Hypotension Prediction Index for Prevention of Hypotension during Moderate- to High-risk Noncardiac Surgery

Maheshwari, Kamal; Shimada, Tetsuya; Yang, Dongsheng; Khanna, Sandeep; Cywiński, Jacek B.; Irefin, Samuel A.; Ayad, Sabry; Turan, Alparslan; Ruetzler, Kurt; Qiu, Yuwei; Saha, Partha; Mascha, Edward J.; Sessler, Daniel I.

doi:10.1097/aln.0000000000003557

Cited by 116 publications

(121 citation statements)

References 18 publications

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“…In contrast to the studies mentioned and our data, a recent study by Maheshwari et al 29 demonstrated no significant difference comparing a HPI‐guided group to an unguided group. They reported a time‐weighted average of 0.14 mmHg and a time‐weighted mean arterial pressure >83 mmHg (84.9 vs. 83.4 mmHg, p = 0.193) in both groups.…”

Section: Discussioncontrasting

confidence: 99%

Hemodynamic monitoring with Hypotension Prediction Index versus arterial waveform analysis alone and incidence of perioperative hypotension

Grundmann

Wischermann

Faßbender

et al. 2021

Acta Anaesthesiol Scand

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Background Intraoperative hypotension is associated with increased morbidity and mortality. The Hypotension Prediction Index (HPI) is an advancement of the arterial waveform analysis to predict intraoperative hypotension minutes before episodes occur enabling preventive treatments. We tested the hypothesis that the HPI combined with a personalized treatment protocol reduces intraoperative hypotension when compared to arterial waveform analysis alone. Methods We conducted a retrospective analysis of 100 adult consecutive patients undergoing moderate‐ or high‐risk noncardiac surgery with invasive arterial pressure monitoring using either index guidance (HPI) or arterial waveform analysis (FloTrac) depending on availability (FloTrac, n = 50; HPI, n = 50). A personalized treatment protocol was applied in both groups. The primary endpoint was the incidence and duration of hypotensive events defined as MAP <65 mmHg evaluated by time‐weighted average of hypotension. Results In the FloTrac group, 42 patients (84%) experienced a hypotension while in the HPI group 26 patients (52%) were hypotensive (p = 0.001). The median (IQR) time‐weighted average of hypotension in the FloTrac group was 0.27 (0.42) mmHg versus 0.10 (0.19) mmHg in the HPI group (p = 0.001). Finally, the median duration of each hypotensive event (IQR) was 2.75 (2.40) min in the FloTrac group compared to 1.00 (2.06) min in the HPI group (p = 0.002). Conclusions The application of the HPI combined with a personalized treatment protocol can reduce incidence and duration of hypotension when compared to arterial waveform analysis alone. This study therefore provides further evidence of the transition from prediction to actual prevention of hypotension using HPI.

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Section: Discussioncontrasting

confidence: 99%

Hemodynamic monitoring with Hypotension Prediction Index versus arterial waveform analysis alone and incidence of perioperative hypotension

Grundmann

Wischermann

Faßbender

et al. 2021

Acta Anaesthesiol Scand

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“…The time-weighted average of hypotension seems a very promising variable to evaluate the degree of intraoperative hypotension, taking into account both the severity of hypotension and its duration as well as the total surgical time. In this regards, our intervention group found similar values of time-weighted average (0.12 mmHg) as compared to other larger studies (0.10 mmHg [10] and 0.14 mmHg [12]).…”

Section: Discussionsupporting

confidence: 85%

“…Indeed, our results seem in line with most of currently published ndings. Although a recent study by Maheshwari et al conducted in 214 patients undergoing non-cardiac surgery questioned the role of HPI [12], most of the published evidence supports the value of HPI in predicting hypotension. Indeed, such results have been found in patients undergoing total hip arthroplasty [13], major/general surgery [14,15] and cardiac surgery [16].…”

Section: Discussionmentioning

confidence: 99%

Performance of Hypotension Prediction Index for Prevention of Hypotension and Results on Biomarkers of Organ Injury and Oxidative Stress During Elective Non-Cardiac Surgery: A Randomized Controlled Trial

Murabito

Astuto

Sanfilippo

et al. 2021

Preprint

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Background: Intraoperative hypotension is associated with increased postoperative morbidity and mortality. We tested whether the clinical application of an early warning system (EWS) in combination with an algorithm for hemodynamic management reduces the occurrence of intraoperative hypotension as well as decrease the degree of organ injury and oxidative stress. Methods: We randomly assigned patients undergoing major general surgery EWS and hemodynamic algorithm (intervention group, n=20) or standard care (n=20). The primary outcome was the difference in hypotension (defined as mean arterial pressure<65mmHg) evaluated as episodes, time and time-weighted average of hypotension. As secondary outcome we assessed surrogate markers of organ injury (neuron specific enolase -NSE), S100B protein, high-sensitive troponin, neutrophil gelatinase-associated lipocalin -NGAL) and oxidative stress (reduced glutathione). Results: The median number of hypotensive episodes was lower in the intervention group [-5.0 (95%CI:-9.0,-0.5);P<0.005], with lower time spent in hypotension [-12.8 minutes (95%CI:-38.0,-2.3 min);P<0.001], correspondent to -4.8% of total surgery time (95%CI: -12.7,0.01%; P<0.05). The median time-weighted average of hypotension was 0.12 mmHg (0.35) in the intervention group and 0.37 mmHg (1.11) in the control group, with a median difference of -0.25 mmHg (95%CI:-0.85, -0.01;P<0.05). NGAL was correlated with time-weighted average of hypotension (R=0.32;P<0.05) and S100B with all primary outcomes investigated (all P<0.001). The intervention group had lower NSE and higher reduced glutathione when compared to the control group. Conclusions: The use of an EWS coupled with an hemodynamic algorithm resulted in reduced intraoperative hypotension. This finding was coupled with a reduction of biomarkers of brain injury and oxidative stress.Trial Registration number and date: “Correlation Between Circulating Biomarkers of Organ Damage and Intraoperative Hypotension Management”, NCT03527758, registered on May 17, 2018.https://www.clinicaltrials.gov/ct2/show/NCT03527758?term=NCT03527758&draw=2&rank=1

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“…To achieve this, repeated re-assessment of risk after early ARRC treatment may be able to identify the 50% of moderate-risk patients who were unlikely to develop major adverse events overnight 27 . Considering the high incidence of hypotension in this study, there may be a role in this for devices with the capacity to predict hypotension 28 . The potential impact of this can then be estimated prospectively using this model, with costs (to now include device consumables and fewer staff) appropriately adjusted.…”

Section: Discussionmentioning

confidence: 95%

Evaluation of a New Model of Postoperative Care: A Preliminary Cost-effectiveness Analysis Using Markov Modelling

Ludbrook¹

2020

Preprint

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Background: Re-design of systems or models of care to manage perioperative care has the potential to generate higher value care (improved outcomes; ideally lower cost). However, this needs high quality measurement of cost-effectiveness to allow stakeholders to select those which provide most value, and to plan future interventions. Data on cost-effective analysis in this area are sparse, and trials often apply relatively simple analytic techniques.Methods: This analysis utilised recently published data from a small feasibility trial of a new model of medium-acuity postoperative care for moderate-risk patients undergoing surgery (Advanced Recovery Room Care; ARRC). The trial 1 data were used to develop a Markov cost-effectiveness model of patient transition (model transition probabilities) between locations of care (model states), each with different effects and cost. Cost was taken from the perspective of hospitals. The effect chosen was patient postoperative days at home after surgery (DAH), an effect reflecting quality of in-hospital care, acknowledged financially by healthcare fundholders, and relevant to consumers. A model cycle time of 4 hours run out to 30 days after surgery reflected clinically relevant timelines and costs.Results: This model showed the potential differences before and after introduction of ARRC in ICU use, re-admissions, and DAH, in particular, which reflected the findings from the ARRC trial. Incremental cost effectiveness ratio (ICER) of introduction of ARRC was minus $601 for every increased day at home. Sensitivity analysis revealed 805 of 1000 simulations found a negative ICER.Conclusions: These data suggest that the ARRC model may have positive cost-effectiveness, something to be examined in a future prospective clinical trial. Such cost-effectiveness modelling may have utility in examination of other innovations in perioperative care.Trial registration: The ARRC trial on which this analysis is based was prospectively registered: ANZCTRN 12617001173381

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Hypotension Prediction Index for Prevention of Hypotension during Moderate- to High-risk Noncardiac Surgery

Cited by 116 publications

References 18 publications

Hemodynamic monitoring with Hypotension Prediction Index versus arterial waveform analysis alone and incidence of perioperative hypotension

Hemodynamic monitoring with Hypotension Prediction Index versus arterial waveform analysis alone and incidence of perioperative hypotension

Performance of Hypotension Prediction Index for Prevention of Hypotension and Results on Biomarkers of Organ Injury and Oxidative Stress During Elective Non-Cardiac Surgery: A Randomized Controlled Trial

Evaluation of a New Model of Postoperative Care: A Preliminary Cost-effectiveness Analysis Using Markov Modelling

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