Чек-лист PRISMA

PRISMA Checklist

Section and Topic Item # Checklist item Location where item is reported
TITLE  
Title 1 Identify the report as a systematic review Титульный лист
ABSTRACT  
Abstract 2 See the PRISMA 2020 for Abstracts checklist Аннотация
INTRODUCTION  
Rationale 3 Describe the rationale for the review in the context of existing knowledge Введение
Objectives 4 Provide an explicit statement of the objective(s) or question(s) the review addresses Введение
METHODS  
Eligibility criteria 5 Specify the inclusion and exclusion criteria for the review and how studies were grouped for the syntheses Критерии включения и отбор исследований
Information sources 6 Specify all databases, registers, websites, organisations, reference lists and other sources searched or consulted to identify studies. Specify the date when each source was last searched or consulted Стратегия поиска
Search strategy 7 Present the full search strategies for all databases, registers and websites, including any filters and limits used Стратегия поиска
Selection process 8 Specify the methods used to decide whether a study met the inclusion criteria of the review, including how many reviewers screened each record and each report retrieved, whether they worked independently, and if applicable, details of automation tools used in the process Критерии включения и отбор исследований
Data collection process 9 Specify the methods used to collect data from reports, including how many reviewers collected data from each report, whether they worked independently, any processes for obtaining or confirming data from study investigators, and if applicable, details of automation tools used in the process Извлечение данных и оценка исходов
Data items 10a List and define all outcomes for which data were sought. Specify whether all results that were compatible with each outcome domain in each study were sought (e.g. for all measures, time points, analyses), and if not, the methods used to decide which results to collect Извлечение данных и оценка исходов
10b List and define all other variables for which data were sought (e.g. participant and intervention characteristics, funding sources). Describe any assumptions made about any missing or unclear information Извлечение данных и оценка исходов
Study risk of bias assessment 11 Specify the methods used to assess risk of bias in the included studies, including details of the tool(s) used, how many reviewers assessed each study and whether they worked independently, and if applicable, details of automation tools used in the process Оценка риска систематической ошибки
Effect measures 12 Specify for each outcome the effect measure(s) (e.g. risk ratio, mean difference) used in the synthesis or presentation of results Извлечение данных и оценка исходов
Synthesis methods 13a Describe the processes used to decide which studies were eligible for each synthesis (e.g. tabulating the study intervention characteristics and comparing against the planned groups for each synthesis (item #5)) Статистический анализ
13b Describe any methods required to prepare the data for presentation or synthesis, such as handling of missing summary statistics, or data conversions Извлечение данных и оценка исходов
13c Describe any methods used to tabulate or visually display results of individual studies and syntheses Статистический анализ
13d Describe any methods used to synthesize results and provide a rationale for the choice(s). If meta-analysis was performed, describe the model(s), method(s) to identify the presence and extent of statistical heterogeneity, and software package(s) used Статистический анализ
13e Describe any methods used to explore possible causes of heterogeneity among study results (e.g. subgroup analysis, meta-regression) Статистический анализ
13f Describe any sensitivity analyses conducted to assess robustness of the synthesized results Статистический анализ
Reporting bias assessment 14 Describe any methods used to assess risk of bias due to missing results in a synthesis (arising from reporting biases) Оценка риска систематической ошибки
Certainty assessment 15 Describe any methods used to assess certainty (or confidence) in the body of evidence for an outcome Оценка риска систематической ошибки
RESULTS  
Study selection 16a Describe the results of the search and selection process, from the number of records identified in the search to the number of studies included in the review, ideally using a flow diagram Характеристика исследований
16b Cite studies that might appear to meet the inclusion criteria, but which were excluded, and explain why they were excluded Табл. Д2
Study characteristics 17 Cite each included study and present its characteristics Характеристика исследований; таблица Д3
Risk of bias in studies 18 Present assessments of risk of bias for each included study Табл. Д5
Results of individual studies 19 For all outcomes, present, for each study: (a) summary statistics for each group (where appropriate) and (b) an effect estimate and its precision (e.g. confidence/credible interval), ideally using structured tables or plots Рис. 2; табл. 2
Results of syntheses 20a For each synthesis, briefly summarise the characteristics and risk of bias among contributing studies Мета-анализ
20b Present results of all statistical syntheses conducted. If meta-analysis was done, present for each the summary estimate and its precision (e. g. confidence/credible interval) and measures of statistical heterogeneity. If comparing groups, describe the direction of the effect Мета-анализ
20c Present results of all investigations of possible causes of heterogeneity among study results Подгрупповой анализ; мета-регрессия
20d Present results of all sensitivity analyses conducted to assess the robustness of the synthesized results Рис. Д1
Reporting biases 21 Present assessments of risk of bias due to missing results (arising from reporting biases) for each synthesis assessed Табл. 3; рис. Д2–Д6
Certainty of evidence 22 Present assessments of certainty (or confidence) in the body of evidence for each outcome assessed Оценка риска систематической ошибки; табл. Д6
DISCUSSION  
Discussion 23a Provide a general interpretation of the results in the context of other evidence Обсуждение
23b Discuss any limitations of the evidence included in the review Обсуждение
23c Discuss any limitations of the review processes used Обсуждение
23d Discuss implications of the results for practice, policy, and future research Обсуждение
OTHER INFORMATION  
Registration and protocol 24a Provide registration information for the review, including register name and registration number, or state that the review was not registered Материалы и методы
24b Indicate where the review protocol can be accessed, or state that a protocol was not prepared Материалы и методы
24c Describe and explain any amendments to information provided at registration or in the protocol Материалы и методы
Support 25 Describe sources of financial or non-financial support for the review, and the role of the funders or sponsors in the review Мета-данные
Competing interests 26 Declare any competing interests of review authors Мета-данные
Availability of data, code and other materials 27 Report which of the following are publicly available and where they can be found: template data collection forms; data extracted from included studies; data used for all analyses; analytic code; any other materials used in the review Мета-данные
Таблица Д1. Чек-лист PRISMA
Table D1. PRISMA Checklist

Исключенные публикации с причинами для исключения

Excluded Publications with Reasons for Exclusion

Причина исключения

Исследование

Нет оценки ЦВД
  1. Xue Y.M., Zeng L.J., Chen D.W., et al. [Cephalic artery peak velocity variation during passive leg raising can predict fluid responsiveness in mechanically ventilated severe sepsis patients with spontaneous breathing]. Zhonghua Yi Xue Za Zhi. 2018; 98(31): 2476–80. DOI: 10.3760/cma.j.issn.0376-2491.2018.31.005
  2. Yonis H., Bitker L., Aublanc M., et al. Change in cardiac output during Trendelenburg maneuver is a reliable predictor of fluid responsiveness in patients with acute respiratory distress syndrome in the prone position under protective ventilation. Crit Care. 2017; 21(1): 295. DOI: 10.1186/s13054-017-1881-0
  3. Kim N., Shim J.-K., Choi H.G., et al. Comparison of positive end-expiratory pressure-induced increase in central venous pressure and passive leg raising to predict fluid responsiveness in patients with atrial fibrillation. Br J Anaesth. 2016; 116(3): 350–6. DOI: 10.1093/bja/aev359
  4. Desebbe O., Vallier S., Gergelé L., et al. Diagnostic accuracy of the peripheral venous pressure variation induced by an alveolar recruitment maneuver to predict fluid responsiveness during High-risk abdominal surgery. BMC Anesthesiol. 2023; 23(1): 249. DOI: 10.1186/s12871-023-02194-x
  5. Wilkman E., Kuitunen A., Pettilä V., et al. Fluid responsiveness predicted by elevation of PEEP in patients with septic shock. Acta Anaesthesiol Scand. 2014; 58(1): 27–35. DOI: 10.1111/aas.12229
  6. Huang H.-B., Xu B., Liu G.-Y., et al. N-terminal pro-B-type natriuretic peptide for predicting fluid challenge in patients with septic shock. Ann Transl Med. 2019; 7(12): 264. DOI: 10.21037/atm.2019.05.60
  7. Dong Z.-Z., Fang Q., Zheng X., et al. Passive leg raising as an indicator of fluid responsiveness in patients with severe sepsis. World J Emerg Med. 2012; 3(3): 191–6. DOI: 10.5847/wjem.j.issn.1920-8642.2012.03.006
  8. Giraud R., Siegenthaler N., Gayet-Ageron A., et al. ScvO(2) as a marker to define fluid responsiveness. J Trauma. 2011; 70(4): 802–7. DOI: 10.1097/TA.0b013e3181e7d649
  9. Vallier S., Bouchet J.-B., Desebbe O., et al. Slope analysis for the prediction of fluid responsiveness by a stepwise PEEP elevation recruitment maneuver in mechanically ventilated patients. BMC Anesthesiol. 2022; 22(1): 4. DOI: 10.1186/s12871-021-01544-x
  10. Cherpanath T.G. V., Geerts B.F., Maas J.J., et al. Ventilator-induced central venous pressure variation can predict fluid responsiveness in post-operative cardiac surgery patients. Acta Anaesthesiol Scand. 2016; 60(10): 1395–403. DOI: 10.1111/aas.12811

Несоответствующий золотой стандарт (не тест с инфузионной нагрузкой)
  1. Pişkin Ö., Öz İ.İ. Accuracy of pleth variability index compared with inferior vena cava diameter to predict fluid responsiveness in mechanically ventilated patients. Medicine (Baltimore). 2017; 96(47): e8889. DOI: 10.1097/MD.0000000000008889
  2. Broch O., Bein B., Gruenewald M., et al. Accuracy of the pleth variability index to predict fluid responsiveness depends on the perfusion index. Acta Anaesthesiol Scand. 2011; 55(6): 686–93. DOI: 10.1111/j.1399-6576.2011.02435.x
  3. Hofer C.K., Senn A., Weibel L., et al. Assessment of stroke volume variation for prediction of fluid responsiveness using the modified FloTrac and PiCCOplus system. Crit Care. 2008; 12(3): R82. DOI: 10.1186/cc6933
  4. Geerts B.F., Aarts L.P.H.J., Groeneveld A.B., et al. Predicting cardiac output responses to passive leg raising by a PEEP-induced increase in central venous pressure, in cardiac surgery patients. Br J Anaesth. 2011; 107(2): 150–6. DOI: 10.1093/bja/aer125
  5. Cannesson M., Slieker J., Desebbe O., et al. Prediction of fluid responsiveness using respiratory variations in left ventricular stroke area by transoesophageal echocardiographic automated border detection in mechanically ventilated patients. Crit Care. 2006; 10(6): R171. DOI: 10.1186/cc5123
  6. Desebbe O., Boucau C., Farhat F., et al. The ability of pleth variability index to predict the hemodynamic effects of positive end-expiratory pressure in mechanically ventilated patients under general anesthesia. Anesth Analg. 2010; 110(3): 792–8. DOI: 10.1213/ANE.0b013e3181cd6d06
  7. Broch O., Renner J., Gruenewald M., et al. Variation of left ventricular outflow tract velocity and global end-diastolic volume index reliably predict fluid responsiveness in cardiac surgery patients. J Crit Care. 2012; 27(3): 325.e7–13. DOI: 10.1016/j.jcrc.2011.07.073

Некардиальные параметры теста с инфузионной нагрузкой
  1. Ismail M.T., El-Iraky A.A., Ibrahim E.E.-D.A., et al. Comparison of inferior vena cava collapsibility and central venous pressure in assessing volume status in shocked patients. African J Emerg Med Rev Africaine La Med d’urgence. 2022; 12(3): 165–71. DOI: 10.1016/j.afjem.2022.04.005
  2. Westphal G.A., Silva E., Gonçalves A.R., et al. Pulse oximetry wave variation as a noninvasive tool to assess volume status in cardiac surgery. Clinics (Sao Paulo). 2009; 64(4): 337–43. DOI: 10.1590/s1807-59322009000400012

Ретроспективное исследование
  1. Keller G., Sinavsky K., Desebbe O., et al. Combination of continuous pulse pressure variation monitoring and cardiac filling pressure to predict fluid responsiveness. J Clin Monit Comput. 2012; 26(6): 401–5. DOI: 10.1007/s10877-012-9365-x
  2. Velissaris D., Pierrakos C., Scolletta S., et al. High mixed venous oxygen saturation levels do not exclude fluid responsiveness in critically ill septic patients. Crit Care. 2011; 15(4): R177. DOI: 10.1186/cc10326
Таблица Д2. Исключенные публикации с причинами для исключения
Table D2. Excluded Publications with Reasons for Exclusion

 

Дополнительные характеристики и исходы

Additional Characteristics and Outcomes

№ Исследование Размер выборки (кол-во набл.) Кол-во пациентов Когорта пациентов Параметр ЗС Раствор для инфузии Тест: точка отсечения Объем инфузии Тип ЗС Метод определения ЗС: точка отсечения Средний возраст Мужчины, % ИМТ, кг/м2 APACHE II, средн. МВ, N Тип дыхания AUROC (mean ± SD) Se Sp
1 Albano BBP (2021) [1] 101 101 К. ОРИТ ∆УО или ∆СИ (%) Крист. 6,0 8 мл/кг FC ТПТД 0,15 55,8 74,3 ND ND 101 МВ 0,40 ± 0,56 0,83 0,51
2 Angappan S (2015) [2] 45 45 Шок ∆СИ (%) Колл. ND 500 FC АКПВ 0,15 45,2 80,0 ND ND 45 МВ 0,56 ± 0,50 ND ND
3 Baker AK (2013) [3] 25 25 Шок ∆УО (%) Колл. ND 500 FC ЭхоКГ 0,15 60,3 68,0 ND ND 25 МВ 0,66 ± 0,55 ND ND
4 Barbier C (2004) [4] 20 20 Шок ∆СИ (%) Колл. 12 7 мл/кг FC ЭхоКГ 0,15 63,0 75,0 ND ND 20 МВ 0,57 ± 0,57 0,90 0,30
5 Berg JM (2021) [5] 56 56 КХ ∆ИУО (%) Крист. ND 5 мл/кг FC ТПТД 0,15 ND ND ND ND 56 МВ 0,48 ± 0,97 ND ND
6 Berkenstadt H (2001) [6] 140 15 НКХ ∆УО (%) Колл. ND 100 Mini-FC ТПТД 0,05 55,0 40,0 ND ND 140 МВ 0,49 ± 0,58 ND ND
7 Biais M (2008) [7] 35 35 Нек. ОРИТ ∆СВ (%) Колл. 3,0 20 мл* ИМТ FC ЭхоКГ 0,15 51,0 65,7 23,0 ND 35 МВ 0,64 ± 0,49 ND ND
8 Botros JM (2023) [8] 48 48 НКХ ∆ИУО (%) Крист. ND 6 мл/кг FC ЭхоКГ 0,1 53,1 21,0 26,2 ND 48 МВ 0,41 ± 0,59 ND ND
9 Bubenek-Turconi ŞI (2019) [9] 266 40 КХ ∆СИ (%) Колл. ND 500 FC АКПВ 0,11 63,0 77,5 ND ND 266 МВ 0,53 ± 0,54 0,55 0,61
10 Cannesson M (2007) [10] 25 25 КХ ∆СИ (%) Колл. ND 500 FC ТПТД 0,15 69,0 72,0 ND ND 25 МВ 0,57 ± 0,12 ND ND
11 Cannesson M (2008)-1 [11] 25 25 КХ ∆СИ (%) Колл. 3,5 500 FC ТПТД 0,15 65,0 60,0 ND ND 25 МВ 0,75 ± 0,11 0,77 0,63
12 Cannesson M (2008)-2 [12] 25 25 КХ ∆СИ (%) Колл. 12,5 500 FC ТПТД 0,15 65,0 64,0 ND ND 25 МВ 0,42 ± 0,57 0,44 0,78
13 Cannesson M (2009) [13] 25 25 КХ ∆СИ (%) Колл. ND 500 FC ТПТД 0,15 67,0 80,0 ND ND 25 МВ 0,53 ± 0,12 ND ND
14 Cannesson M (2011) [14] 413 413 НКХ ∆СВ (%) Колл. ND 500 FC ТПТД, АКПВ или ЭхоКГ 0,15 65,0 74,3 ND ND 413 МВ 0,57 ± 0,26 ND ND
15 Cecconi M (2012) [15] 31 31 Нек. ОРИТ ∆УО (%) Колл. ND 250 Mini-FC АКПВ 0,15 65,0 74,2 ND ND 31 МВ 0,62 ± 0,56 ND ND
16 de Oliveira OH (2016) [16] 20 20 Нек. ОРИТ ∆ИЛСП (%) Крист. 10,0 500 FC ЭхоКГ 0,15 50,0 40,0 ND ND 20 МВ 0,65 ± 0,13 0,55 0,78
17 de Waal EE (2009) [17] 22 22 КХ ∆ИУО (%) Колл. ND 10 мл/кг FC ТПТД 0,12 66,0 81,8 26,3 ND 22 МВ 0,64 ± 0,55 ND ND
18 Dépret F (2018) [18] 28 28 Шок ∆СИ (%) Крист. ND 500 FC ТПТД 0,15 66,5 ND ND ND 28 МВ 0,51 ± 0,12 ND ND
19 Desgranges FP (2011) [19] 28 28 КХ ∆СИ (%) Колл. 8,0 500 FC ТПТД 0,15 62,0 82,1 ND ND 28 МВ 0,58 ± 0,65 0,58 0,33
20 Fu Q (2012) [20] 51 51 НКХ ∆ИУО (%) Колл. 7,5 8 мл/кг FC АКПВ 0,1 48,7 51,0 ND ND 51 МВ 0,61 ± 0,59 0,61 0,64
21 Fu Q (2014) [21] 30 30 ОВ ∆СИ (%) Колл. ND 8 мл/кг FC АКПВ 0,1 52,4 70,0 ND ND 30 МВ 0,56 ± 0,58 0,93 0,44
22 Geerts BF (2011) [22] 24 24 К. ОРИТ ∆СВ (%) Колл. 9,0 500 FC ТПТД 0,1 64,0 79,12 ND ND 24 МВ 0,69 ± 0,48 0,71 0,57
23 Giraud R (2018) [23] 20 20 Нек. ОРИТ ∆СВ (%) Крист. ND 500 FC ТПТД 0,15 62,2 45,0 ND ND 20 МВ 0,54 ± 0,56 ND ND
24 Guarracino F (2014) [24] 50 50 Шок ∆СИ (%) Крист. 8,0 7 мл/кг FC АКПВ 0,15 66,3 64,0 ND ND 50 МВ 0,68 ± 0,53 0,33 1,00
25 Haas S (2012) [25] 22 18 К. ОРИТ ∆СИ (%) Колл. ND 4 мл/кг Mini-FC ТПТД 0,1 67,5 72,2 ND ND 22 МВ 0,81 ± 0,43 ND ND
26 Hahn RG (2016) [26] 80 80 НКХ ∆ИУО (%) Колл. 6,5 9 мл/кг FC АКПВ 0,1 56,0 65,0 ND ND 80 МВ 0,74 ± 0,49 0,68 0,75
27 Hikasa Y (2023) [27] 61 24 НКХ ∆ИУО (%) Колл. 19,0 200 Mini-FC АКПВ 0,15 66,0 75,0 22,3 ND 61 МВ 0,58 ± 0,64 0,25 0,95
28 Hofer CK (2005) [28] 35 35 КХ ∆ИУО (%) Колл. ND 10 мл/кг FC ТПТД 0,25 62,0 ND 27,0 ND 35 МВ 0,54 ± 0,57 ND ND
29 Hofer CK (2018) [29] 34 34 К. ОРИТ ∆УО (%) Колл. ND 500 FC ТПТД 0,15 65,8 82,4 27,9 ND 34 МВ 0,55 ± 0,60 ND ND
30 Høiseth LØ (2011) [30] 34 25 НКХ ∆УО (%) Колл. ND 250 Mini-FC ЭхоКГ 0,15 61,0 48,0 ND ND 34 МВ 0,58 ± 0,50 ND ND
31 Huang CC (2008) [31] 22 22 Нек. ОРИТ ∆СИ (%) Колл. ND 500 FC АКПВ 0,15 54,0 72,7 ND 21,8 22 МВ 0,43 ± 0,38 0,55 0,44
32 Ibarra-Estrada MÁ (2015) [32] 59 19 Шок ∆ИУО (%) Крист. ND 7 мл/кг FC ЭхоКГ 0,15 49,2 62,7 ND ND 59 МВ 0,52 ± 0,52 ND ND
33 Ikeda K (2016) [33] 75 35 К. ОРИТ ∆СИ (%) Смеш. ND 574 (SD: 361) Non-classified ТПТД 0,15 ND ND ND ND 75 МВ 0,49 ± 0,67 ND ND
34 Ishihara H (2013) [34] 43 43 Нек. ОРИТ ∆СИ (%) Колл. 6,5 250 Mini-FC ТПТД 0,15 65,0 97,7 ND ND 43 МВ 0,69 ± 0,54 0,60 0,74
35 Kim SY (2013) [35] 66 66 КХ ∆ИУО (%) Колл. ND 500 FC АКПВ 0,12 ND 74,2 ND ND 66 МВ 0,53 ± 0,57 ND ND
36 Kramer A (2004) [36] 21 21 К. ОРИТ ∆СВ (%) Аутокровь ND 500 FC ТПТД 0,12 64,7 71,4 ND ND 21 МВ 0,49 ± 0,69 ND ND
37 Kumar N (2021) [37] 50 50 Шок ∆СИ (%) Крист. 7,5 10 мл/кг FC АКПВ 0,1 44,9 64,0 ND ND 50 МВ 0,56 ± 0,55 0,63 0,50
38 Kurtz P (2014) [38] 57 10 Нек. ОРИТ ∆СИ (%) Колл. ND 250 Mini-FC АКПВ 0,1 52,7 40,0 ND 25,0 57 МВ 0,61 ± 0,62 ND ND
39 Lakhal K (2010) [39] 102 102 Шок ∆СВ (%) Колл. ND 500 FC ТПТД 0,1 59,0 70,6 ND ND 102 МВ 0,61 ± 0,53 ND ND
40 Lakhal K (2011) [40] 65 65 Шок ∆СВ (%) Колл. ND 500 FC ТПТД 0,1 59,0 69,2 ND ND 65 МВ 0,63 ± 0,50 ND ND
41 Lanspa MJ (2012) [41] 34 25 Шок ∆СИ (%) Крист. или колл. 8,0 10 мл/кг FC ЭхоКГ 0,15 62,1 32,4 ND 20,0 19 Смешанное 0,73 ± 0,59 ND ND
42 Lee JH (2007) [42] 20 20 НКХ ∆ИУО (%) Колл. ND 7 мл/кг FC ЭхоКГ 0,1 49,0 40,0 24,0 ND 20 МВ 0,54 ± 0,13 ND ND
43 Lee JH (2011) [43] 35 35 КХ ∆СИ (%) Колл. ND 10 мл/кг FC ТПТД 0,15 63,0 57,1 25,0 ND 35 МВ 0,70 ± 0,47 ND ND
44 Li J (2012) [44] 157 48 НКХ ∆УО (%) Крист. ND 200 Mini-FC АКПВ 0,1 44,0 58,3 ND ND 157 МВ 0,54 ± 0,06 ND ND
45 Lu N (2017) [45] 49 49 Шок ∆СИ (%) Крист. 6,5 200 Mini-FC ТПТД 0,1 55,4 67,3 24,9 26,8 49 МВ 0,68 ± 0,59 0,65 0,70
46 Ma GG (2018) [46] 70 70 К. ОРИТ ∆УО (%) Колл. 11 500 FC АКПВ 0,15 61,0 62,9 22,0 9,0 70 МВ 0,70 ± 0,48 0,60 0,77
47 Ma Q (2022) [47] 56 56 Нек. ОРИТ ∆СВ (%) Крист. 4 5 мл/кг FC ЭхоКГ 0,15 57,4 55,4 ND ND 0 Спонтанное дыхание 0,64 ± 0,49 0,82 0,47
48 Mallat J (2022) [48] 270 270 Шок ∆СИ (%) Крист. ND 500 FC ЭхоКГ или ТПТД 0,15 67,0 63,0 27,5 ND 270 МВ 0,59 ± 0,63 ND ND
49 Mohamed ZU (2017) [49] 30 30 Шок ∆СИ (%) Колл. ND 500 FC ТПТД 0,15 57,5 40,0 ND ND 30 МВ 0,75 ± 0,46 ND ND
50 Monge García MI (2008) [50] 30 30 Нек. ОРИТ ∆ИУО (%) Колл. ND 500 FC АКПВ 0,15 60,0 63,0 ND 11,0 0 Спонтанное дыхание 0,51 ± 0,11 ND ND
51 Monge García MI (2009) [51] 38 38 Шок ∆ИУО (%) Колл. ND 500 FC АКПВ 0,15 56,2 50,0 ND ND 38 МВ 0,64 ± 0,09 ND ND
52 Moretti R (2010) [52] 29 29 Нек. ОРИТ ∆СИ (%) Колл. ND 7 мл/кг FC ТПТД 0,15 51,8 55,2 ND ND 29 МВ 0,67 ± 0,47 ND ND
53 Muller L (2008) [53] 35 35 Нек. ОРИТ ∆ИУО (%) Колл. 9,0 250 or 500 Non-classified ТПТД 0,15 64,6 60,0 ND 20,0 35 МВ 0,68 ± 0,48 0,61 0,82
54 Muller L (2009) [54] 33 33 Шок ∆ИУО (%) Смеш. 7,0 250 or 500 Non-classified ТПТД 0,15 71,4 63,6 ND 23,3 33 МВ 0,77 ± 0,10 0,54 1,00
55 Muller L (2010) [55] 57 57 Шок ∆ИУО (%) Смеш. 9,0 250 or 500 Non-classified ТПТД 0,15 70,3 68,4 ND 22,9 57 МВ 0,76 ± 0,47 0,68 0,81
56 Muller L (2011) [56] 39 39 Шок ∆ИЛСП (%) Колл. ND 500 FC ЭхоКГ 0,15 66,0 76,9 ND 19,0 39 МВ 0,61 ± 0,59 ND ND
57 Myatra SN (2017) [57] 30 20 Шок ∆СИ (%) Крист. ND 7 мл/кг FC ТПТД 0,15 53,0 50,0 ND 24,0 30 МВ 0,48 ± 0,56 ND ND
58 Oliveira-Costa CD (2012) [58] 37 37 Шок ∆СИ (%) Крист. ND 1000 FC ТПТД 0,15 54,0 54,0 ND 28,0 37 МВ 0,57 ± 0,57 ND ND
59 Pei S (2014) [59] 32 32 НКХ ∆ИУО (%) Колл. 4,5 250 Mini-FC АКПВ 0,1 54,8 56,25 23,0 ND 32 МВ 0,73 ± 0,45 0,46 1,00
60 Peng S (2013) [60] 54 32 Шок ∆УО (%) Крист. ND 250 Mini-FC АКПВ 0,1 67,0 62,5 ND 21,0 54 МВ 0,59 ± 0,57 0,60 0,63
61 Preisman S (2005) [61] 70 18 К. ОРИТ ∆ИУО (%) Колл. ND 250 Mini-FC АКПВ 0,15 66,2 88,9 ND ND 70 МВ 0,61 ± 0,59 ND ND
62 Reuter DA (2002) [62] 20 20 К. ОРИТ ∆ИУО (%) Колл. ND 20 мл* ИМТ FC ТПТД 0,15 ND ND ND ND 20 МВ 0,42 ± 0,61 ND ND
63 Reuter DA (2003) [63] 12 12 К. ОРИТ ∆ИУО (%) Колл. 6,0 10 мл* ИМТ Non-classified ТПТД 0,05 61,0 ND ND ND 12 МВ 0,71 ± 0,33 0,50 0,90
64 Roy S (2013) [64] 37 37 КХ ∆ИУО (%) Колл. ND 500 FC ТПТД 0,15 60,2 81,0 ND ND 37 МВ 0,61 ± 0,52 ND ND
65 Saugel B (2013) [65] 24 24 Нек. ОРИТ ∆СИ (%) Крист. 12,0 7 мл/кг FC ТПТД 0,15 58,8 71,0 ND ND 5 Смешанное 0,63 ± 0,45 0,86 0,41
66 Shim JK (2014) [66] 34 34 КХ ∆ИУО (%) Колл. ND 6 мл/кг FC ТПТД 0,12 59,0 94,1 24,3 ND 34 МВ 0,58 ± 0,50 ND ND
67 Shin YH (2011) [67] 33 33 НКХ ∆СИ (%) Колл. ND 10 мл/кг FC ТПТД 0,15 53,5 87,9 24,4 ND 33 МВ 0,58 ± 0,50 ND ND
68 Soliman RA (2015) [68] 25 25 Шок ∆СИ (%) Колл. ND 500 FC ЭхоКГ 0,15 52,8 60,0 ND ND 25 МВ 0,59 ± 0,26 ND ND
69 Song Y (2014) [69] 40 40 КХ ∆ИУО (%) Колл. ND 6 мл/кг FC АКПВ 0,15 64,6 67,5 25,2 ND 40 МВ 0,68 ± 0,53 ND ND
70 Suehiro K (2012) [70] 80 80 Нек. ОРИТ ∆СИ (%) Крист. ND 500 FC АКПВ 0,15 58,6 65,0 ND ND 80 МВ 0,56 ± 0,48 ND ND
71 Taccheri T (2021) [71] 30 30 Нек. ОРИТ ∆СИ (%) Крист. ND 500 FC ТПТД 0,1 66,5 76,7 ND ND 30 МВ 0,56 ± 0,11 ND ND
72 Thiel SW (2009) [72] 102 89 Нек. ОРИТ ∆УО (%) Крист. ND 500 FC ЭхоКГ 0,15 59,4 56,9 31,0 18,5 67 Смешанное 0,52 ± 0,08 ND ND
73 Trof RJ (2011) [73] 12 12 К. ОРИТ ∆ИУО (%) Колл. ND 200–1800 Non-classified ТПТД 0,1 66,0 75,0 ND 9,0 ND ND 0,89 ± 0,30 ND ND
74 Vistisen ST (2009) [74] 23 30 К. ОРИТ ∆СИ (%) Колл. 8,0 500 FC ТПТД 0,15 71,0 ND ND ND 23 МВ 0,68 ± 0,56 0,35 1,00
75 Vistisen ST (2016) [75] 30 23 К. ОРИТ ∆УО (%) Смеш. ND 500 FC АКПВ 0,15 66,5 76,7 ND ND 27 Смешанное 0,54 ± 0,58 1,00 0,26
76 Wang Y (2018) [76] 18 18 ОВ ∆СИ (%) Колл. 11,0 7 мл/кг FC ТПТД 0,15 54,1 55,56 ND ND 18 МВ 0,60 ± 0,57 0,33 1,00
77 Wyffels PA (2007) [77] 32 32 К. ОРИТ ∆СИ (%) Колл. ND 500 FC ТПТД 0,15 66,0 68,75 ND ND 32 МВ 0,60 ± 0,87 ND ND
78 Xu B (2016) [78] 40 40 Шок ∆СИ (%) Смеш. 11,0 500 FC ТПТД 0,1 60,0 75,0 ND 27,0 37 Смешанное 0,56 ± 0,56 0,56 0,55
79 Xu LY (2019) [79] 75 75 КХ ∆ИЛСП (%) Крист. 7,0 6 мл/кг FC ЭхоКГ 0,15 63,5 82,67 24,5 ND 75 МВ 0,49 ± 0,57 0,57 0,45
80 Xu Y (2022) [80] 76 76 Нек. ОРИТ ∆СИ (%) Крист. 9,0 250 Mini-FC ТПТД 0,15 55,0 50,0 25,0 26,0 76 МВ 0,68 ± 0,48 0,48 0,80
81 Yazigi A (2012) [81] 60 60 К. ОРИТ ∆ИУО (%) Колл. ND 7 мл/кг FC ТПТД 0,15 75,3 63,3 ND ND 60 МВ 0,43 ± 0,58 ND ND
82 Zhang X (2016) [82] 40 40 НКХ ∆ИУО (%) Колл. 6,5 7 мл/кг FC АКПВ 0,15 46,0 60,0 ND ND 40 МВ 0,63 ± 0,59 0,89 0,36
83 Zhao F (2015) [83] 25 25 НКХ ∆ИУО (%) Колл. 7,0 250 Mini-FC АКПВ 0,1 54,8 60,0 23,0 ND 25 МВ 0,52 ± 0,50 0,50 0,62
84 Zimmermann M (2010) [84] 20 20 НКХ ∆ИУО (%) Колл. 10,5 7 мл/кг FC АКПВ 0,15 53,0 65,0 26,1 ND 20 МВ 0,55 ± 0,60 0,66 0,40
Таблица Д3. Дополнительные характеристики и исходы Примечание:  APACHE II — acute physiology and chronic health evaluation II; AUROC — площадь под ROC-кривой; FC — fluid challenge (тест с инфузионной нагрузкой); mini-FC — тест с малой инфузионной нагрузкой; МВ — механическая вентиляция; ND — нет данных (no data); Se — sensitivity (чувствительность); SD — стандартное отклонение (standard deviation); Sp — specificity (специфичность); АКПВ — анализ контура пульсовой волны; ЗС — золотой стандарт; ИМТ — индекс массы тела; К. ОРИТ — кардиологическое отделение реанимации и интенсивной терапии; шок — пациенты с шоком; КХ — кардиохирургия; НКХ — некардиологическая хирургия; Нек. ОРИТ — некардиологическое ОРИТ; ОВ — однолегочная вентиляция; ТПТД — транспульмональная термодилюция; ЭхоКГ — эхокардиография; ∆ИЛСП — изменение интеграла линейной скорости потока; крист. — кристаллоидный; колл. — коллоидный; смеш. — смешанный; ∆ИУО — изменение индекса ударного объема; ∆СВ — изменение сердечного выброса; ∆СИ — изменение сердечного индекса; ∆УО — изменение ударного объема.
Table D3. Additional Characteristics and Outcomes Note: APACHE II — acute physiology and chronic health evaluation II; AUROC — area under ROC curve; FC — fluid challenge; mini-FC — mini-fluid challenge; МВ — Mechanical Ventilation; ND — no data; SD —standard deviation; Se — sensitivity; Sp — specificity; АКПВ — pulse pressure waveform analysis; ЗС — gold standard; ИМТ — body mass index; К. ОРИТ cardiac intensive care unit; шок — patients with shock; КХ — cardiac surgery; НКХ — non-cardiac surgery; Нек. ОРИТ — non-cardiac ICU; ОВ — one-lung ventilation; ТПТД — transpulmonary thermodilution; ЭхоКГ — echocardiography; ∆ИЛСП — change in velocity-time integral; крист. — crystalloids; колл. — colloids; смеш. — mixed; ∆ИУО — change in stroke volume index; ∆СВ — change in cardiac output; ∆СИ — change in cardiac index; ∆УО — change in stroke volume.

 

Метод последовательного исключения: средние значения AUROC с 95% доверительным интервалом. Линия тренда на уровне 0,596.

Leave-One-Out Method: Mean AUROC Values with 95% Confidence Intervals. The trend line is at 0.596

Рис. Д1. Метод последовательного исключения: средние значения AUROC с 95% доверительным интервалом. Линия тренда на уровне 0,596. Fig. D1. Leave-One-Out Method: Mean AUROC Values with 95% Confidence Intervals. The trend line is at 0.596

 

Однофакторная мета-регрессия

Univariate Meta-Regression

Параметр Исследования, N Однофакторный анализ
Коэффициент SE p-value
Средний возраст, годы 80 0,002 0,002 0,129
Мужчины, % 77 –0,00026 0,001 0,757
ИМТ, кг/м2 20 –0,013 0,006 0,053
Таблица Д4. Однофакторная мета-регрессия SE — стандартная ошибка; ИМТ — индекс массы тела.
Table D4. Univariate Meta-Regression SE — standard error; ИМТ — Body mass index.

Мета-регрессия позволяет определить, какие характеристики исследований могут влиять на результаты мета-анализа. В контексте нашей работы мета-регрессия использовалась для выявления параметров исследований, способных влиять на величину AUROC для определения ЦВД по сравнению с тестом с инфузионной нагрузкой.

 

Оценка публикационного смещения и эффекта малых исследований. Воронкообразные диаграммы

Assessment of Publication Bias and Small-Study Effects: Funnel Plots

Рис. Д2. Воронкообразная диаграмма для всех 84 исследований, включенных в мета-анализ Fig. D2. Funnel plot for all 84 studies included in the meta-analysis

 

Рис. Д3. Воронкообразные диаграммы по когортам пациентов Fig. D3. Funnel Plots by Patient Cohorts

Рис. Д4. Воронкообразные диаграммы по типу золотого стандарта Fig. D4. Funnel Plots by Type of Gold Standard

 

Рис. Д5. Воронкообразные диаграммы по типу дыхания Fig. D5. Funnel Plots by Type of Breathing

 

Рис. Д6. Воронкообразные диаграммы по году публикации Fig. D6. Funnel Plots by Year of Publication

 

Оценка риска систематической ошибки

Risk of bias assessment

 

Study Test parameter Test cutoff Risk of bias (QUADAS-2) OVERALL bias Applicability concerns (QUADAS-2)
P I R FT P I R
1 Albano BBP (2021) CVP (mmHg) 6 ✓ ✓ ✓ ✓ Low ✓ ✓ ✓
2 Angappan S (2015) CVP (mmHg) ND ✓ ✗ (ND for cut-off) ✓ ✓ Moderate ✓ ✓ ✓
3 Baker AK (2013) CVP ND ✓ ✗ (ND for cut-off) ✓ ✓ Moderate ✓ ✓ ✓
4 Barbier C (2004) CVP (mmHg) 12 ✓ ✓ ✓ ✓ Low ✓ ✓ ✓
5 Berg JM (2021) CVP ND ✗ (not detailed description of the study population) ✗ (ND for cut-off) ✓ ✓ High ✓ ✓ ✓
6 Berkenstadt H (2001) CVP (mmHg) ND ✓ ✗ (ND for cut-off) ✗ (low value of gold standard cut-off) ✓ High ✓ ✓ ✓
7 Biais M (2008) CVP (mmHg) 3 ✓ ✓ ✓ ✓ Low ✓ ✓ ✓
8 Botros JM (2023) CVP ND ✓ ✗ (ND for cut-off) ✓ ✓ Moderate ✓ ✓ ✓
9 Bubenek-Turconi ŞI (2019) CVP ND ✓ ✗ (ND for cut-off) ✓ ✓ Moderate ✓ ✓ ✓
10 Cannesson M (2007) CVP (mmHg) ND ✓ ✗ (ND for cut-off) ✓ ✓ Moderate ✓ ✓ ✓
11 Cannesson M (2008)-1 CVP (mmHg) 3,5 ✓ ✓ ✓ ✓ Low ✓ ✓ ✓
12 Cannesson M (2008)-2 CVP (mmHg) 12,5 ✓ ✓ ✓ ✓ Low ✓ ✓ ✓
13 Cannesson M (2009) CVP (mmHg) ND ✓ ✗ (ND for cut-off) ✓ ✓ Moderate ✓ ✓ ✓
14 Cannesson M (2011) CVP (mmHg) ND ✓ ✗ (ND for cut-off) ✓ ✓ Moderate ✓ ✓ ✓
15 Cecconi M (2012) CVP ND ✓ ✗ (ND for cut-off) ✓ ✓ Moderate ✓ ✓ ✓
16 de Oliveira OH (2016) CVP (mmHg) 10 ✓ ✓ ✓ ✓ Low ✓ ✓ ✓
17 de Waal EE (2009) CVP (mmHg) ND ✓ ✗ (ND for cut-off) ✓ ✓ Moderate ✓ ✓ ✓
18 Dépret F (2018) CVP (mmHg) ND ✗ (not detailed description of the study population) ✗ (ND for cut-off) ✓ ✓ High ✓ ✓ ✓
19 Desgranges FP (2011) CVP (mmHg) 8 ✓ ✓ ✓ ✓ Low ✓ ✓ ✓
20 Fu Q (2012) CVP (mmHg) 7,5 ✓ ✓ ✓ ✓ Low ✓ ✓ ✓
21 Fu Q (2014) CVP (mmHg) ND ✓ ✗ (ND for cut-off) ✓ ✓ Moderate ✓ ✓ ✓
22 Geerts BF (2011) CVP (mmHg) 9 ✓ ✓ ✓ ✓ Low ✓ ✓ ✓
23 Giraud R (2018) CVP ND ✓ ✗ (ND for cut-off) ✓ ✓ Moderate ✓ ✓ ✓
24 Guarracino F (2014) CVP (mmHg) 8 ✓ ✓ ✓ ✓ Low ✓ ✓ ✓
25 Haas S (2012) CVP ND ✓ ✗ (ND for cut-off) ✓ ✓ Moderate ✓ ✓ ✓
26 Hahn RG (2016) CVP (mmHg) 6,5 ✓ ✓ ✓ ✓ Low ✓ ✓ ✓
27 Hikasa Y (2023) CVP (cmH2O) 19 ✓ ✓ ✓ ✓ Low ✓ ✓ ✓
28 Hofer CK (2005) CVP ND ✗ (not detailed description of the study population) ✗ (ND for cut-off) ✓ ✓ High ✓ ✓ ✓
29 Hofer CK (2018) CVP ND ✓ ✗ (ND for cut-off) ✓ ✓ Moderate ✓ ✓ ✓
30 Høiseth LØ (2011) CVP ND ✓ ✗ (ND for cut-off) ✓ ✓ Moderate ✓ ✓ ✓
31 Huang CC (2008) CVP (mmHg) ND ✓ ✗ (ND for cut-off) ✓ ✗ (not all patients including in analysis) High ✓ ✓ ✓
32 Ibarra-Estrada MÁ (2015) CVP (mmHg) ND ✓ ✗ (ND for cut-off) ✓ ✓ Moderate ✓ ✓ ✓
33 Ikeda K (2016) CVP ND ✗ (not detailed description of the study population and study enroument depence on clinical decision) ✗ (ND for cut-off) ✗ (inaccurate values volume of FC) ✓ Very High ✓ ✓ ✓
34 Ishihara H (2013) CVP (mmHg) 6,5 ✓ ✓ ✓ ✓ Low ✓ ✓ ✓
35 Kim SY (2013) CVP (mmHg) ND ✗ (not detailed description of the study population) ✗ (ND for cut-off) ✓ ✓ High ✓ ✓ ✓
36 Kramer A (2004) CVP (mmHg) ND ✓ ✗ (ND for cut-off) ✓ ✓ Moderate ✓ ✓ ✓
37 Kumar N (2021) CVP (mmHg) 7,5 ✓ ✓ ✓ ✓ Low ✓ ✓ ✓
38 Kurtz P (2014) CVP ND ✓ ✗ (ND for cut-off) ✓ ✓ Moderate ✓ ✓ ✓
39 Lakhal K (2010) CVP ND ✓ ✗ (ND for cut-off) ✓ ✓ Moderate ✓ ✓ ✓
40 Lakhal K (2011) CVP (mmHg) ND ✓ ✗ (ND for cut-off) ✓ ✓ Moderate ✓ ✓ ✓
41 Lanspa MJ (2012) CVP (mmHg) 8 ✓ ✓ ✓ ✓ Low ✓ ✓ ✓
42 Lee JH (2007) CVP (mmHg) ND ✓ ✗ (ND for cut-off) ✓ ✓ Moderate ✓ ✓ ✓
43 Lee JH (2011) CVP (mmHg) ND ✓ ✗ (ND for cut-off) ✓ ✓ Moderate ✓ ✓ ✓
44 Li J (2012) CVP (mmHg) ND ✓ ✗ (ND for cut-off) ✓ ✓ Moderate ✓ ✓ ✓
45 Lu N (2017) CVP (mmHg) 6,5 ✓ ✓ ✓ ✓ Low ✓ ✓ ✓
46 Ma GG (2018) CVP (mmHg) 11 ✓ ✓ ✓ ✓ Low ✓ ✓ ✓
47 Ma Q (2022) CVP (mmHg) 4 ✓ ✓ ✓ ✓ Low ✓ ✓ ✓
48 Mallat J (2022) CVP ND ✓ ✗ (ND for cut-off) ✓ ✓ Moderate ✓ ✓ ✓
49 Mohamed ZU (2017) CVP (mmHg) ND ✓ ✗ (ND for cut-off) ✓ ✓ Moderate ✓ ✓ ✓
50 Monge García MI (2008) CVP (mmHg) ND ✓ ✗ (ND for cut-off) ✓ ✓ Moderate ✓ ✓ ✓
51 Monge García MI (2009) CVP (mmHg) ND ✓ ✗ (ND for cut-off) ✓ ✓ Moderate ✓ ✓ ✓
52 Moretti R (2010) CVP ND ✓ ✗ (ND for cut-off) ✓ ✓ Moderate ✓ ✓ ✓
53 Muller L (2008) CVP (mmHg) 9 ✓ ✓ ✗ (inaccurate values volume of FC) ✓ Moderate ✓ ✓ ✓
54 Muller L (2009) CVP (mmHg) 7 ✓ ✓ ✗ (inaccurate values volume of FC) ✓ Moderate ✓ ✓ ✓
55 Muller L (2010) CVP (mmHg) 9 ✓ ✓ ✗ (inaccurate values volume of FC) ✓ Moderate ✓ ✓ ✓
56 Muller L (2011) CVP (mmHg) ND ✓ ✗ (ND for cut-off) ✓ ✓ Moderate ✓ ✓ ✓
57 Myatra SN (2017) CVP ND ✓ ✗ (ND for cut-off) ✓ ✓ Moderate ✓ ✓ ✓
58 Oliveira-Costa CD (2012) CVP ND ✓ ✗ (ND for cut-off) ✓ ✓ Moderate ✓ ✓ ✓
59 Pei S (2014) CVP (mmHg) 4,5 ✓ ✓ ✓ ✓ Low ✓ ✓ ✓
60 Peng S (2013) CVP (mmHg) ND ✓ ✗ (ND for cut-off) ✓ ✓ Moderate ✓ ✓ ✓
61 Preisman S (2005) CVP ND ✓ ✗ (ND for cut-off) ✓ ✓ Moderate ✓ ✓ ✓
62 Reuter DA (2002) CVP (mmHg) ND ✗ (not detailed description of the study population) ✗ (ND for cut-off) ✓ ✓ High ✓ ✓ ✓
63 Reuter DA (2003) CVP (mmHg) 6 ✗ (not detailed description of the study population) ✓ ✗ (inaccurate values volume of FC and low value of gold standard cut-off) ✓ High ✓ ✓ ✓
64 Roy S (2013) CVP (mmHg) ND ✓ ✗ (ND for cut-off) ✓ ✓ Moderate ✓ ✓ ✓
65 Saugel B (2013) CVP (mmHg) 12 ✓ ✓ ✓ ✓ Low ✓ ✓ ✓
66 Shim JK (2014) CVP ND ✓ ✗ (ND for cut-off) ✓ ✓ Moderate ✓ ✓ ✓
67 Shin YH (2011) CVP (mmHg) ND ✓ ✗ (ND for cut-off) ✓ ✓ Moderate ✓ ✓ ✓
68 Soliman RA (2015) CVP (mmHg) ND ✓ ✗ (ND for cut-off) ✓ ✓ Moderate ✓ ✓ ✓
69 Song Y (2014) CVP (mmHg) ND ✓ ✗ (ND for cut-off) ✓ ✓ Moderate ✓ ✓ ✓
70 Suehiro K (2012) CVP ND ✓ ✗ (ND for cut-off) ✓ ✓ Moderate ✓ ✓ ✓
71 Taccheri T (2021) CVP (mmHg) ND ✓ ✗ (ND for cut-off) ✓ ✓ Moderate ✓ ✓ ✓
72 Thiel SW (2009) CVP (mmHg) ND ✓ ✗ (ND for cut-off) ✓ ✓ Moderate ✓ ✓ ✓
73 Trof RJ (2011) CVP (mmHg) ND ✓ ✗ (ND for cut-off) ✗ (inaccurate values volume of FC) ✓ High ✓ ✓ ✓
74 Vistisen ST (2009) CVP (mmHg) 8 ✗ (not detailed description of the study population) ✓ ✓ ✓ Moderate ✓ ✓ ✓
75 Vistisen ST (2016) CVP ND ✓ ✗ (ND for cut-off) ✓ ✓ Moderate ✓ ✓ ✓
76 Wang Y (2018) CVP (mmHg) 11 ✓ ✓ ✓ ✓ Low ✓ ✓ ✓
77 Wyffels PA (2007) CVP (mmHg) ND ✓ ✗ (ND for cut-off) ✓ ✓ Moderate ✓ ✓ ✓
78 Xu B (2016) CVP (mmHg) 11 ✓ ✓ ✗(saline or gel) ✓ Moderate ✗(CVP) was no less than 8 mmHg ✓ ✓
79 Xu LY (2019) CVP (mmHg) 7 ✓ ✓ ✓ ✓ Low ✓ ✓ ✓
80 Xu Y (2022) CVP (mmHg) 9 ✓ ✓ ✓ ✓ Low ✓ ✓ ✓
81 Yazigi A (2012) CVP (mmHg) ND ✓ ✗ (ND for cut-off) ✓ ✓ Moderate ✓ ✓ ✓
82 Zhang X (2016) CVP (mmHg) 6,5 ✓ ✓ ✓ ✓ Low ✓ ✓ ✓
83 Zhao F (2015) CVP (mmHg) 7 ✓ ✓ ✓ ✓ Low ✓ ✓ ✓
84 Zimmermann M (2010) CVP (mmHg) 10,5 ✓ ✓ ✓ ✓ Low ✓ ✓ ✓
Таблица Д5. Оценка риска систематической ошибки P — отбор пациентов; I — индекс-тест; R — золотой стандарт; FT — соблюдение процедуры и тайминга; CVP — центральное венозное давление; ND — нет данных; ✓ — соответствует низкому риску; ✗ — соответствует высокому риску.
Table D5. Risk of bias assessment Р — patient selection; I —index test; R —reference standard; FT —flow and timing; CVP — central venous pressure; ND — no data; ✓ — indicates low risk; ✗ — indicates High risk.

 

Степень достоверности доказательств по методологии GRADE

Certainty of evidence based on the GRADE methodology

Положение Количество пациентов и исследований Риск /bias Неоднородность / Inconsistency Косвенность / Indirectness Неточность / Imprecision Publication bias Повышение Уровень доказательств
Диагностическая точность
Положение: Центральное венозное давление обладает низкой диагностической точностью относительно определения восприимчивости к инфузионной нагрузке
AUROC 0.596 (0.575; 0.618); I2 = 81.09 % 		3729,
84 исследования 		Нет опасений (0) Статистическая неоднородность (–1) Нет опасений (0) Нет опасений (0) Нет опасений (0) Нет (0) ⚫ ⚫ ⚫ ⚪
Средний
Таблица Д6. Степень достоверности доказательств по методологии GRADE AUROC — площадь под ROC-кривой; 0 — отсутствие снижения достоверности доказательств; –1 — серьезное ограничение; –2 — очень серьезное ограничение; +1 — повышение достоверности доказательств.
Базовый уровень доказательств был высоким.
Table D6. Certainty of evidence based on the GRADE methodology AUROC — area under ROC-curve.
Key Notations: 0 — no downgrading of evidence; –1 — serious limitation; –2 — very serious limitation; +1 —  upgrade of evidence.
The baseline level of evidence was High.

 

Литература/References

[1] Albano B., Habana L.M. Prediction of fluid responsiveness in the immediate post-operative period of cardiac surgery. J Anesth Crit Care Open Access. 2021; 13: 35–45. DOI: 10.15406/jaccoa.2021.13.00467

[2] Angappan S., Parida S., Vasudevan A., et al. The comparison of stroke volume variation with central venous pressure in predicting fluid responsiveness in septic patients with acute circulatory failure. Indian J Crit care Med peer-reviewed, Off Publ Indian Soc Crit Care Med. 2015 Jul; 19(7): 394–400. DOI: 10.4103/0972-5229.160278

[3] Baker A.K., Partridge R.J.O., Litton E., et al. Assessment of the plethysmographic variability index as a predictor of fluid responsiveness in critically ill patients: a pilot study. Anaesth Intensive Care. 2013 Nov; 41(6): 736–41. DOI: 10.1177/0310057X1304100608

[4] Barbier C., Loubières Y., Schmit C., et al. Respiratory changes in inferior vena cava diameter are helpful in predicting fluid responsiveness in ventilated septic patients. Intensive Care Med. 2004 Sep; 30(9): 1740–6. DOI: 10.1007/s00134-004-2259-8

[5] Berg J.M., Nielsen D.V., Abromaitiene V., et al. Changes in arterial blood pressure characteristics following an extrasystolic beat or a fast 50 ml fluid challenge do not predict fluid responsiveness during cardiac surgery. J Clin Monit Comput. 2022 Jun; 36(3): 889–900. DOI: 10.1007/s10877-021-00722-z

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