The influence of cumulative fluid balance on volume status in patients with heart failure: a multicenter cohort study

doi:10.21203/rs.3.rs-1496694/v1

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The influence of cumulative fluid balance on volume status in patients with heart failure: a multicenter cohort study

https://doi.org/10.21203/rs.3.rs-1496694/v1

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Purpose: To explore the influence of cumulative fluid balance (CFB) on volume status in patients with heart failure (HF).

Methods: A total of 206 patients were enrolled and divided into groups of decreasing estimated plasma volume status (△ePVS(-)) (n=106) and increasing estimated plasma volume status(△ePVS(+)) (n=100), or groups of alleviated clinical congestion score(△CCS(-)) (n=86) and aggravated clinical congestion score(△CCS(+)) (n=120) according to the change of plasma volume and congestion status respectively. Data on patients’ general information and CFB at 1 to 7 days were compared between two pairs of groups respectively.

Results: The incidence of positive CFB ranged from 65.53% to 74.76%, and cumulative volume (CV) were from (0.23±1.00)L to (2.36±5.46)L at 1 to 7 days. CV at 4 to 7 days in the △ePVS(+) and △CCS(+) groups were significantly higher than that in △ePVS(-) and △CCS(-) groups respectively. When CV at 4 to 7 days reached 2.308L, 3.361L, 3.625L, and 3.816L, the AUC of ePVS were 0.672, 0.722, 0.644, and 0.754, respectively (P＜0.05), while when CV reached 2.308L, 3.383L, 4.670L, and 4.622L, the AUC of CCS were 0.625, 0.696, 0.656, and 0.709, separately (P＜0.05).

Conclusions: Patients with HF have a high incidence of positive CFB. CV at 4 to 7 days was an independent risk factor for △ePVS(+) and △CCS(+). It is suggested that the duration and volume of positive CFB should not exceed 3 days and 2.308L.

heart failure

water-electrolyte balance

plasma volume

hyperemia

Congestion and fluid retention induced by volume overload are the main cause of hospital admission and poor prognosis in patients with heart failure (HF)[1–3]. Therefore, reducing volume overload to relieve the symptoms of HF and reduce the readmission rate is of vital significance in the treatment of HF. At present, limiting fluid intake and increasing the output are commonly used to alleviate volume overload. According to the guidelines of multiple countries, the goal of volume management for chronic HF patients is to limit the weight gain within two days to 1.5-2 kg and inhibit the exacerbation of signs and symptoms. The amount of negative fluid balance in patients with acute decompensated HF should be reduced and then a general fluid balance can be gradually achieved after the subsiding of pulmonary congestion and edema[1, 4–6]. However, since positive fluid balance is more common in clinical practice and fluid balance is hard to achieve, volume overload is still a vexing problem[7]. Hatton et al.[8] observed positive fluid balance (༞2L) in 49% of critically ill patients. Based on bioelectrical impedance spectroscopy, Benedikt et al.[2] reported that 39% patients with HF suffered fluid overload. Rubio-Gracia J et al.[9] evaluated the congestion status of 1,572 patients with decompensated HF using clinical congestion score (CCS), and found that 97.2% of the patients had obvious congestion (CCS ≥ 3). Meanwhile, 28.7% of patients were found to have obvious congestion (CCS ≥ 3) and 47.8% have mild congestion (CCS = 1 or 2) after 7 days of hospitalization or at discharge. Wayne et al.[10] reported that only two patients had normal plasma volume (PV), and 24 patients has 13%-128% higher-than-normal PV on the day of admission. Even after treatment in hospital, there was hardly any reduction in PV of these patients. Progressive PV and CCS expansion is a hallmark of chronic HF, ultimately contributing to decompensated heart failure. Monitoring PV and CCS might offer prognostic information on volume status.

Zeng et al.[11] observed 1- to 6-day cumulative fluid balance of 94 patients in ICU, and found that the incidence of HF was 4.2% when the fluid balance was less than 0.5L per day; the incidence of HF increased to 51.1% when the fluid balance was between 0.5L and 1L per day; and the incidence of HF was 0 when the fluid balance was more than 1.5L per day if timely treatment was conducted. They suggested that paying attention to the daily fluid balance, while ignoring the cumulative fluid balance (CFB) might have contributed to the increased volume load in patients with HF. A study[12] of patients in ICU showed that the 72-hour increase of CFB was an independent risk factor for death. Margolis et al.[13] studied CFB in patients with myocardial infarction, and found that positive CFB was strongly associated with more severe acute kidney injury, and the possibility of renal function recovery decreased by 21% for each 1-liter increase in positive CFB .

The effect of CFB on the PV of patients with HF is still unclear. In order to explore the influence of CFB on the PV and whether there is a safe value for PV, an observational method was adopted to analyze the relationship between CFB and PV.

A multicenter, prospective, and observational study was conducted. Apart from routine treatment and nursing care, no other interventions were given to the observation objects, and their data was collected and analyzed. The fluid management was carried out according to European Society of Cardiology Guidelines: for patients with fluid retention or congestion that could not be easily controlled by diuretics, the daily fluid intake was restricted to approximately 2L/d; for patients in stage D ± hyponatremia, the fluid intake was restricted to 1.5-2L/d to reduce congestive symptoms; for those with CHF, the fluid intake was not strictly limited. All patients in this study were recruited from 3 tertiary-A general hospitals in China between October 2019 and March 2020.

Inclusion criteria were: age > 18 years; stable guideline-recommended heart failure therapy for > 3 months[4]; absence of an acute heart failure episode in the past 6 months; with informed consent. Exclusion criteria were: with other diseases or conditions causing the disordered fluid intake or output (such as diabetes, insipidus, and preoperational fluid intake restriction); with acute kidney injury or renal failure; with dementia or severe cognitive impairments; with malignant or severe diseases affecting physical capacity (such as tumors, and respiratory failure). Rejection criteria were: with hospitalization of less than 7 days and/or incomplete data.

A form was designed to collect the patient’s demographic and clinical information based on literature review and consultation with a cardiologist, a nurse, and a statistician. Demographic data included gender, age, weight, body mass index (BMI), education level, history of smoking and drinking, and protopathy. The clinical data included cardiac function, left ventricular ejection fraction (LVEF), N-terminal pro-brain natriuretic peptide (NT-proBNP), hemoglobin, hematocrit, estimated plasm volume status (ePVS), estimated glomerular filtration rate (eGFR), and drug use. Data were collected on the day of admission and on day 7 after admission based on medical records, physical examinations, and interview with patients.

The liquid input included liquid drinks and foods with a high concentration of natural liquid (such as watermelon). The liquid output included all fluid lost by means of excrement, urine, vomit, and perspiration. A fluid balance chart was used to record the 24-h input/output of fluid from day 1 to day 7 after admission. The patient or the caregivers filled in the chart after measuring patient’s fluid input and output using cups and urinal with millilitre (ml) scales. A trained investigator inspected the input and output record twice daily: once after lunch, for information about breakfast, morning snack, and lunch; and once after dinner, for information about the afternoon snack, dinner, and supper. The 24-hour fluid balance was then calculated (> 0: positive balance, < 0: negative balance, 0: balance). The water content in food was calculated according to the food moisture table[14] and that in stool was based on the water content of different stool forms[15].

ePVS and CCS represented the PV status and the severity of congestion respectively. The ePVS on both day 1 and day 7 after admission was calculated using Strauss-Duarte formula according to hematocrit and hemoglobin values[16], namely: ePVS = (100-hematocrit (%))/hemoglobin (g/dl). The change of ePVS was calculated using Strauss formula[17], namely: △ePVS = 100⋅(hemoglobin (before)/hemoglobin (after))⋅[(1-hematocrit (after))/(1-hematocrit (before))]-100. △ePVS(+) (△ePVS༞0) represented increased PV, while △ePVS(-) (△ePVS༜0) represented decreased PV[18]. CCS, devised by LE Rohde et al.[19] in 2014, is used to summarize the clinical symptoms and signs of patients with HF. Seven items (pulmonary rales, third heart sound, jugular distension, peripheral edema, hepatojugular reflux, orthopnea, and NYHA classification) are included in this scale. A scale of 0–1 point is applied for the third heart sound and hepatojugular reflux, and a scale of 0–4 points is used to grade other items. The total score of the scale is obtained by adding the score of each item (range: 0–22 points). A higher score indicates more severe congestion. In our study, CCS was evaluated on both day 1 and day 7 of hospitalization, and △CCS represented the change of congestion status (△CCS = [CCS (after) – CCS (before)]). △CCS(+) (△CCS༞0) represented serious aggravation of congestion signs and symptoms, while △CCS(-) (△CCS༜0) represented alleviation of congestion signs and symptoms.

eGFR (mL/min/1.73m²) was calculated using the simplified Modification of Diet in Renal Disease (sMDRD) formula and Chronic Kidney Disease Epidemiology Colaboration (CKD-EPI). NT-proBNP was analyzed by a fully automated, sample-selective analyzer using a Roche Elecsys proBNP Immunoassay. The instrument had a total coefficient of variation (CV) of 0.9% at 107ng/L and 1.3% at 2060ng/L.

All analyses were conducted using the SPSS 25.0 software (IBM Corp, Armonk, NY, USA). The continuous variables with normal distribution were presented as mean ± standard deviation (SD). The count data was presented as number (n) and percentages (%). The general data and the input and output of fluid balance at 1 to 7 days were compared between the two groups of △ePVS(-/+) and the two groups of △CCS(-/+) respectively by using Student’s t-test or χ² test. Univariate and multivariate logistic regression analyses were used to identify the influence of CFB on the increase of △ePVS and △CCS at 1 to 7 days. Factors that were significantly different in the Student’s t-test or χ² test were included as covariates in the multivariate logistic regression analysis. The influence and the cut-off values of the CFB at 1 to 7 days on △ePVS(་) and △CCS(་) were assessed respectively by the receiver operating characteristic curve (ROC) and Youden’s index. A two-sided P-value ༜0.05 was considered statistically significant.

The investigation conformed to the principles outlined in the Declaration of Helsinki. This study protocol was approved by the ethics committee of The First Affiliated Hospital with Nanjing Medical University Hospital (No. 2019-SR-473). It was promised that all data were used only for this study, and all reports would not involve the patient’s name and any other personal data. All patients signed the informed consents.

Among the 224 patients meeting the inclusion criteria, 15 were excluded because of discharge in advance, and 3 due to unqualified records in fluid balance chart. The 206 patients who were finally included were divided into △ePVS(+) group (106 cases, 51.5%) and △ePVS(-) group (100 cases, 48.5%) according to the change of PV. Meanwhile, they were also divided into △CCS(+) group (120 cases, 58.3%) and △CCS(-) group (86 cases, 41.7%) according to the aggravation or alleviation of congestion signs and symptoms. The general information and clinical characteristics of patients was presented in Table 1. Volume status of patients in group △ePVS(-/+) and △CCS(-/+) were compared separately (Table 1).

The volume of CFB, average daily volume and number/proportion of patients at 1 to 7 days were shown in Table 2. There were no statistical difference in the CFB between △ePVS(-/+) groups during the first 3 days. The CFB in △ePVS(+) group was higher than that in △ePVS(-) group at 4 to 7 days, and there was between-group statistical significance (Figure 1A). There was no statistical difference in the CFB between the △CCS(-/+) groups during the first 3 days. CFB in the △CCS(+) group was higher than that in △CCS(-) group at 4 to 7 days, and there was between-group statistical significance (Figure 1B).

Univariate logistic regression analysis was conducted using fluid balance at 1 to 7 days as an independent variable to predict the expansion of PV (△ePVS(+)). The results showed that CFB was a risk factor for △ePVS(+) at 4 days (OR = 1.165, 95%CI = 1.064-1.275, P = 0.001), at 5 days (OR = 1.194, 95%CI = 1.1-1.295, P＜0.001), at 6 days (OR = 1.075, 95%CI = 1.016-1.137, P＜0.001), and at 7 days(OR = 1.164, 95%CI = 1.093-1.239, P＜0.001). After adjusting for the course of HF, pulmonary rales on admission, peripheral edema on admission and 7 days after admission, orthopnea on admission, LVEF, eGFR, NT-proBNP, the multivariate logistic regression indicated that CFB was an independent risk factor for △ePVS(+) at 4 days (aOR = 1.135, 95%CI = 1.025-1.257, P＜0.015), at 5 days (aOR = 1.129, 95%CI = 1.034-1.232, P = 0.007 ), and at 7 days (aOR = 1.103, 95%CI = 1.032-1.179, P = 0.004) (Table 3).

According to ROC analysis of predicting △ePVS(-/+), the AUC of CFB at 4 to 7 days were 0.672 (0.599-0.746, P＜0.001), 0.722 (0.652-0.792, P＜0.001), 0.644 (0.566-0.721, P < 0.001), and 0.754 (0.687-0.822, P < 0.001). The maximum Youden index was considered as a cut-off value according to ROC Analysis[20]. The cut-off values of CFB were 2.308L, 3.361L, 3.625L, and 3.816L at 4 to 7 days, and the corresponding average daily volume was 0.577L, 0.672L, 0.604L, and 0.545L (Table 4, Figure 2A).

Univariate logistic regression analysis was conducted using CFB at 1 to 7 days as an independent variable to predict the aggravation of congestion signs and symptoms (△CCS(+)). The results showed that CFB was a risk factor for △CCS(+) at 4 days (OR = 1.121, 95%CI = 1.031-1.219, P = 0.007), at 5 days (OR = 1.161, 95%CI = 1.076-1.253, P＜0.001), at 6 days (OR = 1.089, 95%CI = 1.029-1.154, P = 0.004), and at 7 days (OR = 1.13, 95%CI = 1.067-1.196, P＜0.001). After adjusting for educational level, course of HF, LVEF, and △ePVS, the multivariate logistic regression indicated that CFB was an independent risk factor for △CCS(+) at 4 days (aOR = 1.109, 95%CI = 1.027-1.196, P = 0.008), at 6 days (aOR = 1.062, 95%CI = 1.001-1.126, P = 0.045), and at 7 days (aOR = 1.084, 95%CI = 1.023-1.149, P = 0.007) (Table 3).

According to ROC analysis of predicting △CCS (-/+), the AUC of CFB at 4 to 7 days were 0.625 (0.547-0.702, P＜0.001), 0.696 (0.625-0.768, P＜0.001), 0.656 (0.581-0.73, P < 0.001), and 0.709 (0.639-0.779, P < 0.001). The cut-off values of CFB were 2.308L, 3.383L, 4.670L, and 4.622L at 4 to 7 days, and the corresponding average daily volume were 0.577L, 0.677L, 0.778L, and 0.660L (Table 4, Figure 2B).

As shown in our study, with the gradual cumulation of fluid intake, the incidence of positive CFB and cumulative volume (CV) showed an increasing trend (Table 2). The positive CFB rate (65.53%) and CV (0.23 ± 1.00L) were the lowest at day 1. The positive CFB rate (74.76%) and CV (2.36 ± 5.46)L were the highest at day 6. Compared with patients after cardiac surgery or myocardial infarction, patients with HF have higher risk of positive CFB. The reason might be attributed to the neglection of the “hidden” expansion of PV during volume management[11]. In the clinical practice of our study sites, although daily fluid balance was estimated, it was believed that the daily fluid balance below 1L exerted almost no influence on the patients. But the results indicated that since excess fluid was not discharged timely, CFB kept increasing as time went by, which was consistent with the findings of Lixia Zeng et al.[11]. Positive CFB might result in increased volume load. As shown in Table 3, higher CFB at 4 to 7 days was associated with higher PV and worse congestion signs and symptoms. Consistent with our findings, Yasser et al.[21] found that the 24-hour CFB was not associated with an increased hazard of 28-day in-hospital death, while there was a stepwise increase in the hazard of death when the quartile of 3-day CFB was higher by observing 1808 ICU patients with sepsis. This can be explained by the effects of multiple regulatory mechanisms of the neuroendocrine system on fluid volume in human body. When positive fluid balance is little in amount and short in duration, the volume balance of body fluid can be maintained by activating the renin-angiotensin-aldosterone system (RAAS)[22]. Yet, if the fluid accumulates continuously, the dysfunction of RAAS might lead to volume overload, which is characterized by PV expansion and congestion[23]. In clinical practice, the observation of CFB should be conducted daily to guide the volume management in a more accurate way for patients with HF, and positive CFB should not last over 3 days.

As shown in Table 4, when CFB reached 2.308L at 4 days, the PV and congestion signs and symptoms became severe, indicating that 2.308L was the upper limit of safe positive CFB volume. This is consistent with the findings about safe volume in patients with peritoneal dialysis (PD) and hemodialysis (HD). Ya-Jun’s research showed that 2L was the upper limit of the safe volume load in PD by comparing the volume load of 92 PD and 45 healthy people[24]. And 2.5L was the cut-off value of overhydration in HD according the studies by Wabel P et al. and Wizemann V et al.[25, 26]. These results were very close to 2.308L, which supported the findings of the present study. Therefore, it was suggested that CFB should be controlled below 2.308L in patients with HF, and excess fluid should be removed as soon as possible in order to reduce the damage caused by volume overload.

As for the influence of CFB on patients with HF, the expansion of PV appeared earlier than congestion signs and symptoms. When CFB reached 2.308L, 3.361L, 3.625L, and 3.816L at 4 to 7 days, it could be judged that the PV expanded significantly (Table 4). When CFB reached 2.308L, 3.383L, 4.670L, and 4.622L at 4 to 7 days, it could be judged that the congestion signs and symptoms were significantly worsened (Table 4). Since the 5th day, the cut-off value indicating the severity of congestion signs and symptoms was higher than that of PV expansion, which suggested that the expansion of PV preceded the aggravation of congestion signs and symptoms. In clinical practice, volume overload tends to be ignored due to the absence of obvious congestion signs and symptoms when CFB is lower than 2.308L. Miller et al.[23] pointed out that hemodynamic changes, characterized by elevation in central venous and cardiac filling pressures, preceded the appearance of congestion signs and symptoms in patients with HF. Therefore, apart from congestion signs and symptoms, positive CFB also needs to be closely observed. Effective measures should be taken promptly to prevent negative outcomes resulted from volume overload.

Limitations: First, this study only discussed the influence of CFB on volume status during hospitalization. In the future, the fluid intake of patients after discharge will be followed up to explore the impact of CFB on death rate and rehospitalization rate. Second, only ePVS and CCS were used in this study to estimate the status of volume status in patients with HF, and more objective measurements are needed in future studies.

In conclusion, Patients with HF have a high incidence of positive CFB, and CFB increases as the fluid intake cumulate day by day. CFB is an independent risk factor for the expansion of PV and aggravation of congestion status. Higher CFB at 4 to 7 days indicates higher PV and more severe congestion. The results of this study suggest that the duration of positive CFB should not exceed 3 days, the upper limit of safe volume is 2.308L, and the expansion of PV appears earlier than congestion signs and symptoms.

Ethics approval and consent to participate

The study was conducted in line with the principles of the Helsinki Declaration. The study was approved by the ethics committee of the First Affiliated Hospital of Nanjing Medical University (approval NO.2019-SR-473) and informed consent was obtained from the participants.

Consent for publication

Not applicable.

Availability of data and materials

The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.

Competing interests

All authors declare no potential competing interests.

Funding

This project was supported by a grant from the Jiangsu Provincial Medical Innovation Team (CXTDA2017019).

Author contributions

WYW, ZJW and YFS conceived and designed the study. WYW, YLH and XHL collected the data. YFT and GZS performed the statistical analysis and interpreted the data. WYW and CHL wrote the first draft of the paper. ZJG revised the article. This manuscript was read and approved by all credited authors. All authors read and approved the final manuscript.

Acknowledgements

Not applicable.

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Table 1 General information and volume status of patients

	Total(n=206)	△ePVS(-)(n=106)	△ePVS(＋)(n=100)	p Value	△CCS(-)(n=86)	△CCS(＋)(n=120)	p Value
Age, years	65.83±12.81	67.5±13.59	64.07±11.73	0.055	66.35±13.25	65.47±12.52	0.627
Men, n (%)	130(63.11%)	69(65.7%)	61(61.6%)	0.543	54(62.8%)	76(64.4%)	0.056
BMI(kg/㎡)	23.4±3.69	23.56±3.39	23.24±3.99	0.528	23.47±3.68	23.36±3.72	0.825
NYHA class				0.394			0.155
1	4(1.94%)	2(1.9%)	2(2%)		1(1.2%)	3(2.5%)
2	42(20.39%)	19(17.9%)	23(23%)		16(18.6%)	26(21.7%)
3	124(60.19%)	62(58.5%)	62(62%)		48(55.8%)	76(63.3%)
4	36(17.48%)	23(21.7%)	13(13%)		21(24.4%)	15(12.5%)
Course of heart failure(month)	30.62±55.51	41±72.83^a	19.62±22.73^a	0.005*	40.26±78.3^b	23.72±28.52^b	0.035*
LVEF (%)	52.01±14.83	49.98±15.31^a	54.17±14.06^a	0.042*	48.9±15.97^b	54.24±13.59^b	0.010*
eGFR (mL/min/1.73 m²)	82.69±20.2	79.67±21^a	85.88±18.91^a	0.027*	80.72±19.76	84.09±20.47	0.239
NT-proBNP (pg/mL)	3225.97±5356.4	4387.71±6916.01^a	1994.53±2388.3^a	0.001*	3315.97±5357.88	3161.47±5376.88	0.839
Medicine, n (%)
ACEI/ARB	88(42.7%)	47(44.3%)	41(41%)	0.569	41(47.6%)	47(39.2%)	0.205
β-adrenoceptor blockers	116(56.31%)	58(54.7%)	58(58%)	0.635	53(61.6%)	63(52.5%)	0.193
Diuretic	144(69.9%)	71(67%)	73(73%)	0.347	56(65.1%)	88(73.3%)	0.205
Digitalis Glycosides	38(18.45%)	22(20.8%)	16(16%)	0.379	19(22.1%)	19(15.8%)	0.253
Admission CCS	4.3±1.13	4.68±1.15	3.9±0.97	＜0.001*	4.41±1.2	4.23±1.08	0.257
CCS at day 7	4.39±2.27	4.16±2.42	4.63±2.09	0.139	2.73±1.84^b	5.58±1.76^b	＜0.001
△CCS	0.09±2.05	-0.51±2.03	0.72±1.89	＜0.001*	-1.6±1.46^b	4.78±1.11	＜0.001
Admission Hemoglobin, (g/L)	129.35±18.46	123.59±17.63	135.45±17.4	＜0.001*	128.05±18.17	130.28±18.68	0.392
Admission Hematocrit (%)	39.42±5.51	37.75±5.34	41.19±5.15	＜0.001*	39.04±5.75	39.69±5.34	0.407
Admission ePVS (dl/g)	4.84±1.13	5.19±1.13^a	4.47±1.02^a	＜0.001*	4.92±1.17	4.78±1.11	0.393
Hemoglobin at day 7 (g/L)	129.39±17.74	126.41±17.96^a	132.55±17.03^a	0.013*	129.49±18.2	129.32±17.48	0.946
Hematocrit at day 7 (%)	39.31±5.3	39.25±5.43	39.36±5.19	0.887	39.92±5.32	38.86±5.26	0.158
ePVS at day 7 (dl/g)	4.83±1.06	4.95±1.08	4.7±1.02	0.088	4.79±1.08	4.86±1.05	0.597
△ePVS (dl/g)	0.35±7.2	-4.51±5.01^a	5.5±5.36^a	＜0.001*	-2.24±7.59^b	2.21±6.32^b	＜0.001

^ap＜0.05, △ePVS(-) vs. △ePVS(＋); ^bp＜0.05, △CCS(-) vs. △CCS(＋)

CCS: clinical congestion scores; ePVS: estimated plasma volume; PND: paroxysmal nocturnal dyspnea

Table 2

CFB at 1 to 7 days(n = 206)
Cumulative days	Volume of CFB(L/d)	Average daily volume(L/d)	Number (proportion) of people in positive balance
T₁	0.229 ± 0.996	0.229 ± 0.996	135(65.534%)
T₂	0.568 ± 1.882	0.284 ± 0.941	142(68.932%)
T₃	0.832 ± 2.475	0.277 ± 0.825	143(69.417%)
T₄	1.591 ± 3.665	0.398 ± 0.916	153(74.272%)
T₅	2.009 ± 4.586	0.402 ± 0.917	150(72.816%)
T₆	2.362 ± 5.462	0.394 ± 0.910	154(74.757%)
T₇	2.171 ± 6.394	0.310 ± 0.913	143(69.417%)
CFB: Cumulative fluid balance; T1-T7 represent cumulative 1 to 7 days respectively

Table 3 Univariate and multivariate logistic regression analyses of the influence of CFB on △ePVS (-/+) and △CCS (-/+) at 1 to 7 days

	Univariable analysis					Multivariable analysis
	OR (95%CI)		p value			aOR (95%CI)	p value
△ePVS(-/+)
T₁FB	1.036(0.787-1.364)		0.801			0.892(0.627-1.269)	0.526
T₂FB	0.889(0.764-1.033)		0.124			1.01(0.843-1.209)	0.917
T₃FB	1.064(0.951-1.192)		0.279			1.109(0.966-1.274)	0.142
T₄FB	1.165(1.064-1.275)		0.001			1.135(1.025-1.257)	0.015
T₅FB	1.194(1.100-1.295)		0.000			1.129(1.034-1.232)	0.007
T₆FB	1.075(1.016-1.137)		0.013			1.04(0.979-1.105)	0.206
T₇FB	1.164(1.093-1.239)		0.000			1.103(1.032-1.179)	0.004
△CCS(-/+)
T₁FB		0.894(0.674-1.185)		0.435	0.904(0.664-1.229)			0.518
T₂FB		1.016(0.877-1.177)		0.837	1.044(0.888-1.228)			0.602
T₃FB		1.026(0.918-1.148)		0.647	1.024(0.903-1.161)			0.716
T₄FB		1.121(1.031-1.219)		0.007	1.073(0.982-1.173)			0.117
T₅FB		1.161(1.076-1.253)		＜0.001	1.109(1.027-1.196)			0.008
T₆FB		1.089(1.029-1.154)		0.004	1.062(1.001-1.126)			0.045
T₇FB		1.13(1.067-1.196)		＜0.001	1.084(1.023-1.149)			0.007

Multivatiable analysis of △ePVS(-/+) was adjusted for course of heart failure, left ventricular ejection fraction, estimated glomerular filtration rate, N-terminal pro-B-type natriuretic peptide

Multivatiable analysis of △CCS(-/+) was adjusted for course of heart failure, left ventricular ejection fraction, △ePVS

CFB: cumulative fluid balance; CCS: clinical congestion scores; ePVS: estimated plasma volume; T1FB-T7FB abbreviate from the cumulative fluid balance at 1 to 7 days; aOR: adjusted odd ratio

Table 4 ROC curve analysis of CFB in prognosis of △ePVS(-/＋) and △CCS (-/+)

Item		AUC（95%CI）		P value		Clinical cut-off		Average daily volume		Sensitivity		Specificity
△ePVS(-/＋)
T₁FB		0.519(0.439-0.598)		0.639		-		-		-		-
T₂FB		0.428(0.349-0.507)		0.074		-		-		-		-
T₃FB		0.528(0.449-0.607)		0.490		-		-		-		-
T₄FB		0.672(0.599-0.746)		＜0.001		2.308		0.577		0.57		0.75
T₅FB		0.722(0.652-0.792)		＜0.001		3.361		0.672		0.61		0.81
T₆FB		0.644(0.566-0.721)		＜0.001		3.625		0.604		0.59		0.76
T₇FB		0.754(0.687-0.822)		＜0.001		3.816		0.545		0.68		0.83
△CCS(-/＋)
T₁FB	0.476(0.397-0.555)		0.560		-				-		-
T₂FB	0.492(0.413-0.571)		0.850		-				-		-
T₃FB	0.509(0.429-0.589)		0.826		-				-		-
T₄FB	0.625(0.547-0.702)		0.002		2.308		0.577		0.500		0.721
T₅FB	0.696(0.625-0.768)		＜0.001		3.383		0.677		0.550		0.837
T₆FB	0.656(0.581-0.73)		＜0.001		4.670		0.778		0.458		0.895
T₇FB	0.709(0.639-0.779)		＜0.001		4.622		0.660		0.500		0.907

CFB: cumulative fluid balance; ePVS: estimated plasm volume; CCS: clinical congestion scores; T1FB-T7FB: the cumulative fluid balance at 1 to 7 days

No competing interests reported.

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The influence of cumulative fluid balance on volume status in patients with heart failure: a multicenter cohort study

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