Associations between intraoperative hypotension, duration of surgery and postoperative myocardial injury after noncardiac surgery: a retrospective single-centre cohort study.

BACKGROUND: Studies of intraoperative hypotension typically specify a blood pressure threshold associated with adverse outcomes. Such thresholds are likely to be study-biased, investigator-biased, or both. We hypothesised that a newly developed modelling method without a threshold, which is biologically more plausible than a threshold-based approach, would reveal a continuous association between exposure to intraoperative hypotension and adverse outcomes. METHODS: Single-centre, retrospective cohort study of subjects ≥60 yr old undergoing noncardiac surgery. We modelled intraoperative hypotension using three different approaches: (1) unweighted, (2) weighted for degree of hypotension (depth), and (3) weighted for duration of hypotension. The primary outcome was myocardial injury, defined as elevated troponin I (>60 ng L-1) measured during the first 3 days after surgery. The associations between the three models, postoperative myocardial injury, and mortality (secondary outcome) were reported as penalised adjusted odds ratios (ORs) scaled between the 75th and 25th percentiles. RESULTS: Myocardial injury occurred in 1812/15 452 (12%) procedures, with 554/15 452 (3.6%) procedures resulting in death before discharge from hospital. The unweighted lower blood pressure measure (OR: 0.26, 95% confidence interval [CI]: 0.12-0.53) and the depth-weighted measure (OR: 4.4, 95% CI: 2.6-7.4) were associated with myocardial injury. The duration-weighted measure was not associated with myocardial injury (OR: 0.89, 95% CI: 0.61-1.3). The unweighted measure (OR 0.08, 95% CI: 0.01-0.40) and the depth-weighted measure (OR: 12, 95% CI, 3.8-35) were associated with in-hospital mortality, but not the duration-weighted measure (OR: 1.3, 95% CI: 0.53-3.0). CONCLUSIONS: Intraoperative hypotension appears to have a graded association with postoperative myocardial injury and mortality, with depth appearing to contribute more than duration.

Intraoperative hypotension and delirium among older adults undergoing transcatheter aortic valve replacement.

BACKGROUND: Postoperative delirium (POD) is a frequently observed complication after transcatheter aortic valve replacement (TAVR). The effects of intraoperative hypotension (IOH) on POD occurrence are currently unclear. METHODS: A retrospective observational cohort study of patients who underwent TAVR was conducted. We predefined IOH as area under the threshold (AUT) of five mean arterial blood pressures (MBP), varying from <100 to <60 mmHg. The AUT consisted of the combination of duration and depth under the MBP thresholds, expressed in mmHg*min. All MBP AUTs were computed based on the complete procedure, independent of procedural phase or duration. RESULTS: This cohort included 675 patients who underwent TAVR under general anesthesia (n = 128, 19%) or procedural sedation (n = 547, 81%). Delirium occurred mostly during the first 2 days after TAVR, and was observed in n = 93 (14%) cases. Furthermore, 674, 672, 663, 630, and 518 patients had at least 1 min intraoperative MBP <100, <90, <80, <70, and <60 mmHg, respectively. Patients who developed POD had higher AUT based on all five MBP thresholds during TAVR. The penalized adjusted odds ratio varied between 1.08 (99% confidence interval [CI] 0.74-1.56) for the AUT based on MBP < 100 mmHg and OR 1.06 (99% CI 0.88-1.28) for the AUT based on MBP < 60 mmHg. CONCLUSIONS: Intraoperative hypotension is frequently observed during TAVR, but not independently associated with POD after TAVR. Other potential factors than intraoperative hypotension may explain the occurrence of delirium after TAVR.

Case-control study on the interplay between immunoparalysis and delirium after cardiac surgery.

BACKGROUND: Delirium occurs frequently following cardiothoracic surgery, and infectious disease is an important risk factor for delirium. Surgery and cardiopulmonary bypass induce suppression of the immune response known as immunoparalysis. We aimed to investigate whether delirious patients had more pronounced immunoparalysis following cardiothoracic surgery than patients without delirium, to explain this delirium-infection association. METHODS: A prospective matched case-control study was performed in two university hospitals. Cytokine production (tumor necrosis factor (TNF)-α, interleukin (IL)-6, IL-8 and IL-10) of ex vivo lipopolysaccharide (LPS)-stimulated whole blood was analyzed in on-pump cardiothoracic surgery patients preoperatively, and at 5 timepoints up to 3 days after cardiothoracic surgery. Delirium was assessed by trained staff using two validated delirium scales and chart review. RESULTS: A total of 89 patients were screened of whom 14 delirious and 52 non-delirious patients were included. Ex vivo-stimulated production of TNF-α, IL-6, IL-8, and IL-10 was severely suppressed following cardiothoracic surgery compared to pre-surgery. Postoperative release of cytokines in non-delirious patients was attenuated by 84% [IQR: 13-93] for TNF-α, 95% [IQR: 78-98] for IL-6, and 69% [IQR: 55-81] for IL-10. The attenuation in ex vivo-stimulated production of these cytokines was not significantly different in patients with delirium compared to non-delirious patients (p > 0.10 for all cytokines). CONCLUSIONS: The post-operative attenuation of ex vivo-stimulated production of pro- and anti-inflammatory cytokines was comparable between patients that developed delirium and those who remained delirium-free after on-pump cardiothoracic surgery. This finding suggests that immunoparalysis is not more common in cardiothoracic surgery patients with delirium compared to those without.

Artifacts annotations in anesthesia blood pressure data by man and machine.

Physiologic data from anesthesia monitors are automatically captured. Yet erroneous data are stored in the process as well. While this is not interfering with clinical care, research can be affected. Researchers should find ways to remove artifacts. The aim of the present study was to compare different artifact annotation strategies, and to assess if a machine learning algorithm is able to accept or reject individual data points. Non-cardiac procedures requiring invasive blood pressure monitoring were eligible. Two trained research assistants observed procedures live for artifacts. The same procedures were also retrospectively annotated for artifacts by a different person. We compared the different ways of artifact identifications and modelled artifacts with three different learning algorithms (lasso restrictive logistic regression, neural network and support vector machine). In 88 surgical procedures including 5711 blood pressure data points, the live observed incidence of artifacts was 2.1% and the retrospective incidence was 2.2%. Comparing retrospective with live annotation revealed a sensitivity of 0.32 and specificity of 0.98. The performance of the learning algorithms which we applied ranged from poor (kappa 0.053) to moderate (kappa 0.651). Manual identification of artifacts yielded different incidences in different situations, which were not comparable. Artifact detection in physiologic data collected during anesthesia could be automated, but the performance of the learning algorithms in the present study remained moderate. Future research should focus on optimization and finding ways to apply them with minimal manual work. The present study underlines the importance of an explicit definition for artifacts in database research.