 afib_postop afib_postop_datetime afib_hours_between_orouttime_and_afib_postop_datetime afib_postop_ecg stroke_postop ventilation_time

The size of the registry for cardiac surgery patients in currently over 8,000 patients which should be more than enough to demonstrate an effect.

The following is a brief description of the investigators data analysis:

• Categorical variables will be expressed as frequency and percentage.
• Continuous variables will be reported as median and interquartile range (IQR).
• the investigators will compare the prevalence of medication use with the incidence of postoperative delirium and adjust for confounders.
• Analysis will initially be completed with adjusting for confounders, and then consider matching patients with propensity score based on initial results.
• Statistical significance (p≤0.05) for categorical variables will be computed using the Fisher's exact test or chi-squared and the Deuchler-Wilcoxon procedure or t-test for continuous variables.
• An iterative expectation-maximization (EM) algorithm will be considered to account for missing values or other form of imputation method unless deletion of missing data is more ideal.