Postoperative blood pressure variability as a risk factor for postoperative delirium in the patients receiving cardiac surgery

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The purpose of our study was to assess the relationship between perioperative blood pressure variability (BPV) and postoperative delirium (POD) in the patients after cardiac surgery. Methods : Adult patients received cardiac surgery and stayed in Cardiovascular Intensive Care Unit (ICU) for more than 24h after surgery during the study period between June 2019 and December 2022 were included in this study. Baseline characteristics, perioperative hemodynamic variables and postoperative laboratory results of the cardiac patients were collected and analyzed. Perioperative BPV was quantified by calculating the standard deviation (SD) and average real variability (ARV) of blood pressure. Assessment of delirium was based on the mental status of the patients and CAM-positive. The relationship between perioperative BPV and POD was analyzed by LASSO and logistic regression using R (R package, 4.3.2). Results: The incidence of POD was 15.0% (324/2164) in the patients receiving cardiac surgery, and the average day for POD occurred at day 3 after surgery. Patients with delirium had markedly lower levels of intraoperative mean blood pressure (BP_mean, P=0.015) and BP variability (BP_arv, P<0.001) as well as postoperative mean blood pressure within 24h (PM_IBPm_24h_mean, P=0.003) when compared to those patients without delirium. Whereas, postoperative ARV for systolic blood pressure (PM_IBPs_24h_arv, 8.64 [7.32, 10.2] vs. 7.91 [6.57, 9.43] mmHg, P<0.001), diastolic blood pressure (PM_IBPd_24h_arv, 4.00 [3.17, 4.83] vs. 3.77 [3.11, 4.60] mmHg, P=0.014) and mean blood pressure (PM_IBPm_24h_arv, 5.23 [4.46, 6.19] vs. 4.94 [4.11, 5.94] mmHg, P=0.001) at 24h was significantly higher in the patients with POD than those without. LASSO regression and further logistic regression revealed that intraoperative BP_arv (OR:0.92, 95%CI: 0.89-0.96, P<0.001), PM_CVPm_24h_mean (mean central venous pressure at 24h postoperatively, OR:1.05, 95%CI: 1.00-1.10, P=0.048) and PM_IBPs_24h_arv (OR:1.17, 95%CI: 1.06-1.30, P=0.002) were independent risk factors for POD. Conclusions : Postoperatively high BPV exposure rather than hypotension contributed to the occurrence of POD in the patients after cardiac surgery. Maintaining a relatively stable blood pressure after surgery might be beneficial in reducing the incidence of POD in the patients receiving cardiac surgery. blood pressure variability postoperative delirium neurological complication cardiac surgery Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Introduction Delirium, manifested by disturbance of consciousness, irregular behavior, and inability to concentrate, is one of the most common postoperative complications in both cardiac patients and non-cardiac patients[ 1 ]. In cardiac patients, delirium is the most common neurological complications after cardiac surgery. Delirium after cardiac surgery may lead to prolonged length of Intensive Care Unit (ICU) stay and hospital stay, as well as increased mortality. Causes of postoperative delirium (POD) in the cardiac surgery may attribute to the use of anesthetic agents, the infection of surgery procedure and cardiopulmonary bypass (CPB), inflammation, etc.[ 2 , 3 ]. Several studies have investigated the risk factors for POD in cardiac patients. A meta-analysis revealed the following risk factors for POD after cardiac surgery, including age, New York Heart Association (NYHA) functional class III or IV, preoperative depression, co-morbidities of mild cognitive impairment, diabetes and carotid artery stenosis, duration of mechanical ventilation as well as length of ICU stay[ 4 ]. However, current studies mainly focused on the baseline characteristics, surgery time and postoperative laboratory variables of the cardiac patients, studies on the influence of perioperative hemodynamic variables for POD were rare. Recent studies dedicated to clarify the correlation between blood pressure and delirium. A post-hoc analysis for DECADE trial assessed the association between perioperative hypotension and POD after cardiac surgery and found that neither intraoperative nor postoperative hypotension were associated with delirium[ 5 ]. Whereas, blood pressure variability (BPV) was found to be associated with delirium in certain populations. A retrospective study by Zorko et al. revealed that BPV in the first 24h after ICU admission was associated with an increased likelihood of delirium in the patients with critical illness[ 6 ]. Another pilot study assessed the optimal mean arterial pressure (MAP) by cerebral blood flow autoregulation using ultrasound-tagged near-infrared spectroscopy during CPB procedure and the first 3h after surgery in 110 cardiac patients[ 7 ]. This study found that the incidence and severity of delirium on postoperative day 2 was associated with excursions above the optimal MAP. Whereas, studies on the correlations between BPV and POD in the cardiac patients were insufficient. Therefore, the purposes of our study were: 1) to investigate the impact of perioperative hemodynamic variables on POD in the cardiac patients after on-pump cardiac surgery; 2) to assess the relationship between perioperative BPV and POD in the cardiac patients. Material and methods This study was a retrospective, case-control study performed at the Cardiovascular Intensive Care Unit (CVICU) of Nanjing First Hospital, a tertiary teaching hospital affiliated to Nanjing Medical University. The study was approved by the Ethics Committee of Nanjing First Hospital, Nanjing Medical University (KY20220518-01-KS-01) with a waiver of the requirement for informed consent. Patient population Adult cardiac patients (aged ≥ 18 years old) that received cardiac surgery and admitted to CVICU after surgery during the study period between June 2019 and December 2022 were screened for potential analysis. Those who underwent CPB procedure and received invasive blood pressure and central venous pressure (CVP) monitoring during and after surgery were included in this study. Patients were excluded from the study if they met the following criteria: 1) died during and within 48h after surgery; 2) admitted to ICU before surgery; 3) stayed in ICU for less than 24h after cardiac surgery; 4) received allograft orthotopic heart transplantation; 5) unable to communicate due to pre-existing stroke, dementia, and other brain diseases; 6) were receiving the therapy of psychotropic drugs before surgery; 7) complicated with stroke after surgery; 8) with missing data in hemodynamic variables, medical records, and CAM-ICU evaluation during and after surgery. Data collection Baseline characteristics of the cardiac patients included gender, age, body mass index (BMI), Acute Physiology and Chronic Health Evaluation II (APACHE II) score, European System for Cardiac Operative Risk Evaluation (euroSCORE) score and co-morbidities (medical history of stroke, hypertension, diabetes mellitus, coronary artery disease [CAD], chronic renal failure [CRF], atrial fibrillation [AF], chronic obstructive pulmonary disease [COPD], etc.) were obtained from the electronic health records (EHRs). Intraoperative blood pressure was obtained from the anesthesia system (DoCare), which was recorded every five minutes via invasive arterial pressure monitoring during the procedure of cardiac surgery. Intraoperative variables included surgery types, surgery time, CPB time, aortic cross-clamp time and fluid balance were also assessed and recorded. Postoperative hemodynamic variables including heart rate (HR), blood pressure (BP, including systolic blood pressure [IBPs], diastolic blood pressure [IBPd] and mean blood pressure [IBPm]), central venous pressure (CVP) and pulse oxygen saturation (SpO2) were measured in 5-min to 1-h interval during the first 24h after ICU admission by ECG monitoring, invasive arterial pressure and CVP monitoring. Furthermore, postoperative laboratory results at ICU admission, maximum doses of inotropic drugs within the first 24h after ICU admission and requirement for mechanical-assisted circulation including intra-aortic balloon pump (IABP) and extracorporeal membrane oxygenation (ECMO) were also collected and analyzed. In addition, prognosis indexes including mechanical ventilation time, length of ICU stay and hospital stays, hospital mortality, incidence of acute kidney injury (AKI) and requirement for renal replacement therapy (RRT) were also recorded for analysis. Delirium assessment Assessment of delirium was routinely performed twice a day during ICU stay, and as needed after ICU discharge using confusion assessment method for ICU (CAM-ICU). First of all, the consciousness levels of the patients were assessed by Richmond Agitation-Sedation scale (RASS). After that, the mental status of the patients was evaluated with CAM-ICU in those patients with RASS score ≥ -3. The diagnosis of delirium was mainly based on the mental status of the patients. There were four characteristics of delirium diagnosis in CAM-ICU: ① acute change or fluctuation of mental state; ② Lack of concentration; ③ Disorder of thinking; ④ Changes in the level of consciousness. The patients were diagnosed with delirium when they met the characteristics of ①, ② and ③ or ④[ 8 ]. Calculation of BPV Intraoperative blood pressure (mean blood pressure) was measured every five minutes during the operation and postoperative blood pressure (IBPs, IBPd and IBPm) was measured every 30 minutes for the first 24h after cardiac surgery during ICU stay. Systolic blood pressure below 40mmHg or above 300 mmHg and diastolic blood pressure below 20mmHg or above 150 mm Hg were set to missing and excluded from analysis. BPV was quantified by calculating the standard deviation (SD) and average real variability (ARV) of blood pressure. The calculation formula of SD was according to the following formula as previously reported[ 9 ]: SD= \(\sqrt{({\sum }_{i=1}^{n}{\left({x}_{i}-\stackrel{-}{x}\right)}^{2})/n-1}\) \({x}_{i}\) : blood pressure at different time point, \(\stackrel{-}{x}\) : mean value of blood pressure, \(n\) : number of blood pressure measurements. ARV of blood pressure was calculated based on the calculation formula that was reported in the literature and listed as follows[ 10 ]: ARV= \({\sum }_{i=1}^{n-1}({x}_{i+1}-{x}_{i})/n-1\) \({x}_{i}\) : blood pressure at different time point, \({x}_{i+1}\) : blood pressure at next time point, \(n\) : number of blood pressure measurements. Statistical analysis R statistical software (R version 4.3.2) was used for statistical analysis in this study. Continuous variables were expressed as mean plus SD for those conforming to normal distribution and median plus interquartile range (IQR) for those not conforming to normal distribution. Independent-sample T test was preformed to compare the difference in the two groups for continuous variables conforming to normal distribution. For continuous variables not conforming to normal distribution, Mann–Whitney U-test was carried out to compare the difference between the two groups. Categorical variables were presented as absolute values plus proportions analyzed by Chi-square test. The Least absolute shrinkage and selection operator (LASSO) regression was adopted to screen the potential hemodynamic variables contributing to the occurrence of POD. Afterwards, multivariate logistic regression was performed and logistic regression forest plot was drawn based on the hemodynamic variables screened by LASSO analysis. Furthermore, Restricted cubic spline (RCS) analysis was performed to assess the nonlinear associations between BPV and POD after cardiac surgery. Statistically significance was considered as a two-sided P < 0.05. Results 4490 cardiac patients who received cardiac surgery and admitted to CVICU after surgery during the study period between June 2019 and December 2022 were screened for potential enrollment. Finally, 2164 patients were enrolled and included in our study (Fig. 1 ). Of all the study patients, the incidence of POD was15.0% (324/2164), and the average day for POD occurred at day 3 (1, 5) after surgery. Patients were divided into two groups based on the occurrence of POD: Delirium group (n = 324) and No Delirium group (n = 1840). Comparison of baseline characteristics The comparison of baseline characteristics of the patients in the two groups were presented in Table 1 . Cardiac patients in the delirium group were predominantly male (237 [73.1%] vs. 1060 [57.6%], P < 0.001), with older age (69.0 [61.0, 74.0] vs. 65 [57.0, 71.0] years, P < 0.001) and higher APACHE II score (14.0 [12.0, 17.0] vs. 12.0 [10.0, 15.0], P < 0.001) and euroSCORE (6.0 [5.0, 8.0] vs. 5.0 [4.0, 7.0], P < 0.001). Moreover, patients with co-morbidities of CAD and CRF were more likely to suffer POD when compared to those without. In terms of surgery type, cardiac patients in the delirium group had a significantly higher proportion to receive combined surgery of valve replacement/repair and coronary artery bypass grafting (CABG) and acute Stanford Type A aortic dissection (AAAD) surgery, and a lower proportion to receive valve surgery. In addition, patients in the delirium group had markedly longer operation time (290 [249, 340] vs. 260 [220, 310] min, P < 0.001), CPB time (128 [101, 167] vs. 115 [88, 147] min, P < 0.001) and aortic cross-clamp time (85.5 [67, 114] vs. 78 [59, 103] min, P < 0.001). Besides, patients in delirium group received higher doses of inotropic drugs within 24h after cardiac surgery when compared with those in no delirium group. Table 1 Baseline characteristics of the cardiac patients with or without postoperative delirium Variables No Delirium (n = 1840) Delirium (n = 324) P value Male, n (%) 1060 (57.6%) 237 (73.1%) < 0.001 Age, years 65.0 [57.0;71.0] 69.0 [61.0;74.0] <0.001 BMI, kg/m² 20.2 [19.0;21.5] 20.0 [18.8;22.0] 0.196 APACHE II score 12.0 [10.0;15.0] 14.0 [12.0;17.0] < 0.001 EuroSCORE 5.0 [4.0;7.0] 6.0 [5.0;8.0] < 0.001 Co-morbidities, n (%) Stroke 250 (13.6%) 50 (15.4%) 0.424 Hypertension 901 (49.0%) 171 (52.8%) 0.228 Diabetes mellitus 418 (22.7%) 83 (25.6%) 0.285 CHD 832 (45.2%) 190 (58.6%) < 0.001 CRF 92 (5.00%) 40 (12.3%) < 0.001 AF 465 (25.3%) 68 (21.0%) 0.114 COPD 99 (5.38%) 18 (5.56%) 1.000 Surgery types, n (%) CABG 539 (29.3%) 108 (33.3%) 0.162 Valve surgery 780 (42.4%) 93 (28.7%) <0.001 Combined surgery of valve and CABG 215 (11.7%) 58 (17.9%) 0.003 Aortic surgery 173 (9.40%) 33 (10.2%) 0.734 AAAD 48 (2.61%) 24 (7.41%) < 0.001 Other surgery 84 (4.57%) 8 (2.47%) 0.115 Intra-operative variables Operation time, min 260 [220;310] 290 [249;340] <0.001 CPB time, min 115 [88;147] 128 [101;167] <0.001 Aortic cross-clamp time, min 78 [59;103] 85.5 [67;114] <0.001 Fluid input, ml 2000 [1500;2131] 2000 [1500;2500] 0.001 Blood input, ml 1250 [1000;1561] 1396 [1042;1752] <0.001 Fluid output, ml 2000 [1600;2500] 2100 [1688;2555] 0.140 Blood loss, ml 1100 [1000;1300] 1200 [1000;1500] <0.001 Urine output, ml 800 [560;1250] 800 [500;1200] 0.084 Fluid balance, ml -100.00 [-622.50;350] 0.00 [-550.00;400] 0.220 Maximum doses of inotropic drugs within 24h after surgery Norepinephrine, ug/kg/min 0.00 [0.00;0.10] 0.08 [0.00;0.18] <0.001 Dopamine, ug/kg/min 0.00 [0.00;4.00] 0.00 [0.00;3.25] 0.254 Dobutamine, ug/kg/min 0.00 [0.00;3.00] 0.00 [0.00;4.00] 0.055 Epinephrine, ug/kg/min 0.00 [0.00;0.01] 0.00 [0.00;0.04] <0.001 Milrinone, ug/kg/min 0.00 [0.00;0.00] 0.00 [0.00;0.00] 0.101 Olprinone, ug/kg/min 0.00 [0.00;0.00] 0.00 [0.00;0.00] 0.307 Levosimendan, ug/kg/min 0.00 [0.00;0.00] 0.00 [0.00;0.00] 0.001 Hypophysin, U/h 0.00 [0.00;0.00] 0.00 [0.00;0.00] <0.001 VISmax 7.00 [3.00;15.0] 12.0 [5.00;24.0] <0.001 Mechanical ventilation time, h 13.3 [8.8;19.3] 20.2 [13.3;44.8] <0.001 Length of ICU stay, d 2.00 [2.00;3.00] 4.00 [2.00;6.00] <0.001 Length of hospital stay, d 18.0 [15.0;22.0] 21.0 [17.0;28.0] <0.001 Hospital mortality, n (%) 50 (2.72%) 29 (8.95%) <0.001 Re-intubation, n (%) 74 (4.02%) 57 (17.6%) < 0.001 AKI, n (%) 585 (31.8%) 164 (50.8%) < 0.001 RRT requirement, n (%) 42 (2.28%) 21 (6.48%) < 0.001 Requirement of MCS, n (%) IABP 49 (2.66%) 31 (9.57%) < 0.001 ECMO 2 (0.11%) 3 (0.93%) 0.026 BMI: body mass index, APACHE II: Acute Physiology, Age, Chronic Health Evaluation II, EuroSCORE: European system for cardiac operative risk evaluation, CHD: coronary heart disease, CRF: chronic renal failure, AF: atrial fibrillation, COPD: chronic obstructive pulmonary disease, CABG: Coronary Artery Bypass Grafting, AAAD: Acute Stanford Type A Aortic Dissection, CPB: cardiopulmonary bypass, VIS: vasoactive-inotropic score, ICU: intensive care unit, AKI: acute kidney injury, RRT: renal replacement therapy, MCS: mechanical circulatory support, IABP: intra-aortic balloon pump, ECMO: extracorporeal membrane oxygenation. In the aspect of prognostic indexes, cardiac patients in delirium group were more likely to have prolonged time for mechanical ventilation (20.2 [13.3, 44.8] vs. 13.3 [8.8, 19.3] min, P < 0.001), longer duration of ICU stay (4 [ 2 , 6 ] vs. 2 [ 2 , 3 ] d, P < 0.001) and hospital stay (21 [17, 28] vs. 18 [15, 22] d, P < 0.001), as well as higher hospital mortality (29 [8.95%] vs. 50 [2.72%], P < 0.001). Comparison of perioperative hemodynamic variables To evaluate the impact of perioperative hemodynamic variables on POD, we compared the perioperative hemodynamic variables in the two groups (Table 2 ). Patients in delirium group had markedly lower levels of intraoperative mean blood pressure (BP_mean, 63.8 [59.2, 67.2] vs. 64.3 [60.2, 68.5] mmHg, P = 0.015) and BP variability (BP_arv, 8.52 [6.40, 10.2] vs. 8.94 [7.08, 11.5] mmHg, P < 0.001) when compared to those in no delirium group. Table 2 Perioperative hemodynamic parameters of the cardiac patients with or without postoperative delirium Variables No Delirium (n = 1840) Delirium (n = 324) P value Intra-operative hemodynamic variables AUT_65 1575 [1015;2195] 1842 [1160;2706] <0.001 AUT_60 980 [585;1451] 1155 [680;1846] <0.001 AUT_55 590 [319;935] 685 [360;1146] 0.004 AUT_50 312 [135;560] 365 [155;686] 0.021 BP_65_time, min 125 [90.0;165] 150 [105;195] <0.001 BP_60_time, min 90.0 [60.0;125] 110 [70.0;155] <0.001 BP_55_time, min 60.0 [40.0;90.0] 70.0 [45.0;110] <0.001 BP_50_time, min 35.0 [20.0;60.0] 45.0 [20.0;71.2] 0.005 TWA_BP_65 12.2 [9.97;14.8] 12.3 [10.1;15.0] 0.691 TWA_BP_60 10.7 [8.57;13.5] 10.7 [8.42;13.2] 0.629 TWA_BP_55 9.25 [7.00;12.3] 9.35 [7.10;12.2] 0.972 TWA_BP_50 7.70 [5.40;11.3] 8.21 [5.76;11.3] 0.268 BP_mean, mmHg 64.3 [60.2;68.5] 63.8 [59.2;67.2] 0.015 BP_arv, mmHg 8.94 [7.08;11.5] 8.52 [6.40;10.2] <0.001 Postoperative hemodynamic variables PM_HR_6h_mean, bpm 85.6 [79.4;91.8] 86.9 [80.2;94.9] 0.025 PM_IBPs_6h_mean, mmHg 111 [104;118] 110 [103;118] 0.214 PM_IBPd_6h_mean, mmHg 59.9 [55.3;65.5] 57.4 [52.6;64.0] <0.001 PM_IBPm_6h_mean, mmHg 77.0 [72.5;81.9] 75.3 [70.3;80.5] <0.001 PM_CVPm_6h_mean, mmHg 7.88 [6.08;9.75] 8.48 [6.49;10.5] <0.001 PM_SpO2_6h_mean, % 99.8 [99.3;100] 99.8 [99.3;100] 0.154 PM_MPP_6h_mean, mmHg 68.9 [64.2;74.3] 66.9 [60.8;72.2] < 0.001 PM_HR_6h_sd, bpm 5.08 [2.90;7.90] 5.06 [3.13;8.17] 0.583 PM_IBPs_6h_sd, mmHg 10.8 [8.45;13.3] 11.0 [8.50;13.6] 0.276 PM_IBPd_6h_sd, mmHg 5.38 [4.05;7.02] 5.26 [3.98;6.93] 0.424 PM_IBPm_6h_sd, mmHg 6.86 [5.33;8.78] 6.93 [5.37;8.49] 0.932 PM_CVPm_6h_sd, mmHg 1.26 [0.95;1.70] 1.31 [1.00;1.83] 0.031 PM_HR_6h_arv, bpm 3.09 [1.75;4.82] 3.27 [2.06;4.76] 0.234 PM_IBPs_6h_arv, mmHg 8.55 [6.50;10.8] 8.70 [6.59;11.5] 0.334 PM_IBPd_6h_arv, mmHg 4.18 [3.10;5.50] 4.09 [3.00;5.55] 0.406 PM_IBPm_6h_arv, mmHg 5.45 [4.10;7.00] 5.45 [4.09;7.09] 0.867 PM_CVPm_6h_arv, mmHg 0.91 [0.70;1.20] 1.00 [0.80;1.30] <0.001 PM_HR_6h_min, bpm 79.0 [70.0;85.0] 80.0 [72.0;87.0] 0.065 PM_HR_12h_mean, bpm 86.9 [80.5;92.8] 87.1 [81.0;95.4] 0.216 PM_IBPs_12h_mean, mmHg 113 [107;120] 112 [106;120] 0.289 PM_IBPd_12h_mean, mmHg 60.6 [56.2;65.6] 58.4 [53.5;64.0] <0.001 PM_IBPm_12h_mean, mmHg 78.1 [73.8;82.8] 76.4 [71.8;81.1] <0.001 PM_CVPm_12h_mean, mmHg 7.78 [6.08;9.55] 8.40 [6.61;10.1] <0.001 PM_SpO2_12h_mean, % 99.8 [99.3;100.0] 99.8 [99.3;100.0] 0.911 PM_MPP_12h_mean, mmHg 70.4 [65.9;75.0] 68.5 [62.6;73.1] < 0.001 PM_HR_12h_sd, bpm 6.44 [4.12;9.02] 6.08 [4.04;9.02] 0.957 PM_IBPs_12h_sd, mmHg 11.2 [9.26;13.6] 11.3 [9.29;13.7] 0.760 PM_IBPd_12h_sd, mmHg 5.48 [4.40;6.78] 5.47 [4.28;6.89] 0.542 PM_IBPm_12h_sd, mmHg 7.09 [5.83;8.56] 6.99 [5.73;8.50] 0.578 PM_CVPm_12h_sd, mmHg 1.49 [1.16;1.88] 1.49 [1.15;1.92] 0.681 PM_HR_12h_arv, bpm 3.17 [2.00;4.41] 3.22 [2.13;4.44] 0.649 PM_IBPs_12h_arv, mmHg 7.75 [6.22;9.59] 7.88 [6.41;10.0] 0.391 PM_IBPd_12h_arv, mmHg 3.74 [2.96;4.70] 3.74 [2.91;4.69] 0.574 PM_IBPm_12h_arv, mmHg 4.91 [3.95;6.05] 4.91 [3.96;6.22] 0.828 PM_CVPm_12h_arv, mmHg 0.91 [0.73;1.13] 0.96 [0.78;1.16] 0.012 PM_HR_12h_min, bpm 76.0 [68.0;83.0] 78.0 [70.0;84.0] 0.141 PM_HR_24h_mean, bpm 87.4 [82.0;93.3] 88.6 [82.4;95.7] 0.036 PM_IBPs_24h_mean, mmHg 116 [109;123] 116 [110;123] 0.902 PM_IBPd_24h_mean, mmHg 61.4 [56.6;66.0] 59.3 [54.9;65.2] <0.001 PM_IBPm_24h_mean, mmHg 79.4 [75.3;84.1] 78.2 [73.8;83.2] 0.003 PM_CVPm_24h_mean, mmHg 7.75 [6.18;9.43] 8.38 [6.89;10.2] <0.001 PM_SpO2_24h_mean, % 99.7 [99.2;99.9] 99.6 [99.2;99.9] 0.538 PM_MPP_24h_mean, mmHg 71.6 [67.2;76.4] 69.9 [65.5;74.5] < 0.001 PM_HR_24h_sd, bpm 7.42 [5.20;10.0] 7.72 [5.34;10.7] 0.190 PM_IBPs_24h_sd, mmHg 12.3 [10.2;14.6] 12.9 [10.4;15.1] 0.016 PM_IBPd_24h_sd, mmHg 5.81 [4.78;7.07] 5.88 [4.74;7.37] 0.276 PM_IBPm_24h_sd, mmHg 7.60 [6.34;8.92] 7.86 [6.42;9.45] 0.105 PM_CVPm_24h_sd, mmHg 1.66 [1.36;2.03] 1.68 [1.40;2.16] 0.140 PM_HR_24h_arv, bpm 3.34 [2.36;4.57] 3.42 [2.42;4.89] 0.133 PM_IBPs_24h_arv, mmHg 7.91 [6.57;9.43] 8.64 [7.32;10.2] <0.001 PM_IBPd_24h_arv, mmHg 3.77 [3.11;4.60] 4.00 [3.17;4.83] 0.014 PM_IBPm_24h_arv, mmHg 4.94 [4.11;5.94] 5.23 [4.46;6.19] 0.001 PM_CVPm_24h_arv, mmHg 0.94 [0.81;1.14] 1.00 [0.86;1.18] 0.001 PM_HR_24h_min, bpm 74.0 [67.0;81.0] 76.0 [69.0;82.0] 0.063 AUT_65: the area under blood pressure (BP) 65mmHg-time curve, AUT_60: the area under BP 60mmHg-time curve, AUT_55: the area under BP 55mmHg-time curve, AUT_50: the area under BP 50mmHg-time curve, BP_65_time: time of BP < 65mmHg, BP_60_time: time of BP < 60mmHg, BP_55_time: time of BP < 55mmHg, BP_50_time: time of BP < 50mmHg, TWA_BP_65: time-weighted average threshold value for BP < 65mmHg, TWA_BP_60: time-weighted average threshold value for BP < 60mmHg, TWA_BP_55: time-weighted average threshold value for BP < 55mmHg, TWA_BP_50: time-weighted average threshold value for BP < 50mmHg, arv: average real variability, HR: heart Rate, bpm: beats per minute, IBPs: systolic blood pressure, IBPd: diastolic blood pressure, IBPm: mean blood pressure, CVP: central venous pressure, MPP: mean perfusion pressure, SD: standard deviation, min: minimum. Whereas, postoperative ARV of systolic blood pressure (PM_IBPs_24h_arv, 8.64 [7.32, 10.2] vs. 7.91 [6.57, 9.43] mmHg, P < 0.001), diastolic blood pressure (PM_IBPd_24h_arv, 4.00 [3.17, 4.83] vs. 3.77 [3.11, 4.60] mmHg, P = 0.014) and mean blood pressure (PM_IBPm_24h_arv, 5.23 [4.46, 6.19] vs. 4.94 [4.11, 5.94] mmHg, P = 0.001) at 24h after surgery was significantly higher in the patients with POD than those without (Fig. 2 ). Perioperative BPV in predicting POD LASSO regression of the perioperative variables in predicting POD found that intraoperative BP_65_time (time of blood pressure below 65mmHg during operation), BP_60_time (time of blood pressure below 60mmHg during operation) and BP_arv (ARV of intraoperative blood pressure), and postoperative PM_MPP_6h_mean (mean perfusion pressure at 6h postoperatively), PM_MPP_12h_mean (mean perfusion pressure at 12h postoperatively), PM_CVPm_24h_mean (mean central venous pressure at 24h postoperatively), PM_IBPs_24h_arv and PM_IBPm_24h_arv were closely associated with POD (Fig. 3 ). Further logistic regression revealed that BP_arv (OR:0.92, 95%CI: 0.89–0.96, P < 0.001), PM_CVPm_24h_mean (OR:1.05, 95%CI: 1.00-1.10, P = 0.048) and PM_IBPs_24h_arv (OR:1.17, 95%CI: 1.06–1.30, P = 0.002) were independent risk factors for POD (Table 3 and Fig. 4 ). RCS analysis revealed that, the cut-off values for BP_arv and PM_IBPs_24h_arv were 5.640mmHg and 5.087mmHg, respectively (Fig. 5 ). Table 3 Logistics regression for postoperative delirium in the patients receiving cardiac surgery Dependent: Delirium No Yes OR (univariable) OR (multivariable) BP_65_time Mean (SD) 135.5 (64.1) 158.0 (68.5) 1.00 (1.00-1.01, p < 0.001) 1.00 (0.99-1.00, p = 0.794) BP_60_time Mean (SD) 99.2 (54.7) 118.2 (60.9) 1.01 (1.00-1.01, p < 0.001) 1.00 (1.00-1.01, p = 0.287) BP_arv Mean (SD) 9.7 (3.7) 8.7 (3.1) 0.92 (0.88–0.95, p < 0.001) 0.92 (0.89–0.96, p < 0.001) PM_MPP_6h_mean Mean (SD) 69.2 (7.5) 66.6 (8.6) 0.96 (0.94–0.97, p < 0.001) 0.99 (0.96–1.03, p = 0.749) PM_MPP_12h_mean Mean (SD) 70.5 (7.0) 68.2 (8.0) 0.96 (0.94–0.97, p < 0.001) 0.97 (0.93–1.01, p = 0.178) PM_CVPm_24h_mean Mean (SD) 8.0 (2.5) 8.7 (2.9) 1.11 (1.06–1.16, p < 0.001) 1.05 (1.00-1.10, p = 0.048) PM_IBPs_24h_arv Mean (SD) 8.1 (2.3) 10.6 (33.0) 1.12 (1.06–1.17, p < 0.001) 1.17 (1.06–1.30, p = 0.002) PM_IBPm_24h_arv Mean (SD) 5.1 (1.5) 5.4 (1.5) 1.11 (1.03–1.20, p = 0.006) 0.97 (0.82–1.13, p = 0.714) OR: odds ratio, BP: blood pressure, BP_65_time: time of BP < 65mmHg, BP_60_time: time of BP < 60mmHg, arv: average real variability, MPP: mean perfusion pressure, CVP: central venous pressure, IBPs: systolic blood pressure, IBPm: mean blood pressure. Discussion Our study was a single-center, retrospective, observational study conducted at CVICU of Nanjing First Hospital. In our study, we mainly focused on the influence of perioperative hemodynamic parameters on the occurrence of POD in the patients receiving cardiac surgery. We retrospectively enrolled 2164 cardiac patients in this study and assessed the impact of perioperative hemodynamic variables on the occurrence of POD. Our study found that, the incidence of POD was 15.0% in the cardiac patients received cardiac surgery and stayed in ICU for more than 24h after surgery, which was familiar to other studies[ 11 ]. Perioperative BPV rather than hypotension contributed to the occurrence of POD. Lower level of BPV during operation and higher level of BPV after surgery were independent risk factors for POD in the patients received cardiac surgery. Our study showed that, lower level of BPV during operation would increase the incidence of POD in the cardiac patients. The patients we included in this study were all the cardiac patients underwent CPB procedure. Therefore, the patients would experience a period of relatively constant blood pressure during the process of CPB, leading to a low BPV. As a result, BPV during operation may be greatly affected by CPB time. A longer CPB time would lead to a lower BPV during the operation. Consistently, cardiac patients that suffered POD had a significantly longer CPB time (128min vs. 115min, P < 0.001) when compared to those did not. The association between CPB time and POD in the cardiac patients has been confirmed by numerous studies in the literature[ 12 – 15 ]. Longer CPB time have been recognized as one of the independent risk factors for POD in the cardiac surgery, which is consistent with our results. Recent studies have revealed a relationship between BPV and delirium in critically ill patients. A retrospective observational study by Garbajs et al. found that BPV in the first 24h after ICU admission was associated with a higher burden of delirium during hospitalization in the critically ill patients from both medical and surgical ICU[ 16 ]. In the surgical patients, perioperative BPV was also identified as an independent risk factor for POD in non-cardiac patients. A study by Hirsch et al. evaluated the correlation between intraoperative blood pressure and early POD in the non-cardiac patients[ 9 ]. The results showed that increased blood pressure fluctuation rather than relative hypotension was predictive of POD in the elder patients undergoing major non-cardiac surgery. Another recent study also confirmed the influence of perioperative blood pressure regulation on POD in patients undergoing head and neck free flap reconstruction[ 17 ]. They showed that low intraoperative minimum blood pressure were risk factors for POD. Whereas, data on the association between perioperative BPV and POD in patients receiving cardiac surgery were insufficient. Our studies first evaluated the relationship between perioperative BPV and POD in the patients receiving cardiac surgery. Familiar to previous studies, we also found a close correlation between high postoperative BPV and the occurrence of early POD in the cardiac patients. The influencing factors for the variability of blood pressure are various, including age, intraoperative blood loss, operation time, intravascular volume, use of anesthetic agents, inotropic and vasoactive drugs, etc.[ 18 ]. In the cardiac patients, BPV is mostly affected by the volume status and the vasoactive drugs that used during the perioperative period. The potential mechanism for the association between BPV and POD might be as follows: Although the mean arterial pressure changes, cerebral perfusion could remain relatively stable within the range of cerebral perfusion pressure from 50mmHg to 150mmHg under normal physiological conditions. Whereas, under anesthesia condition, cardiac patients with various co-morbidities such as hypertension, diabetes, smoking history, hypercapnia or obstructive sleep apnea syndrome and other diseases, may lead to the decline of brain autonomic regulation. In this way, a high perioperative BPV may affect the autoregulation function of the cerebrovascular vessels, leading to impaired brain function and the occurrence of POD. Perioperative hypotension used to be regarded as the risk factor for POD in the patients underwent major surgeries. However, recent studies presented different opinions. A sub-analysis of the DECADE multi-center randomized trial performed by Wang et al. evaluated the relationship between perioperative hypotension and risk of delirium in the cardiac patients with CPB at the Cleveland Clinic. The results suggested that neither intraoperative or postoperative hypotension were associated with POD[ 5 ]. Another study in elderly patients undergoing non-cardiac surgery also confirmed the same opinion. They found that increased blood pressure fluctuation rather than hypotension was predictive for POD[ 9 ]. Consistent with previous studies, our results also convinced that perioperative hypotension was not the major determining factors for POD when compared to perioperative BPV in the cardiac patients. Our study also has several limitations that require consideration. First of all, due to the retrospective nature of this study, the time interval for blood pressure measurement was every 30 minutes after ICU admission, which was relatively fixed. In this way, we may ignore the blood pressure fluctuation outside these time points. Secondly, we only included the cardiac patients that stayed in ICU for more than 24h after surgery in this study, leading to the exclusion of over 50% of the cardiac patients with relatively short length of ICU stay. Whereas, the incidence of POD in our study was consistent with previous studies, showing little influence on the exclusion of those patients. Lastly, we only focused on the postoperative cognitive and mental conditions of the patients in this study, the preoperative cognitive and mental conditions were not well evaluated. However, those patients with obvious cognitive disorder and unable to communicate were excluded from this study. Further large-scale prospective clinical trials might be needed to better clarify the association between perioperative BPV and POD in the patients receiving cardiac surgery. Conclusions Postoperatively high BPV exposure rather than hypotension contributed to the occurrence of POD in the patients after cardiac surgery. Maintaining a relatively stable blood pressure after surgery might be beneficial in reducing the incidence of POD in the patients receiving cardiac surgery. Abbreviations BPV: blood pressure variability POD: postoperative delirium ICU: Intensive Care Unit SD: standard deviation (SD) ARV: average real variability AUT_65: the area under blood pressure (BP) 65mmHg-time curve AUT_60: the area under BP 60mmHg-time curve AUT_55: the area under BP 55mmHg-time curve AUT_50: the area under BP 50mmHg-time curve BP_65_time: time of BP < 65mmHg BP_60_time: time of BP < 60mmHg BP_55_time: time of BP < 55mmHg BP_50_time: time of BP < 50mmHg TWA_BP_65: time-weighted average threshold value for BP < 65mmHg TWA_BP_60: time-weighted average threshold value for BP < 60mmHg TWA_BP_55: time-weighted average threshold value for BP < 55mmHg TWA_BP_50: time-weighted average threshold value for BP < 50mmHg HR: heart Rate IBPs: systolic blood pressure IBPd: diastolic blood pressure IBPm: mean blood pressure CVP: central venous pressure MPP: mean perfusion pressure BP_mean: mean blood pressure BP_arv: BP variability PM_IBPm_24h_mean: postoperative mean blood pressure within 24h PM_IBPs_24h_arv: postoperative average real variability for systolic blood pressure PM_IBPd_24h_arv: postoperative average real variability for diastolic blood pressure PM_IBPm_24h_arv: postoperative average real variability for mean blood pressure PM_CVPm_24h_mean: mean central venous pressure at 24h postoperatively CPB: cardiopulmonary bypass NYHA: New York Heart Association MAP: mean arterial pressure CVICU: Cardiovascular Intensive Care Unit BMI: body mass index APACHE II: Acute Physiology and Chronic Health Evaluation II score euroSCORE: European System for Cardiac Operative Risk Evaluation CAD: coronary artery disease CRF: chronic renal failure AF: atrial fibrillation COPD: chronic obstructive pulmonary disease EHRs: electronic health records BP: blood pressure SpO2: pulse oxygen saturation IABP: intra-aortic balloon pump ECMO: extracorporeal membrane oxygenation AKI: acute kidney injury RRT: renal replacement therapy CAM-ICU: confusion assessment method for Intensive Care Unit RASS: Richmond Agitation-Sedation scale IQR: interquartile range LASSO: Least absolute shrinkage and selection operator RCS: restricted cubic spline CABG: coronary artery bypass grafting AAAD: acute Stanford Type A aortic dissection Declarations Ethics approval and consent to participate: For the conduction and data collection of the study, the approval was gained from the institutional Ethics Committee of Nanjing First Hospital. Consent for publication : Not applicable. Availability of data and materials : The datasets generated and/or analyzed during the current study are not publicly available due to the protection for the patients’ privacy but are available from the corresponding author on reasonable request. Competing interests ：The authors declare that they have no competing interests. Funding: This study was supported by National Natural Science Foundation of China (82372217) and Natural Science Foundation of Jiangsu Province (BK20231128). The funding agency had no role in study design, the collection of data, in the interpretation of data, in the writing of the article, or in the decision to submit the article for publication. Authors’ contributions: XS and HT contributed to design, data acquisition, statistical analysis and drafted the manuscript. WXC and JKS contributed to data acquisition, data analysis and presentation. RHJ and WHZ contributed to data acquisition and data analysis. LH and CZ contributed to study control, study design and manuscript drafting. CZ contributed to manuscript drafting and revision. XS and HT contributed equally to the paper. All authors have read and approved the final manuscript. Acknowledgements : Not applicable. References Jin, Z., J. Hu, and D. Ma, POD: perioperative assessment, risk reduction, and management. Br J Anaesth, 2020. 125 (4): p. 492-504. Pang, Y., et al., Effects of inflammation and oxidative stress on POD in cardiac surgery. Front Cardiovasc Med, 2022. 9 : p. 1049600. Sugimura, Y., et al., Risk and Consequences of POD in Cardiac Surgery. Thorac Cardiovasc Surg, 2020. 68 (5): p. 417-424. Chen, H., et al., Risk factors of POD after cardiac surgery: a meta-analysis. J Cardiothorac Surg, 2021. 16 (1): p. 113. Wang, J., et al., Association between perioperative hypotension and POD and atrial fibrillation after cardiac surgery: A post-hoc analysis of the DECADE trial. J Clin Anesth, 2022. 76 : p. 110584. Zorko Garbajs, N., et al., Association of Blood Pressure Variability with Delirium in Patients with Critical Illness. Neurocrit Care, 2022: p. 1-9. Hori, D., et al., Blood Pressure Deviations From Optimal Mean Arterial Pressure During Cardiac Surgery Measured With a Novel Monitor of Cerebral Blood Flow and Risk for Perioperative Delirium: A Pilot Study. J Cardiothorac Vasc Anesth, 2016. 30 (3): p. 606-12. Inouye, S.K., et al., Clarifying confusion: the confusion assessment method. A new method for detection of delirium. Ann Intern Med, 1990. 113 (12): p. 941-8. Hirsch, J., et al., Impact of intraoperative hypotension and blood pressure fluctuations on early POD after non-cardiac surgery. Br J Anaesth, 2015. 115 (3): p. 418-26. Coccina, F., et al., Prognostic value of average real variability of systolic blood pressure in elderly treated hypertensive patients. Blood Press Monit, 2019. 24 (4): p. 179-184. Huet, O., et al., Prevention of post-operative delirium using an overnight infusion of dexmedetomidine in patients undergoing cardiac surgery: a pragmatic, randomized, double-blind, placebo-controlled trial. Crit Care, 2024. 28 (1): p. 64. Andrási, T.B., et al., Risk factors for POD after cardiac surgical procedures with cardioplegic arrest. Eur J Cardiothorac Surg, 2022. 62 (1). Ushio, M., et al., Timing, Threshold, and Duration of Intraoperative Hypotension in Cardiac Surgery: Their Associations With POD. J Cardiothorac Vasc Anesth, 2022. 36 (11): p. 4062-4069. Brown, C.H.t., et al., Effect of Targeting Mean Arterial Pressure During Cardiopulmonary Bypass by Monitoring Cerebral Autoregulation on Postsurgical Delirium Among Older Patients: A Nested Randomized Clinical Trial. JAMA Surg, 2019. 154 (9): p. 819-826. Baron Shahaf, D., et al., Association Between Risk of Stroke and Delirium After Cardiac Surgery and a New Electroencephalogram Index of Interhemispheric Similarity. J Cardiothorac Vasc Anesth, 2023. 37 (9): p. 1691-1699. Zorko Garbajs, N., et al., Association of Blood Pressure Variability with Delirium in Patients with Critical Illness. Neurocrit Care, 2023. 39 (3): p. 646-654. Ooms, M., et al., Influence of perioperative blood pressure regulation on POD in patients undergoing head and neck free flap reconstruction. Eur J Med Res, 2023. 28 (1): p. 365. Rothwell, P.M., Does blood pressure variability modulate cardiovascular risk? Curr Hypertens Rep, 2011. 13 (3): p. 177-86. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 25 Nov, 2024 Read the published version in BMC Anesthesiology → Version 1 posted Editorial decision: Revision requested 02 Jul, 2024 Editor assigned by journal 28 Jun, 2024 Submission checks completed at journal 28 Jun, 2024 First submitted to journal 26 Jun, 2024 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4643702","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":321651603,"identity":"347a6bcd-763f-4538-87e8-62aee030f0bd","order_by":0,"name":"Xiao Shen#","email":"","orcid":"","institution":"Nanjing Medical University","correspondingAuthor":false,"prefix":"","firstName":"Xiao","middleName":"","lastName":"Shen#","suffix":""},{"id":321651604,"identity":"123545d2-4999-410a-961d-b0f1b0620af7","order_by":1,"name":"Hong Tao#","email":"","orcid":"","institution":"Nanjing Medical University","correspondingAuthor":false,"prefix":"","firstName":"Hong","middleName":"","lastName":"Tao#","suffix":""},{"id":321651605,"identity":"5a4ae90b-966d-471c-8879-f1db1721af15","order_by":2,"name":"Wenxiu Chen","email":"","orcid":"","institution":"Nanjing Medical University","correspondingAuthor":false,"prefix":"","firstName":"Wenxiu","middleName":"","lastName":"Chen","suffix":""},{"id":321651606,"identity":"ec521b30-5c50-4a34-9321-6fe2b415a605","order_by":3,"name":"Jiakui Sun","email":"","orcid":"","institution":"Nanjing Medical University","correspondingAuthor":false,"prefix":"","firstName":"Jiakui","middleName":"","lastName":"Sun","suffix":""},{"id":321651607,"identity":"614be623-2b62-49a7-816d-9cbfe5d213cb","order_by":4,"name":"Renhua Jin","email":"","orcid":"","institution":"Nanjing Medical University","correspondingAuthor":false,"prefix":"","firstName":"Renhua","middleName":"","lastName":"Jin","suffix":""},{"id":321651608,"identity":"6511640a-0cd8-49a9-9258-890e8595375a","order_by":5,"name":"Wenhao Zhang","email":"","orcid":"","institution":"Nanjing Medical University","correspondingAuthor":false,"prefix":"","firstName":"Wenhao","middleName":"","lastName":"Zhang","suffix":""},{"id":321651609,"identity":"6dbee14f-587b-45a9-8bdd-20e22dd511bc","order_by":6,"name":"Liang Hong","email":"","orcid":"","institution":"Nanjing Medical University","correspondingAuthor":false,"prefix":"","firstName":"Liang","middleName":"","lastName":"Hong","suffix":""},{"id":321651610,"identity":"7bad8cff-f133-4666-8546-3bfd754cf02e","order_by":7,"name":"Cui Zhang","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA2UlEQVRIiWNgGAWjYDACCQjFA8SMDxIqakjTwmzw4Mwx4rWAAJvkwxZmwjrkZzc/e/il5rAMf/vhZxWJDWwM/O3dCXi1MM45Zm4sc+wwj8SZNLMbiTtkGCTOnN2AVwuzRIKZtGTDYR6GGzxsNxLPsDEYSOTi18Imkf4NrEUeqKUgsY2ZsBYeiRwzyY9ALQZALQxEaZGQyCmTZjiWzmN4Js1YIuHMMR6CfpGfkb5N8keNtb3c8cMPP/6oqJHjb+/FrwUEmHmQXUpQOQgw/iBK2SgYBaNgFIxYAAB+ckM1Gm2JPAAAAABJRU5ErkJggg==","orcid":"","institution":"Nanjing Medical University","correspondingAuthor":true,"prefix":"","firstName":"Cui","middleName":"","lastName":"Zhang","suffix":""}],"badges":[],"createdAt":"2024-06-26 15:21:24","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4643702/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4643702/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s12871-024-02817-x","type":"published","date":"2024-11-25T15:57:10+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":60810373,"identity":"ec384228-019b-4b03-a30b-74ce0d8c680c","added_by":"auto","created_at":"2024-07-22 10:48:06","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":89665,"visible":true,"origin":"","legend":"\u003cp\u003eScreening flowchart of the study patients. ICU: Intensive Care Unit.\u003c/p\u003e","description":"","filename":"Figure1.flowchatdelirium.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4643702/v1/53ad241424f10986a7f6a74d.jpg"},{"id":60811477,"identity":"cbfa49cd-8038-478f-923f-8eb78a551a3c","added_by":"auto","created_at":"2024-07-22 10:56:06","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":316651,"visible":true,"origin":"","legend":"\u003cp\u003eViolin diagram for the average real variability (ARV) of intraoperative blood pressure, postoperative systolic blood pressure at 6h, 12h and 24h after surgery.\u003c/p\u003e\n\u003cp\u003eBP_arv: average real variability (ARV) of intraoperative blood pressure, PM_IBPs_6h_arv: ARV of systolic blood pressure at 6h after surgery, PM_IBPs_12h_arv: ARV of systolic blood pressure at 12h after surgery, PM_IBPs_24h_arv: ARV of systolic blood pressure at 24h after surgery. *: \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.05; **: \u003cem\u003ep \u003c/em\u003e\u0026lt; 0.01; ***: \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.001, ns: no significance.\u003c/p\u003e","description":"","filename":"Figure2.BPV.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4643702/v1/beb5c5bba929b8b7afa0072c.jpg"},{"id":60810374,"identity":"ee3b0421-31e9-4373-a0d2-4f9e1c276f53","added_by":"auto","created_at":"2024-07-22 10:48:06","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":396787,"visible":true,"origin":"","legend":"\u003cp\u003eSelection of perioperative hemodynamic variables contributing to postoperative delirium using the Least absolute shrinkage and selection operator (LASSO) regression method. (A) Plot of LASSO coefficient profiles of the 68 variables. The log (lambda) sequence was plotted against a coefficient profile plot. There were 8 variables with non-zero coefficients generated by the ideal lambda; (B) 10-fold cross-validation for LASSO model parameter adjustment. The binomial deviation curve was displayed with log (lambda). The minimum criteria and its one standard error were used to construct dotted vertical lines at the optimal values (the 1-SE criteria).\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-4643702/v1/4f11935c98314b8af9332c49.png"},{"id":60810377,"identity":"3f6b2718-0b31-48ba-8e58-05e1e01d75a2","added_by":"auto","created_at":"2024-07-22 10:48:06","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":134306,"visible":true,"origin":"","legend":"\u003cp\u003eForest plot of the perioperative hemodynamic variables in predicting postoperative delirium.\u003c/p\u003e\n\u003cp\u003eOR: Odds ratio, BP_65_time: time of blood pressure below 65mmHg during operation, BP_60_time: time of blood pressure below 60mmHg during operation, BP_arv: average real variability (ARV) of intraoperative blood pressure, PM_MPP_6h_mean: mean perfusion pressure at 6h postoperatively, PM_MPP_12h_mean: mean perfusion pressure at 12h postoperatively, PM_CVPm_24h_mean: mean central venous pressure at 24h postoperatively, PM_IBPs_24h_arv: ARV of systolic blood pressure at 24h after surgery, PM_IBPm_24h_arv: ARV of mean blood pressure at 24h after surgery.\u003c/p\u003e","description":"","filename":"Figure4.forestplot.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4643702/v1/fbdb1012c78a43ef57dd3a00.jpg"},{"id":60810375,"identity":"1413c8a4-cff4-4da6-8417-973ccf66b4c0","added_by":"auto","created_at":"2024-07-22 10:48:06","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":1753396,"visible":true,"origin":"","legend":"\u003cp\u003eRestricted cubic spline (RCS) analysis in assessing the nonlinear associations between perioperative blood pressure variability (BPV) and postoperative delirium after cardiac surgery. (A) The nonlinear associations between average real variability (ARV) of intraoperative blood pressure (BP_arv) and postoperative delirium after cardiac surgery. (B) The nonlinear associations between ARV of systolic blood pressure at 24h after surgery (PM_IBPs_24h_arv) and postoperative delirium after cardiac surgery.\u003c/p\u003e\n\u003cp\u003eOR: Odds ratio, 95% CI: 95% confidence interval.\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-4643702/v1/7619241251fd4e3dcfd8067f.png"},{"id":70382105,"identity":"0f9abc5f-ade3-48bd-aaac-db2dabc32d2e","added_by":"auto","created_at":"2024-12-02 16:23:23","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":3768977,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4643702/v1/0bb9c500-8d0a-4a5f-877d-ce7637737e8b.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Postoperative blood pressure variability as a risk factor for postoperative delirium in the patients receiving cardiac surgery","fulltext":[{"header":"Introduction","content":"\u003cp\u003eDelirium, manifested by disturbance of consciousness, irregular behavior, and inability to concentrate, is one of the most common postoperative complications in both cardiac patients and non-cardiac patients[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. In cardiac patients, delirium is the most common neurological complications after cardiac surgery. Delirium after cardiac surgery may lead to prolonged length of Intensive Care Unit (ICU) stay and hospital stay, as well as increased mortality. Causes of postoperative delirium (POD) in the cardiac surgery may attribute to the use of anesthetic agents, the infection of surgery procedure and cardiopulmonary bypass (CPB), inflammation, etc.[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eSeveral studies have investigated the risk factors for POD in cardiac patients. A meta-analysis revealed the following risk factors for POD after cardiac surgery, including age, New York Heart Association (NYHA) functional class III or IV, preoperative depression, co-morbidities of mild cognitive impairment, diabetes and carotid artery stenosis, duration of mechanical ventilation as well as length of ICU stay[\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. However, current studies mainly focused on the baseline characteristics, surgery time and postoperative laboratory variables of the cardiac patients, studies on the influence of perioperative hemodynamic variables for POD were rare.\u003c/p\u003e \u003cp\u003eRecent studies dedicated to clarify the correlation between blood pressure and delirium. A post-hoc analysis for DECADE trial assessed the association between perioperative hypotension and POD after cardiac surgery and found that neither intraoperative nor postoperative hypotension were associated with delirium[\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Whereas, blood pressure variability (BPV) was found to be associated with delirium in certain populations. A retrospective study by Zorko et al. revealed that BPV in the first 24h after ICU admission was associated with an increased likelihood of delirium in the patients with critical illness[\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Another pilot study assessed the optimal mean arterial pressure (MAP) by cerebral blood flow autoregulation using ultrasound-tagged near-infrared spectroscopy during CPB procedure and the first 3h after surgery in 110 cardiac patients[\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. This study found that the incidence and severity of delirium on postoperative day 2 was associated with excursions above the optimal MAP. Whereas, studies on the correlations between BPV and POD in the cardiac patients were insufficient.\u003c/p\u003e \u003cp\u003eTherefore, the purposes of our study were: 1) to investigate the impact of perioperative hemodynamic variables on POD in the cardiac patients after on-pump cardiac surgery; 2) to assess the relationship between perioperative BPV and POD in the cardiac patients.\u003c/p\u003e"},{"header":"Material and methods","content":"\u003cp\u003e This study was a retrospective, case-control study performed at the Cardiovascular Intensive Care Unit (CVICU) of Nanjing First Hospital, a tertiary teaching hospital affiliated to Nanjing Medical University. The study was approved by the Ethics Committee of Nanjing First Hospital, Nanjing Medical University (KY20220518-01-KS-01) with a waiver of the requirement for informed consent.\u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003ePatient population\u003c/h2\u003e \u003cp\u003eAdult cardiac patients (aged\u0026thinsp;\u0026ge;\u0026thinsp;18 years old) that received cardiac surgery and admitted to CVICU after surgery during the study period between June 2019 and December 2022 were screened for potential analysis. Those who underwent CPB procedure and received invasive blood pressure and central venous pressure (CVP) monitoring during and after surgery were included in this study. Patients were excluded from the study if they met the following criteria: 1) died during and within 48h after surgery; 2) admitted to ICU before surgery; 3) stayed in ICU for less than 24h after cardiac surgery; 4) received allograft orthotopic heart transplantation; 5) unable to communicate due to pre-existing stroke, dementia, and other brain diseases; 6) were receiving the therapy of psychotropic drugs before surgery; 7) complicated with stroke after surgery; 8) with missing data in hemodynamic variables, medical records, and CAM-ICU evaluation during and after surgery.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eData collection\u003c/h2\u003e \u003cp\u003eBaseline characteristics of the cardiac patients included gender, age, body mass index (BMI), Acute Physiology and Chronic Health Evaluation II (APACHE II) score, European System for Cardiac Operative Risk Evaluation (euroSCORE) score and co-morbidities (medical history of stroke, hypertension, diabetes mellitus, coronary artery disease [CAD], chronic renal failure [CRF], atrial fibrillation [AF], chronic obstructive pulmonary disease [COPD], etc.) were obtained from the electronic health records (EHRs).\u003c/p\u003e \u003cp\u003eIntraoperative blood pressure was obtained from the anesthesia system (DoCare), which was recorded every five minutes via invasive arterial pressure monitoring during the procedure of cardiac surgery. Intraoperative variables included surgery types, surgery time, CPB time, aortic cross-clamp time and fluid balance were also assessed and recorded.\u003c/p\u003e \u003cp\u003ePostoperative hemodynamic variables including heart rate (HR), blood pressure (BP, including systolic blood pressure [IBPs], diastolic blood pressure [IBPd] and mean blood pressure [IBPm]), central venous pressure (CVP) and pulse oxygen saturation (SpO2) were measured in 5-min to 1-h interval during the first 24h after ICU admission by ECG monitoring, invasive arterial pressure and CVP monitoring. Furthermore, postoperative laboratory results at ICU admission, maximum doses of inotropic drugs within the first 24h after ICU admission and requirement for mechanical-assisted circulation including intra-aortic balloon pump (IABP) and extracorporeal membrane oxygenation (ECMO) were also collected and analyzed. In addition, prognosis indexes including mechanical ventilation time, length of ICU stay and hospital stays, hospital mortality, incidence of acute kidney injury (AKI) and requirement for renal replacement therapy (RRT) were also recorded for analysis.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eDelirium assessment\u003c/h2\u003e \u003cp\u003eAssessment of delirium was routinely performed twice a day during ICU stay, and as needed after ICU discharge using confusion assessment method for ICU (CAM-ICU). First of all, the consciousness levels of the patients were assessed by Richmond Agitation-Sedation scale (RASS). After that, the mental status of the patients was evaluated with CAM-ICU in those patients with RASS score \u0026ge; -3. The diagnosis of delirium was mainly based on the mental status of the patients. There were four characteristics of delirium diagnosis in CAM-ICU: ① acute change or fluctuation of mental state; ② Lack of concentration; ③ Disorder of thinking; ④ Changes in the level of consciousness. The patients were diagnosed with delirium when they met the characteristics of ①, ② and ③ or ④[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eCalculation of BPV\u003c/h2\u003e \u003cp\u003eIntraoperative blood pressure (mean blood pressure) was measured every five minutes during the operation and postoperative blood pressure (IBPs, IBPd and IBPm) was measured every 30 minutes for the first 24h after cardiac surgery during ICU stay. Systolic blood pressure below 40mmHg or above 300 mmHg and diastolic blood pressure below 20mmHg or above 150 mm Hg were set to missing and excluded from analysis. BPV was quantified by calculating the standard deviation (SD) and average real variability (ARV) of blood pressure.\u003c/p\u003e \u003cp\u003eThe calculation formula of SD was according to the following formula as previously reported[\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]:\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eSD=\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\sqrt{({\\sum }_{i=1}^{n}{\\left({x}_{i}-\\stackrel{-}{x}\\right)}^{2})/n-1}\\)\u003c/span\u003e\u003c/span\u003e\u003c/h2\u003e \u003cp\u003e \u003cspan class=\"InlineEquation\"\u003e \u003cspan class=\"mathinline\"\u003e\\({x}_{i}\\)\u003c/span\u003e \u003c/span\u003e: blood pressure at different time point, \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\stackrel{-}{x}\\)\u003c/span\u003e\u003c/span\u003e: mean value of blood pressure, \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(n\\)\u003c/span\u003e\u003c/span\u003e: number of blood pressure measurements.\u003c/p\u003e \u003cp\u003eARV of blood pressure was calculated based on the calculation formula that was reported in the literature and listed as follows[\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]:\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eARV=\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({\\sum }_{i=1}^{n-1}({x}_{i+1}-{x}_{i})/n-1\\)\u003c/span\u003e\u003c/span\u003e\u003c/h2\u003e \u003cp\u003e \u003cspan class=\"InlineEquation\"\u003e \u003cspan class=\"mathinline\"\u003e\\({x}_{i}\\)\u003c/span\u003e \u003c/span\u003e: blood pressure at different time point, \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({x}_{i+1}\\)\u003c/span\u003e\u003c/span\u003e: blood pressure at next time point, \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(n\\)\u003c/span\u003e\u003c/span\u003e: number of blood pressure measurements.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eR statistical software (R version 4.3.2) was used for statistical analysis in this study. Continuous variables were expressed as mean plus SD for those conforming to normal distribution and median plus interquartile range (IQR) for those not conforming to normal distribution. Independent-sample T test was preformed to compare the difference in the two groups for continuous variables conforming to normal distribution. For continuous variables not conforming to normal distribution, Mann\u0026ndash;Whitney U-test was carried out to compare the difference between the two groups. Categorical variables were presented as absolute values plus proportions analyzed by Chi-square test. The Least absolute shrinkage and selection operator (LASSO) regression was adopted to screen the potential hemodynamic variables contributing to the occurrence of POD. Afterwards, multivariate logistic regression was performed and logistic regression forest plot was drawn based on the hemodynamic variables screened by LASSO analysis. Furthermore, Restricted cubic spline (RCS) analysis was performed to assess the nonlinear associations between BPV and POD after cardiac surgery. Statistically significance was considered as a two-sided \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003e4490 cardiac patients who received cardiac surgery and admitted to CVICU after surgery during the study period between June 2019 and December 2022 were screened for potential enrollment. Finally, 2164 patients were enrolled and included in our study (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Of all the study patients, the incidence of POD was15.0% (324/2164), and the average day for POD occurred at day 3 (1, 5) after surgery. Patients were divided into two groups based on the occurrence of POD: Delirium group (n\u0026thinsp;=\u0026thinsp;324) and No Delirium group (n\u0026thinsp;=\u0026thinsp;1840).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eComparison of baseline characteristics\u003c/h2\u003e \u003cp\u003eThe comparison of baseline characteristics of the patients in the two groups were presented in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. Cardiac patients in the delirium group were predominantly male (237 [73.1%] vs. 1060 [57.6%], P\u0026thinsp;\u0026lt;\u0026thinsp;0.001), with older age (69.0 [61.0, 74.0] vs. 65 [57.0, 71.0] years, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and higher APACHE II score (14.0 [12.0, 17.0] vs. 12.0 [10.0, 15.0], P\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and euroSCORE (6.0 [5.0, 8.0] vs. 5.0 [4.0, 7.0], P\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Moreover, patients with co-morbidities of CAD and CRF were more likely to suffer POD when compared to those without. In terms of surgery type, cardiac patients in the delirium group had a significantly higher proportion to receive combined surgery of valve replacement/repair and coronary artery bypass grafting (CABG) and acute Stanford Type A aortic dissection (AAAD) surgery, and a lower proportion to receive valve surgery. In addition, patients in the delirium group had markedly longer operation time (290 [249, 340] vs. 260 [220, 310] min, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001), CPB time (128 [101, 167] vs. 115 [88, 147] min, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and aortic cross-clamp time (85.5 [67, 114] vs. 78 [59, 103] min, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Besides, patients in delirium group received higher doses of inotropic drugs within 24h after cardiac surgery when compared with those in no delirium group.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eBaseline characteristics of the cardiac patients with or without postoperative delirium\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo Delirium (n\u0026thinsp;=\u0026thinsp;1840)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eDelirium (n\u0026thinsp;=\u0026thinsp;324)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1060 (57.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e237 (73.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge, years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e65.0 [57.0;71.0]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e69.0 [61.0;74.0]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBMI, kg/m\u0026sup2;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e20.2 [19.0;21.5]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e20.0 [18.8;22.0]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.196\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAPACHE II score\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e12.0 [10.0;15.0]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14.0 [12.0;17.0]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEuroSCORE\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5.0 [4.0;7.0]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6.0 [5.0;8.0]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCo-morbidities, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStroke\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e250 (13.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e50 (15.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.424\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHypertension\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e901 (49.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e171 (52.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.228\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDiabetes mellitus\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e418 (22.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e83 (25.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.285\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCHD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e832 (45.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e190 (58.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCRF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e92 (5.00%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e40 (12.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e465 (25.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e68 (21.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.114\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCOPD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e99 (5.38%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e18 (5.56%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSurgery types, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCABG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e539 (29.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e108 (33.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.162\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eValve surgery\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e780 (42.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e93 (28.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCombined surgery of valve and CABG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e215 (11.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e58 (17.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.003\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAortic surgery\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e173 (9.40%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e33 (10.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.734\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAAAD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e48 (2.61%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e24 (7.41%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOther surgery\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e84 (4.57%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8 (2.47%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.115\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIntra-operative variables\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOperation time, min\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e260 [220;310]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e290 [249;340]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCPB time, min\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e115 [88;147]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e128 [101;167]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAortic cross-clamp time, min\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e78 [59;103]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e85.5 [67;114]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFluid input, ml\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2000 [1500;2131]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2000 [1500;2500]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBlood input, ml\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1250 [1000;1561]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1396 [1042;1752]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFluid output, ml\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2000 [1600;2500]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2100 [1688;2555]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.140\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBlood loss, ml\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1100 [1000;1300]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1200 [1000;1500]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUrine output, ml\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e800 [560;1250]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e800 [500;1200]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.084\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFluid balance, ml\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-100.00 [-622.50;350]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.00 [-550.00;400]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.220\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMaximum doses of inotropic drugs within 24h after surgery\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNorepinephrine, ug/kg/min\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.00 [0.00;0.10]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.08 [0.00;0.18]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDopamine, ug/kg/min\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.00 [0.00;4.00]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.00 [0.00;3.25]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.254\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDobutamine, ug/kg/min\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.00 [0.00;3.00]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.00 [0.00;4.00]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.055\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEpinephrine, ug/kg/min\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.00 [0.00;0.01]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.00 [0.00;0.04]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMilrinone, ug/kg/min\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.00 [0.00;0.00]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.00 [0.00;0.00]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.101\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOlprinone, ug/kg/min\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.00 [0.00;0.00]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.00 [0.00;0.00]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.307\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLevosimendan, ug/kg/min\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.00 [0.00;0.00]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.00 [0.00;0.00]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHypophysin, U/h\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.00 [0.00;0.00]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.00 [0.00;0.00]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVISmax\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7.00 [3.00;15.0]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e12.0 [5.00;24.0]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMechanical ventilation time, h\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e13.3 [8.8;19.3]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e20.2 [13.3;44.8]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLength of ICU stay, d\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.00 [2.00;3.00]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.00 [2.00;6.00]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLength of hospital stay, d\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e18.0 [15.0;22.0]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e21.0 [17.0;28.0]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHospital mortality, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e50 (2.72%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e29 (8.95%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRe-intubation, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e74 (4.02%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e57 (17.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAKI, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e585 (31.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e164 (50.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRRT requirement, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e42 (2.28%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e21 (6.48%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRequirement of MCS, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIABP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e49 (2.66%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e31 (9.57%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eECMO\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2 (0.11%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3 (0.93%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.026\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003eBMI: body mass index, APACHE II: Acute Physiology, Age, Chronic Health Evaluation II, EuroSCORE: European system for cardiac operative risk evaluation, CHD: coronary heart disease, CRF: chronic renal failure, AF: atrial fibrillation, COPD: chronic obstructive pulmonary disease, CABG: Coronary Artery Bypass Grafting, AAAD: Acute Stanford Type A Aortic Dissection, CPB: cardiopulmonary bypass, VIS: vasoactive-inotropic score, ICU: intensive care unit, AKI: acute kidney injury, RRT: renal replacement therapy, MCS: mechanical circulatory support, IABP: intra-aortic balloon pump, ECMO: extracorporeal membrane oxygenation.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eIn the aspect of prognostic indexes, cardiac patients in delirium group were more likely to have prolonged time for mechanical ventilation (20.2 [13.3, 44.8] vs. 13.3 [8.8, 19.3] min, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001), longer duration of ICU stay (4 [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e] vs. 2 [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e] d, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and hospital stay (21 [17, 28] vs. 18 [15, 22] d, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001), as well as higher hospital mortality (29 [8.95%] vs. 50 [2.72%], P\u0026thinsp;\u0026lt;\u0026thinsp;0.001).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eComparison of perioperative hemodynamic variables\u003c/h2\u003e \u003cp\u003eTo evaluate the impact of perioperative hemodynamic variables on POD, we compared the perioperative hemodynamic variables in the two groups (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Patients in delirium group had markedly lower levels of intraoperative mean blood pressure (BP_mean, 63.8 [59.2, 67.2] vs. 64.3 [60.2, 68.5] mmHg, P\u0026thinsp;=\u0026thinsp;0.015) and BP variability (BP_arv, 8.52 [6.40, 10.2] vs. 8.94 [7.08, 11.5] mmHg, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001) when compared to those in no delirium group.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003ePerioperative hemodynamic parameters of the cardiac patients with or without postoperative delirium\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo Delirium (n\u0026thinsp;=\u0026thinsp;1840)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eDelirium (n\u0026thinsp;=\u0026thinsp;324)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIntra-operative hemodynamic variables\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAUT_65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1575 [1015;2195]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1842 [1160;2706]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAUT_60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e980 [585;1451]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1155 [680;1846]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAUT_55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e590 [319;935]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e685 [360;1146]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.004\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAUT_50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e312 [135;560]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e365 [155;686]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.021\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBP_65_time, min\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e125 [90.0;165]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e150 [105;195]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBP_60_time, min\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e90.0 [60.0;125]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e110 [70.0;155]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBP_55_time, min\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e60.0 [40.0;90.0]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e70.0 [45.0;110]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBP_50_time, min\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e35.0 [20.0;60.0]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e45.0 [20.0;71.2]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.005\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTWA_BP_65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e12.2 [9.97;14.8]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e12.3 [10.1;15.0]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.691\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTWA_BP_60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10.7 [8.57;13.5]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10.7 [8.42;13.2]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.629\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTWA_BP_55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9.25 [7.00;12.3]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9.35 [7.10;12.2]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.972\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTWA_BP_50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7.70 [5.40;11.3]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8.21 [5.76;11.3]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.268\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBP_mean, mmHg\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e64.3 [60.2;68.5]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e63.8 [59.2;67.2]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.015\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBP_arv, mmHg\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8.94 [7.08;11.5]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8.52 [6.40;10.2]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePostoperative hemodynamic variables\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePM_HR_6h_mean, bpm\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e85.6 [79.4;91.8]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e86.9 [80.2;94.9]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.025\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePM_IBPs_6h_mean, mmHg\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e111 [104;118]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e110 [103;118]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.214\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePM_IBPd_6h_mean, mmHg\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e59.9 [55.3;65.5]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e57.4 [52.6;64.0]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePM_IBPm_6h_mean, mmHg\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e77.0 [72.5;81.9]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e75.3 [70.3;80.5]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePM_CVPm_6h_mean, mmHg\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7.88 [6.08;9.75]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8.48 [6.49;10.5]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePM_SpO2_6h_mean, %\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e99.8 [99.3;100]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e99.8 [99.3;100]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.154\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePM_MPP_6h_mean, mmHg\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e68.9 [64.2;74.3]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e66.9 [60.8;72.2]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePM_HR_6h_sd, bpm\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5.08 [2.90;7.90]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.06 [3.13;8.17]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.583\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePM_IBPs_6h_sd, mmHg\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10.8 [8.45;13.3]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11.0 [8.50;13.6]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.276\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePM_IBPd_6h_sd, mmHg\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5.38 [4.05;7.02]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.26 [3.98;6.93]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.424\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePM_IBPm_6h_sd, mmHg\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6.86 [5.33;8.78]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6.93 [5.37;8.49]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.932\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePM_CVPm_6h_sd, mmHg\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.26 [0.95;1.70]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.31 [1.00;1.83]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.031\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePM_HR_6h_arv, bpm\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.09 [1.75;4.82]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.27 [2.06;4.76]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.234\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePM_IBPs_6h_arv, mmHg\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8.55 [6.50;10.8]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8.70 [6.59;11.5]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.334\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePM_IBPd_6h_arv, mmHg\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4.18 [3.10;5.50]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.09 [3.00;5.55]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.406\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePM_IBPm_6h_arv, mmHg\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5.45 [4.10;7.00]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.45 [4.09;7.09]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.867\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePM_CVPm_6h_arv, mmHg\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.91 [0.70;1.20]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.00 [0.80;1.30]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePM_HR_6h_min, bpm\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e79.0 [70.0;85.0]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e80.0 [72.0;87.0]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.065\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePM_HR_12h_mean, bpm\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e86.9 [80.5;92.8]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e87.1 [81.0;95.4]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.216\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePM_IBPs_12h_mean, mmHg\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e113 [107;120]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e112 [106;120]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.289\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePM_IBPd_12h_mean, mmHg\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e60.6 [56.2;65.6]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e58.4 [53.5;64.0]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePM_IBPm_12h_mean, mmHg\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e78.1 [73.8;82.8]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e76.4 [71.8;81.1]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePM_CVPm_12h_mean, mmHg\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7.78 [6.08;9.55]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8.40 [6.61;10.1]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePM_SpO2_12h_mean, %\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e99.8 [99.3;100.0]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e99.8 [99.3;100.0]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.911\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePM_MPP_12h_mean, mmHg\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e70.4 [65.9;75.0]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e68.5 [62.6;73.1]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePM_HR_12h_sd, bpm\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6.44 [4.12;9.02]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6.08 [4.04;9.02]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.957\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePM_IBPs_12h_sd, mmHg\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e11.2 [9.26;13.6]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11.3 [9.29;13.7]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.760\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePM_IBPd_12h_sd, mmHg\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5.48 [4.40;6.78]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.47 [4.28;6.89]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.542\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePM_IBPm_12h_sd, mmHg\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7.09 [5.83;8.56]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6.99 [5.73;8.50]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.578\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePM_CVPm_12h_sd, mmHg\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.49 [1.16;1.88]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.49 [1.15;1.92]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.681\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePM_HR_12h_arv, bpm\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.17 [2.00;4.41]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.22 [2.13;4.44]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.649\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePM_IBPs_12h_arv, mmHg\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7.75 [6.22;9.59]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7.88 [6.41;10.0]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.391\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePM_IBPd_12h_arv, mmHg\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.74 [2.96;4.70]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.74 [2.91;4.69]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.574\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePM_IBPm_12h_arv, mmHg\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4.91 [3.95;6.05]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.91 [3.96;6.22]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.828\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePM_CVPm_12h_arv, mmHg\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.91 [0.73;1.13]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.96 [0.78;1.16]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.012\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePM_HR_12h_min, bpm\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e76.0 [68.0;83.0]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e78.0 [70.0;84.0]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.141\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePM_HR_24h_mean, bpm\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e87.4 [82.0;93.3]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e88.6 [82.4;95.7]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.036\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePM_IBPs_24h_mean, mmHg\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e116 [109;123]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e116 [110;123]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.902\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePM_IBPd_24h_mean, mmHg\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e61.4 [56.6;66.0]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e59.3 [54.9;65.2]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePM_IBPm_24h_mean, mmHg\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e79.4 [75.3;84.1]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e78.2 [73.8;83.2]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.003\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePM_CVPm_24h_mean, mmHg\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7.75 [6.18;9.43]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8.38 [6.89;10.2]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePM_SpO2_24h_mean, %\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e99.7 [99.2;99.9]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e99.6 [99.2;99.9]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.538\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePM_MPP_24h_mean, mmHg\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e71.6 [67.2;76.4]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e69.9 [65.5;74.5]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePM_HR_24h_sd, bpm\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7.42 [5.20;10.0]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7.72 [5.34;10.7]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.190\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePM_IBPs_24h_sd, mmHg\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e12.3 [10.2;14.6]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e12.9 [10.4;15.1]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.016\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePM_IBPd_24h_sd, mmHg\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5.81 [4.78;7.07]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.88 [4.74;7.37]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.276\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePM_IBPm_24h_sd, mmHg\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7.60 [6.34;8.92]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7.86 [6.42;9.45]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.105\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePM_CVPm_24h_sd, mmHg\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.66 [1.36;2.03]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.68 [1.40;2.16]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.140\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePM_HR_24h_arv, bpm\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.34 [2.36;4.57]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.42 [2.42;4.89]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.133\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePM_IBPs_24h_arv, mmHg\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7.91 [6.57;9.43]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8.64 [7.32;10.2]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePM_IBPd_24h_arv, mmHg\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.77 [3.11;4.60]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.00 [3.17;4.83]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.014\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePM_IBPm_24h_arv, mmHg\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4.94 [4.11;5.94]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.23 [4.46;6.19]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePM_CVPm_24h_arv, mmHg\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.94 [0.81;1.14]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.00 [0.86;1.18]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePM_HR_24h_min, bpm\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e74.0 [67.0;81.0]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e76.0 [69.0;82.0]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.063\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003eAUT_65: the area under blood pressure (BP) 65mmHg-time curve, AUT_60: the area under BP 60mmHg-time curve, AUT_55: the area under BP 55mmHg-time curve, AUT_50: the area under BP 50mmHg-time curve, BP_65_time: time of BP\u0026thinsp;\u0026lt;\u0026thinsp;65mmHg, BP_60_time: time of BP\u0026thinsp;\u0026lt;\u0026thinsp;60mmHg, BP_55_time: time of BP\u0026thinsp;\u0026lt;\u0026thinsp;55mmHg, BP_50_time: time of BP\u0026thinsp;\u0026lt;\u0026thinsp;50mmHg, TWA_BP_65: time-weighted average threshold value for BP\u0026thinsp;\u0026lt;\u0026thinsp;65mmHg, TWA_BP_60: time-weighted average threshold value for BP\u0026thinsp;\u0026lt;\u0026thinsp;60mmHg, TWA_BP_55: time-weighted average threshold value for BP\u0026thinsp;\u0026lt;\u0026thinsp;55mmHg, TWA_BP_50: time-weighted average threshold value for BP\u0026thinsp;\u0026lt;\u0026thinsp;50mmHg, arv: average real variability, HR: heart Rate, bpm: beats per minute, IBPs: systolic blood pressure, IBPd: diastolic blood pressure, IBPm: mean blood pressure, CVP: central venous pressure, MPP: mean perfusion pressure, SD: standard deviation, min: minimum.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eWhereas, postoperative ARV of systolic blood pressure (PM_IBPs_24h_arv, 8.64 [7.32, 10.2] vs. 7.91 [6.57, 9.43] mmHg, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001), diastolic blood pressure (PM_IBPd_24h_arv, 4.00 [3.17, 4.83] vs. 3.77 [3.11, 4.60] mmHg, P\u0026thinsp;=\u0026thinsp;0.014) and mean blood pressure (PM_IBPm_24h_arv, 5.23 [4.46, 6.19] vs. 4.94 [4.11, 5.94] mmHg, P\u0026thinsp;=\u0026thinsp;0.001) at 24h after surgery was significantly higher in the patients with POD than those without (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003ePerioperative BPV in predicting POD\u003c/h2\u003e \u003cp\u003eLASSO regression of the perioperative variables in predicting POD found that intraoperative BP_65_time (time of blood pressure below 65mmHg during operation), BP_60_time (time of blood pressure below 60mmHg during operation) and BP_arv (ARV of intraoperative blood pressure), and postoperative PM_MPP_6h_mean (mean perfusion pressure at 6h postoperatively), PM_MPP_12h_mean (mean perfusion pressure at 12h postoperatively), PM_CVPm_24h_mean (mean central venous pressure at 24h postoperatively), PM_IBPs_24h_arv and PM_IBPm_24h_arv were closely associated with POD (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). Further logistic regression revealed that BP_arv (OR:0.92, 95%CI: 0.89\u0026ndash;0.96, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001), PM_CVPm_24h_mean (OR:1.05, 95%CI: 1.00-1.10, P\u0026thinsp;=\u0026thinsp;0.048) and PM_IBPs_24h_arv (OR:1.17, 95%CI: 1.06\u0026ndash;1.30, P\u0026thinsp;=\u0026thinsp;0.002) were independent risk factors for POD (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e and Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). RCS analysis revealed that, the cut-off values for BP_arv and PM_IBPs_24h_arv were 5.640mmHg and 5.087mmHg, respectively (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eLogistics regression for postoperative delirium in the patients receiving cardiac surgery\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDependent: Delirium\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eOR (univariable)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eOR (multivariable)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBP_65_time\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMean (SD)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e135.5 (64.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e158.0 (68.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.00 (1.00-1.01, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.00 (0.99-1.00, p\u0026thinsp;=\u0026thinsp;0.794)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBP_60_time\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMean (SD)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e99.2 (54.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e118.2 (60.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.01 (1.00-1.01, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.00 (1.00-1.01, p\u0026thinsp;=\u0026thinsp;0.287)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBP_arv\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMean (SD)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e9.7 (3.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e8.7 (3.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.92 (0.88\u0026ndash;0.95, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.92 (0.89\u0026ndash;0.96, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePM_MPP_6h_mean\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMean (SD)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e69.2 (7.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e66.6 (8.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.96 (0.94\u0026ndash;0.97, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.99 (0.96\u0026ndash;1.03, p\u0026thinsp;=\u0026thinsp;0.749)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePM_MPP_12h_mean\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMean (SD)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e70.5 (7.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e68.2 (8.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.96 (0.94\u0026ndash;0.97, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.97 (0.93\u0026ndash;1.01, p\u0026thinsp;=\u0026thinsp;0.178)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePM_CVPm_24h_mean\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMean (SD)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e8.0 (2.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e8.7 (2.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.11 (1.06\u0026ndash;1.16, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.05 (1.00-1.10, p\u0026thinsp;=\u0026thinsp;0.048)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePM_IBPs_24h_arv\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMean (SD)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e8.1 (2.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e10.6 (33.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.12 (1.06\u0026ndash;1.17, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.17 (1.06\u0026ndash;1.30, p\u0026thinsp;=\u0026thinsp;0.002)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePM_IBPm_24h_arv\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMean (SD)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e5.1 (1.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e5.4 (1.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.11 (1.03\u0026ndash;1.20, p\u0026thinsp;=\u0026thinsp;0.006)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.97 (0.82\u0026ndash;1.13, p\u0026thinsp;=\u0026thinsp;0.714)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003eOR: odds ratio, BP: blood pressure, BP_65_time: time of BP\u0026thinsp;\u0026lt;\u0026thinsp;65mmHg, BP_60_time: time of BP\u0026thinsp;\u0026lt;\u0026thinsp;60mmHg, arv: average real variability, MPP: mean perfusion pressure, CVP: central venous pressure, IBPs: systolic blood pressure, IBPm: mean blood pressure.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eOur study was a single-center, retrospective, observational study conducted at CVICU of Nanjing First Hospital. In our study, we mainly focused on the influence of perioperative hemodynamic parameters on the occurrence of POD in the patients receiving cardiac surgery. We retrospectively enrolled 2164 cardiac patients in this study and assessed the impact of perioperative hemodynamic variables on the occurrence of POD. Our study found that, the incidence of POD was 15.0% in the cardiac patients received cardiac surgery and stayed in ICU for more than 24h after surgery, which was familiar to other studies[\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. Perioperative BPV rather than hypotension contributed to the occurrence of POD. Lower level of BPV during operation and higher level of BPV after surgery were independent risk factors for POD in the patients received cardiac surgery.\u003c/p\u003e \u003cp\u003eOur study showed that, lower level of BPV during operation would increase the incidence of POD in the cardiac patients. The patients we included in this study were all the cardiac patients underwent CPB procedure. Therefore, the patients would experience a period of relatively constant blood pressure during the process of CPB, leading to a low BPV. As a result, BPV during operation may be greatly affected by CPB time. A longer CPB time would lead to a lower BPV during the operation. Consistently, cardiac patients that suffered POD had a significantly longer CPB time (128min vs. 115min, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001) when compared to those did not. The association between CPB time and POD in the cardiac patients has been confirmed by numerous studies in the literature[\u003cspan additionalcitationids=\"CR13 CR14\" citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. Longer CPB time have been recognized as one of the independent risk factors for POD in the cardiac surgery, which is consistent with our results.\u003c/p\u003e \u003cp\u003eRecent studies have revealed a relationship between BPV and delirium in critically ill patients. A retrospective observational study by Garbajs et al. found that BPV in the first 24h after ICU admission was associated with a higher burden of delirium during hospitalization in the critically ill patients from both medical and surgical ICU[\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. In the surgical patients, perioperative BPV was also identified as an independent risk factor for POD in non-cardiac patients. A study by Hirsch et al. evaluated the correlation between intraoperative blood pressure and early POD in the non-cardiac patients[\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. The results showed that increased blood pressure fluctuation rather than relative hypotension was predictive of POD in the elder patients undergoing major non-cardiac surgery. Another recent study also confirmed the influence of perioperative blood pressure regulation on POD in patients undergoing head and neck free flap reconstruction[\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. They showed that low intraoperative minimum blood pressure were risk factors for POD. Whereas, data on the association between perioperative BPV and POD in patients receiving cardiac surgery were insufficient. Our studies first evaluated the relationship between perioperative BPV and POD in the patients receiving cardiac surgery. Familiar to previous studies, we also found a close correlation between high postoperative BPV and the occurrence of early POD in the cardiac patients.\u003c/p\u003e \u003cp\u003eThe influencing factors for the variability of blood pressure are various, including age, intraoperative blood loss, operation time, intravascular volume, use of anesthetic agents, inotropic and vasoactive drugs, etc.[\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. In the cardiac patients, BPV is mostly affected by the volume status and the vasoactive drugs that used during the perioperative period. The potential mechanism for the association between BPV and POD might be as follows: Although the mean arterial pressure changes, cerebral perfusion could remain relatively stable within the range of cerebral perfusion pressure from 50mmHg to 150mmHg under normal physiological conditions. Whereas, under anesthesia condition, cardiac patients with various co-morbidities such as hypertension, diabetes, smoking history, hypercapnia or obstructive sleep apnea syndrome and other diseases, may lead to the decline of brain autonomic regulation. In this way, a high perioperative BPV may affect the autoregulation function of the cerebrovascular vessels, leading to impaired brain function and the occurrence of POD.\u003c/p\u003e \u003cp\u003ePerioperative hypotension used to be regarded as the risk factor for POD in the patients underwent major surgeries. However, recent studies presented different opinions. A sub-analysis of the DECADE multi-center randomized trial performed by Wang et al. evaluated the relationship between perioperative hypotension and risk of delirium in the cardiac patients with CPB at the Cleveland Clinic. The results suggested that neither intraoperative or postoperative hypotension were associated with POD[\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Another study in elderly patients undergoing non-cardiac surgery also confirmed the same opinion. They found that increased blood pressure fluctuation rather than hypotension was predictive for POD[\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. Consistent with previous studies, our results also convinced that perioperative hypotension was not the major determining factors for POD when compared to perioperative BPV in the cardiac patients.\u003c/p\u003e \u003cp\u003eOur study also has several limitations that require consideration. First of all, due to the retrospective nature of this study, the time interval for blood pressure measurement was every 30 minutes after ICU admission, which was relatively fixed. In this way, we may ignore the blood pressure fluctuation outside these time points. Secondly, we only included the cardiac patients that stayed in ICU for more than 24h after surgery in this study, leading to the exclusion of over 50% of the cardiac patients with relatively short length of ICU stay. Whereas, the incidence of POD in our study was consistent with previous studies, showing little influence on the exclusion of those patients. Lastly, we only focused on the postoperative cognitive and mental conditions of the patients in this study, the preoperative cognitive and mental conditions were not well evaluated. However, those patients with obvious cognitive disorder and unable to communicate were excluded from this study. Further large-scale prospective clinical trials might be needed to better clarify the association between perioperative BPV and POD in the patients receiving cardiac surgery.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003ePostoperatively high BPV exposure rather than hypotension contributed to the occurrence of POD in the patients after cardiac surgery. Maintaining a relatively stable blood pressure after surgery might be beneficial in reducing the incidence of POD in the patients receiving cardiac surgery.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eBPV: blood pressure variability\u0026nbsp;\u003c/p\u003e\n\u003cp\u003ePOD: postoperative delirium\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eICU: Intensive Care Unit\u003c/p\u003e\n\u003cp\u003eSD: standard deviation (SD)\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eARV: average real variability\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAUT_65: the area under blood pressure (BP) 65mmHg-time curve\u003c/p\u003e\n\u003cp\u003eAUT_60: the area under BP 60mmHg-time curve\u003c/p\u003e\n\u003cp\u003eAUT_55: the area under BP 55mmHg-time curve\u003c/p\u003e\n\u003cp\u003eAUT_50: the area under BP 50mmHg-time curve\u003c/p\u003e\n\u003cp\u003eBP_65_time: time of BP \u0026lt; 65mmHg\u003c/p\u003e\n\u003cp\u003eBP_60_time: time of BP \u0026lt; 60mmHg\u003c/p\u003e\n\u003cp\u003eBP_55_time: time of BP \u0026lt; 55mmHg\u003c/p\u003e\n\u003cp\u003eBP_50_time: time of BP \u0026lt; 50mmHg\u003c/p\u003e\n\u003cp\u003eTWA_BP_65: time-weighted average threshold value for BP \u0026lt; 65mmHg\u003c/p\u003e\n\u003cp\u003eTWA_BP_60: time-weighted average threshold value for BP \u0026lt; 60mmHg\u003c/p\u003e\n\u003cp\u003eTWA_BP_55: time-weighted average threshold value for BP \u0026lt; 55mmHg\u003c/p\u003e\n\u003cp\u003eTWA_BP_50: time-weighted average threshold value for BP \u0026lt; 50mmHg\u003c/p\u003e\n\u003cp\u003eHR: heart Rate\u003c/p\u003e\n\u003cp\u003eIBPs: systolic blood pressure\u003c/p\u003e\n\u003cp\u003eIBPd: diastolic blood pressure\u003c/p\u003e\n\u003cp\u003eIBPm: mean blood pressure\u003c/p\u003e\n\u003cp\u003eCVP: central venous pressure\u003c/p\u003e\n\u003cp\u003eMPP: mean perfusion pressure\u003c/p\u003e\n\u003cp\u003eBP_mean: mean blood pressure\u003c/p\u003e\n\u003cp\u003eBP_arv: BP variability\u003c/p\u003e\n\u003cp\u003ePM_IBPm_24h_mean: postoperative mean blood pressure within 24h\u0026nbsp;\u003c/p\u003e\n\u003cp\u003ePM_IBPs_24h_arv: postoperative average real variability for systolic blood pressure\u003c/p\u003e\n\u003cp\u003ePM_IBPd_24h_arv: postoperative average real variability for diastolic blood pressure\u003c/p\u003e\n\u003cp\u003ePM_IBPm_24h_arv: postoperative average real variability for mean blood pressure\u003c/p\u003e\n\u003cp\u003ePM_CVPm_24h_mean: mean central venous pressure at 24h postoperatively\u003c/p\u003e\n\u003cp\u003eCPB: cardiopulmonary bypass\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eNYHA: New York Heart Association\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eMAP: mean arterial pressure\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eCVICU: Cardiovascular Intensive Care Unit\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eBMI: body mass index\u003c/p\u003e\n\u003cp\u003eAPACHE II: Acute Physiology and Chronic Health Evaluation II score\u003c/p\u003e\n\u003cp\u003eeuroSCORE: European System for Cardiac Operative Risk Evaluation\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eCAD: coronary artery disease\u003c/p\u003e\n\u003cp\u003eCRF: chronic renal failure\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAF: atrial fibrillation\u003c/p\u003e\n\u003cp\u003eCOPD: chronic obstructive pulmonary disease\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eEHRs: electronic health records\u003c/p\u003e\n\u003cp\u003eBP: blood pressure\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eSpO2: pulse oxygen saturation\u003c/p\u003e\n\u003cp\u003eIABP: intra-aortic balloon pump\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eECMO: extracorporeal membrane oxygenation\u003c/p\u003e\n\u003cp\u003eAKI: acute kidney injury\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eRRT: renal replacement therapy\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eCAM-ICU: confusion assessment method for Intensive Care Unit\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eRASS: Richmond Agitation-Sedation scale\u003c/p\u003e\n\u003cp\u003eIQR: interquartile range\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eLASSO: Least absolute shrinkage and selection operator\u003c/p\u003e\n\u003cp\u003eRCS: restricted cubic spline\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eCABG: coronary artery bypass grafting\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAAAD: acute Stanford Type A aortic dissection\u0026nbsp;\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate:\u0026nbsp;\u003c/strong\u003eFor the conduction and data collection of the study, the approval was gained from the institutional Ethics Committee of Nanjing First Hospital.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e: Not applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e: The datasets generated and/or analyzed during the current study are not publicly available due to the protection for the patients’ privacy but are available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e：The authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003eFunding: This study was supported by National Natural Science Foundation of China (82372217) and Natural Science Foundation of Jiangsu Province (BK20231128). The funding agency had no role in study design, the collection of data, in the interpretation of data, in the writing of the article, or in the decision to submit the article for publication.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors’ contributions:\u003c/strong\u003e XS and HT contributed to design, data acquisition, statistical analysis and drafted the manuscript. WXC and JKS contributed to data acquisition, data analysis and presentation. RHJ and WHZ contributed to data acquisition and data analysis. LH and CZ contributed to study control, study design and manuscript drafting. CZ contributed to manuscript drafting and revision. XS and HT contributed equally to the paper. All authors have read and approved the final manuscript.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e: Not applicable.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eJin, Z., J. Hu, and D. Ma, \u003cem\u003ePOD: perioperative assessment, risk reduction, and management.\u003c/em\u003e Br J Anaesth, 2020. \u003cstrong\u003e125\u003c/strong\u003e(4): p. 492-504.\u003c/li\u003e\n\u003cli\u003ePang, Y., et al., \u003cem\u003eEffects of inflammation and oxidative stress on POD in cardiac surgery.\u003c/em\u003e Front Cardiovasc Med, 2022. \u003cstrong\u003e9\u003c/strong\u003e: p. 1049600.\u003c/li\u003e\n\u003cli\u003eSugimura, Y., et al., \u003cem\u003eRisk and Consequences of POD in Cardiac Surgery.\u003c/em\u003e Thorac Cardiovasc Surg, 2020. \u003cstrong\u003e68\u003c/strong\u003e(5): p. 417-424.\u003c/li\u003e\n\u003cli\u003eChen, H., et al., \u003cem\u003eRisk factors of POD after cardiac surgery: a meta-analysis.\u003c/em\u003e J Cardiothorac Surg, 2021. \u003cstrong\u003e16\u003c/strong\u003e(1): p. 113.\u003c/li\u003e\n\u003cli\u003eWang, J., et al., \u003cem\u003eAssociation between perioperative hypotension and POD and atrial fibrillation after cardiac surgery: A post-hoc analysis of the DECADE trial.\u003c/em\u003e J Clin Anesth, 2022. \u003cstrong\u003e76\u003c/strong\u003e: p. 110584.\u003c/li\u003e\n\u003cli\u003eZorko Garbajs, N., et al., \u003cem\u003eAssociation of Blood Pressure Variability with Delirium in Patients with Critical Illness.\u003c/em\u003e Neurocrit Care, 2022: p. 1-9.\u003c/li\u003e\n\u003cli\u003eHori, D., et al., \u003cem\u003eBlood Pressure Deviations From Optimal Mean Arterial Pressure During Cardiac Surgery Measured With a Novel Monitor of Cerebral Blood Flow and Risk for Perioperative Delirium: A Pilot Study.\u003c/em\u003e J Cardiothorac Vasc Anesth, 2016. \u003cstrong\u003e30\u003c/strong\u003e(3): p. 606-12.\u003c/li\u003e\n\u003cli\u003eInouye, S.K., et al., \u003cem\u003eClarifying confusion: the confusion assessment method. A new method for detection of delirium.\u003c/em\u003e Ann Intern Med, 1990. \u003cstrong\u003e113\u003c/strong\u003e(12): p. 941-8.\u003c/li\u003e\n\u003cli\u003eHirsch, J., et al., \u003cem\u003eImpact of intraoperative hypotension and blood pressure fluctuations on early POD after non-cardiac surgery.\u003c/em\u003e Br J Anaesth, 2015. \u003cstrong\u003e115\u003c/strong\u003e(3): p. 418-26.\u003c/li\u003e\n\u003cli\u003eCoccina, F., et al., \u003cem\u003ePrognostic value of average real variability of systolic blood pressure in elderly treated hypertensive patients.\u003c/em\u003e Blood Press Monit, 2019. \u003cstrong\u003e24\u003c/strong\u003e(4): p. 179-184.\u003c/li\u003e\n\u003cli\u003eHuet, O., et al., \u003cem\u003ePrevention of post-operative delirium using an overnight infusion of dexmedetomidine in patients undergoing cardiac surgery: a pragmatic, randomized, double-blind, placebo-controlled trial.\u003c/em\u003e Crit Care, 2024. \u003cstrong\u003e28\u003c/strong\u003e(1): p. 64.\u003c/li\u003e\n\u003cli\u003eAndr\u0026aacute;si, T.B., et al., \u003cem\u003eRisk factors for POD after cardiac surgical procedures with cardioplegic arrest.\u003c/em\u003e Eur J Cardiothorac Surg, 2022. \u003cstrong\u003e62\u003c/strong\u003e(1).\u003c/li\u003e\n\u003cli\u003eUshio, M., et al., \u003cem\u003eTiming, Threshold, and Duration of Intraoperative Hypotension in Cardiac Surgery: Their Associations With POD.\u003c/em\u003e J Cardiothorac Vasc Anesth, 2022. \u003cstrong\u003e36\u003c/strong\u003e(11): p. 4062-4069.\u003c/li\u003e\n\u003cli\u003eBrown, C.H.t., et al., \u003cem\u003eEffect of Targeting Mean Arterial Pressure During Cardiopulmonary Bypass by Monitoring Cerebral Autoregulation on Postsurgical Delirium Among Older Patients: A Nested Randomized Clinical Trial.\u003c/em\u003e JAMA Surg, 2019. \u003cstrong\u003e154\u003c/strong\u003e(9): p. 819-826.\u003c/li\u003e\n\u003cli\u003eBaron Shahaf, D., et al., \u003cem\u003eAssociation Between Risk of Stroke and Delirium After Cardiac Surgery and a New Electroencephalogram Index of Interhemispheric Similarity.\u003c/em\u003e J Cardiothorac Vasc Anesth, 2023. \u003cstrong\u003e37\u003c/strong\u003e(9): p. 1691-1699.\u003c/li\u003e\n\u003cli\u003eZorko Garbajs, N., et al., \u003cem\u003eAssociation of Blood Pressure Variability with Delirium in Patients with Critical Illness.\u003c/em\u003e Neurocrit Care, 2023. \u003cstrong\u003e39\u003c/strong\u003e(3): p. 646-654.\u003c/li\u003e\n\u003cli\u003eOoms, M., et al., \u003cem\u003eInfluence of perioperative blood pressure regulation on POD in patients undergoing head and neck free flap reconstruction.\u003c/em\u003e Eur J Med Res, 2023. \u003cstrong\u003e28\u003c/strong\u003e(1): p. 365.\u003c/li\u003e\n\u003cli\u003eRothwell, P.M., \u003cem\u003eDoes blood pressure variability modulate cardiovascular risk?\u003c/em\u003e Curr Hypertens Rep, 2011. \u003cstrong\u003e13\u003c/strong\u003e(3): p. 177-86.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-anesthesiology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bane","sideBox":"Learn more about [BMC Anesthesiology](http://bmcanesthesiol.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bane","title":"BMC Anesthesiology","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"blood pressure variability, postoperative delirium, neurological complication, cardiac surgery","lastPublishedDoi":"10.21203/rs.3.rs-4643702/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4643702/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground: \u003c/strong\u003eDelirium is one of the most common neurological complications after cardiac surgery. The purpose of our study was to assess the relationship between perioperative blood pressure variability (BPV) and postoperative delirium (POD) in the patients after cardiac surgery.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods\u003c/strong\u003e: Adult patients received cardiac surgery and stayed in Cardiovascular Intensive Care Unit (ICU) for more than 24h after surgery during the study period between June 2019 and December 2022 were included in this study. Baseline characteristics, perioperative hemodynamic variables and postoperative laboratory results of the cardiac patients were collected and analyzed. Perioperative BPV was quantified by calculating the standard deviation (SD) and average real variability (ARV) of blood pressure. Assessment of delirium was based on the mental status of the patients and CAM-positive. The relationship between perioperative BPV and POD was analyzed by LASSO and logistic regression using R (R package, 4.3.2).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults:\u003c/strong\u003e The incidence of POD was 15.0% (324/2164) in the patients receiving cardiac surgery, and the average day for POD occurred at day 3 after surgery. Patients with delirium had markedly lower levels of intraoperative mean blood pressure (BP_mean, P=0.015) and BP variability (BP_arv, P\u0026lt;0.001) as well as postoperative mean blood pressure within 24h (PM_IBPm_24h_mean, P=0.003) when compared to those patients without delirium. Whereas, postoperative ARV for systolic blood pressure (PM_IBPs_24h_arv, 8.64 [7.32, 10.2] vs. 7.91 [6.57, 9.43] mmHg, P\u0026lt;0.001), diastolic blood pressure (PM_IBPd_24h_arv, 4.00 [3.17, 4.83] vs. 3.77 [3.11, 4.60] mmHg, P=0.014) and mean blood pressure (PM_IBPm_24h_arv, 5.23 [4.46, 6.19] vs. 4.94 [4.11, 5.94] mmHg, P=0.001) at 24h was significantly higher in the patients with POD than those without. LASSO regression and further logistic regression revealed that intraoperative BP_arv (OR:0.92, 95%CI: 0.89-0.96, P\u0026lt;0.001), PM_CVPm_24h_mean (mean central venous pressure at 24h postoperatively, OR:1.05, 95%CI: 1.00-1.10, P=0.048) and PM_IBPs_24h_arv (OR:1.17, 95%CI: 1.06-1.30, P=0.002) were independent risk factors for POD.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusions\u003c/strong\u003e: Postoperatively high BPV exposure rather than hypotension contributed to the occurrence of POD in the patients after cardiac surgery. Maintaining a relatively stable blood pressure after surgery might be beneficial in reducing the incidence of POD in the patients receiving cardiac surgery.\u003c/p\u003e","manuscriptTitle":"Postoperative blood pressure variability as a risk factor for postoperative delirium in the patients receiving cardiac surgery","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-07-22 10:48:01","doi":"10.21203/rs.3.rs-4643702/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2024-07-02T10:20:51+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-06-28T08:34:47+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-06-28T07:12:21+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Anesthesiology","date":"2024-06-26T15:18:45+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-anesthesiology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bane","sideBox":"Learn more about [BMC Anesthesiology](http://bmcanesthesiol.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bane","title":"BMC Anesthesiology","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"9e42864e-6de9-4457-ad0e-8b0e92e2836d","owner":[],"postedDate":"July 22nd, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2024-12-02T16:00:33+00:00","versionOfRecord":{"articleIdentity":"rs-4643702","link":"https://doi.org/10.1186/s12871-024-02817-x","journal":{"identity":"bmc-anesthesiology","isVorOnly":false,"title":"BMC Anesthesiology"},"publishedOn":"2024-11-25 15:57:10","publishedOnDateReadable":"November 25th, 2024"},"versionCreatedAt":"2024-07-22 10:48:01","video":"","vorDoi":"10.1186/s12871-024-02817-x","vorDoiUrl":"https://doi.org/10.1186/s12871-024-02817-x","workflowStages":[]},"version":"v1","identity":"rs-4643702","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4643702","identity":"rs-4643702","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}