Vol. 30 No. 2 (2026)
ANESTHESIOLOGY & RESUSCITATION

Diagnostic accuracy of passive leg raising test: systematic review and network meta-analysis

PDF (Русский) PDF HTML (Русский) Дополнительные материалы (Русский) Supplementary materials JATS XML (Русский)
  • Mikhail Ya. Yadgarov,
  • Levan B. Berikashvili,
  • Ivan V. Kuznetsov,
  • Pavel V. Ryzhkov,
  • Andrey G. Yavorovskiy,
  • Alexey A. Yakovlev,
  • Valery V. Likhvantsev
Mikhail Ya. Yadgarov
Federal Research and Clinical Center of Intensive Care Medicine and Rehabilitology
Levan B. Berikashvili
Federal Research and Clinical Center of Intensive Care Medicine and Rehabilitology
Ivan V. Kuznetsov
Federal Research and Clinical Center of Intensive Care Medicine and Rehabilitology
Pavel V. Ryzhkov
Federal Research and Clinical Center of Intensive Care Medicine and Rehabilitology
Andrey G. Yavorovskiy
First Moscow State Medical University
Alexey A. Yakovlev
Federal Research and Clinical Center of Intensive Care Medicine and Rehabilitology
Valery V. Likhvantsev
Federal Research and Clinical Center of Intensive Care Medicine and Rehabilitology
DOI: https://doi.org/10.21688/1681-3472-2026-2-34-44

Published 2026-08-10

Keywords

  • cardiac output; fluid therapy; hemodynamic monitoring; posture; stroke volume; venous return

How to Cite

Yadgarov, M. Y. ., Berikashvili, L. B. ., Kuznetsov, I., Ryzhkov, P. V. ., Yavorovskiy , A. G., Yakovlev, A. A. ., & Likhvantsev, V. V. . (2026). Diagnostic accuracy of passive leg raising test: systematic review and network meta-analysis. Patologiya Krovoobrashcheniya I Kardiokhirurgiya, 30(2), 34–44. https://doi.org/10.21688/1681-3472-2026-2-34-44

Copyright (c) 2026 Yadgarov et al.

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

Abstract

Introduction: The passive leg raising (PLR) test is a non-invasive diagnostic tool for assessing fluid responsiveness, a pivotal aspect in hypotension management. Despite its growing application, a unified comparative assessment of prognostic accuracy for various PLR test parameters is currently lacking.

Objective: Our study aimed to evaluate the efficacy of different PLR test indicators in predicting fluid responsiveness.

Methods: We conducted a network meta-analysis, analyzing prospective
studies that explored diagnostic accuracy of PLR test for fluid responsiveness. Electronic databases were searched until March 2024; this search was supplemented by snowballing methods. The Grading of Recommendations Assessment, Development, and Evaluation (GRADE) approach was used to determine the certainty of evidence.

Results: Sixteen prospective cohort studies involving 784 patients were included. The network meta-analysis revealed that cardiac output parameters measured during the PLR test have the highest prognostic significance for assessing fluid responsiveness compared to other parameters (SUCRA score = 88.3). Utilizing arterial blood flow indicators results in a moderate prognostic value for the PLR test (SUCRA score = 72.0). The use of such conventional parameters as arterial blood pressure and inferior vena cava diameter reduces prognostic accuracy to unsatisfactory levels (SUCRA score < 50). The superiority of PLR test prognostic capability when using cardiac output parameters over arterial blood pressure indicators is supported by high-quality evidence.

Conclusion: Our network meta-analysis demonstrated that using PLR test with cardiac output parameters ensures maximum sensitivity and specificity. Consequently, the use of more straightforward and easily obtainable
parameters (arterial blood pressure, inferior vena cava diameter) is not recommended for assessing fluid responsiveness.

Received 9 October 2025. Revised 14 October 2025. Accepted 18 February 2026.

Funding
The study did not have sponsorship.

Conflict of interest
The authors declare no conflict of interest.

Contribution of the authors
Conception and study design: V.V. Likhvantsev, L.B. Berikashvili

Data collection and analysis: I.V. Kuznetsov, P.V. Ryzhkov, M.Ya. Yadgarov, L.B. Berikashvili

Statistical analysis: M.Ya. Yadgarov
Drafting the article: I.V. Kuznetsov, L.B. Berikashvili, M.Ya. Yadgarov, A.G. Yavorovskiy, A.A. Yakovlev

Critical revision of the article: V.V. Likhvantsev

Final approval of the version to be published: all authors

PDF (Русский) PDF HTML (Русский) Дополнительные материалы (Русский) Supplementary materials JATS XML (Русский)

References

  1. Durand F., Kellum J.A., Nadim M.K. Fluid resuscitation in patients with cirrhosis and sepsis: A multidisciplinary perspective. J Hepatol. 2023;79(1):240-246. PMID: 36868480. https://doi.org/10.1016/j.jhep.2023.02.024
  2. Rivasi G., Fedorowski A. Hypertension, hypotension and syncope. Minerva Med. 2022;113(2):251-262. PMID: 33881284. https://doi.org/10.23736/S0026-4806.21.07562-5
  3. Bijker J.B., van Klei W.A., Kappen T.H., van Wolfswinkel L., Moons K.G.M., Kalkman C.J. Incidence of intraoperative hypotension as a function of the chosen definition: literature definitions applied to a retrospective cohort using automated data collection. Anesthesiology. 2007;107(2):213-20. PMID: 17667564. https://doi.org/10.1097/01.anes.0000270724.40897.8e
  4. Wieling W., Jardine D.L., De Lange F.J., Brignole M., Nielsen H.B., Stewart J., Sutton R. Cardiac output and vasodilation in the vasovagal response: An analysis of the classic papers. Heart Rhythm. 2016;13(3):798-805. PMID: 26598322; PMCID: PMC5234327. https://doi.org/10.1016/j.hrthm.2015.11.023
  5. Halvorsen S., Mehilli J., Cassese S., Hall T.S., Abdelhamid M., Barbato E., De Hert S., de Laval I., Geisler T., Hinterbuchner L., Ibanez B., Lenarczyk R., Mansmann U.R., McGreavy P., Mueller C., Muneretto C., Niessner A., Potpara T.S., Ristić A., Sade L.E., Schirmer H., Schüpke S., Sillesen H., Skulstad H., Torracca L., Tutarel O., Van Der Meer P., Wojakowski W., Zacharowski K. 2022 ESC Guidelines on cardiovascular assessment and management of patients undergoing non-cardiac surgery. Eur Heart J. 2022;43(39):3826-3924. PMID: 36017553. https://doi.org/10.1093/eurheartj/ehad270
  6. Monnet X., Marik P.E., Teboul J.L. Prediction of fluid responsiveness: an update. Ann Intensive Care. 2016;6(1):111. PMID: 27858374; PMCID: PMC5114218. https://doi.org/10.1186/s13613-016-0216-7
  7. Saugel B., Vincent J.L. Cardiac output monitoring: How to choose the optimal method for the individual patient. Curr Opin Crit Care. 2018;24(3):165172. PMID: 29621027. https://doi.org/10.1097/MCC.0000000000000492
  8. Hasanin A. Fluid responsiveness in acute circulatory failure. J Intensive Care. 2015;3:50. PMID: 26594361; PMCID: PMC4653888. https://doi.org/10.1186/s40560-015-0117-0
  9. Паромов К.В., Волков Д.А., Киров М.Ю. Восприимчивость к инфузионной нагрузке на фоне регионарной анестезии после коронарного шунтирования на работающем сердце. Общая реаниматология. 2023;19(5):31-38. https://doi.org/10.15360/1813-9779-2023-5-2352 Paromov K. V., Volkov D.A., Kirov M.Y. Responsiveness to Infusion Load under Regional Anesthesia after Off-Pump Coronary Artery Bypass Graft Surgery. General Reanimatology. 2023;19(5):31-38. (In Russ.) https://doi.org/10.15360/1813-9779-2023-5-2352
  10. Monnet X., Teboul J.L. Passive leg raising: five rules, not a drop of fluid! Crit Care. 2015;19(1):18. PMID: 25658678; PMCID: PMC4293822. https://doi.org/10.1186/s13054-014-0708-5
  11. Monnet X., Shi R., Teboul J.L. Prediction of fluid responsiveness. What’s new? Ann Intensive Care. 2022;12(1):46. PMID: 35633423; PMCID: PMC9148319. https://doi.org/10.1186/s13613-022-01022-8
  12. Hutton B., Salanti G., Caldwell D.M., Chaimani A., Schmid C.H., Cameron C., Ioannidis J.P., Straus S., Thorlund K., Jansen J.P., Mulrow C., Catalá-López F., Gøtzsche P.C., Dickersin K., Boutron I., Altman D.G., Moher D. The PRISMA extension statement for reporting of systematic reviews incorporating network metaanalyses of health care interventions: checklist and explanations. Ann Intern Med. 2015;162(11):777-84. PMID: 26030634. https://doi.org/10.7326/M14-2385
  13. Higgins J.P.T., Green S. Cochrane Handbook for Systematic Reviews of Interventions | Cochrane Training. Handbook. https://training.cochrane.org/handbook [accessed 11 ноябрь 2024 г.].
  14. Literature Map Software for Lit Reviews & Research | Litmaps. 15. Luo D., Wan X., Liu J., Tong T. Optimally estimating the sample mean from the sample size, median, mid-range, and/or midquartile range. Stat Methods Med Res. 2018;27(6):1785-1805. PMID: 27683581. https://doi.org/10.1177/0962280216669183
  15. Wan X., Wang W., Liu J., Tong T. Estimating the sample mean and standard deviation from the sample size, median, range and/or interquartile range. BMC Med Res Methodol. 2014;14:135. PMID: 25524443; PMCID: PMC4383202. https://doi.org/10.1186/1471-2288-14-135
  16. Nikolakopoulou A., Higgins J.P.T., Papakonstantinou T., Chaimani A., Giovane C. Del., Egger M., Salanti G. Cinema: An approach for assessing confidence in the results of a network meta-analysis. PLoS Med. 2020;17(4):e1003082. PMID: 32243458. https://doi.org/10.1371/JOURNAL.PMED.1003082
  17. Papakonstantinou T., Nikolakopoulou A., Higgins J.P.T., Egger M., Salanti G. CINeMA: Software for semiautomated assessment of the confidence in the results of network meta-analysis. Campbell Syst Rev. 2020;16(1):e1080. PMID: 37131978; PMCID: PMC8356302. https://doi.org/10.1002/cl2.1080
  18. Chiocchia V., Nikolakopoulou A., Higgins J.P.T., Page M.J., Papakonstantinou T., Cipriani A., Furukawa T.A., Siontis G.C.M., Egger M., Salanti G. ROB-MEN: a tool to assess risk of bias due to missing evidence in network meta-analysis. BMC Med.2021;19(1):304. PMID: 34809639; PMCID: PMC8609747. https://doi.org/10.1186/s12916-021-02166-3
  19. Owen R.K., Bradbury N., Xin Y., Cooper N., Sutton A. MetaInsight:An interactive web-based tool for analyzing, interrogating, and visualizing network meta-analyses using R-shiny and netmeta. Res Synth Methods. 2019;10(4):569-581. PMID: 31349391; PMCID: PMC6973101. https://doi.org/10.1002/jrsm.1373
  20. Nevill C.R., Cooper N.J., Sutton A.J. A multifaceted graphical display, including treatment ranking, was developed to aid interpretation of network meta-analysis. J Clin Epidemiol. 2023;157:83-91. PMID: 36870376. https://doi.org/10.1016/j.jclinepi.2023.02.016
  21. Whiting P.F., Rutjes A.W., Westwood M.E., Mallett S., Deeks J.J., Reitsma J.B., Leeflang M.M., Sterne J.A., Bossuyt P.M.; QUADAS-2 Group. QUADAS-2: a revised tool for the quality assessment of diagnostic accuracy studies. Ann Intern Med. 2011;155(8):529-36. PMID: 22007046. https://doi.org/10.7326/0003-4819-155-8-201110180-00009
  22. Elsayed A.I., Selim K.A., Zaghla H.E., Mowafy H.E., Fakher M.A. Comparison of changes in PPV using a tidal volume challenge with a passive leg raising test to predict fluid responsiveness in patients ventilated using low tidal volume. Indian J Crit Care Med. 2021;25(6):685-690. PMID: 34316150; PMCID: PMC8286417. https://doi.org/10.5005/jp-journals-10071-23875
  23. Si X., Cao D.Y., Chen J., Wu J.F., Liu Z.M., Xu H.L., Chen M.Y., Liu Y.J., Guan X.D. Effect of Systolic Cardiac Function on Passive Leg Raising for Predicting Fluid Responsiveness: A Prospective Observational Study. Chin Med J (Engl). 2018;131(3):253-261. PMID: 29363638; PMCID: PMC5798044. https://doi.org/10.4103/0366-6999.223841
  24. Monge García M.I., Gil Cano A., Gracia Romero M., Monterroso Pintado R., Pérez Madueño V., Díaz Monrové J.C. Non-invasive assessment of fluid responsiveness by changes in partial end-tidal CO2 pressure during a passive leg-raising maneuver. Ann Intensive Care. 2012;2:9. PMID: 22449292; PMCID: PMC3327636. https://doi.org/10.1186/2110-5820-2-9
  25. Monnet X., Bataille A., Magalhaes E., Barrois J., Le Corre M., Gosset C., Guerin L., Richard C., Teboul J.L. End-tidal carbon dioxide is better than arterial pressure for predicting volume responsiveness by the passive leg raising test. Intensive Care Med. 2013;39(1):93-100. PMID: 22990869. https://doi.org/10.1007/s00134-012-2693-y
  26. Lakhal K., Ehrmann S., Runge I., Benzekri-Lefevre D., Legras A., Dequin P.F., Mercier E., Wolff M., Regnier B., Boulain T. Central venous pressure measurements improve the accuracy of leg raising-induced change in pulse pressure to predict fluid responsiveness. Intensive Care Med. 2010;36(6):940-8. PMID: 20111858. https://doi.org/10.1007/s00134-010-1755-2
  27. Wu J., Wang Z., Wang T., Yu T., Yuan J., Zhang Q., Lu W., Zhang X. Evaluation of the fluid responsiveness in patients with septic shock by ultrasound plus the passive leg raising test. J Surg Res. 2018;224:207-214. PMID: 29506842. https://doi.org/10.1016/j.jss.2017.12.014
  28. Zhao Z., Zhang Z., Lin Q., Shen L., Wang P., Zhang S., Xia Z., Li F., Xing Q., Zhu B. Changes in the Cardiac Index Induced by Unilateral Passive Leg Raising in Spontaneously Breathing Patients: A Novel Way to Assess Fluid Responsiveness. Front Med (Lausanne). 2022;9:862226. PMID: 35479952; PMCID: PMC9035785. https://doi.org/10.3389/fmed.2022.862226
  29. Taccheri T., Gavelli F., Teboul J.L., Shi R., Monnet X. Do changes in pulse pressure variation and inferior vena cava distensibility during passive leg raising and tidal volume challenge detect preload responsiveness in case of low tidal volume ventilation? Crit Care. 2021;25(1):110. PMID: 33736672; PMCID: PMC7972024. https://doi.org/10.1186/s13054-021-03515-7
  30. Xu J., Peng X., Pan C., Cai S., Zhang X., Xue M., Yang Y., Qiu H. Fluid responsiveness predicted by transcutaneous partial pressure of oxygen in patients with circulatory failure: a prospective study. Ann Intensive Care. 2017;7(1):56. PMID: 28536944; PMCID: PMC5442033. https://doi.org/10.1186/s13613-017-0279-0
  31. Marik P.E., Levitov A., Young A., Andrews L. The use of bioreactance and carotid Doppler to determine volume responsiveness and blood flow redistribution following passive leg raising in
  32. hemodynamically unstable patients. Chest. 2013;143(2):364-370. PMID: 22910834. https://doi.org/10.1378/chest.12-1274
  33. Saugel B., Kirsche S.V., Hapfelmeier A., Phillip V., Schultheiss C., Schmid R.M., Huber W. Prediction of fluid responsiveness in patients admitted to the medical intensive care unit. J Crit Care. 2013;28(4):537.e1-9. PMID: 23142517. https://doi.org/10.1016/j.jcrc.2012.10.008
  34. Monnet X., Osman D., Ridel C., Lamia B., Richard C., Teboul J.L. Predicting volume responsiveness by using the end-expiratory occlusion in mechanically ventilated intensive care unit patients. Crit Care Med. 2009;37(3):951-6. PMID: 19237902. https://doi.org/10.1097/CCM.0b013e3181968fe1
  35. Monnet X., Rienzo M., Osman D., Anguel N., Richard C., Pinsky M.R., Teboul J.L. Passive leg raising predicts fluid responsiveness in the critically ill. Crit Care Med. 2006;34(5):1402-7. PMID: 16540963. https://doi.org/10.1097/01.CCM.0000215453.11735.06
  36. Préau S., Saulnier F., Dewavrin F., Durocher A., Chagnon J.L. Passive leg raising is predictive of fluid responsiveness in spontaneously breathing patients with severe sepsis or acute pancreatitis. Crit Care Med. 2010;38(3):819-25. PMID: 20016380. https://doi.org/10.1097/CCM.0b013e3181c8fe7a
  37. Krige A., Bland M., Fanshawe T. Fluid responsiveness prediction using Vigileo FloTrac measured cardiac output changes during passive leg raise test. J Intensive Care. 2016;4:63. PMID: 27721980; PMCID: PMC5052799. https://doi.org/10.1186/s40560-016-0188-6
  38. Ma G.G., Tu G.W., Zheng J.L., Zhu D.M., Hao G.W., Hou J.Y., Su Y., Luo J.C., Liu K., Luo Z. Changes in Stroke Volume Variation Induced by Passive Leg Raising to Predict Fluid Responsiveness in Cardiac Surgical Patients With Protective Ventilation. J Cardiothorac Vasc Anesth. 2020;34(6):1526-1533. PMID: 31753747. https://doi.org/10.1053/j.jvca.2019.10.002
  39. Alvarado Sánchez J.I., Caicedo Ruiz J.D., Diaztagle Fernández J.J., Cruz Martínez L.E., Carreño Hernández F.L., Santacruz Herrera C.A., Ospina-Tascón G.A. Variables influencing the prediction of fluid responsiveness: a systematic review and meta-analysis. Crit Care. 2023;27(1):361. PMID: 37730622; PMCID: PMC10510289. https://doi.org/10.1186/s13054-023-04629-w
  40. Cherpanath T.G., Hirsch A., Geerts B.F., Lagrand W.K., Leeflang M.M., Schultz M.J., Groeneveld A.B. Predicting fluid responsiveness by passive leg raising: A systematic review and meta-analysis of 23 clinical trials. Crit Care Med. 2016;44(5):981-91. PMID: 26741579. https://doi.org/10.1097/CCM.0000000000001556
  41. Monnet X., Marik P., Teboul J.L. Passive leg raising for predicting fluid responsiveness: a systematic review and meta-analysis. Intensive Care Med. 2016;42(12):1935-1947. PMID: 26825952. https://doi.org/10.1007/s00134-015-4134-1
  42. Shahoud J.S., Sanvictores T., Aeddula N.R. Physiology, Arterial Pressure Regulation. 2023 Aug 28. In: StatPearls [Internet]. Treasure Island (FL): StatPearls Publishing; 2026 Jan–. PMID: 30860744.
  43. Lakhal K., Ehrmann S., Benzekri-Lefèvre D., Runge I., Legras A., Dequin P.F., Mercier E., Wolff M., Régnier B., Boulain T. Brachial cuff measurements of blood pressure during passive leg raising for fluid responsiveness prediction. Ann Fr Anesth Reanim. 2012;31(5):e67-72. PMID: 22464162. https://doi.org/10.1016/j.annfar.2012.01.032