Association of Body Mass Index With Postoperative Early Adverse Outcomes in Acute Type a Aortic Dissection Patients in Fujian Province, China: A Retrospective Study

doi:10.21203/rs.3.rs-96028/v1

Download PDF

Research article

Association of Body Mass Index With Postoperative Early Adverse Outcomes in Acute Type a Aortic Dissection Patients in Fujian Province, China: A Retrospective Study

https://doi.org/10.21203/rs.3.rs-96028/v1

This work is licensed under a CC BY 4.0 License

Journal Publication

published 23 Mar, 2021

Read the published version in Journal of Cardiothoracic Surgery →

You are reading this older preprint version

Read the latest preprint version →

Background: Abnormal body mass index (BMI) has been related to a higher risk of adverse perioperative outcomes in patients undergoing cardiac surgery. However, the effects of BMI in patients with acute type A aortic dissection (AAAD) on postoperative outcomes remain unclear. The aims of this study were to explore the relationships of BMI and postoperative early adverse outcomes in AAAD patients

Methods: Patients who underwent AAAD surgery at Fujian Province Cardiac Medical Research Center from June 2013 to March 2020 were retrospectively evaluated. They were divided into three groups on the basis of Chinese BMI classification established by the World Health Organization: normal group (BMI 18.5-23.9 kg/m²), overweight group (BMI 24-27.9 kg/m²), and obesity group (BMI > 28kg/m²). Preoperative, intraoperative, and postoperative data were collected. Multivariable and univariable logistic regression analysis models were performed to identify whether BMI was independently associated with postoperative adverse outcomes.

Results: Of 777 cases, 31.9% were normal weight, 52.5% were overweight, and 15.6% were obese. The percentage of prolonged mechanical ventilation (44.9% vs 55.8% vs 66.1%, respectively; P<0.001) and the median duration of intensive care unit stays (8.1 vs 9.5 vs 12.0 days, respectively; P<0.001) were higher and longer in the overweight and obese group. Multivariable logistic regression analysis demonstrated that a higher risk of postoperative early adverse outcomes in the overweight (odds ratio [OR]: 2.374, 95%CI: 1.647–3.422), and obese patients (OR: 3.659, 95%CI: 2.122–6.308) with reference to the normal BMI patients, and age, heart rate, and surgery duration were also associated with postoperative early adverse outcomes (P<0.05).

Conclusion: Overweight and obese patients are independently associated with higher postoperative early adverse outcomes in patients who underwent AAAD surgery.

Cardiothoracic Surgery

Acute aortic dissection

Body mass index

Adverse outcomes

Obesity is generally considered to be a strong risk factor for morbidity and mortality during the perioperative period in patients with heart disease^[1]. Studies have reported obesity patients who underwent cardiac surgery were associated with adverse outcomes in recent years^[2,3]. However, some reports suggest that obesity is unable to increase the incidence rate of in-hospital mortality and even reduce it^[4,5]. The improved survival and functional outcomes in overweight and obese cardiac surgery patients are termed as the “obesity paradox” in the literature^[6].

So far, the "obesity paradox" has been demonstrated in patients undergoing coronary artery bypass grafting or valve surgery^[7-9]. However, it has not been fully studied in patients with acute type A aortic dissection (AAAD). Only two studies have evaluated the effect of body mass index (BMI) on postoperative clinical outcomes in patients with AAAD ^[10,11], but the study was in western countries whose cases were categorized by the World Health Organization (WHO) standard. Considering ethnic differences, the WHO standard of BMI is not suitable for the Chinese population which the results of the mentioned studies might therefore not be valid for. No existing studies have reported the associations between BMI and early clinical outcomes in AAAD patients undergoing surgery. Moreover, it is unknown whether the "obesity paradox" in Chinese AAAD patients exists. This study adopted the Chinese BMI classification standard to determine the relationship between BMI and postoperative adverse outcomes in AAAD patients.

Study population

This retrospective study enrolled 777 consecutive patients aged 18-80 years at Fujian Province Cardiac Medical Research Center that underwent AAAD surgery between June 2013 and March 2020.

Patients with the following conditions were excluded: (1) Pregnant women; (2) Patients with malignancy; (3) Traumatic dissection; (4) Patients lost to follow-up within 30 days; (5) Patients with incomplete clinical data.

All patients were divided into three groups on the basis of Chinese BMI classification established by WHO: BMI = 18.5-23.9 kg/m² (normal group); BMI = 24-27.9 kg/m²(overweight group); BMI＞28 kg/m² (obesity group). Underweight patients (BMI<18.5) were excluded to avoid biased results because of the small sample size. Ethics approval has been obtained from the ethics committee of Fujian Medical University Union Hospital (approval number:2013002) and conformed to the Declaration of Helsinki.

Data collection

All data were collected by investigators who had been uniformly trained, including preoperative characteristics, intraoperative, and postoperative data. The endpoints were postoperative early adverse outcomes during hospitalization or in the first 30 postoperative days, including in-hospital mortality, prolonged mechanical ventilation (MV), respiratory failure, hypoproteinemia, acute renal failure, acute liver failure, aortic dissection rupture, gastrointestinal bleeding, neurological complications (cerebral hemorrhage, cerebral infarction, epilepsy, and delirium), arrhythmia, septicemia and Multiple Organ Dysfunction Syndrome (MODS). Besides, the duration of intensive care unit (ICU) stays and hospital stays were also recorded.

Criteria

In-hospital mortality was defined as both all-cause deaths occurring during the hospitalization or in the first 30 postoperative days ^[12]. Prolonged mechanical ventilation was defined as the duration of mechanical ventilation (＞48hours) ^[13]. MODS was defined as the Sequential Organ Failure Assessment (SOFA) score of ≥6 on two or more consecutive days after surgery^[14]. Postoperative complications were identified as any of the following: respiratory failure, hypoproteinemia, acute renal failure, aortic dissection rupture, acute liver failure, gastrointestinal bleeding, neurological complications (cerebral hemorrhage, cerebral infarction, epilepsy, and delirium), septicemia, MODS, prolonged MV, and arrhythmia. Postoperative early adverse outcomes were defined as one or two of the following: in-hospital mortality and postoperative complications.

Statistical Analysis

Continuous variables were presented as mean±SD or median (interquartile range), based on Gaussian distribution, and categorical variables were presented as numbers/percentages. Continuous variables were analyzed using analysis of variance (ANOVA) or the Kruskal–Wallis tests, and categorical variables were done using Chi-squared test or Fisher’s exact test. Univariable and multivariable logistic regression analyses were done to assess the relationship between BMI and postoperative early adverse outcomes, and variables with P ≤ 0.1 at univariable analysis were included in the multivariable analysis. Data were performed using the Statistical Package for the Social Science (SPSS version 23.0). P < 0.05 was considered to be statistically significant.

From June 2013 to March 2020, a total of 807 AAAD patients aged 18-80 years received surgical treatment. And a cohort of 777 AAAD patients met inclusion criteria. The flow chart of patient inclusion is demonstrated in Figure 1.

Table 1 shows the baseline characteristics of the three groups. Among the 777 AAAD patients, 248 (31.9%) were classified into the normal group with a BMI of (21.7 ± 1.5) kg/m², 408 (52.5%) were classified into the overweight group having a BMI of (25.4 ± 1.0) kg/m², and 121(15.6%) patients were classified into the obese group with a BMI of (31.6 ± 6.5) kg/m². The oldest age was seen in the normal group (age of 55.7 ± 11.8 years, P＜0.05) as compared with the overweight and obesity groups, and with a high proportion of females, and drinker（P＜0.05). However, there was no significant difference in the history of smoker, and hypertension, coronary artery heart disease (CHD), type 2 diabetes (DM2), and previous cardiac surgery (PCS) among the three groups (P > 0.05).

Patient preoperative, intraoperative, and postoperative clinical variables are summarized in Table 2. The mean of systolic blood pressure (BP), diastolic BP, and pulse pressure were significantly lower in the normal group compared with the overweight and obesity groups (P < 0.05). There were significant differences in serum creatinine (Scr), hemoglobin, and white blood cell (WBC) among the three groups (P＜0.05). No significant differences were observed among other preoperative and operative variables (P＞0.05).

Compared with the normal group, the ICU stay and hospital stay was longer in the overweight group and obesity group (P＜0.05). But the in-hospital mortality was no significant difference between the three groups (16.9% vs 21.8% vs 24.0%, respectively; P=0.198). No significant difference was present in respiratory failure, hypoproteinemia, acute renal failure, aortic dissection rupture, acute liver failure, gastrointestinal complications, neurological complications, septicemia, arrhythmia, and MODS among the three groups (P＞0.05) except prolonged MV, postoperative complications, and adverse outcomes (P＜0.05).

The results of the univariable logistic regression analysis of risk factors are presented in Table 3. BMI would predict postoperative adverse outcomes (P<0.05). Besides, age, hypertension, surgery duration, cardiopulmonary bypass (CPB), aortic cross-clamping duration, diastolic BP, and heart rate were related to postoperative adverse outcomes (P <0.05).

The results of the multivariable logistic regression analyses are presented in Table 4. After adjusting for aortic clamping time, CPB time, diastolic BP, and the history of hypertension, BMI, age, heart rate, and surgery duration were associated with postoperative adverse outcomes (P <0.05). It also demonstrated a higher risk of postoperative early adverse outcomes in the overweight (OR 2.374, 95%CI: 1.647–3.422), and obese patients (OR 3.659, 95%CI: 2.122–6.308) with reference to the normal BMI patients.

Several previous studies have investigated the impact of BMI in the prognosis of cardiac disease^[10,11], but the conclusions remain in dispute. The present study is innovative to demonstrate the impact of BMI on postoperative early adverse outcomes in Chinese AAAD patients undergoing surgery. A total of 777 AAAD patients were included in the study, which we found that the incidence of in-hospital mortality was 20.6%. We observed patients who were overweight and obese were significantly higher in postoperative early adverse outcomes with longer ICU stays and hospital stays compared with the normal group. Besides, age, heart rate, and surgery duration were significantly and strongly related to postoperative early adverse outcomes in patients following AAAD surgery, even after adjusting for other risk factors.

It is unclear why overweight and obese affects the prognosis of AAAD patients, but variability in adherence to DNA methylation or adipose tissue in overweight and obese patients may explain our observations. Recently, Dr. Simone Wahl and colleagues carried out studies^[15] about epigenome-wide association amongst 5,387 individuals from three different population, demonstrating that alterations in DNA methylation are more likely to be the consequence of overweight or obesity, which methylation loci are related to lipid and lipoprotein metabolism, substrate transport, and inflammatory pathways. In addition, large amounts of bioactive mediators can be released from the adipose tissue, affecting blood pressure, inflammation, and other changes, and lead to endothelial dysfunction and arteriosclerosis^[16]. Based on these analyses, it could be concluded that overweight and obese may affect postoperative inflammatory reactions in AAAD patients, thus lead to an increase in mortality and adverse outcomes.

Although there is a huge amount of literature in support of the concept of the ‘obesity paradox’, which indicates that a protective effect, or no effect was observed in overweight or even obese on adverse outcomes ^[6]. However, a recent network meta-analysis suggested that the ‘obesity paradox’ disappeared in Asians, which is consistent with our results^[8]. Kreibich et al. pointed out that obesity was not significantly associated with postoperative adverse outcomes in AAAD patients ^[11]. Lio et al. reported that obese patients were more likely to develop postoperative mortality and adverse outcomes compared to non-obese patients ^[10]. Our findings indicate that overweight and obese are at increased risk of postoperative early adverse outcomes in AAAD patients, which wasn’t consistent with their studies. These inconsistencies might be explained by the three follows: first, BMI showed great differences in different racial persons and especially between the Caucasian and the yellow race^[17]; second, the BMI cutoffs of underweight, normal weight, overweight and obese in Chinese are different from those in other countries; third, there are differences between the studies at baseline, for example, patients with acute aortic dissection (AAD) in China had an earlier onset about ten years than the International Registry of Acute Aortic Dissection^[18]. Finally, the body fat content of Asian people is generally higher than white people of the same gender, age and BMI even if their BMI is less than 25 kg/m², they are more likely to develop type II diabetes and cardiovascular disease ^[19]. Therefore, it is not surprising that the results are quite different.

In this study, we found that the postoperative adverse outcomes in AAAD patients increased with increasing age. It has been reported that age was an established risk factor for perioperative mortality in AAAD patients ^[20,21]. Then we have a deep analysis of reasons. In the first instance, elderly patients are often poorly performed having asymptomatic clinical features in comparison with the young patients which usually led to a delay in diagnosis and treatment. It may also reflect that patients do not obtain timely medical attention ^[22]. Secondly, it is known that older patients often suffered from concomitant comorbidities, such as hypertension, coronary heart, diabetes, and a history of cardiac surgery. That means older patients are more serious when they arrive at the hospital, which may thereby lead to worse surgical prognosis. Moreover, compared with younger, older patients were more seem to have a poor prognosis due to their low cardiopulmonary reserve, and the poor responses to cardiopulmonary bypass surgery, anesthesia, various drugs, and fluid infusion. The elderly people are more physically to have weakness ^[23,24], which can cause physiological disorders including heart rate variability, systemic inflammatory states, a decline in immune function, and hormonal changes^[25-27], and thus increased risk of adverse outcomes.

Another notable finding was that independent risk factors for adverse outcomes were heart rate and surgery duration, which was consistent with the results of the previous studies^[28,29]. As we known, heart rate is a powerful predictor of early adverse outcomes which increased linearly with the heart rate^[30]. The effect of pain stimulus and stress response in AAAD patients can increase the heart rate. It not only improves the metabolism and accelerates the heart rate, but also lengthens the systolic period, shortens the diastolic period, and reduce the coronary artery perfusion^[31,32]. Thus, the altered systemic hemodynamics could break the balance of the circulatory system and make patients more frequently affected by adverse outcomes. The strong association between surgery duration and early adverse outcomes has been observed by other investigators as well^[33]. The longer the surgery duration, on the one hand, reflects the severity of the patient's condition, on the other hand, this may be vulnerable to overdose anesthetic drugs, greater volumes of blood transfusion, or the disturbance of electrolytes or acid-base balance ^[34]. It will affect the organ perfusion, for example cerebral perfusion, and the injury will increase with the perfusion time. Besides, due to the demanding anatomy and difficulty of arterial access in overweight or obese patients, the difficulty of the procedure is increased. For the above reasons, the incidence of postoperative adverse outcomes will inevitably increase.

A further important finding is the longer ICU stay and the higher proportion of prolonged MV in the overweight and obese group, whose finding was compatible with those of other studies.^[35,36]. The reasons could be as follows: (1) The proportion of smokers is higher in overweight and obese groups when compared to the normal group respectively. The decreased pulmonary function in smokers may lead to the inconsistency of baseline lung function on admission in different BMI groups. In this study, the group with a higher proportion of smokers has a higher incidence of prolonged MV. (2) The adipose tissue creates a number of estrogens in overweight and obese patients that play an important role in pulmonary hypertension and remodeling ^[37]. It generally focuses on the changes in pulmonary and chest wall structures, which led to the increase of residual lung volume and chest wall impedance, a decrease of lung compliance and ventilation driving force, and abnormal ventilation-perfusion ^[38]. Furthermore, reduction or loss of lung volume due to the weight of adipose tissue can occur in obesity or overweight patients during operation^[39], leading impaired lung function and delayed extubation. And prolonged time on mechanical ventilation may result in prolonged ICU stay and vice versa ^[40]. In summary, medical staff should establish reasonable ventilation strategies to shorten the length in mechanical ventilation and ICU stay.

However, there are several limitations. First, this was a single-center retrospective study which has its inherent shortcomings, and the findings may not be generalizable to other regions. Second, the measure of body proportion relies solely on BMI which does not yield information on the distribution of body fat. Third, the follow-up period (30 days) in this study was relatively shorter, further studies with longer follow-up periods would be explored to provide additional insight into the impact of BMI on long-term prognosis. Finally, we excluded the underweight patients (< 18.5 kg / m²) with a small sample size in order to avoid the error of the results, which may affect the results when their cases are large enough.

In summary, the present study demonstrates that overweight and obese patients are independently associated with higher postoperative early adverse outcomes in patients who underwent AAAD surgery. And age, heart rate, and surgery duration are also risk factors for postoperative adverse outcomes. The focus should be placed on overweight and obese patients in risk assessment before surgery. Further works need to provide additional insight into the impact of BMI on long-term prognosis.

body mass index (BMI)

acute type A aortic dissection (AAAD)

cardiopulmonary bypass (CPB)

standard deviation (SD)

interquartile range (IQR)

the analysis of variance(ANOVA)

odds ratios (ORs)

confidence intervals (CIs)

World Health Organization (WHO)

Multiple Organ Dysfunction Syndrome (MODS)

the Sequential Organ Failure Assessment (SOFA)

the Statistical Package for the Social Science (SPSS)

acute aortic dissection (AAD)

type 2 diabetes (DM2)

Marfan syndrome (MFS)

previous cardiac surgery (PCS)

Coronary artery heart disease (CHD)

Serum creatinine (Scr)

white blood cell (WBC)

blood pressure (BP)

pulse pressure (PP)

intensive care unit (ICU)

Ethics approval and consent to participate: The work was conducted at the Department of Cardiac Surgery, Fujian Medical University Union Hospital. The study was approved by the Ethics Committee of Fujian Medical University Union Hospital (approval number:2013002). Informed consent was waived because of the retrospective nature of this study.

Consent for publication：Not applicable

Availability of data and materials：The datasets used and analyzed during the current study are available from the corresponding author on reasonable request.

Competing interests：The Authors declare that there is no conflict of interest.

Funding：This work was supported by grants from the Joint Finds for the innovation of science and Technology, Fujian province (Grant number: 2017Y9052) and Guiding project of science and technology department of Fujian province (Grant number:2017Y0038).

Authors' contributions：L-YL and S-LL assessed the delirium of the subjects. Y-CP and QC collected socio-demographic and clinical data. X-ZH, Y-JL, and L-WC analyzed and interpreted the data; L-YL and QC drafted the manuscript; all authors critically revised the manuscript. All authors read and approved the final manuscript.

Acknowledgements：The authors thanks to the Heart Medicine Research Center of Fujian Medical University Union Hospital.

Authors' information (optional)：Not applicable

[1] Guh DP, Zhang W, Bansback N, et al. The incidence of co-morbidities related to obesity and overweight: a systematic review and meta-analysis. BMC Public Health, 2009,9: 88.

[2] Gao M, Sun J, Young N, et al. Impact of Body Mass Index on Outcomes in Cardiac Surgery. J Cardiothorac Vasc Anesth, 2016,30: 1308-1316.

[3] Ghanta RK, LaPar DJ, Zhang Q, et al. Obesity Increases Risk-Adjusted Morbidity, Mortality, and Cost Following Cardiac Surgery. J Am Heart Assoc, 2017,6.

[4] Wang TK, Ramanathan T, Stewart R, et al. Lack of relationship between obesity and mortality or morbidity after coronary artery bypass grafting. N Z Med J, 2013,126: 56-65.

[5] Borracci RA, Ingino CA, Miranda JM. Association of body mass index with short-term outcomes after cardiac surgery: retrospective study and meta-analysis. Medicina (B Aires), 2018,78: 171-179.

[6] Doehner W, Clark A, Anker SD. The obesity paradox: weighing the benefit. Eur Heart J, 2010,31: 146-148.

[7] Rapetto F, Bruno VD, King M, et al. Impact of body mass index on outcomes following mitral surgery: does an obesity paradox exist? Interact Cardiovasc Thorac Surg, 2018,26: 590-595.

[8] Ma WQ, Sun XJ, Wang Y, et al. Does body mass index truly affect mortality and cardiovascular outcomes in patients after coronary revascularization with percutaneous coronary intervention or coronary artery bypass graft? A systematic review and network meta-analysis. Obes Rev, 2018,19: 1236-1247.

[9] Johnson AP, Parlow JL, Whitehead M, et al. Body Mass Index, Outcomes, and Mortality Following Cardiac Surgery in Ontario, Canada. J Am Heart Assoc, 2015,4.

[10] Lio A, Bovio E, Nicolò F, et al. Influence of Body Mass Index on Outcomes of Patients Undergoing Surgery for Acute Aortic Dissection: A Propensity-Matched Analysis. Tex Heart Inst J, 2019,46: 7-13.

[11] Kreibich M, Rylski B, Bavaria JE, et al. Outcome After Operation for Aortic Dissection Type A in Morbidly Obese Patients. Ann Thorac Surg, 2018,106: 491-497.

[12] Allama A, Ibrahim I, Abdallah A, et al. Effect of body mass index on early clinical outcomes after cardiac surgery. Asian Cardiovasc Thorac Ann, 2014,22: 667-673.

[13] Kimura N, Tanaka M, Kawahito K, et al. Risk factors for prolonged mechanical ventilation following surgery for acute type a aortic dissection. Circ J, 2008,72: 1751-1757.

[14] Manson J, Cole E, De'Ath HD, et al. Early changes within the lymphocyte population are associated with the development of multiple organ dysfunction syndrome in trauma patients. Crit Care, 2016,20: 176.

[15] Wahl S, Drong A, Lehne B, et al. Epigenome-wide association study of body mass index, and the adverse outcomes of adiposity. Nature, 2017,541: 81-86.

[16] Oikonomou EK, Antoniades C. The role of adipose tissue in cardiovascular health and disease. Nat Rev Cardiol, 2019,16: 83-99.

[17] Heymsfield SB, Peterson CM, Thomas DM, et al. Scaling of adult body weight to height across sex and race/ethnic groups: relevance to BMI. Am J Clin Nutr, 2014,100: 1455-1461.

[18] Wang W, Duan W, Xue Y, et al. Clinical features of acute aortic dissection from the Registry of Aortic Dissection in China. J Thorac Cardiovasc Surg, 2014,148: 2995-3000.

[19] Ko T, Higashitani M, Sato A, et al. Impact of Acute Kidney Injury on Early to Long-Term Outcomes in Patients Who Underwent Surgery for Type A Acute Aortic Dissection. Am J Cardiol, 2015,116: 463-468.

[20] Nienaber CA, Clough RE. Management of acute aortic dissection. Lancet, 2015,385: 800-811.

[21] Trimarchi S, Eagle KA, Nienaber CA, et al. Role of age in acute type A aortic dissection outcome: report from the International Registry of Acute Aortic Dissection (IRAD). J Thorac Cardiovasc Surg, 2010,140: 784-789.

[22] Hiratzka LF, Bakris GL, Beckman JA, et al. 2010 ACCF/AHA/AATS/ACR/ASA/SCA/SCAI/SIR/STS/SVM guidelines for the diagnosis and management of patients with thoracic aortic disease: executive summary. A report of the American College of Cardiology Foundation/American Heart Association Task Force on Practice Guidelines, American Association for Thoracic Surgery, American College of Radiology, American Stroke Association, Society of Cardiovascular Anesthesiologists, Society for Cardiovascular Angiography and Interventions, Society of Interventional Radiology, Society of Thoracic Surgeons, and Society for Vascular Medicine. Catheter Cardiovasc Interv, 2010,76: E43-86.

[23] Makary MA, Segev DL, Pronovost PJ, et al. Frailty as a predictor of surgical outcomes in older patients. J Am Coll Surg, 2010,210: 901-908.

[24] Lin HS, Watts JN, Peel NM, et al. Frailty and post-operative outcomes in older surgical patients: a systematic review. BMC Geriatr, 2016,16: 157.

[25] Varadhan R, Chaves PH, Lipsitz LA, et al. Frailty and impaired cardiac autonomic control: new insights from principal components aggregation of traditional heart rate variability indices. J Gerontol A Biol Sci Med Sci, 2009,64: 682-687.

[26] Ferrucci L, Fabbri E. Inflammageing: chronic inflammation in ageing, cardiovascular disease, and frailty. Nat Rev Cardiol, 2018,15: 505-522.

[27] Wilson D, Jackson T, Sapey E, et al. Frailty and sarcopenia: The potential role of an aged immune system. Ageing Res Rev, 2017,36: 1-10.

[28] Zhang J, Jiang Y, Gao C, et al. Risk factors for hospital death in patients with acute aortic dissection. Heart Lung Circ, 2015,24: 348-353.

[29] Tian L, Fan X, Zhu J, et al. Plasma D-dimer and in-hospital mortality in patients with Stanford type A acute aortic dissection. Blood Coagul Fibrinolysis, 2014,25: 161-166.

[30] Zhang D, Shen X, Qi X. Resting heart rate and all-cause and cardiovascular mortality in the general population: a meta-analysis. Cmaj, 2016,188: E53-e63.

[31] Jonker FH, Trimarchi S, Muhs BE, et al. The role of age in complicated acute type B aortic dissection. Ann Thorac Surg, 2013,96: 2129-2134.

[32] Qiu S, Cai X, Sun Z, et al. Heart Rate Recovery and Risk of Cardiovascular Events and All-Cause Mortality: A Meta-Analysis of Prospective Cohort Studies. J Am Heart Assoc, 2017,6.

[33] Kawahito K, Adachi H, Yamaguchi A, et al. Preoperative risk factors for hospital mortality in acute type A aortic dissection. Ann Thorac Surg, 2001,71: 1239-1243.

[34] Liu Z, Pang X, Zhang X, et al. Incidence and Risk Factors of Delirium in Patients After Type-A Aortic Dissection Surgery. J Cardiothorac Vasc Anesth, 2017,31: 1996-1999.

[35] Sharma V, Rao V, Manlhiot C, et al. A derived and validated score to predict prolonged mechanical ventilation in patients undergoing cardiac surgery. J Thorac Cardiovasc Surg, 2017,153: 108-115.

[36] Fernandez-Zamora MD, Gordillo-Brenes A, Banderas-Bravo E, et al. Prolonged Mechanical Ventilation as a Predictor of Mortality After Cardiac Surgery. Respir Care, 2018,63: 550-557.

[37] Mair KM, Harvey KY, Henry AD, et al. Obesity alters oestrogen metabolism and contributes to pulmonary arterial hypertension. Eur Respir J, 2019,53.

[38] Dixon AE, Peters U. The effect of obesity on lung function. Expert Rev Respir Med, 2018,12: 755-767.

[39] Imber DA, Pirrone M, Zhang C, et al. Respiratory Management of Perioperative Obese Patients. Respir Care, 2016,61: 1681-1692.

[40] Li B, Sun G, Cheng Z, et al. Analysis of Nosocomial Infections in Post-Cardiac Surgery Extracorporeal Membrane Oxygenation Support Therapy. Heart Surg Forum, 2018,21: E387-e391.

Table 1. Patients’ baseline characteristics stratified by BMI categories

Variables	Normal (N=248)	Overweight (N=408)	Obese (N=121)	P-value
Age, years, mean (SD)	55.7(11.8)	51.9(10.9)	48.5(11.5)	<0.001
Sex, n (%)				<0.001
Male	172（69.4）	329（80.6）	103（85.1）
Female	76（30.6）	79（19.4）	18（14.9）
BMI (kg/m2), mean (SD)	21.7 (1.5)	25.4 (1.0)	31.6 (6.5)	<0.001
History of
Smoker, n (%)				0.201
Yes	108 (43.5)	199 (48.8)	64 (52.9)
No	140 (56.5)	209 (51.2)	57 (47.1)
Drinker, n (%)				0.040

Yes	83 (29.8)	147 (36.0)	52 (43.0)
No	174 (70.2)	261 (64.0)	69 (57.0)

Hypertension, n (%)				0.205
No	84 (33.9)	114 (27.9)	27 (22.3)
Level 1	26 (10.5)	51 (12.5)	14 (11.6)
Level 2	44 (17.7)	66 (16.2)	18 (14.9)
Level 3	94 (37.9)	177 (43.4)	62 (51.2)
DM2, n (%)				0.177
Yes	7 (2.8)	14 (3.4)	8 (6.6)
No	241 (97.2)	394 (96.6)	113 (93.4)
MFS, n (%)				<0.001
Yes	11 (4.4)	11 (2.7)	17 (14.0)
No	237 (95.6)	397 (97.3)	104 (86.0)
PCS, n (%)
Yes	7 (2.8)	10 (2.5)	4 (3.3)	0.870
No	257 (97.2)	389 (97.5)	110 (96.7)
CHD, n (%)				0.854
Yes	2 (0.8)	2 (0.5)	1(0.8)
No	246 (99.2)	406 (99.5)	120 (99.2)

Abbreviations: BMI, body mass index; DM2, type 2 diabetes; MFS, Marfan syndrome; PCS, previous cardiac surgery; CHD, Coronary artery heart disease; SD, standard deviation;

Table 2. Preoperative, operative and postoperative data of stratified by BMI categories

Variables	Normal (N=248)	Overweight (N=408)	Obese (N=121)	P-value
Preoperative
Systolic BP (mm/Hg), mean (SD)	133.7(27.4)	143.6(31.0)	147.1(27.9)	<0.001
Diastolic BP (mm/Hg), mean (SD)	71.9(14.7)	76.8(17.8)	78.1(15.7)	<0.001
PP (mm/Hg), mean (SD)	61.7(21.1)	67.0(23.5)	69.0(22.6)	0.003
Heart rate, mean (SD)	80.7 (16.0)	81.7 (17.3)	83.6 (14.8)	0.296
Neutrophil (× 10⁹/L), mean (SD)	22.7(29.6)	26.9(31.8)	21.0(25.6)	0.082
Platelet (× 10⁹/L), median (IQR)	184.3(174.7,194.0)	182.1(175.4,188.9)	189.4(178.6,200.2)	0.607
Lymphocyte (× 10⁹/L), median (IQR)	2.6(2.0,3.1)	2.6(2.2,3.0)	2.3(1.4,3.1)	0.734
Scrμmol/L, median (IQR)	98.5 (92.0,105.0)	119.4 (108.7,130.2)	100.0 (90.2，109.4)	0.008
Hemoglobin(g/l), mean (SD)	122.9 (18.5)	128.5 (19.4)	136.1 (18.0)	<0.001
WBC (×10⁹/l), mean (SD)	11.3 (3.8)	12.9 (4.2)	13.4 (4.5)	<0.001
Operative
Surgery duration(min), median (IQR)	320.4 (309.2,331.7)	318.5 (309.8,327.2)	334.2 (315.7,352.7)	0.251
CPB(min), median (IQR)	168.9 (159.9,177.9)	162.8 (156.8,168.9)	172.9 (157.8,188.1)	0.288
Aortic cross-clamping duration(min), median (IQR)	80.2 (73.9,86.5)	80.8 (76.0,85.7)	72.3 (64.5,80.0)	0.265
Postoperative
ICU stay, median (IQR)	8.1 (7.1,9.2)	9.5 (8.6,10.5)	12.0 (10.0,14.1)	0.001
Hospital stay, median (IQR)	21.0 (19.8,22.2)	22.6(21.3,23.9)	27.4 (24.3,30.5)	<0.001
In-hospital mortality, n (%)	42 (16.9)	89 (21.8)	29 (24.0)	0.198
Adverse outcome, n (%)	130 (52.4)	283 (69.4)	93 (76.9)	<0.001
Respiratory failure, n (%)	3 (1.2)	6 (1.5)	0 (0)	0.412
Hypoproteine-mia, n (%)	15(6.0)	25(6.1)	7(5.8)	0.990
Acute renal failure, n (%)	46(18.5)	105 (25.7)	30(24.8)	0.098
Aortic dissection rupture, n (%)	3（1.2）	5（1.2）	0（0）	0.474
Acute liver failure, n (%)	31(12.5)	82(20.1)	24(19.8)	0.037
Gastrointestinal complications, n (%)	17(6.9)	41(10.0)	12(9.9)	0.356
Neurological complications, n (%)	18(7.3)	31(7.6)	9(7.4)	0.987
Septicemia, n (%)	1(0.4)	0(0)	1(0.8)	0.249
Arrhythmia, n (%)	3(1.2)	14(3.4)	3(2.5)	0.219
MODS, n (%)	8(3.2）	16(3.9）	4(3.3）	0.882
Prolonged MV ( > 48h), n (%)	111(44.9)	227(55.8)	80(66.1)	<0.001
Postoperative complications, n (%)	127(51.2)	278(68.1)	91(75.2)	<0.001

Abbreviations: BP, blood pressure; PP, pulse pressure; Scr，Serum creatinine; WBC, white blood cell; CPB, cardiopulmonary bypass time; MODS: Multiple Organ Dysfunction Syndrome ; MV, mechanical ventilation; SD, standard deviation; IQR, interquartile range

Table 3. Univariable logistic regression of A composite outcome

Variables	OR	95% CI	P-value
Age	1.021	(1.008, 1.034)	0.002
Sex	0.979	(0.687, 1.394)	0.905
Smoker	1.056	(0.786, 1.419)	0.718
Drinker	1.198	(0.877, 1.637)	0.255
DM2	1.500	(0.714, 3.151)	0.284
CHD	2.151	(0.239, 19.345)	0.494
Hypertension			0.043
No	Reference
Level 1	1.127	(0.685, 1.856)	0.638
Level 2	1.393	（0.886, 2.190）	0.152
Level 3	1.642	(1.152, 2.339)	0.006
MFS	0.609	(0.318, 1.163)	0.133
PCS	0.867	(0.355,2.118)	0.754
BMI			<0.001
18.5-23.9	Reference
24.0-27.9	2.055	(1.483, 2.848)	<0.001
＞28.0	3.015	（1.846, 4.924）	<0.001
Surgery duration	1.005	(1.003, 1.007)	<0.001
CPB	1.007	(1.004, 1.010)	<0.001
Aortic cross-clamping duration	1.007	(1.003, 1.011)	<0.001
Systolic BP (mm/Hg)	1.004	(0.998, 1.009)	0.171
Diastolic BP (mm/Hg)	1.009	(1.000, 1.018)	0.049
PP (mm/Hg)	1.002	(0.995,1.008)	0.621
Heart rate	1.013	(1.003,1.022)	0.007

Abbreviations: DM2, type 2 diabetes; CHD, Coronary artery heart disease; MFS, Marfan syndrome; PCS, previous cardiac surgery; BMI, body mass index; CPB, cardiopulmonary bypass time; BP, blood pressure; PP, pulse pressure; ORs, Odds ratio; CI, Confidence intervals

Table 4. Multivariable logistic regression of A composite outcome

Variables	OR	95% CI	P-value
BMI			<0.001
18.5-23.9	Reference
24.0-27.9	2.374	(1.647,3.422)	<0.001
＞28.0	3.659	(2.122,6.308)	<0.001
age	1.034	(1.018,1.049)	<0.001
Heart rate	1.014	(1.004,1.025)	0.006
Surgery duration	1.005	(1.002,1.008)	0.003
Hypertension			0.471
No	Reference
Level 1	1.064	(0.621,1.820)	0.822
Level 2	1.294	(0.784,2.134)	0.313
Level 3	1.346	(0.904,2.004)	0.143
Aortic cross-clamping duration	1.002	(0.996,1.006)	0.669
CPB	1.001	(0.997,1.007)	0.469
Diastolic BP (mm/Hg)	1.003	(0.993,1.013)	0.579

Abbreviations: BMI, body mass index; ORs, Odds ratio; CI, Confidence intervals; CPB, cardiopulmonary bypass time; BP, blood pressure

Download PDF

Journal Publication

published 23 Mar, 2021

Read the published version in Journal of Cardiothoracic Surgery →

Editorial decision: Major revision
08 Jan, 2021
Review #1 received at journal
13 Nov, 2020
Review #2 received at journal
05 Nov, 2020
Reviewer #2 agreed at journal
04 Nov, 2020
Reviewer #1 agreed at journal
01 Nov, 2020
Reviewers invited by journal
31 Oct, 2020
First submitted to journal
19 Oct, 2020
Editor assigned by journal
19 Oct, 2020
Submission checks completed at journal
18 Oct, 2020
Editor invited by journal
18 Oct, 2020

You are reading this older preprint version

Read the latest preprint version →

Association of Body Mass Index With Postoperative Early Adverse Outcomes in Acute Type a Aortic Dissection Patients in Fujian Province, China: A Retrospective Study

Status:

Journal Publication

Version 1

Abstract

Figures

Background

Methods

Results

Discussion

Conclusions

List Of Abbreviations

Declarations

References

Tables

Status:

Journal Publication

Version 1