Effectiveness of the hypotension prediction index in non-cardiac surgeries: a systematic review, meta-analysis and trial sequential analysis
Efetividade do índice de previsão de hipotensão em cirurgias não cardíacas: uma revisão sistemática, meta-análise e análise sequencial de ensaios
Vitor Alves Felippe, Ana C. Pinho, Lucas M. Barbosa, Ivo Queiroz, Arthur H. Tavares, Rodrigo Diaz, Carlos Darcy Bersot, Jean-Louis Vincent
Abstract
Background
The efficacy of the Hypotension Prediction Index (HPI) for reducing Intraoperative Hypotension (IOH) among patients undergoing non-cardiac surgeries remains unclear. We aimed to perform a systematic review, meta-analysis, and trial sequential analysis to determine whether the HPI is effective for adult patients undergoing non-cardiac surgeries. This study was prospectively registered in the PROSPERO database (CRD42024571931).
Methods
PubMed, Embase, and Cochrane were systematically searched for Randomized Controlled Trials (RCTs) comparing HPI-guided therapy with standard care in non-cardiac surgeries. We computed Mean Difference (MD) and Risk Ratios (RR) for continuous and binary outcomes, respectively, with 95 % Confidence Intervals (95 % CI). Statistical analyses were performed using R Software, version 4.2.3.
Results
We included 11 RCTs, comprising a total of 789 patients, of whom 395 (50.1 %) received HPI-guided management. HPI significantly reduced the Time-Weighted Average (TWA) of Mean Arterial Pressure (MAP) < 65 mmHg (MD = -0.23 mmHg.min-1; 95 % CI -0.35 to -0.10; p < 0.01) and the Area Under the Curve (AUC) of MAP < 65 mmHg (MD = -97.2 mmHg.min-1; 95 % CI -143.4 to -50.98; p < 0.01). HPI also decreased the duration of MAP < 65 mmHg (MD = -16.22 min; 95 % CI -25.87 to -6.57; p < 0.01) and the number of hypotensive episodes per patient (MD = -3.38; 95 % CI -5.38 to -1.37; p < 0.01). No significant differences were observed in the number of hypotensive events, phenylephrine use, or AKI incidence (p > 0.05).
Conclusion
In adult patients undergoing non-cardiac surgeries, HPI use was associated with a reduction in the duration and severity of IOH, with no significant difference for adverse events. Limitations include significant heterogeneity across studies, differences in HPI implementation, and lack of long-term outcome data.
Keywords
Resumo
Introdução
A eficácia do Índice de Predição de Hipotensão (HPI) para reduzir a hipotensão intraoperatória (IOH) em pacientes submetidos a cirurgias não cardíacas ainda não está clara. O objetivo deste estudo foi realizar uma revisão sistemática, meta-análise e análise sequencial de ensaios para determinar se o HPI é eficaz em pacientes adultos submetidos a cirurgias não cardíacas. Este estudo foi registrado prospectivamente no banco de dados PROSPERO (CRD42024571931).
Métodos
As bases PubMed, Embase e Cochrane foram pesquisadas sistematicamente para identificar ensaios clínicos randomizados (RCTs) comparando a terapia guiada por HPI com o cuidado padrão em cirurgias não cardíacas. Foram calculadas a Diferença Média (MD) e as Razões de Risco (RR) para desfechos contínuos e binários, respectivamente, com Intervalos de Confiança de 95% (IC 95%). As análises estatísticas foram realizadas no R Software, versão 4.2.3.
Resultados
Foram incluídos 11 RCTs, totalizando 789 pacientes, dos quais 395 (50,1%) receberam manejo guiado por HPI. O HPI reduziu significativamente a Média Ponderada pelo Tempo (TWA) da Pressão Arterial Média (PAM) < 65 mmHg (MD = -0,23 mmHg·min⁻¹; IC 95% -0,35 a -0,10; p < 0,01) e a Área sob a Curva (AUC) da PAM < 65 mmHg (MD = -97,2 mmHg·min⁻¹; IC 95% -143,4 a -50,98; p < 0,01). O HPI também diminuiu a duração da PAM < 65 mmHg (MD = -16,22 min; IC 95% -25,87 a -6,57; p < 0,01) e o número de episódios hipotensivos por paciente (MD = -3,38; IC 95% -5,38 a -1,37; p < 0,01). Não foram observadas diferenças significativas no número de eventos hipotensivos, uso de fenilefrina ou incidência de lesão renal aguda (LRA) (p > 0,05).
Conclusão
Em pacientes adultos submetidos a cirurgias não cardíacas, o uso do HPI esteve associado à redução da duração e da gravidade da IOH, sem diferenças significativas em eventos adversos. Limitações incluem heterogeneidade significativa entre os estudos, diferenças na implementação do HPI e ausência de dados sobre desfechos a longo prazo.
Palavras-chave
References
1. Cohen B, Rivas E, Yang D, et al. Intraoperative Hypotension and Myocardial Injury After Noncardiac Surgery in Adults with or Without Chronic Hypertension: a Retrospective Cohort Analysis. Anesth Analg. 2022;135:329−40.
2. D’Amico F, Fominskiy EV, Turi S, et al. Intraoperative hypotension and postoperative outcomes: a meta-analysis of randomized trials. Br J Anaesth. 2023;131:823−31.
3. Hallqvist L, Granath F, Huldt E, Bell M. Intraoperative hypotension is associated with acute kidney injury in noncardiac surgery: an observational study. Eur J Anaesthesiol. 2018; 35:273−9.
4. Ripolles-Melchor J, Ramírez-Rodríguez JM, Casans-Franc es R, et al. Association Between Use of Enhanced Recovery After Surgery Protocol and Postoperative Complications in Colorectal Surgery: the Postoperative Outcomes Within Enhanced Recovery After Surgery Protocol (POWER) Study. JAMA Surg. 2019;154:725.
5. Silva ED, Perrino AC, Teruya A, et al. Consenso Brasileiro sobre terapia hemodinamica perioperat ^ oria guiada por objetivos em pacientes submetidos a cirurgias nao cardíacas: estrat ~ egia de gerenciamento de fluidos − produzido pela Sociedade de Anestesiologia do Estado de Sao Paulo (SAESP). Braz J Anesthesiol. ~ 2016;66:557−71.
6. Salmasi V, Maheshwari K, Yang D, et al. Relationship between Intraoperative Hypotension, Defined by Either Reduction from Baseline or Absolute Thresholds, and Acute Kidney and Myocardial Injury after Noncardiac Surgery: a Retrospective Cohort Analysis. Anesthesiology. 2017;126:47−65.
7. Davis R, Carestia A, Jenne C. Impaired hepatic leukocyte recruitment and increased thrombin generation during acute bacterial challenge in a mouse model of non-alcoholic fatty liver disease (NAFLD). Can Liver J. 2020;3:119.
8. Dong S, Wang Q, Wang S, Zhou C, Wang H. Hypotension prediction index for the prevention of hypotension during surgery and critical care: a narrative review. Comput Biol Med. 2024;170:107995.
9. JPRN-jRCT1012220033. Efficacy of Acumen HPI system. HttpstrialsearchwhointTrial2aspxTrialIDJPRN-JRCT1012220033 [Internet]. 2022; Available from: https://www.cochranelibrary.com/central/ doi/10.1002/central/CN-02593120/full.
10. Schneck E, Schulte D, Habig L, et al. Hypotension Prediction Index based protocolized haemodynamic management reduces the incidence and duration of intraoperative hypotension in primary total hip arthroplasty: a single centre feasibility randomised blinded prospective interventional trial. J Clin Monit Comput. 2020;34:1149−58.
11. Sribar A, Jurinjak IS, Almahariq H, et al. Hypotension prediction index guided versus conventional goal directed therapy to reduce intraoperative hypotension during thoracic surgery: a randomized trial. BMC Anesthesiol. 2023;23:101.
12. Murabito P, Astuto M, Sanfilippo F, et al. Proactive Management of Intraoperative Hypotension Reduces Biomarkers of Organ Injury and Oxidative Stress during Elective Non-Cardiac Surgery: a Pilot Randomized Controlled Trial. J Clin Med. 2022;11(2):392.
13. Frassanito L, Sonnino C, Piersanti A, et al. Performance of the Hypotension Prediction Index with Noninvasive Arterial Pressure Waveforms in Awake Cesarean Delivery Patients Under Spinal Anesthesia. Anesth Analg. 2022;134:633−43.
14. Page MJ, McKenzie JE, Bossuyt PM, et al. The PRISMA 2020 statement: an updated guideline for reporting systematic reviews. BMJ. 2021;372:n71.
15. Cochrane Handbook for Systematic Reviews of Interventions, version 6.4 (updated February 2023). Available from: https:// training.cochrane.org/handbook (accessed August 26, 2024).
16. Sterne JAC, Savovic J, Page MJ, et al. RoB 2: a revised tool for assessing risk of bias in randomised trials. BMJ. 2019;366:l4898.
17. Peters JL, Sutton AJ, Jones DR, Abrams KR, Rushton L. Contourenhanced meta-analysis funnel plots help distinguish publication bias from other causes of asymmetry. J Clin Epidemiol. 2008;61:991−6.
18. Higgins JPT. Measuring inconsistency in meta-analyses. BMJ. 2003;327:557−60.
19. DerSimonian R, Laird N. Meta-analysis in clinical trials. Control Clin Trials. 1986;7:177−88.
20. Thorlund K, Engstrøm J, Wetterslev J, et al. User manual for Trial Sequential Analysis (TSA) Available from https://www.ctu. dk/tsa/files/tsa_manual.pdf; 2017.
21. Yoshikawa Y, Maeda M, Kunigo T, Sato T, Takahashi K, Ohno S, et al. Effect of using hypotension prediction index versus conventional goal-directed haemodynamic management to reduce intraoperative hypotension in non-cardiac surgery: a randomised controlled trial. J Clin Anesth. 2024;93:111348.
22. Wijnberge M, Geerts BF, Hol L, et al. Effect of a Machine Learning-Derived Early Warning System for Intraoperative Hypotension vs Standard Care on Depth and Duration of Intraoperative Hypotension During Elective Noncardiac Surgery: the HYPE Randomized Clinical Trial. JAMA. 2020;323:1052.
23. Tsoumpa M, Kyttari A, Matiatou S, et al. The Use of the Hypotension Prediction Index Integrated in an Algorithm of Goal Directed Hemodynamic Treatment during Moderate and HighRisk Surgery. J Clin Med. 2021;10:5884.
24. Pouska J, Kletecka J, Zatloukal J, Cerveny V, Benes J. A protocol based on hypotension probability indicator vs. standard care to prevent intraoperative hypotension during supratentorial brain surgery: a prospective randomized pilot trial. Minerva Anestesiol. 2023;89:510−9.
25. Maheshwari K, Shimada T, Yang D, et al. Hypotension Prediction Index for Prevention of Hypotension during Moderateto High-risk Noncardiac Surgery. Anesthesiology. 2020;133: 1214−22.
26. Lai CJ, Cheng YJ, Han YY, et al. Hypotension prediction index for prevention of intraoperative hypotension in patients undergoing general anesthesia: a randomized controlled trial. Perioper Med. 2024;13:57.
27. Koo JM, Choi H, Hwang W, et al. Clinical Implication of the Acumen Hypotension Prediction Index for Reducing Intraoperative Haemorrhage in Patients Undergoing Lumbar Spinal Fusion Surgery: a Prospective Randomised Controlled Single-Blinded Trial. J Clin Med. 2022;11:4646.
28. Char DS, Burgart A. Machine-Learning Implementation in Clinical Anesthesia: opportunities and Challenges. Anesth Analg. 2020;130:1709−12.
29. Lee S, Lee HC, Chu YS, et al. Deep learning models for the prediction of intraoperative hypotension. Br J Anaesth. 2021;126:808−17.
30. Cecconi M, Greco M, Shickel B, Vincent JL, Bihorac A. Artificial intelligence in acute medicine: a call to action. Crit Care. 2024;28:258.
31. Sun LY, Wijeysundera DN, Tait GA, Beattie WS. Association of intraoperative hypotension with acute kidney injury after elective noncardiac surgery. Anesthesiology. 2015;123:515−23.
32. Gregory A, Stapelfeldt WH, Khanna AK, et al. Intraoperative Hypotension Is Associated with Adverse Clinical Outcomes After Noncardiac Surgery. Anesth Analg. 2021;132:1654−65.
33. Monge García MI, García-Lopez D, Gayat E, et al. Hypotension Prediction Index Software to Prevent Intraoperative Hypotension during Major Non-Cardiac Surgery: protocol for a European Multicenter Prospective Observational Registry (EU-HYPROTECT). J Clin Med. 2022;11:5585.
34. Lombardi F, Lucarelli K, Frassanito L, et al. Role of the Machine Learning-Derived Hypotension Index (HPI) to Contain Intraoperative Hypotension During Transcatheter Edge to Edge Repair Procedures. Eur Heart J Suppl. 2024;26. ((Lombardi F.; Lucarelli K.; Frassanito L.; Casamassima V.; Troisi F.; Bellomo V.; Argentiero A.; Mancini G.; Casamassima F.; Lanza G.; Burzotta F.; Grimaldi M.) 1Ospedale Generale Regionale F.Miulli, Acquaviva delle Fonti; Policlinico Universitario Agostino Gemelli, Roma):ii117.
35. Lapage KG, Wouters PF. The patient with hypertension undergoing surgery. Curr Opin Anaesthesiol. 2016;29:397−402.
36. Maheshwari K, Khanna S, Bajracharya GR, et al. A Randomized Trial of Continuous Noninvasive Blood Pressure Monitoring During Noncardiac Surgery. Anesth Analg. 2018;127:424−31.
37. Hatib F, Jian Z, Buddi S, et al. Machine-learning Algorithm to Predict Hypotension Based on High-fidelity Arterial Pressure Waveform Analysis. Anesthesiology. 2018;129:663−74.
38. Lu SY, Dalia AA. Continuous Noninvasive Arterial Pressure Monitoring for Transcatheter Aortic Valve Replacement. J Cardiothorac Vasc Anesth. 2021;35:2026−33.
39. Saugel B, Kouz K, Scheeren TWL, et al. Cardiac output estimation using pulse wave analysis ‒ physiology, algorithms, and technologies: a narrative review. Br J Anaesth. 2021;126:67−76.
Submitted date:
02/07/2025
Accepted date:
05/23/2025
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