Journal of Peking University (Health Sciences) ›› 2021, Vol. 53 ›› Issue (5): 946-951. doi: 10.19723/j.issn.1671-167X.2021.05.023

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Comparison of pulse pressure variation, stroke volume variation, and plethysmographic variability index in pediatric patients undergoing craniotomy

LIU Ya-fei1,SONG Lin-lin1,(),XING Mao-wei1,CAI Li-xin2,WANG Dong-xin1   

  1. 1. Department of Anesthesiology, Beijing 100034, China
    2. Pediatric Epilepsy Center, Peking University First Hospital, Beijing 100034, China
  • Received:2020-11-16 Online:2021-10-18 Published:2021-10-11
  • Contact: Lin-lin SONG E-mail:songlinlinlynkia@163.com

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Abstract:

Objective: To compare well-known preload dynamic parameters intraoperatively including stroke volume variation (SVV), pulse pressure variation (PPV), and plethysmographic variability index (PVI) in children who underwent craniotomy for epileptogenic lesion excision. Methods: A total of 30 children aged 0 to 14 years undergoing craniotomy for intracranial epileptogenic lesion excision were enrolled. During surgery, we measured PPV, SVV (measured by the Flotrac/Vigileo device), and PVI (measured by the Masimo Radical-7 monitor) simultaneously and continuously. Preload dynamic parameter measurements were collected at predefined steps: after induction of anesthesia, during opening the skull, intraoperative electroencephalogram monitoring, excision of epileptogenic lesion, skull closure, at the end of the operation. After exclusion of outliers, agreement among SVV, PPV, and PVI was assessed using repeated measures of Bland-Altman approach. The 4-quadrant and polar plot techniques were used to assess the trending ability among the changes in the three parameters. Results: The mean SVV, PPV, and PVI were 8%±2%, 10%±3%, and 15%±7%, respectively during surgery. We analyzed a total of 834 paired measurements (3 to 8 data sets for each phase per patient). Repeated measures Bland-Altman analysis identified a bias of -2.3 and 95% confidence intervals between -1.9 and -2.7 (95% limits of agreement between -6.0 and 1.5) between PPV and SVV, showing significant correlation at all periods. The bias between PPV and PVI was -5.0 with 95% limits of agreement between -20.5 and 10.5, and that between SVV and PVI was -7.5 with 95% limits of agreement between -22.7 and 7.8, both not showing significant correlation. Reflected by 4-quadrant plots, the con-cordance rates showing the trending ability between the changes in PPV and SVV, PPV and PVI, SVV and PVI were 88.6%, 50.4%, and 50.1%, respectively. The concordance rate between PPV and SVV was higher (92.7%) in children aged less than 3 years compared with those aged 3 and more than 3 years. The mean angular bias, radial limits of agreement, and angular concordance rate in the polar analysis were not clinically acceptable in the changes between arterial pressure waveform-based parameters and volume-based PVI (PPV vs. PVI: angular mean bias 8.4°, angular concordance rate 29.9%; SVV vs. PVI: angular mean bias 2.4°, angular concordance rate 29.1%). There was a high concordance between the two arterial pressure waveform-based parameters reflected by the polar plot (angular mean bias -0.22°, angular concordance rate 86.6%). Conclusion: PPV can be viewed as a surrogate for SVV, especially in children aged less than 3 years. The agreement between arterial pressure waveform-based preload parameters (PPV and SVV) and PVI is poor and these two should not be considered interchangeable. Attempt to combine PVI and PPV for improving the anesthesiologist’s ability to monitor cardiac preload in major pediatric surgery is warranted.

Key words: Stroke volume variation, Pulse pressure variation, Plethysmographic variability index, Craniotomy, Child

CLC Number: 

  • R726.1

Table 1

Demographic and intraoperative clinical hemodynamics of Children"

Items All children (n=30) <3 years (n=15) ≥3 years (n=15)
Age/years 4.4±2.9 2.0±0.5 6.8±2.0
Male/Female 20/10 10/6 10/4
Height/cm 109.0±21.6 91.3±5.4 126.6±16.3
Weight/kg 21.5±11.5 12.3±2.5 29.8±11.1
BMI/(kg/m2) 17.0±2.7 15.8±2.3 18.1±2.7
Time of anesthesia/min 285±48 270±55 299±37
Total volume/mL 1 008±557 620±177 1 395±538
Urine volume/mL 470±309 275±189 665±286
Blood volume/mL 138±48 105±55 170±42
SBP/mmHg 94±19 90±15 97±21
HR/(beats/min) 81±14 91±9 71±9
OI before incision/mmHg 626±64 634±67 617±61
OI after surgery/mmHg 638±51 639±37 636±60
Lactate before incision/mmHg 0.9±0.3 0.7±0.3 1.0±0.3
Lactate after surgery/mmHg 1.0±0.4 0.8±0.2 1.2±0.5
SVV/% 8±2 7±2 9±3
PVV/% 10±3 9±3 11±3
PVI/% 15±7 14±6 16±7

Figure 1

The agreement among SVV, PPV and PVI reflected by the repeated measures Bland-Altman plot analysis A, SVV-PPV; B, SVV-PVI; C, PPV-PVI. SVV, stroke volume variation; PPV, pulse pressure variation; PVI, plethysmographic variability index."

Figure 2

Concordance rates among ΔSVV, ΔPPV, and ΔPVI reflected by the four-quadrant plots A, ΔSVV-ΔPPV; B, ΔSVV-ΔPVI; C, ΔPPV-ΔPVI. ΔSVV, change in stroke volume variation; ΔPPV, change in pulse pressure variation; ΔPVI, change in plethysmographic variability index."

Table 2

Concordance rates among ΔSVV, ΔPPV, and ΔPVI reflected by the four-quadrant plots based on age"

Items All children <3 years ≥3 years
ΔSVV-ΔPPV 88.6% 92.7% 84.2%
ΔSVV-ΔPVI 50.1% 52.6% 49.4%
ΔPPV-ΔPVI 50.4% 40.4% 61.1%

Figure 3

Concordance rates among ΔSVV, ΔPPV, and ΔPVI reflected by the polar plots ΔSVV, change in stroke volume variation; ΔPPV, change in pulse pressure variation; ΔPVI, change in plethysmographic variability index."

[1] Chen PH, Chan KC, Liao MH, et al. Accuracy of dynamic preload variables for predicting fluid responsiveness in patients with pediatric liver cirrhosis: a prospective study [J]. Paediatr Anaesth, 2020, 30(4):455-461.
doi: 10.1111/pan.v30.4
[2] Cheng YW, Xu F, Li J. Identification of volume parameters monitored with a noninvasive ultrasonic cardiac output monitor for predicting fluid responsiveness in children after congenital heart disease surgery [J]. Medicine (Baltimore), 2018, 97(39):e12289.
doi: 10.1097/MD.0000000000012289
[3] Liu T, Xu C, Wang M, et al. Reliability of pleth variability index in predicting preload responsiveness of mechanically ventilated patients under various conditions: a systematic review and meta-analysis [J]. BMC Anesthesiol, 2019, 19(1):67.
doi: 10.1186/s12871-019-0744-4
[4] Kim DH, Shin S, Kim JY, et al. Pulse pressure variation and pleth variability index as predictors of fluid responsiveness in patients undergoing spinal surgery in the prone position [J]. Ther Clin Risk Manag, 2018, 14:1175-1183.
doi: 10.2147/TCRM
[5] Saugel B, Heeschen J, Hapfelmeier A, et al. Cardiac output estimation using multi-beat analysis of the radial arterial blood pressure waveform: a method comparison study in patients having off-pump coronary artery bypass surgery using intermittent pulmonary artery thermodilution as the reference method [J]. J Clin Monit Comput, 2020, 34(4):649-654.
doi: 10.1007/s10877-019-00375-z pmid: 31456072
[6] Monnet X, Marik PE, Teboul JL. Prediction of fluid responsiveness: an update [J]. Ann Intensive Care, 2016, 2016(6):111.
[7] Joosten A, Jacobs A, Desebbe O, et al. Monitoring of pulse pressure variation using a new smartphone application (Capstesia) versus stroke volume variation using an uncalibrated pulse wave analysis monitor: a clinical decision making study during major abdominal surgery [J]. J Clin Monit Comput, 2019, 33(5):787-793.
doi: 10.1007/s10877-018-00241-4
[8] Ji SH, Song IK, Jang YE, et al. Comparison of pulse pressure variation and pleth variability index in the prone position in pediatric patients under 2 years old [J]. Korean J Anesthesiol, 2019, 72(5):466-471.
doi: 10.4097/kja.19128
[9] Desgranges FP, Evain JN, Pereira de Souza NE, et al. Does the plethysmographic variability index predict fluid responsiveness in mechanically ventilated children? A meta-analysis [J]. Br J Anaesth, 2016, 117(3):409-410.
doi: 10.1093/bja/aew245 pmid: 27543550
[10] Lee JH, Kim EH, Jang YE, et al. Fluid responsiveness in the pediatric population [J]. Korean J Anesthesiol, 2019, 72(5):429-440.
doi: 10.4097/kja.19305
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