Dataset Information

Hypotension Prediction Index software for management of hypotension during moderate- to high-risk noncardiac surgery: protocol for a randomized trial.

ABSTRACT: BACKGROUND:Hypotension is associated with serious complications, including myocardial infarction, acute kidney injury, and mortality. Consequently, predicting and preventing hypotension may improve outcomes. We will therefore determine if use of a novel hypotension prediction tool reduces the duration and severity of hypotension in patients having non-cardiac surgery. METHODS/DESIGN:We will conduct a two-center, pragmatic, randomized controlled trial (N?=?213) in noncardiac surgical patients >?45?years old who require intra-arterial blood pressure monitoring. All participating patients will be connected to a Flortrac IQ sensor and EV1000 platform (Edwards Lifesciences, Irvine). They will be randomly assigned to blinded or unblinded arms. The Hypotension Prediction Index (HPI) and advanced hemodynamic information will be universally recorded, but will only be available to clinicians when patients are assigned to unblinded monitoring. The primary outcome will be the effect of HPI software guidance on intraoperative time-weighted average mean arterial pressure under a threshold of 65?mmHg, which will be assessed with a Wilcoxon-Mann-Whitney 2-sample, two-tailed test. DISCUSSION:Our trial will determine whether the Hypotension Prediction Index and associated hemodynamic information substantively reduces hypotension during non-cardiac surgery. TRIAL REGISTRATION:ClinicalTrials.gov, NCT03610165 . Registered on 1 August 2018.

SUBMITTER: Maheshwari K

PROVIDER: S-EPMC6499972 | biostudies-literature | 2019 May

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Hypotension Prediction Index software for management of hypotension during moderate- to high-risk noncardiac surgery: protocol for a randomized trial.

Maheshwari Kamal K Shimada Tetsuya T Fang Jonathan J Ince Ilker I Mascha Edward J EJ Turan Alparslan A Kurz Andrea A Sessler Daniel I DI

Trials 20190503 1

<h4>Background</h4>Hypotension is associated with serious complications, including myocardial infarction, acute kidney injury, and mortality. Consequently, predicting and preventing hypotension may improve outcomes. We will therefore determine if use of a novel hypotension prediction tool reduces the duration and severity of hypotension in patients having non-cardiac surgery.<h4>Methods/design</h4>We will conduct a two-center, pragmatic, randomized controlled trial (N = 213) in noncardiac surgic ...[more]

PMID: 31053082

Similar Datasets

Project description:BackgroundIntraoperative hypotension (IOH) occurs frequently during surgery and may be associated with organ ischemia; however, few multicenter studies report data regarding its associations with adverse postoperative outcomes across varying hemodynamic thresholds. Additionally, no study has evaluated the association between IOH exposure and adverse outcomes among patients by various age groups.MethodsA multicenter retrospective cohort study was conducted between 2008 and 2017 using intraoperative blood pressure data from the US electronic health records database to examine postoperative outcomes. IOH was assessed in 368,222 noncardiac surgical procedures using 5 methods: (a) absolute maximum decrease in mean arterial pressure (MAP) during surgery, (b) time under each absolute threshold, (c) total area under each threshold, (d) time-weighted average MAP under each threshold, and (e) cumulative time under the prespecified relative MAP thresholds. MAP thresholds were defined by absolute limits (≤75, ≤65, ≤55 mm Hg) and by relative limits (20% and 40% lower than baseline). The primary outcome was major adverse cardiac or cerebrovascular events; secondary outcomes were all-cause 30- and 90-day mortality, 30-day acute myocardial injury, and 30-day acute ischemic stroke. Residual confounding was minimized by controlling for observable patient and surgical factors. In addition, we stratified patients into age subgroups (18-40, 41-50, 51-60, 61-70, 71-80, >80) to investigate how the association between hypotension and the likelihood of major adverse cardiac or cerebrovascular events and acute kidney injury differs in these age subgroups.ResultsIOH was common with at least 1 reading of MAP ≤75 mm Hg occurring in 39.5% (145,743) of cases; ≤65 mm Hg in 19.3% (70,938) of cases, and ≤55 mm Hg in 7.5% (27,473) of cases. IOH was significantly associated with the primary outcome for all age groups. For an absolute maximum decrease, the estimated odds of a major adverse cardiac or cerebrovascular events in the 30-day postsurgery was increased by 12% (95% confidence interval [CI], 11-14) for ≤75 mm Hg; 17.0% (95% CI, 15-19) for ≤65 mm Hg; and by 26.0% (95% CI, 22-29) for ≤55 mm Hg.ConclusionsIOH during noncardiac surgery is common and associated with increased 30-day major adverse cardiac or cerebrovascular events. This observation is magnified with increasing hypotension severity. The potentially avoidable nature of the hazard, and the extent of the exposed population, makes hypotension in the operating room a serious public health issue that should not be ignored for any age group.

Project description:(1) Background: The Hypotension Prediction Index (HPI) is an algorithm that predicts hypotension, defined as mean arterial pressure (MAP) less than 65 mmHg for at least 1 min, based on arterial waveform features. We tested the hypothesis that the use of this index reduces the duration and severity of hypotension during noncardiac surgery. (2) Methods: We enrolled adults having moderate- or high-risk noncardiac surgery with invasive arterial pressure monitoring. Participating patients were randomized 1:1 to standard of care or hemodynamic management with HPI guidance with a goal directed hemodynamic treatment protocol. The trigger to initiate treatment (with fluids, vasopressors, or inotropes) was a value of HPI of 85 (range, 0-100) or higher in the intervention group. Primary outcome was the amount of hypotension, defined as time-weighted average (TWA) MAP less than 65 mmHg. Secondary outcomes were time spent in hypertension defined as MAP more than 100 mmHg for at least 1 min; medication and fluids administered and postoperative complications. (3) Results: We obtained data from 99 patients. The median (IQR) TWA of hypotension was 0.16 mmHg (IQR, 0.01-0.32 mmHg) in the intervention group versus 0.50 mmHg (IQR, 0.11-0.97 mmHg) in the control group, for a median difference of -0.28 (95% CI, -0.48 to -0.09 mmHg; p = 0.0003). We also observed an increase in hypertension in the intervention group as well as a higher weight-adjusted administration of phenylephrine in the intervention group. (4) Conclusions: In this single-center prospective study of patients undergoing elective noncardiac surgery, the use of this prediction model resulted in less intraoperative hypotension compared with standard care. An increase in the time spent in hypertension in the treatment group was also observed, probably as a result of overtreatment. This should provide an insight for refining the use of this prediction index in future studies to avoid excessive correction of blood pressure.

Project description:ImportanceIntraoperative hypotension is associated with increased morbidity and mortality. A machine learning-derived early warning system to predict hypotension shortly before it occurs has been developed and validated.ObjectiveTo test whether the clinical application of the early warning system in combination with a hemodynamic diagnostic guidance and treatment protocol reduces intraoperative hypotension.Design, setting, and participantsPreliminary unblinded randomized clinical trial performed in a tertiary center in Amsterdam, the Netherlands, among adult patients scheduled for elective noncardiac surgery under general anesthesia and an indication for continuous invasive blood pressure monitoring, who were enrolled between May 2018 and March 2019. Hypotension was defined as a mean arterial pressure (MAP) below 65 mm Hg for at least 1 minute.InterventionsPatients were randomly assigned to receive either the early warning system (n = 34) or standard care (n = 34), with a goal MAP of at least 65 mm Hg in both groups.Main outcomes and measuresThe primary outcome was time-weighted average of hypotension during surgery, with a unit of measure of millimeters of mercury. This was calculated as the depth of hypotension below a MAP of 65 mm Hg (in millimeters of mercury) × time spent below a MAP of 65 mm Hg (in minutes) divided by total duration of operation (in minutes).ResultsAmong 68 randomized patients, 60 (88%) completed the trial (median age, 64 [interquartile range {IQR}, 57-70] years; 26 [43%] women). The median length of surgery was 256 minutes (IQR, 213-430 minutes). The median time-weighted average of hypotension was 0.10 mm Hg (IQR, 0.01-0.43 mm Hg) in the intervention group vs 0.44 mm Hg (IQR, 0.23-0.72 mm Hg) in the control group, for a median difference of 0.38 mm Hg (95% CI, 0.14-0.43 mm Hg; P = .001). The median time of hypotension per patient was 8.0 minutes (IQR, 1.33-26.00 minutes) in the intervention group vs 32.7 minutes (IQR, 11.5-59.7 minutes) in the control group, for a median difference of 16.7 minutes (95% CI, 7.7-31.0 minutes; P < .001). In the intervention group, 0 serious adverse events resulting in death occurred vs 2 (7%) in the control group.Conclusions and relevanceIn this single-center preliminary study of patients undergoing elective noncardiac surgery, the use of a machine learning-derived early warning system compared with standard care resulted in less intraoperative hypotension. Further research with larger study populations in diverse settings is needed to understand the effect on additional patient outcomes and to fully assess safety and generalizability.Trial registrationClinicalTrials.gov Identifier: NCT03376347.

Project description:ImportanceThe Simple Postoperative AKI Risk (SPARK) index is a prediction model for postoperative acute kidney injury (PO-AKI) in patients undergoing noncardiac surgery. External validation has not been performed.ObjectiveTo externally validate the SPARK index.Design, setting, and participantsThis single-center retrospective cohort study included adults who underwent noncardiac surgery under general anesthesia from 2007 to 2011. Those with obstetric or urological surgery, estimated glomerular filtration rate (eGFR) of less than 15 mL/min/1.73 m2, preoperative dialysis, or an expected surgical duration of less than 1 hour were excluded. The study was conducted at Nara Medical University Hospital. Data analysis was conducted from January to July 2021.ExposuresRisk factors for AKI included in SPARK index.Main outcomes and measuresPO-AKI, defined as an increase in serum creatinine of at least 0.3 mg/dL within 48 hours or 150% compared with preoperative baseline value or urine output of less than 0.5 mL/kg/h for at least 6 hours within 1 week after surgery, and critical AKI, defined as either AKI stage 2 or greater and/or any AKI connected to postoperative death or requiring kidney replacement therapy before discharge. The discrimination and calibration of the SPARK index were examined with area under the receiver operating characteristic curves (AUC) and calibration plots, respectively.ResultsAmong 5135 participants (2410 [46.9%] men), 303 (5.9%) developed PO-AKI, and 137 (2.7%) developed critical AKI. Compared with the SPARK cohort, participants in our cohort were older (median [IQR] age, 56 [44-66] years vs 63 [50-73] years), had lower baseline eGFR (median [IQR], 82.1 [71.4-95.1] mL/min/1.73 m2 vs 78.2 [65.6-92.2] mL/min/1.73 m2), and had a higher prevalence of comorbidities (eg, diabetes: 3956 of 51 041 [7.8%] vs 802 [15.6%]). The incidence of PO-AKI and critical AKI increased as the scores on the SPARK index increased. For example, 10 of 593 participants (1.7%) in SPARK class A, indicating lowest risk, experienced PO-AKI, while 53 of 332 (16.0%) in SPARK class D, indicating highest risk, experienced PO-AKI. However, AUCs for PO-AKI and critical AKI were 0.67 (95% CI, 0.63-0.70) and 0.62 (95% CI, 0.57-0.67), respectively, and the calibration was poor (PO-AKI: y = 0.24x + 3.28; R2 = 0.86; critical AKI: y = 0.20x + 2.08; R2 = 0.51). Older age, diabetes, expected surgical duration, emergency surgery, renin-angiotensin-aldosterone system blockade use, and hyponatremia were not associated with PO-AKI in our cohort, resulting in overestimation of the predicted probability of AKI in our cohort.Conclusions and relevanceIn this study, the incidence of PO-AKI increased as the scores on the SPARK index increased. However, the predicted probability might not be accurate in cohorts with older patients with more comorbidities.

Dataset Information

Hypotension Prediction Index software for management of hypotension during moderate- to high-risk noncardiac surgery: protocol for a randomized trial.

Publications

Hypotension Prediction Index software for management of hypotension during moderate- to high-risk noncardiac surgery: protocol for a randomized trial.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure