Effects of pulse indicated continuous cardiac output monitoring on outcomes of intensive care unit patients with shock: a propensity score matching analysis

doi:10.5847/wjem.j.1920-8642.2025.0100

Abstract

Abstract:

BACKGROUND: Pulse indicated continuous cardiac output (PiCCO) has largely replaced Swan-Ganz catheterization in shock patients. However, whether PiCCO monitoring can improve outcomes of shock patients, such as mortality, length of hospital stay, duration of mechanical ventilation, or laboratory parameters, remains unknown.

METHODS: This retrospective cohort study included patients with shock in the intensive care unit (ICU) from January 2013 to January 2020. Patients were divided into PiCCO group and non-PiCCO group based on treatment with PiCCO monitoring or not. Demographic characteristics, Acute Physiology and Chronic Health Evaluation (APACHE) II scores, quick Sequential Organ Failure Assessment (qSOFA) scores, 14-day mortality, and N-terminal pro-B-type natriuretic peptide (NT-proBNP) levels at 0, 1, 3 and 7 days after onset of shock, duration of mechanical ventilation, length of hospital stay and hospitalization costs were compiled and analyzed using propensity score matching (PSM).

RESULTS: Real-world analysis of 1,583 ICU patients suffering shock after propensity score matching revealed that 14-day mortality did not differ between PiCCO and non-PiCCO groups (36.2% vs. 32.6%, P=0.343). Duration of mechanical ventilation, hospital stay, and hospitalization costs were also similar between the two groups (P>0.05). No differences in changes of NT-proBNP levels on days 0, 1, 3, and 7 as compared to baseline were noted between the two groups (P>0.05).

CONCLUSIONS: The results of our real-world indicate that PiCCO monitoring may not shorten the duration of mechanical ventilation, length of hospital stay, or reduce hospitalization costs, nor will it bring survival benefits to ICU patients suffering shock.

Key words: Pulse indicated continuous cardiac output, Shock, Real-world study, Propensity score matching, Intensive care unit

Danyang Li, Yi Xia, Yangmin Hu, Linlin Du, Tiancha Huang, Chengyang Chen, Yufei Xiao, Leiqing Li, Yang Yu, Shujun Dai, Wei Cui, Huahao Shen. Effects of pulse indicated continuous cardiac output monitoring on outcomes of intensive care unit patients with shock: a propensity score matching analysis[J]. World Journal of Emergency Medicine, 2025, 16(5): 469-474.

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References 18

1	Cecconi M, Backer D, Antonelli M, Beale R, Bakker J, Hofer C, et al. Consensus on circulatory shock and hemodynamic monitoring. Task force of the European Society of Intensive Care Medicine. Intensive Care Med. 2014; 40(12):1795-815. doi: 10.1007/s00134-014-3525-z pmid: 25392034
2	Kondo T, Araki T, Imaizumi T, Sumita Y, Nakai M, Tanaka A, et al. Prognosis in patients with cardiogenic shock who received temporary mechanical circulatory support. JACC Asia. 2022; 3(1):122-34.
3	Sandham JD, Hull RD, Brant RF, Knox L, Pineo GF, Doig CJ, et al. A randomized, controlled trial of the use of pulmonary-artery catheters in high-risk surgical patients. N Engl J Med. 2003; 348(1):5-14.
4	Lichtwarck-Aschoff M, Zeravik J, Pfeiffer UJ. Intrathoracic blood volume accurately reflects circulatory volume status in critically ill patients with mechanical ventilation. Intensive Care Med. 1992; 18(3):142-7.
5	Kirton OC, Calabrese RC, Staff I. Increasing use of less-invasive hemodynamic monitoring in 3 specialty surgical intensive care units. J Intensive Care Med. 2015; 30(1):30-6.
6	Wernly B, Lichtenauer M, Franz M, Fritzenwanger M, Kabisch B, Figulla HR, et al. Pulse contour cardiac output monitoring in acute heart failure patients. Wiener Klinische Wochenschrift. 2016; 128(23-24):864-9.
7	Zhang Z, Ni H, Qian Z. Effectiveness of treatment based on PiCCO parameters in critically ill patients with septic shock and/or acute respiratory distress syndrome: a randomized controlled trial. Intensive Care Med. 2015; 41(3):444-51. doi: 10.1007/s00134-014-3638-4 pmid: 25605469
8	Chen XF, Ye JL, Zhu ZY, Xue H, Pu XH, Miao XL. Evaluation of high volume hemofiltration according to pulse-indicated continuous cardiac output on patients with acute respiratory distress syndrome. Zhonghua Wei Zhong Bing Ji Jiu Yi Xue. 2014; 26(9): 650-4.
9	Misir HD, Demir N, Kasimzade F, Yahşi C. A case of post traumatic mitral chordae rupture mimicking acute respiratory distress syndrome. World J Emerg Med. 2024; 15(4):322-4. doi: 10.5847/wjem.j.1920-8642.2024.054 pmid: 39050215
10	Sun Y, Lu ZH, Zhang XS, Geng XP, Cao LJ, Yin L. The effects of fluid resuscitation according to PiCCO on the early stage of severe acute pancreatitis. Pancreatology. 2015; 15(5):497-502. doi: S1424-3903(15)00597-9 pmid: 26160657
11	Thorpe KE, Zwarenstein M, Oxman AD, Treweek S, Furberg CD, Altman DG, et al. A pragmatic-explanatory continuum indicator summary (PRECIS): a tool to help trial designers. CMAJ. 2009; 180(10):E47-E57.
12	Chen HT, Xu JF, Huang XX, Zhou NY, Wang YK, Mao Y. Blood eosinophils and mortality in patients with acute respiratory distress syndrome: A propensity score matching analysis. World J Emerg Med. 2021; 12(2):131-6.
13	Werner M, Wernly B, Lichtenauer M, Franz M, Kabisch B, Muessig JM, et al. Real-world extravascular lung water index measurements in critically ill patients: Pulse index continuous cardiac output measurements: time course analysis and association with clinical characteristics. Wien Klin Wochenschr. 2019; 131(13-14):321-8.
14	Dettmer M, Holthaus CV, Fuller BM. The impact of serial lactate monitoring on emergency department resuscitation interventions and clinical outcomes in severe sepsis and septic shock. Shock. 2015; 43(1):55-61.
15	van Beest PA, Brander L, Jansen SP, Rommes JH, Kuiper MA, Spronk PE. Cumulative lactate and hospital mortality in ICU patients. Ann Intensive Care. 2013; 3(1):6. doi: 10.1186/2110-5820-3-6 pmid: 23446002
16	Núñez J, Núñez E, Robles R, Bodí V, Sanchis J, Carratalá A, et al. Prognostic value of brain natriuretic peptide in acute heart failure:mortality and hospital readmission. Revista Española De Cardiol Engl Ed. 2008; 61(12):1332-7.
17	Ajuluchukwu JNA, Ekure EN, Mbakwem AC, Okoromah CN, Oladipo OO. Reliability and accuracy of point-of-care amino-terminal ProBrain natriuretic peptide in congestive heart failure patients. Internet J Cardiol. 2010; 9(1):2.
18	Li DY, Li XY, Cui W, Shen HH, Zhu H, Xia Y. Liberal versus conservative fluid therapy in adults and children with Sepsis or septic shock. Cochrane Database Syst Rev. 2018; 12:CD010593.

Variables	Before matching			After matching
Variables	PiCCO (n=308)	Non-PiCCO (n=1,275)	P-value	PiCCO (n=298)	Non-PiCCO (n=298)	P-value
Age, years	64.9±17.0	64.2±15.4	0.507	64.9±17.2	65.2±15.1	0.845
Male, n (%)	221 (71.8)	769 (60.3)	<0.001	211(70.8)	218 (73.2)	0.523
APACHE II score	23 (19, 28)	21 (15, 27)	<0.001	23 (19, 28)	23 (17, 29)	0.652
qSOFA score	2 (1, 2)	2 (1, 2)	<0.001	2 (1, 2)	2 (1, 2)	0.823
WBC, ×10⁹	9.7 (6.4, 14.2)	9.5 (6.8, 16.6)	0.240	9.6 (6.1, 13.5)	9.4 (6.5, 15.7)	0.280
PLT, ×10⁹	159 (111, 212)	152 (101, 208)	0.047	160 (100, 216)	152 (101, 210)	0.230
Total bilirubin, μmol/L	13.4 (9.0, 20.0)	15.7 (10.0, 26.3)	<0.001	15 (9.3, 21.7)	15.3 (9.6, 26.1)	0.151
ALT, U/L	28 (18, 45)	35 (18, 65)	<0.001	28 (20, 47)	35 (18, 64)	0.006
Creatinine, μmol/L	64 (50, 96)	87 (63, 154)	<0.001	66 (53, 101)	87 (63.5, 149.5)	<0.001
Outcomes
Mechanical ventilation duration, h	148.4 (64.8, 359.5)	136.0 (33.9, 312.9)	0.008	150.8 (65.6, 373.4)	166.3 (42.9, 376.3)	0.482
Length of hospital stay, d	16.8 (7.7, 28.8)	16.8 (8.0, 28.0)	0.851	16.4 (7.8, 28.8)	18.8 (7.6, 29.2)	0.723
Hospitalization cost, RMB	126,595 (69,440, 230,363)	103,490 (56,714, 171,715)	<0.001	120,397 (69,451, 223,826)	118,788 (56,213, 197,360)	0.091

Variables	PiCCO group Non-PiCCO group		Z	P-value
NT-proBNP, pg/mL
Day 0	3,033 (1,131, 14,385)	1,347 (913, 9,752)	-5.401	<0.001
Day 1	4,365 (1,318, 21,284)	2,892 (1,091, 15,071)	-1.620	0.105
Day 3	4,837 (1,958, 24,931)	3,224 (1,355, 14,348)	-2.093	0.036
Day 7	3,440 (1,845, 18,167)	2,102 (1,168, 13,048)	-2.373	0.018
Maximum	14,262 (5,559, 35,000)	13,493 (4,292, 35,000)	-7.849	<0.001
Day 1 vs. day 0	69 (-756, 681)	506 (-179, 3,199)	-1.726	0.084
Day 3 vs. day 0	154 (-4,233, 2,954)	798 (-371, 5,438)	-1.540	0.124
Day 7 vs. day 0	270 (-2,510, 4,014)	607 (-1,160, 9,817)	-0.546	0.585

Variables	OR	95% CI	P-value
PiCCO monitoring (yes/no)	0.959	0.648-1.419	0.833
Age	1.030	1.021-1.038	<0.001
APACHE II score	1.037	1.014-1.060	0.001
NT-proBNP level on day 0	1.000	1.000-1.000	0.108
Maximum NT-proBNP level	1.000	1.000-1.000	0.121
Difference between maximum and day 0 levels of NT-proBNP	1.000	1.000-1.000	0.035

Variables	Duration of mechanical ventilation			Length of intensive care unit stay
Variables	Standardized coefficients	t	P-value	Standardized coefficients	t	P-value
PiCCO monitoring (yes/no)	0.025	0.544	0.586	0.037	0.819	0.413
Age	0.054	1.209	0.227	0.041	0.946	0.344
APACHE II score	0.020	0.440	0.660	-0.005	-0.121	0.904
NT-proBNP level on day 0	-0.002	-0.029	0.977	0.000	-0.006	0.995
Maximum NT-proBNP level	-0.059	-0.952	0.341	-0.043	-0.712	0.477

Groups	Before matching					After matching
Groups	Survival	Death	Mortality, %	χ²	P-value	Survival	Death	Mortality, %	χ²	P-value
PiCCO	197	111	36.0	3.306	0.069	190	108	36.2	0.900	0.343
Non-PiCCO	884	391	30.7	3.306	0.069	201	97	32.6	0.900	0.343