Serum sodium on admission affects postoperative in-hospital mortality in acute aortic dissection patients.

BACKGROUND: Acute aortic dissection (AAD) is very fatal without surgical treatment. Higher serum sodium can increase in-hospital mortality of many diseases; however, the effect of serum sodium on postoperative in-hospital mortality in AAD patients remains unknown.
METHODS: We collected a total of 415 AAD patients from January 2015 to December 2019. Patients were classified into four categories (Q1-Q4) according to the admission serum sodium quartile. The cox proportional hazards model evaluated the association between serum sodium and in-hospital mortality. All-cause in-hospital mortality was set as the endpoint.
RESULTS: By adjusting many covariates, cox proportional hazards model revealed the in-hospital mortality risk of both Q3 and Q4 groups was 3.086 (1.242-7.671, P = 0.015) and 3.370 (1.384-8.204, P = 0.007) respectively, whereas the risk of Q2 group was not significantly increased. Univariate and multiple Cox analysis revealed that Stanford type A, serum glucose, α-hydroxybutyrate dehydrogenase and serum sodium were risk factors correlated with in-hospital death in AAD patients.
CONCLUSION: The study indicates that the admission serum sodium of AAD patients has a vital impact on postoperative hospital mortality.

Introduction

Acute aortic dissection (AAD) has a high mortality rate, and the mortality risk for AAD patients increases by 1% per hour before medical and surgical intervention [1]. Presently, the best way to reduce mortality rate for AAD patients is timely operation. Despite increasingly rapid diagnosis and surgical management, the in-hospital mortality rate for AAD remains at >30% [2]. In addition, due to the change of economic level and residents’ eating habits recently, the incidence rate of AAD remains rising.

Hypernatremia, defined as >145 mmol/L sodium levels, was reported in 2% of patients admitted to the emergency department [3]. The abnormal increase of serum sodium levels is positively associated with the mortality risk of patients with various diseases, like severe craniocerebral injury [4], aneurysm subarachnoid hemorrhage [5], and nervous system disease [6]. A study of an unrestricted hospitalized adult population in the United States reported that >142 mmol/L serum sodium concentration has been associated with mortality and different degrees of hypernatremia including mild, middle, and higher levels are associated with in-hospital mortality [7]. Even in a healthy population, higher levels of plasma sodium starting from 138 mmol/L were associated with a higher risk of mortality, especially when the sodium level exceeded 145 mmol/L [8, 9]. However, no study on the relationship between serum sodium upon admission and in-hospital mortality of AAD patients exists, since electrolyte disturbances in emergency AAD patients can easily be ignored. Therefore, this study aims to discuss whether the serum sodium associates with the postoperative in-hospital mortality of AAD patients.

Methods

Study population

This study was designed as a retrospective observational study that continuously collected data on AAD patients who underwent surgery in the Fourth Hospital of Hebei Medical University from January 2015 to December 2019. All patients were diagnosed by computed tomographic angiography (CTA) or magnetic resonance angiography (MRA), and medical history. The aortic dissection is considered as AAD if the time from the onset of the symptom to operation is within 14 days. Exclusion criteria included connective tissue diseases, pregnancy, traumatic dissection, and infection diseases as well as the severe lack of clinical data which is defined as the absence of complete hospitalization records, involving lack of blood glucose, blood pressure and other important indicators associated with the known risk factors of AAD. Except for basic information and indicators associated with the known risk factors of AAD, some other defect data were considered to be a moderate missing for some individual patients, who were included in the study.

All clinical data related to the study were obtained after approved by the ethics committee of the Fourth Hospital of Hebei Medical University. As patient data were anonymized, the ethics committee of the Fourth Hospital of Hebei Medical University waived the written informed consent. All procedures followed were in accordance with the revised Declaration of Helsinki.

Clinical data collection

Clinical variables of enrolled patients with AAD was obtained through review of medical records, including gender, age, Stanford type, medical history (hypertension, diabetes, coronary artery disease, prior surgery, prior trauma, smoking and drinking), vital signs on admission (systolic blood pressure, SBP; diastolic blood pressure, DBP; heart rate) and laboratory data on admission (alanine transaminase, ALT; aspartate transaminase, AST; creatinine; urea nitrogen; serum glucose; α-hydroxybutyric dehydrogenase, α-HBDH; white blood cell count, WBC; neutrophil count, serum sodium, et al.) as well as the length of in-hospital [10]. Smoking is defined as at least 1 cigarette daily for 1 year or more, and alcohol consumption is defined as at least once per week for a period of one month or longer. Notely, the determination of serum sodium and other ions was done by automatic electrolyte analyzer (Shenzhen Kangli AFT—500D), with high accuracy and good precision (the CV value of Na detection was generally 0.60%), which is sufficient to meet the accuracy of this research. Stanford type A aortic dissections involve the ascending aorta whereas Stanford type B dissections involve the descending but not the ascending aorta [11]. The laboratory results were obtained using the patients’ first venous blood samples taken on admission to the hospital. The principles and strategies of surgical techniques were determined by experienced surgeons. The outcomes of in-hospital patients with AAD were gathered from medical records. All-cause mortality during hospitalization was defined as the endpoint.

Statistical analysis

According to the quartile of serum sodium concentration on admission, the patients were divided into four groups (quartile 1- quartile 4, Q1- Q4). Continuous variables were expressed as mean ± SD or median (quartile range). Categorical variables were expressed as the number of patients (%). One-way analysis of variance (ANOVA) test and Kruskal-Wallis H test were used to compare the difference of continuous variables between quartile groups. The chi-squared test or Fisher’s exact test was used to compare categorical variables. Proportional hazards assumption (PH) and Schoenfeld residual method were performed to test the availability of Cox proportional risk model. Univariate and multivariate cox proportional hazards model was employed to evaluate the association between serum sodium and in-hospital mortality. We constructed three models: crude model, with no adjustment of covariates; model 1, adjusted for age and gender; and model 2 including other covariates presented in Tables 3 and 4 [12]. Survival curves were constructed using the Kaplan–Meier method estimates and compared with the log-rank test. All the analyses were carried out with SPSS 25.0, two sided P values < 0.05 were considered statistically significant.

Result

Baseline characteristics of selected participants

A total of 415 AAD patients were enrolled in the present study based on the inclusion and exclusion criteria (Fig 1). Table 1 shows patient characteristics according to the survival situation at the time of discharge. Among the 415 patients, 61 (14.70%) died after surgery during hospitalization, and 354 (85.30%) survived. The SBP (130.07 ± 23.87 vs. 140.5 ± 28.91 mmHg, P = 0.008) and the DBP (75.28 ± 18.00 vs. 81.25 ± 19.39 mmHg, P = 0.025) of the non-survivors were lower than the survivors. The percentage of Stanford type A in the non-survivor group was more than that in the survivor group (93.44 vs. 56.78%, P < 0.001). The length of the in-hospital stay was significantly shorter in the death group than in the survival group (2 [1, 9] vs. 14 [7, 21] days, P < 0.001). AST (43.20 [24.05, 81.75] vs. 29.75 [19.00, 49.80] U/L, P = 0.006), creatinine (105.00 [68.00, 141.50] vs. 77.50 [62.00, 104.25] μmol/L, P = 0.004), and serum glucose (7.76 [6.43, 10.37] vs. 7.13 [5.98, 8.53] mmol/L, P = 0.009) levels were significantly higher in the death than in the survival group. α-HBDH (206.00 [165.80, 298.70] vs. 258.30 [173.00, 371.40] U/L, P = 0.029) was lower in the death than in the survival group. Serum sodium (140 ± 6.55 vs. 138 ± 4.38 mmol/L, P = 0.006) and serum chloride (105.70 [103.00, 110.00] vs. 104.00 [101.00, 107.00] mmol/L, P = 0.002) levels were also higher in the death than in the survival group.

Fig 1

Flow chart of patient enrollment.

Table 1

Baseline characteristics of patients with AAD.

Variable	Non-survivor (n = 61)	Survivor (n = 354)	P
Years	54.21±12.68	53.01±12.15	0.479
Male(N,%)	39,63.93	266,71.14	0.067
Hypertension(N,%)	46,75.41	258,72.88	0.680
Diabetes(N,%)	2,3.28	6,1.69	0.405
CAD(N,%)	4,6.56	14,3.95	0.357
Smoking(N,%)	27,44.26	190,53.67	0.174
Drinking(N,%)	31,50.82	202,57.06	0.364
Stanford type A(N,%)	57,93.44	201,56.78	<0.001
History of trauma(N,%)	4,6.56	17,4.80	0.564
Surgical history(N,%)	18,29.50	90,25.42	0.502
Heart rate(b.P.m)	79±16.97	80.57±17.60	0.577
SBP(mmHg)	130.07±23.87	140.50±28.91	0.008
DBP(mmHg)	75.28±18.00	81.25±19.39	0.025
length of hospital(day)	2(1,9)	14(7,21)	<0.001
ALT(U/L)	26.70(16.4,43.55)	21.75(15.50,31.88)	0.084
AST(U/L)	43.20(24.05,81.7)	29.75(19.00,49.80)	0.006
Creatinine(μmol/L)	105.00(68.00,141.50)	77.50(62.00,104.25)	0.004
Urea nitrogen(mmol/L)	7.00(5.45,9.25)	6.10(4.70,8.10)	0.060
Serum glucose(mmol/L)	7.76(6.43,10.37)	7.13(5.98,8.53)	0.009
AHB(U/L)	206.00(165.80,298.70)	258.30(173.00,371.40)	0.029
WBC count(10*9/L)	12.45±4.83	11.74±3.88	0.282
Neutrophil count(10*9/L)	9.56(7.47,12.57)	9.83(7.46,12.46)	0.570
Lymphocyte count(10*9/L)	0.87(0.67,1.08)	0.94(0.65,1.33)	0.291
Monocyte count(10*9/L)	0.66(0.50,0.93)	0.67(0.51,0.92)	0.714
Serum sodium(mmol/L)	140±6.55	138±4.38	0.006
Serum potassium(mmol/L)	4.00(3.35,4.10)	4.00(3.40,4.00)	0.418
Serum chloride(mmol/L)	105.70(103.00,110.00)	104.00(101.00,107.00)	0.002
Serum calcium(mmol/L)	2.14(2.06,2.26)	2.18(2.10,2.28)	0.129

CAD: coronary artery disease; SBP: systolic blood pressure; DBP, diastolic blood pressure; ALT: Alanine transaminase; AST: Aspartate transaminase; α-HBDH: alpha-hydroxybutyric dehydrogenase; WBC: white blood cell.

For numerical raw data, please see S1 Data.

Moreover, across all quartiles (Q1: ≤ 136 mmol/L, Q2: 137–138 mmol/L, Q3: 139–140 mmol/L, Q4: ≥141 mmol/L), there were statistical differences in years, monocyte count, and serum chloride. Meanwhile, the highest serum sodium quartile group had a higher neutrophil count (Table 2).

Table 2

Clinical characteristics of patients of serum sodium quartiles.

Variable	Q1(n = 114)	Q2(n = 103)	Q3(n = 102)	Q4(n = 96)
Age(years)*	51.18±12.61	52.50±13.11	56.11±11.93	53.21±10.53
Male(N,%)	83,72.80	79,76.70	75,73.53	68,79.83
Hypertension(N,%)	80,70.18	74,71.84	78,76.47	72,75.00
Diabetes(N,%)	1,0.87	3,2.91	1,0.98	3,3.13
CAD(N,%)	4,3.51	7,6.80	5,4.90	2,2.08
Smoking(N,%)	60,52.63	47,45.63	61,59.80	49,51.04
Drinking(N,%)	62,53.39	57,55.33	59,57.84	55,57.29
Stanford type A	63,55.26	67,65.05	59,57.84	69,71.88
non-survivor **	6,9.52	11,16.42	18,30.51	22,31.88
survivor	57,90.48	56,83.58	42,71.19	47,68.12
History of trauma(N,%)	4,3.51	4,3.88	9,8.82	4,4.17
Surgical history(N,%)	27,23.68	28,27.18	28,27.45	25,26.04
Heart rate(b.p.m)	82.18±15.46	80.03±21.02	79.90±14.94	79.07±18.23
SBP(mmHg)	139.02±26.92	140.65±27.24	138.75±31.60	137.33±28.26
DBP(mmHg)	80.25±17.48	81.94±19.77	80.68±21.22	78.49±18.63
length of in-hospital(day)	13.46±8.62	12.83±8.48	11.54±8.94	13.89±9.73
ALT(U/L)	24.25(15.45,32.53)	19.80(14.00,29.20)	22.60(15.90,31.96)	24.75(16.65,36.00)
AST(U/L)	33.80(19.93,52.80)	28.00(18.30,46.70)	29.25(19.45,49.53)	32.65(20.61,67.55)
Creatinine(μmol/L)	79.50(61.75,110.00)	80.00(63.00,111.00)	72.50(60.75,103.50)	84.50(65.00,122.25)
Urea nitrogen(mmol/L)	6.00(4.30,7.35)	6.80(5.00,8.90)	5.95(4.80,7.70)	6.60(5.40,8.70)
Serum glucose(mmol/L)	7.17(6.13,9.09)	7.11(5.97,9.32	7.70(5.97,8.11)	7.40(6.32,9.15)
α-HBDH(U/L)	214.90(167.50,302.95)	208.80(160.90,311.90)	197.90(161.95,271.60)	233.85(182.90,328.85)
WBC count(10*9/L)	11.81±4.19	11.51±3.61	11.47±3.29	12.64±4.86
Neutrophil count(10*9/L)*	9.93±4.04	9.78±3.57	9.71±3.28	11.35±4.75
Lymphocyte count(10*9/L)	0.94(0.65,1.28)	0.96(0.67,1.40)	0.62(0.44,0.86)	0.94(0.65,1.23)
Monocyte count(10*9/L)*	0.70(0.55,0.97)	0.62(0.44,0.86)	0.64(0.51,0.93)	0.75(0.54,1.03)
Serum potassium(mmol/L)	3.90(3.40,4.00)	4.00(3.40,4.00)	4.00(3.40,4.10)	4.00(3.40,4.18)
Serum chloride(mmol/L)*	101.00(97.99,104.00)	105.00(102.00,106.00)	105.85(103.00,109.00)	107.35(104.00,110.00)
Serum calcium(mmol/L)	2.16(2.09,2.24)	2.17(2.10,2.29)	2.20(2.10,2.28)	2.18(2.11,2.29)

*: P < 0.05

**: Stanford type A as subgroup, compared in-hospital mortality in Q1-Q4 groups, P < 0.05. CAD: coronary artery disease; SBP: systolic blood pressure; DBP, diastolic blood pressure; ALT: Alanine transaminase; AST: Aspartate transaminase; α-HBDH: alpha-hydroxybutyric dehydrogenase; WBC: white blood cell.

For numerical raw data, please see S1 Data.

Survival curve analysis

To further investigate the relationship between patient survival and serum sodium in AAD, a comparison of Kaplan–Meier curves with the different serum sodium levels was conducted. Fig 2 shows Kaplan–Meier survival curves that proved a decreased short-term survival associated with admission serum sodium in AAD patients (from Q1 to Q4 groups, log-rank test P = 0.010).

Fig 2

Kaplan-Meier curves for the chronological trend in mortality on serum sodium quartiles groups.

In-hospital mortality analysis

Next, the in-hospital mortality of AAD patients was further analyzed in accordance with the admission serum sodium quartiles. Fig 3 shows that the significant increase of in-hospital mortality was accompanied by a gradual elevation in serum sodium levels in admitted AAD patients (Q1, 7.02%; Q2, 11.65%; Q3, 18.62%; Q4, 22.92%; P = 0.006).

Fig 3

In-hospital mortality stratified by admission serum sodium quartiles.

Basing on the Q1 group as a reference, in-hospital mortality risk slightly increased in the Q2 group, however, it was significantly increased by 2.890-fold with Q3 and by 3.253-fold with Q4, respectively.

Following the adjustment for gender and years (model 1), the death risk of the Q3 and Q4 groups was still 2.825-fold (95% CI, 1.228–6.502-fold; P = 0.015) and 3.241-fold (95% CI, 1.441–7.290-fold; P = 0.004), respectively, while a 1.728-fold elevation in the Q2 group also occurred (95% CI, 0.705–4.233; P = 0.232).

More importantly, following the adjustment for gender, age, Stanford type, hypertension, diabetes, coronary artery disease, smoking, drinking, serum glucose, and α-HBDH (model 2), the in-hospital mortality risk was further elevated in Q3 (HR = 3.086, 95% CI, 1.242–7.671; P = 0.015) and Q4 (HR = 3.370, 95% CI, 1.384–8.204; P = 0.007), respectively, although the risk in Q2 (HR = 1.718, 95% CI, 0.658–4.486; P = 0.269) still is not significantly increased (Table 3).

Table 3

Relationship between serum sodium and in-hospital mortality in different models of serum sodium quartiles.

		Q1(n = 114)	Q2(n = 103)	Q3(n = 102)	Q4(n = 96)
in-hospital mortality		8(7.0%)	12(11.7%)	19(18.6%)	22(22.9%)
in-hospital mortality(HR)	Crude model	ref	1.707(0.698–4.178), P = 0.241	2.890(1.264–6.604), P = 0.012	3.253(1.447–7.312), P = 0.004
	Model 1	ref	1.728(0.705–4.233), P = 0.232	2.825(1.228–6.502), P = 0.015	3.241(1.441–7.290), P = 0.004
	Model 2	ref	1.718(0.658–4.486), P = 0.269	3.086(1.242–7.671), P = 0.015	3.370(1.384–8.204), P = 0.007

Model 1: Adjusted for age, gender; Model 2: Adjusted for age, gender, Stanford type, hypertension, diabetes, CAD, smoking, drinking, serum glucose, α-HBDH.

For numerical raw data, please see S1 Data.

Univariate and multiple Cox analysis for in-hospital mortality

In order to verify whether Cox proportional risk model would be available for the short-term survival analysis in AAD patients, proportional hazards assumption (PH) and schoenfeld residual method were performed to test the assumption. We plot the smooth curve residual diagram of Schoenfeld’s residual with time, and the results showed no linear correlation between Schoenfeld’s residual and time rank (Fig 4). Moreover, we tested that the correlation between Schoenfeld’s residual and time rank, and found that Schoenfeld’s residual was independent on time variables (Pearson correlation coefficient, r = -0.22, P = 0.864). Based on these two results of the smooth curve trend and the Pearson correlation from Schoenfeld’s residual analysis, indicating that Cox model is suitable for the short-term survival analysis.

Fig 4

The smooth curve residual diagram of Schoenfeld’s residual with time.

Univariate analysis indicated that eight variables, including Stanford type A, SBP, DBP, creatinine, serum glucose, α-HBDH, serum sodium, and serum calcium, were associated with in-hospital mortality with a P-value of <0.10 and were put into cox regression (forward LR method) analysis, the results showing that Stanford type A (HR = 3.634, 95% CI, 1.638–8.086; P = 0.002), serum glucose (HR = 1.077, 95% CI, 1.025–1.132; P = 0.003), α-HBDH (HR = 1.001, 95% CI, 1.001–1.002; P < 0.001), and serum sodium (HR = 1.068, 95% CI, 1.029–1.109, P = 0.001) were risk factors correlated with in-hospital mortality in AAD patients (Table 4).

Table 4

Univariate and multiple Cox analysis for in-hospital mortality of serum sodium quartiles groups.

	Univariate			Multivariate
	HR	95%CI	P	HR	95%CI	P
years	1.014	0.994–1.034	0.171
male	0.678	0.414–1.111	0.123
Hypertension	1.312	0.684–2.152	0.509
Diabetes	1.004	0.246–4.101	0.995
CAD	1.430	0.617–3.317	0.404
Smoking	0.768	0.474–1.243	0.282
Drinking	0.873	9,543–1.405	0.576
Stanford type A	4.503	2.048–9.899	<0.001	3.634	1.638–8.060	0.002
History of trauma	1.485	0.540–4.081	0.443
Surgical history	1.127	0.663–1.914	0.659
Heart rate	0.998	0.984–1.012	0.770
SBP	0.987	0.978–0.995	0.002
DBP	0.986	0.973–0.999	0.032
ALT	1.000	0.999–1.001	0.814
AST	1.000	1.000–1.000	0.996
Creatinine	1.002	1.000–1.003	0.044
Urea nitrogen	1.028	0.994–1.063	0.106
Serum glucose	1.067	1.018–1.117	0.007	1.077	1.025–1.132	0.003
α-HBDH	1.001	1.001–1.002	<0.001	1.001	1.001–1.002	<0.001
WBC count	1.029	0.973–1.088	0.312
Neutrophil count	1.032	0.975–1.093	0.274
lymphocyte count	0.754	0.462–1.228	0.256
Monocyte count	1.405	0.738–2.675	0.300
Serum sodium	1.074	1.035–1.116	<0.001	1.068	1.029–1.109	0.001
Serum potassium	0.999	0.983–1.015	0.889
Serum chloride	1.011	0.989–1.033	0.344
Serum calcium	0.255	0.073–0.899	0.034

CAD: coronary artery disease; SBP: systolic blood pressure; DBP, diastolic blood pressure; ALT: Alanine transaminase; AST: Aspartate transaminase; α-HBDH: alpha-hydroxybutyric dehydrogenase; WBC: white blood cell.

For numerical raw data, please see S1 Data.

Discussion

AAD is a fatal cardiovascular disease [13]. Since the underlying mechanisms of the development and progression of spontaneous AAD cases remain unclear, a screening or prevention strategy for these patients has yet to be developed [14]. In previous studies, preoperative creatinine, uric acid, serum tenascin-C, and inflammatory factors were all associated with postoperative mortality following AAD [10, 15–17]. Additionally, poor organ perfusion and hemodynamic conditions, such as hypotension, shock, pericardial tamponade, pulse deficiency, and renal failure, further contribute to higher mortality in AAD patients [12]. The present study was the first to evaluate the relationship between serum sodium upon admission and in-hospital mortality of AAD patients, the results showing the increased in-hospital mortality risk in AAD patients with high-sodium levels upon admission. The higher serum sodium levels remained independently associated with in-hospital mortality even when adjusted for gender, years, Stanford type, hypertension, diabetes, coronary artery disease, smoking, drinking, serum glucose, and α-HBDH. Serum sodium ≥139 mmol/L will increase the in-hospital mortality risk in AAD patients.

Serum sodium within or above the normal range, as a common consequence of dehydration and high salt consumption [9], has been associated with decreased left ventricular contractility, increased peripheral insulin resistance, and neuromuscular disturbances [18]. High-sodium intake or an excess of aldosterone increases both local and systemic inflammatory reactions, which are T cell- and macrophage-related [19]. It has been suggested that serum sodium may change vascular function. Oberleithner et al. reported that, in cultured human endothelial cells, cell stiffness increased by 20% within minutes of raising the medium sodium concentration from 135 to 145 mmol/L, which is associated with a reduced nitric oxide formation and endothelial nitric oxide synthase activity, suggesting that an altered plasma sodium concentration may affect vascular endothelial function and thus control vascular tone [20]. Dmitrieva NI et al. [21] also showed that the serum sodium can significantly predict a 10-year risk of coronary heart disease and demonstrated that slight elevations of extracellular sodium increase the expression of pro-inflammatory mediators in endothelial cells and their adhesive properties, which is accompanied by vascular biology changes, contributing to the development of cardiovascular diseases. Importantly, Anzai et al. [22] found that the massive neutrophil accumulation in the tunica adventitia of the dissected aorta leads to the onset of aortic dissection as well as subsequent aortic rupture [11]. Consistently, in our study, the neutrophil count in AAD patients with the highest serum sodium level (Q4 group) was significantly greater than that in the other three groups, suggesting that serum sodium may provoke and/or promote the formation and development of AAD through neutrophils, but the specific molecular mechanism needs to be further investigated.

Using the quartile for grouped serum sodium, the postoperative in-hospital mortality of AAD patients was higher in the Q3 (139–140 mmol/L) and Q4 (≥ 140 mmol/L) groups than that in the Q1 (≤ 136 mmol/L) group (P < 0.05). Tsipotis et al. [7] found that > 142 mmol/L serum sodium upon admission increased mortality on unselected in-hospital cohort. Similarly, we also found that the elevated serum sodium (≥ 139 mmol/L) can increase the postoperative in-hospital mortality in AAD patients. Thus, for AAD in-patients, it is not appropriate to take corresponding treatment measures only dependent on the standard of hypernatremia; accurately, managing patients with high serum sodium (139–145 mmol/L) is necessary to improve the prognosis of patients.

Acute type A aortic dissection (ATAAD) is a surgical emergency, with a 90% mortality rate in patients who do not receive timely operative intervention. Despite significant advances in imaging, perioperative care, and surgical technique, ATAAD operative mortality rates have remained relatively unchanged between 10% and 30% over the past two decades [23]. Abdelhamed et al. [24] reported an ATAAD early mortality after surgery of 15.4%. Our results also showed that ATAAD patients had higher in-hospital mortality (22.09%, 57/258), and ATAAD patients with increased serum sodium also had a higher early mortality after surgery (Q1, 9.52%; Q2, 16.42%; Q3, 30.51%; Q4, 31.88%), suggesting that serum sodium may be a surgical risk predictor for early mortality after ATAAD.

There were several limitations of the small cohort of patients in our study. First, this study was a single-center study; a multi-center study is needed in the future to demonstrate serum sodium levels independently associated with in-hospital mortality of AAD patients. Second, the long-term studies for the effect of serum sodium on in-hospital mortality in AAD patients are necessary to better assess and prevent the formation and progress of AAD. Additionally, due to the deaths occurred quickly before or after admission, AAD patients’ serum sodium value and other relevant data could not be collected immediately, where 6 hours is the shortest operation interval after admission in our hospital, therefore, some patients who died before surgery were not involved in this study, and these defect data may affect the results of the study.

Conclusions

Our data indicated that the admission serum sodium would be a potential predictive risk factor for postoperative hospital death of AAD patients. More attention must be paid to high admission serum sodium level in clinic.

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9 Apr 2021

PONE-D-20-40304

Serum sodium on admission affects postoperative in-hospital mortality in acute aortic dissection patients

PLOS ONE

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Reviewers' comments:

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Comments to the Author

1. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #1: Yes

Reviewer #2: Yes

**********

2. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: No

Reviewer #2: Yes

**********

3. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #1: Yes

Reviewer #2: Yes

**********

4. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #1: Yes

Reviewer #2: No

**********

5. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: Wang and colleagues carried-out a Research article testing the association between serum sodium quartile and in hospital mortality in patients with acute aortic dissection. The topis seems of interest. Please see below my criticisms:

- In abstract, serum sodium has been splitted into quartiles according to distribution. Was Q1 considered the reference in che cox model ? please specify this information since it has been stated that hazard ratio in Q3 and Q4 was increased but it was not reported the reference category. Please remember that the hazard ratio is a measure of relative risk (in time-to-event analyses)

- Methods: how variables have been added to the model 2 ? based on the plausibility of their association with short term mortality ? please clarify

- Methods: usually the variable sodium has a biphasic association with risk (U-shaped). This means that risk increases for both low and high sodium values. Was the linearity of effect of sodium on the endpoint tested?

- Following the previous point, I would suggest Authors to do a sensitivity analysis by replacing the category Q1 with Q2 as reference for the Cox model

- I am not fully sure that Cox model is appropriate for such analysis with short-term follow-up (of some days). It seems that the event occurs almost in the same period of sodium measurement. Can Authors provide one or more references which may clarify this point?

Reviewer #2: Abnormal serum sodium concentrations are common in patients presenting for surgery. It remains unclear whether these abnormalities are independent risk factors for postoperative mortality. The authors indicated that the admission serum sodium was an independent risk factor for postoperative hospital death of AAD patients. I would suggest

1. an English language editing;

2; to review fig n. 2 (low quality image)

3. to write the small cohort of patients in the study limitations

**********

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Reviewer #1: No

Reviewer #2: Yes: GIUSEPPE FILIBERTO SERRAINO

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15 Jun 2021

Point-by-point response to referees.

Reviewer #1:

Major concerns:

Q: (1) In abstract, serum sodium has been splitted into quartiles according to distribution. Was Q1 considered the reference in che cox model ? please specify this information since it has been stated that hazard ratio in Q3 and Q4 was increased but it was not reported the reference category. Please remember that the hazard ratio is a measure of relative risk (in time-to-event analyses)

A: Thanks for your careful review. According to your suggestion, we emphasized that Q1 is the reference in che cox model and marked in red word in revised manuscript.

Q: (2) Methods: how variables have been added to the model 2? based on the plausibility of their association with short term mortality ? please clarify

A: Thanks for your question. According to reference (Huaping He, Xiangping Chai, Yang Zhou, et al. Association of lactate dehydrogenase with in-hospital mortality in patients with acute aortic dissection: a retrospective observational study. Int J Hypertens. 2020, 2020:1347165.), we adjusted for age, gender, Stanford type, hypertension, diabetes, CAD, smoking, drinking, serum glucose, α-HBDH in model 2 to further analyse the association with short term mortality.

Q: (3) usually the variable sodium has a biphasic association with risk (U-shaped). This means that risk increases for both low and high sodium values. Was the linearity of effect of sodium on?

A: Thanks for your valuable suggestion. In this study, we only found that there was an increase of sodium levels in serum from AAD patients, and this increased value was not linear association with the endpoint tested (after surgery). Additionally, in the most studies, the increased sodium level is general in clinical reports, which is consistant with our result.

Q: (4) Following the previous point, I would suggest Authors to do a sensitivity analysis by replacing the category Q1 with Q2 as reference for the Cox model

A: Thanks for your suggestion. We performed strict inclusion and exclusion criteria to ensure the authenticity of the data. The methods used in the study are mature and reliable to ensure the accuracy of the results. Thus, we believe our conclusion is stable.

Q: (5) I am not fully sure that Cox model is appropriate for such analysis with short-term follow-up (of some days). It seems that the event occurs almost in the same period of sodium measurement. Can Authors provide one or more references which may clarify this point?

A: Thanks for your suggestion. There has been a reported paper on Cox model for short-term follow-up (Zhang S, Guo M, Duan L, et al. Development and validation of a risk factor-based system to predict short-term survival in adult hospitalized patients with COVID-19: a multicenter, retrospective, cohort study[J]. Crit Care, 2020, 24(1): 438.).

Reviewer #2:

Q: (1). an English language editing

A: Thank you for your valuable suggestion. We have changed the format as required. Please check.

Q: (2). to review fig n. 2 (low quality image)

A: Thank for your careful review. We uploaded a high quality image of fig2. Please check.

Q: (3). to write the small cohort of patients in the study limitations

A: Thanks for your suggestion. The first limitation was a single-center study, which is not enough to get strong warrant to prove serum sodium levels independently associated with in-hospital mortality of AAD patients. The other limitation is the short-term studies could not better assess the effect of serum sodium on in-hospital mortality in AAD patients. We have added these limitations in discussion.

Submitted filename: Response to Reviewers.docx

Click here for additional data file.

15 Jul 2021

PONE-D-20-40304R1

Serum sodium on admission affects postoperative in-hospital mortality in acute aortic dissection patients

PLOS ONE

Dear Dr. Ma,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

==============================

ACADEMIC EDITOR:

The Statistical Referee raised major concerns about the methodolgy used in this article. Please try to revise the manuscript in accordance to the comments reported below

==============================

Please submit your revised manuscript by Aug 29 2021 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at plosone@plos.org. When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.

Please include the following items when submitting your revised manuscript:

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If you would like to make changes to your financial disclosure, please include your updated statement in your cover letter. Guidelines for resubmitting your figure files are available below the reviewer comments at the end of this letter.

If applicable, we recommend that you deposit your laboratory protocols in protocols.io to enhance the reproducibility of your results. Protocols.io assigns your protocol its own identifier (DOI) so that it can be cited independently in the future. For instructions see: http://journals.plos.org/plosone/s/submission-guidelines#loc-laboratory-protocols. Additionally, PLOS ONE offers an option for publishing peer-reviewed Lab Protocol articles, which describe protocols hosted on protocols.io. Read more information on sharing protocols at https://plos.org/protocols?utm_medium=editorial-email&utm_source=authorletters&utm_campaign=protocols.

We look forward to receiving your revised manuscript.

Kind regards,

Michele Provenzano

Academic Editor

PLOS ONE

Additional Editor Comments (if provided):

Please note that the present manuscript has not yet sufficiently improved. In fact, several methodological flaws still persist. Please see the comments below

[Note: HTML markup is below. Please do not edit.]

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation.

Reviewer #3: (No Response)

**********

2. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #3: No

**********

3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #3: No

**********

4. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #3: Yes

**********

5. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #3: No

**********

6. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #3: In this manuscript, Huang et al examined the association of serum sodium level on admission with postoperative in-hospital mortality in 415 acute aortic dissection patients enrolled in the Fourth Hospital of Hebei Medical University. The authors found the serum sodium was significantly associated with in-hospital mortality risk. However, there are several concerns about the study.

1. One major concern is the proportional hazards assumption. There is huge difference between patients who survived and those who died (14 days vs 2 days). The authors should formally test the assumption before using the Cox model.

2. Another concern is that this is an association study. There is no way to derive causality effect. Please remove any implication of causality.

3. Please clarify how the variables were determined. For example, for the smoking, is it current smoker or past smoker? For drinking, how many drinks were used to determine the drinker status?

4. The exclusion criteria included the serious lack of clinical data. How is it defined? What about other variables with a moderate missing rate? Were they excluded or imputed?

5. Did any patient die before the operation? If so, will it affect the association? What is the time interval between admission and the operation?

6. It seems that the variation of sodium levels is very small (SD=4.8). All four quartiles included some participants with normal sodium levels (Q1 : ≤ 136 mmol/L, Q2 : 137 – 138 mmol/L, Q3: 139 -140 mmol/L, Q4 : ≥141 mmol/L). What would be measurement variability?

7. Can authors comment on the possible reasons why Q2 was not significant, but Q3 and Q4 were significant?

8. In Figure 2, please indicate the number of events under the x-axis. Also it is unclear why there was a big drop of survival probability in Day 40 for Q4, especially given the median of 2 days in the non-survival group.

9. In Figure 3, given that there is no direct connection between quarters, a barplot would be more appropriate.

**********

7. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

If you choose “no”, your identity will remain anonymous but your review may still be made public.

Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #3: No

[NOTE: If reviewer comments were submitted as an attachment file, they will be attached to this email and accessible via the submission site. Please log into your account, locate the manuscript record, and check for the action link "View Attachments". If this link does not appear, there are no attachment files.]

While revising your submission, please upload your figure files to the Preflight Analysis and Conversion Engine (PACE) digital diagnostic tool, https://pacev2.apexcovantage.com/. PACE helps ensure that figures meet PLOS requirements. To use PACE, you must first register as a user. Registration is free. Then, login and navigate to the UPLOAD tab, where you will find detailed instructions on how to use the tool. If you encounter any issues or have any questions when using PACE, please email PLOS at figures@plos.org. Please note that Supporting Information files do not need this step.

11 Sep 2021

Dear PLoS One Publications

Thank you very much for giving us an opportunity to revise our manuscript entitled" Serum sodium on admission affects postoperative in-hospital mortality in acute aortic dissection patients" (Manuscript No.: PONE-D-20-40304).

We have carefully read your letter and the reviewer comments and have performed a number of new experiments and revised the manuscript accordingly. All changes have been highlighted in red color in the revised manuscript. Point by point responses to the reviewers’ comments are listed below this letter.

Thank you and all the reviewers for the kind advice.

We hope that the revised version of the manuscript is acceptable for publication in PLoS One. Look forward to hearing from you.

Yours sincerely,

Dong Ma

Point-by-point response to referees.

Reviewer #3:

Major concerns:

Q: (1) One major concern is the proportional hazards assumption. There is huge difference between patients who survived and those who died (14 days vs 2 days). The authors should formally test the assumption before using the Cox model.

A: Thanks for your careful review. In order to verify whether Cox proportional risk model would be available for the short-term survival analysis in AAD patients, proportional hazards assumption (PH) and schoenfeld residual method were performed to test the assumption. We plot the smooth curve residual diagram of Schoenfeld's residual with time, and the results showed no linear correlation between Schoenfeld's residual and time rank (Fig 4). Moreover, we tested that the correlation between Schoenfeld's residual and time rank, and found that Schoenfeld's residual was independent on time variables (Pearson correlation coefficient, r = -0.22, P = 0.864). Based on these two results of the smooth curve trend and the Pearson correlation from Schoenfeld's residual analysis, indicating that Cox model is available to the short-term survival analysis of patients with AAD.

Fig 4 Schoenfeld residual diagram

Q: (2) Another concern is that this is an association study. There is no way to derive causality effect. Please remove any implication of causality.

A: Thanks for your good suggestion. We modified these inappropriate words as required in revised manuscript. Please check.

Q: (3). Please clarify how the variables were determined. For example, for the smoking, is it current smoker or past smoker? For drinking, how many drinks were used to determine the drinker status?

A: Thanks for your careful review. In this study, smoking is defined as at least 1 cigarette daily for 1 year or more, and alcohol consumption is defined as at least once per week for a period of one month or longer. We added these in part of methods and marked in red word. Please check.

Q: (4). The exclusion criteria included the serious lack of clinical data. How is it defined? What about other variables with a moderate missing rate? Were they excluded or imputed?

A: Thanks for your suggestion. In this study, the severe lack of clinical data is defined as the absence of complete hospitalization records, involving lack of blood glucose, blood pressure and other important indicators associated with the known risk factors of AAD. Except for basic information and indicators associated with the known risk factors of AAD, the other defect data were considered to be a moderate missing for some individual patients, who were included in the study. We revised the exclusion criteria in the part of methods marked in red word.

Q: (5) Did any patient die before the operation? If so, will it affect the association? What is the time interval between admission and the operation?

A: Thanks for your suggestion. Aortic dissection is a very dangerous disease, especially Stanford A type. Once AAD patient is diagnosed, emergency surgical treatment should be firstly required in principle. Due to the deaths occurred quickly before or after admission, AAD patients’ serum sodium value and other relevant data could not be collected immediately, where 6 hours is the shortest operation interval after admission in our hospital, therefore, some patients who died before surgery were not involved in this study, and these defect data may affect the results of the study. This is a limit for the study added in discussion in red word.

Q: (6). It seems that the variation of sodium levels is very small (SD=4.8). All four quartiles included some participants with normal sodium levels (Q1 : ≤ 136 mmol/L, Q2 : 137 – 138 mmol/L, Q3: 139 -140 mmol/L, Q4 : ≥141 mmol/L). What would be measurement variability?

A: In this study, automatic electrolyte analyzer (Shenzhen Kangli AFT--500D) was used for the determination of serum sodium and other ions, with high accuracy and good precision. The CV value of Na detection was generally 0.60%, which is sufficient to meet the accuracy of this research. We marked this analyzer in the part of methods in red word.

Q: (7). Can authors comment on the possible reasons why Q2 was not significant, but Q3 and Q4 were significant?

A: Thank for your suggestion. It was possible that Q2 (137-138 mmol/L) slightly affected postoperative mortality in patients with AAD, but it was not independent related to postoperative death in patients with AAD (HR=1.718 95%CI 0.688-4.486, P=0.269).The results of Q3 and Q4 showed that when the serum sodium≥ 139mmoL/L, the postoperative in-hospital mortality of AAD patients may be increased significantly, there exists an important association between serum sodium and the postoperative in-hospital mortality in the study.

Q: (8). In Figure 2, please indicate the number of events under the x-axis. Also it is unclear why there was a big drop of survival probability in Day 40 for Q4, especially given the median of 2 days in the non-survival group.

A: Thanks for your suggestion. We revised image of fig2, and please check.

Q: (9). In Figure 3, given that there is no direct connection between quarters, a barplot would be more appropriate.

A: Thanks for your suggestion. We replaced figure 3 with a barplot.

Submitted filename: Response to Reviewers2.docx

Click here for additional data file.

29 Nov 2021

Serum sodium on admission affects postoperative in-hospital mortality in acute aortic dissection patients

PONE-D-20-40304R2

Dear Dr. Ma,

We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements.

Within one week, you’ll receive an e-mail detailing the required amendments. When these have been addressed, you’ll receive a formal acceptance letter and your manuscript will be scheduled for publication.

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Kind regards,

Michele Provenzano

Academic Editor

PLOS ONE

Additional Editor Comments (optional):

The manuscript is nicely improved. Thank you for your work

Reviewers' comments:

6 Dec 2021

PONE-D-20-40304R2

Serum sodium on admission affects postoperative in-hospital mortality in acute aortic dissection patients

Dear Dr. Ma:

I'm pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now with our production department.

If your institution or institutions have a press office, please let them know about your upcoming paper now to help maximize its impact. If they'll be preparing press materials, please inform our press team within the next 48 hours. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information please contact onepress@plos.org.

If we can help with anything else, please email us at plosone@plos.org.

Thank you for submitting your work to PLOS ONE and supporting open access.

Kind regards,

PLOS ONE Editorial Office Staff

on behalf of

Dr. Michele Provenzano

Academic Editor

PLOS ONE