Skip to main content

Impact of body mass index on perioperative mortality of acute stanford type A aortic dissection: a systematic review and meta-analysis

Abstract

Background

Obesity may increase perioperative mortality of acute Stanford type A aortic dissection (ATAAD). However, the available evidence was limited. This study aimed to systematically review published literatures about body mass index (BMI) and perioperative mortality of ATAAD.

Methods

Electronic literature search was conducted in PubMed, Medline, Embase and Cochrane Library databases. All observational studies that investigated BMI and perioperative mortality of ATAAD were included. Pooled odds ratio (OR) and 95% confidence interval (CI) were calculated using a random-effects model. Meta-regression analysis was performed to assess the effects of different clinical variables on BMI and perioperative mortality of ATAAD. Sensitivity analysis was performed to determine the sources of heterogeneity. Egger’s linear regression method and funnel plot were used to determine the publication bias.

Results

A total of 12 studies with 5,522 patients were eligible and included in this meta-analysis. Pooled analysis showed that perioperative mortality of ATAAD increased by 22% for each 1 kg/m2 increase in BMI (OR = 1.22, 95% CI: 1.10–1.35). Univariable meta-regression analysis indicated that age and female gender significantly modified the association between BMI and perioperative mortality of ATAAD in a positive manner (meta-regression on age: coefficient = 0.04, P = 0.04; meta-regression on female gender: coefficient = 0.02, P = 0.03). Neither significant heterogeneity nor publication bias were found among included studies.

Conclusions

BMI is closely associated with perioperative mortality of ATAAD. Optimal perioperative management needs to be further explored and individualized for obese patient with ATAAD, especially in elderly and female populations.

Trial registration

PROSPERO (CRD42022358619).

Graphical Abstract

BMI and perioperative mortality of ATAAD.

Peer Review reports

Introduction

Acute Stanford type A aortic dissection (ATAAD) is a devastating cardiovascular emergency that is triggered by internal and external factors and usually requires urgent surgical repair [1]. Despite the technical development, perioperative mortality of ATAAD remained as high as 9%–25% [2,3,4,5]. Therefore, identification of potential risk factors could improve personalized management of ATAAD among specific individuals.

Obesity is a critical issue of public health and is associated with the poor prognosis of many cardiovascular diseases [6]. Some studies reported that obesity raised the risk of perioperative mortality of ATAAD [7, 8]. However, other studies failed to demonstrate a significant association between body mass index (BMI) and perioperative mortality of ATAAD [9, 10]. Relatively low sample size and single-center design of most previous studies may contribute to controversial conclusions. Currently, solid evidence for the association between BMI and perioperative mortality of ATAAD is still lacking and evidence-based guidelines for management of obese ATAAD patients are also absent [11].

Herein, we systematically review published literature and performed this meta-analysis to explore the association between BMI and perioperative mortality of ATAAD. In addition, we assessed the effect of different clinical variables on this association.

Methods and materials

Search strategy

This meta-analysis was designed and conducted in the guidance of the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) checklist [12]. In addition, we also followed the Meta-analysis of Observational Studies in Epidemiology (MOOSE) guidelines because the included studies were observational in design [13]. A systematic search of published articles was conducted in PubMed, Medline, Embase and Cochrane Library databases until December 2022. Combination of following terms were used: (1) “Type A aortic dissection” or “Stanford type A aortic dissection” or “ATAAD”; and (2) “BMI” or “Body Mass Index” or “Obesity” or “Body Weight”; and (3) “Mortality” or “Mortalities” or “Fatality Rate” or “Death Rate” or “Fatality Rates” or “Death Rates”. References from selected literatures were also manually scrutinized for potentially relevant citations using the snowball methodology [14]. The references were imported to EndNote online and Excel to remove duplicated records. Eligibility assessment of the first screening was performed based on titles and abstracts by three independent investigators (W.S., J.L. and L.P.). The second screening was conducted with the inclusion and exclusion criteria on the full text by all three investigators (W.S., J.L. and L.P.). In case of uncertainty, an agreement was negotiated and where necessary, a fourth researcher was consulted (J.C.).

Inclusion and exclusion criteria

Studies meeting the following criteria were included in this meta-analysis: (1) Observational studies; (2) Patients were diagnosed as ATAAD regardless of age and underwent surgical repair; (3) Concerning the effect of BMI on perioperative mortality of ATAAD; (4) Publication in English. On the contrary, studies meeting the following criteria were excluded: (1) Duplicated records; (2) Failure to focus on BMI and perioperative mortality of ATAAD; (3) Concerning the effect of BMI on other outcomes instead of perioperative mortality; (4) Effect values of BMI on perioperative mortality of aortic dissection were not available. (5) Reviews, editorial comments, case reports, conference abstracts, and expert opinions; (6) Full text was not available.

Data extraction

The following information was collected for each study enrolled in this meta-analysis: (1) First author’s name; (2) Region; (3) Study period; (4) Study design; (5) Sample size; (6) Female proportion; (7) Mean age; (8) Smoker proportion; (9) Hypertension proportion; (10) Diabetes proportion; (11) Obesity measure; (12) Effect values with 95% confidence intervals (CIs).

Definitions and endpoints

All cases of ATAAD were clearly diagnosed using computed tomography angiography in 12 enrolled studies [1]. Perioperative mortality was defined as in-hospital mortality or 30-day mortality of ATAAD patients after surgical repair.

Quality assessment

The quality assessment was performed by three independent investigators (W.S., J.L. and L.P.). A fourth investigator was consulted in cases of uncertainty (J.C.). Quality assessment was conducted with the Newcastle–Ottawa Quality Assessment Scale (NOS), a validated scale for non-randomized observational studies [15]. Case–control and cohort study were assessed according to three aspects: (1) selection (0–4 points); (2) comparability (0–2 points); (3) exposure/outcome (0–3 points). Higher total scores represented higher quality. The acceptable score was at least 6.

Statistical analysis

Odds ratio (OR) was calculated according to its definition if effect value was not given directly. In order to set an unified standard of effect values, hazard ratio (HR) was directly regarded as OR according to a previous meta-analysis [16]. Adjusted OR and 95% CI were used to evaluate the association between BMI and perioperative mortality of ATAAD. To investigate the potential sources of result variations, we conducted univariable meta-regression analysis to explore whether the research results were influenced by different clinical variables and participant characteristics. Heterogeneity among studies was evaluated through Q statistic. Given that heterogeneity was nonnegligible between only 12 studies included in this meta-analysis, a random-effects model was applied to calculate the combined effect value compared with fixed effects models according to our previous study [17]. Further, a one-by-one elimination method was used to perform sensitivity analysis. Egger’s linear regression method was used to check publication bias. Statistical analyses were conducted through STATA 16.0 (Stata Corp, Texas, USA). Statistical significance was set at P < 0.05. All tests were two-sided.

Results

Literature selection

The literature search identified 169 records from databases concerning effects of BMI (or obesity) on perioperative mortality of ATAAD. After further exclusions, 12 literatures met our selection criteria and were included for this meta-analysis. The flow chart of the literature search was shown in Fig. 1.

Fig. 1
figure 1

The flow chart of the study procedure

Study characteristics and quality assessment

Basic characteristics of the studies included in this meta-analysis were shown in Table 1. A total of 12 observational studies included 4 case–control and 8 cohort studies. Of these studies, 8 were performed in China, 2 in Japan, 1 in Germany and 1 in Italy. Sample size ranged from 72 to 1,059. Percent of female patients ranged from 12.5% to 48.0%. Mean age of patients ranged from 46.0 to 65.7 years. Clinical characteristics of these studies were shown in Table 2. The percent of smokers, hypertension and diabetes mellitus ranged from 31.3% to 54.2%, 46.0% to 88.2%, and 2.2% to 54.0%, respectively. Five studies used mean BMI, while six studies divided the BMI into two categories by the cut-off value of 25.0 or 30.0 kg/m2. One study classified patients into four groups: normal weight (18.0 ≤ BMI < 25.0 kg/m2), overweight (25.0 ≤ BMI < 30.0 kg/m2), obese (30.0 ≤ BMI < 35.0 kg/m2) and morbidly obese (BMI ≥ 35.0 kg/m2). NOS scores of all 12 studies ranged from 6 to 8 (Tables 3 and 4).

Table 1 Basic characteristics of the studies included in the meta-analysis
Table 2 Clinical characteristics of the subjects in the included studies
Table 3 Study quality of case–control studies
Table 4 Study quality of cohort studies

Association between BMI and Perioperative Mortality of ATAAD

The effect of BMI on perioperative mortality of ATAAD was extracted from 12 studies which included 5,522 patients. Single-center studies in China observed that mean BMI was associated with perioperative mortality of ATAAD, including 30-days mortality [21] (HR = 1.13, 95% CI: 1.03–1.25), in-hospital mortality [19, 20, 23, 25] (OR = 1.15, 95% CI: 1.03–1.29, OR = 1.32, 95% CI: 1.03–1.70, HR = 2.61, 95% CI: 1.30–5.22 and OR = 1.09, 95% CI: 1.04–1.15). Consistently, different perioperative mortality of ATAAD was found between different BMI categories. For example, a retrospective study in China observed significantly increased perioperative mortality in overweight patients [18] (BMI > 25.0 kg/m2, OR = 7.52, 95% CI: 1.37–41.36). Moreover, 2 independent retrospective cohort studies in Japan [7, 8] and 1 in Italy [22] identified obesity (BMI ≥ 30.0) as a risk factor of in-hospital mortality in ATAAD patients who underwent surgical repairs (OR = 3.00, 95% CI: 1.40–6.20, OR = 3.16, 95% CI: 1.48–6.74, and OR = 2.14, 95% CI: 1.22–3.78). However, a retrospective cohort study conducted in Germany [9] and 2 in China [10, 24] found no associations.

Through integration of these studies by a random-effects model, perioperative mortality of ATAAD increased by 22% for each 1 kg/m2 increase in BMI (Fig. 2, OR = 1.22, 95% CI: 1.10–1.35). Due to the low sample study of Wu Y. H. et al. [20], there may be potential publication bias. We added a forest plot excluding the research of Wu Y. H. et al., and the results still show the significant association between BMI and perioperative mortality of ATAAD (Figure S1, OR = 1.21, 95%CI: 1.09–1.35).

Fig. 2
figure 2

Effect of BMI on perioperative mortality of ATAAD

Meta-regression

The meta-regression analysis was conducted to assess the impact of four continuous variables on the association between BMI and perioperative mortality of ATAAD, including age, gender, hypertension, and diabetes (Table 5). The results demonstrated that each 1-unit increase in age was associated with a 0.04-unit increase in the effect of BMI on the perioperative mortality on ATAAD (regression coefficient = 0.04, P = 0.04). Similarly, a 1-unit increase in the proportion of females was associated with a substantial 0.02-unit increase in the effect (regression coefficient = 0.02, P = 0.03). However, we found no statistically significant association between the proportion of hypertension patients (regression coefficient = -0.01, P = 0.27) or diabetes patients (regression coefficient = 0.01, P = 0.55) and the effect.

Table 5 Univariable meta-regression of four variables on the risk of perioperative mortality of ATAAD

Sensitivity analysis

Sensitivity analysis was performed in Fig. 3. The pooled OR and 95% CI did not show evident differences after excluding each individual article one by one, which indicated that the studies included in our meta-analysis were credible.

Fig. 3
figure 3

Sensitivity analysis of BMI on perioperative mortality of ATAAD

Publication bias

Publication bias was assessed with Egger’s test and funnel plot. Our statistical test showed no evidence of publication bias (Egger’s test P = 0.001). However, five points fall outside, suggesting the possibility of heterogeneity (Fig. 4). Too few studies were included which may lead to the biased result.

Fig. 4
figure 4

Funnel plot of the BMI on perioperative mortality of ATAAD

Discussion

Over the decades, many risk factors have been identified in the morbidity and mortality of ATAAD [26,27,28]. A recent meta-analysis identified five risk factors for early death after surgery in patients with ATAAD, including age, gender, shock, malperfusion and cardiac tamponade [29]. However, there is still no high-quality evidence on the association between BMI and perioperative mortality of ATAAD. In this meta-analysis, we observed a positive association between BMI and perioperative mortality of ATAAD through integration of 12 independent studies (Graphic Abstract).

In clinical practice, surgical repair of ATAAD on obese patients is difficult and challenging. It usually required prolonged operation time, cardiopulmonary bypass time and myocardial ischemia time compared with non-obese individuals [22, 30,31,32,33]. These patients might suffer from multiple complications including cardiopulmonary dysfunction, multiple organ dysfunction syndrome and severe surgical site infection after surgical repair [22, 30, 34]. It was reported that obese ATAAD patients had a prolonged ICU stay (9 days) compared with non-obese patients (6 days) [8]. Meanwhile, the incidence of ECMO usage and renal replacement therapy increased from 2.4% and 7.1% in non-obese to 8.7% and 14.5% in obese ATAAD patients, respectively8. The difficulty of surgical repair and postsurgical management indicated that BMI might also be a major concern in perioperative mortality of ATAAD.

Respiratory dysfunction including preoperative [35] and postoperative hypoxemia [36] was a common complication of obese ATAAD patients undergoing surgical repair. The underlying mechanism might be multifactorial. Obese patients have lower functional residual capacity (FRC) secondary to cephalad diaphragmatic displacement. A low FRC increases the risk of both expiratory flow limitation and airway closure [37]. Biologically, obesity patients share systemic chronic inflammation in vivo compared to control individuals [38]. Under chronic persistent hypoxia, adipose tissue produces reactive oxygen species [39] and inflammatory factors [40, 41] into blood circulation including TNF-α, IL-1β and IL-6. It further leads to inflammatory reaction and oxidative stress which may contribute to increased lung injury [35, 42,43,44]. Resultantly, prolonged ventilation time and increased pulmonary morbidity were observed after cardiac surgery on obese patients [31,32,33]. In-depth understanding of cellular and molecular mechanisms could facilitate us to treat respiratory complication after surgical repair for obese ATAAD patients.

Other potential mechanisms may be used to explain the relation between BMI and perioperative mortality of ATAAD. Obesity is closely associated with various types of cardiovascular disorders such as hypertension, coronary heart disease and cerebrovascular disease. Hypertension incidence was 87.0% in obese ATAAD patients compared with 68.9% in non-obese individuals [8]. In addition, higher incidence of hemodynamic instability was found among obese ATAAD patients during perioperative periods [8]. These cardiovascular dysfunctions might increase the difficulty of perioperative management of ATAAD patients.

Given that obesity might increase perioperative mortality of ATAAD, obese patients with ATAAD should be specially focused and treated. Ventilation management is an important concern of perioperative management of obese ATAAD patients. Positive end-expiratory mandatory ventilation was recommended for obese patients at different phases of surgery including before intubation, on mechanical ventilation and after extubation [45]. Considering higher incidence of infection and hemodynamic instability among obese ATAAD patients, rational administration of antibiotics and vasoactive agents also needs to be focused during the perioperative management [22, 30]. In addition, high incidence of obstructive sleep apnea syndrome was found among obese ATAAD patients [9, 46], which indicated that personalized airway assessment, choice of anesthesia and analgesia technique and extubating time are also important for perioperative management of these patients [47, 48].

Meta-regression analysis further indicated that the effect of BMI on perioperative mortality of ATAAD might be stronger in elderly and female populations. Elderly patients should be paid more attention in clinical management due to the decreased metabolic and immune function, degraded physiological function of organs, poor body reserve and compensation ability in these populations [49, 50]. The impact of gender on perioperative mortality of ATAAD still remains controversial. Several studies have reported worse mortality for women who undergo surgery for aortic dissection [51,52,53,54], while other studies drew the opposite conclusion [29]. Pooled analysis demonstrated that female gender was not associated with increased perioperative mortality of ATAAD [55]. However, few studies have focused on the impact of gender on the association between BMI and perioperative mortality of ATAAD. Our meta-regression analysis indicated that female obese ATAAD patients may have increased risk of perioperative mortality than male obese ATAAD patients, which called for specialized management of female obese ATAAD patients.

The present study has some limitations. First, only 12 literatures were included in the study. Different study designs, classification criteria of BMI and outcome indicators may contribute to heterogeneity in this meta-analysis. Some original research literature might not reach enough high quality due to limited sample volume. Second, different countries may have different definitions on obesity. Thus, we mainly analyzed the relationship between perioperative mortality and the gain of BMI. Here, BMI was regarded as a continuous variable. In addition, different methods of surgical repairs of ATAAD were performed in these studies, such as Sun’s operation, David operation and Bentall operation, which could not be adjusted only through statistical manners.

Conclusions

BMI is closely associated with perioperative mortality of ATAAD. Optimal perioperative management needs to be further explored and individualized for obese patient with ATAAD, especially in elderly and female populations.

Availability of data and materials

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

References

  1. Isselbacher EM, Preventza O, Hamilton Black J 3rd, Augoustides JG, Beck AW, Bolen MA, Braverman AC, Bray BE, Brown-Zimmerman MM, Chen EP, et al. 2022 ACC/AHA Guideline for the Diagnosis and Management of Aortic Disease: A Report of the American Heart Association/American College of Cardiology Joint Committee on Clinical Practice Guidelines. Circulation. 2022;146(24):e334–482.

    Article  PubMed  Google Scholar 

  2. Pape LA, Awais M, Woznicki EM, Suzuki T, Trimarchi S, Evangelista A, Myrmel T, Larsen M, Harris KM, Greason K, et al. Presentation, Diagnosis, and Outcomes of Acute Aortic Dissection: 17-Year Trends From the International Registry of Acute Aortic Dissection. J Am Coll Cardiol. 2015;66(4):350–8.

    Article  PubMed  Google Scholar 

  3. Chiappini B, Schepens M, Tan E, Dell’ Amore A, Morshuis W, Dossche K, Bergonzini M, Camurri N, Reggiani LB, Marinelli G, et al. Early and late outcomes of acute type A aortic dissection: analysis of risk factors in 487 consecutive patients. Eur Heart J. 2005;26(2):180–6.

    Article  PubMed  Google Scholar 

  4. Trimarchi S, Nienaber CA, Rampoldi V, Myrmel T, Suzuki T, Mehta RH, Bossone E, Cooper JV, Smith DE, Menicanti L, et al. Contemporary results of surgery in acute type A aortic dissection: The international registry of acute aortic dissection experience. J Thorac Cardiovasc Surg. 2005;129(1):112–22.

    Article  PubMed  Google Scholar 

  5. Fukui T. Management of acute aortic dissection and thoracic aortic rupture. J Intensive Care. 2018;6:15.

    Article  PubMed  PubMed Central  Google Scholar 

  6. Ortega FB, Lavie CJ, Blair SN. Obesity and cardiovascular disease. Circ Res. 2016;118(11):1752–70.

    Article  CAS  PubMed  Google Scholar 

  7. Kawahito K, Kimura N, Yamaguchi A, Aizawa K, Misawa Y, Adachi H. Early and late surgical outcomes of acute type A aortic dissection in octogenarians. Ann Thorac Surg. 2018;105(1):137–43.

    Article  PubMed  Google Scholar 

  8. Shimizu T, Kimura N, Mieno M, Hori D, Shiraishi M, Tashima Y, Yuri K, Itagaki R, Aizawa K, Kawahito K, et al. Effects of obesity on outcomes of acute type A aortic dissection repair in Japan. Circ Rep. 2020;2(11):639–47.

    Article  PubMed  PubMed Central  Google Scholar 

  9. Kreibich M, Rylski B, Bavaria JE, Branchetti E, Dohle D, Moeller P, Vallabhajosyula P, Szeto WY, Desai ND. Outcome after operation for aortic dissection type A in morbidly obese patients. Ann Thorac Surg. 2018;106(2):491–7.

    Article  PubMed  Google Scholar 

  10. Liu Y, Zhang B, Liang S, Dun Y, Wang L, Gao H, Ren J, Guo H, Sun X. Impact of body mass index on early and mid-term outcomes after surgery for acute Stanford type A aortic dissection. J Cardiothorac Surg. 2021;16(1):179.

    Article  PubMed  PubMed Central  Google Scholar 

  11. Bossone E, Eagle KA. Epidemiology and management of aortic disease: aortic aneurysms and acute aortic syndromes. Nat Rev Cardiol. 2021;18(5):331–48.

    Article  PubMed  Google Scholar 

  12. Shamseer L, Moher D, Clarke M, Ghersi D, Liberati A, Petticrew M, Shekelle P, Stewart LA, Group P-P. Preferred reporting items for systematic review and meta-analysis protocols (PRISMA-P) 2015: elaboration and explanation. BMJ. 2015;350.

    Article  PubMed  Google Scholar 

  13. Stroup DF, Berlin JA, Morton SC, Olkin I, Williamson GD, Rennie D, Moher D, Becker BJ, Sipe TA, Thacker SB. Meta-analysis of observational studies in epidemiology: a proposal for reporting Meta-analysis Of Observational Studies in Epidemiology (MOOSE) group. JAMA. 2000;283(15):2008–12.

    Article  CAS  PubMed  Google Scholar 

  14. C W: Guidelines for snowballing in systematic literature studies and a replication in software engineering. ACM Int Conf Proc Ser 2014(38(1–38)):10.

  15. Stang A. Critical evaluation of the Newcastle-Ottawa scale for the assessment of the quality of nonrandomized studies in meta-analyses. Eur J Epidemiol. 2010;25(9):603–5.

    Article  PubMed  Google Scholar 

  16. Biller VS, Leitzmann MF, Sedlmeier AM, Berger FF, Ortmann O, Jochem C. Sedentary behaviour in relation to ovarian cancer risk: a systematic review and meta-analysis. Eur J Epidemiol. 2021;36(8):769–80.

    Article  PubMed  PubMed Central  Google Scholar 

  17. Liu J, Chen D, Huang Y, Bigambo FM, Chen T, Wang X. Effect of maternal triclosan exposure on neonatal birth weight and children triclosan exposure on children’s BMI: A meta-analysis. Front Public Health. 2021;9: 648196.

    Article  PubMed  PubMed Central  Google Scholar 

  18. Huo Y, Zhang H, Li B, Zhang K, Li B, Guo SH, Hu ZJ, Zhu GJ. Risk factors for postoperative mortality in patients with acute stanford type A aortic dissection. Int J Gen Med. 2021;14:7007–15.

    Article  PubMed  PubMed Central  Google Scholar 

  19. Zhang Y, Chen T, Chen Q, Min H, Nan J, Guo Z. Development and evaluation of an early death risk prediction model after acute type A aortic dissection. Ann Transl Med. 2021;9(18):1442.

    Article  PubMed  PubMed Central  Google Scholar 

  20. Wu Y, Jiang R, Xu P, Wang G, Wang J, Yang S. Perioperative results and risk factors for in-hospital mortality in patients with stanford type A aortic dissection undergoing sun’s procedure - a single center study. Heart Surg Forum. 2018;21(6):E432–7.

    Article  PubMed  Google Scholar 

  21. Wang M, Fan R, Gu T, Zou C, Zhang Z, Liu Z, Qiao C, Sun L, Gong M, Li H, et al. Short-term outcomes of acute coronary involvement in type A aortic dissection without myocardial ischemia: a multiple center retrospective cohort study. J Cardiothorac Surg. 2021;16(1):107.

    Article  PubMed  PubMed Central  Google Scholar 

  22. Lio A, Bovio E, Nicolo F, Saitto G, Scafuri A, Bassano C, Chiariello L, Ruvolo G. 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(1):7–13.

    Article  PubMed  PubMed Central  Google Scholar 

  23. Pan X, Xing Z, Yang G, Ding N, Zhou Y, Chai X. Obesity increases in-hospital mortality of acute type A aortic dissection patients undergoing open surgical repair: a retrospective study in the chinese population. Front Cardiovasc Med. 2022;9: 899050.

    Article  PubMed  PubMed Central  Google Scholar 

  24. Luo ZR, Chen XD, Chen LW. Age-dependent differences in the prognostic relevance of body composition-related variables in type A aortic dissection patients. J Cardiothorac Surg. 2021;16(1):359.

    Article  PubMed  PubMed Central  Google Scholar 

  25. Lin YJ, Lin JL, Peng YC, Li SL, Chen LW. TG/HDL-C ratio predicts in-hospital mortality in patients with acute type A aortic dissection. BMC Cardiovasc Disord. 2022;22(1):346.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  26. Hibino M, Otaki Y, Kobeissi E, Pan H, Hibino H, Taddese H, Majeed A, Verma S, Konta T, Yamagata K, et al. Blood pressure, hypertension, and the risk of aortic dissection incidence and mortality: results from the J-SCH Study, the UK Biobank study, and a meta-analysis of cohort studies. Circulation. 2022;145(9):633–44.

    Article  CAS  PubMed  Google Scholar 

  27. Meccanici F, Gokalp AL, Thijssen CGE, Mokhles MM, Bekkers JA, van Kimmenade R, Verhagen HJ, Roos-Hesselink JW, Takkenberg JJM. Male-female differences in acute thoracic aortic dissection: a systematic review and meta-analysis. Interact Cardiovasc Thorac Surg. 2022;34(4):616–27.

    Article  PubMed  Google Scholar 

  28. Odofin X, Houbby N, Hagana A, Nasser I, Ahmed A, Harky A. Thoracic aortic aneurysms in patients with heritable connective tissue disease. J Card Surg. 2021;36(3):1083–90.

    Article  PubMed  Google Scholar 

  29. Zhang Y, Yang Y, Guo J, Zhang X, Cheng Y, Sun T, Lin L. Risk factors for early death after surgery in patients with acute Stanford type A aortic dissection: A systematic review and meta-analysis. Int J Cardiol. 2023;377:33–41.

    Article  PubMed  Google Scholar 

  30. Li Y, Jiang H, Xu H, Li N, Zhang Y, Wang G, Xu Z. Impact of a higher body mass index on prolonged intubation in patients undergoing surgery for acute thoracic aortic dissection. Heart Lung Circ. 2020;29(11):1725–32.

    Article  PubMed  Google Scholar 

  31. Gao M, Sun J, Young N, Boyd D, Atkins Z, Li Z, Ding Q, Diehl J, Liu H. Impact of body mass index on outcomes in cardiac surgery. J Cardiothorac Vasc Anesth. 2016;30(5):1308–16.

    Article  PubMed  PubMed Central  Google Scholar 

  32. Tafelski S, Yi H, Ismaeel F, Krannich A, Spies C, Nachtigall I. Obesity in critically ill patients is associated with increased need of mechanical ventilation but not with mortality. J Infect Public Health. 2016;9(5):577–85.

    Article  PubMed  Google Scholar 

  33. Devarajan J, Vydyanathan A, You J, Xu M, Sessler DI, Sabik JF, Bashour CA. The association between body mass index and outcome after coronary artery bypass grafting operations. Eur J Cardiothorac Surg. 2016;50(2):344–9.

    Article  PubMed  Google Scholar 

  34. Imber DA, Pirrone M, Zhang C, Fisher DF, Kacmarek RM, Berra L. Respiratory management of perioperative obese patients. Respir Care. 2016;61(12):1681–92.

    Article  PubMed  Google Scholar 

  35. Wu Z, Wang Z, Wu H, Hu R, Ren W, Hu Z, Chang J. Obesity is a risk factor for preoperative hypoxemia in Stanford A acute aortic dissection. Medicine (Baltimore). 2020;99(11): e19186.

    Article  CAS  PubMed  Google Scholar 

  36. Nakajima T, Kawazoe K, Izumoto H, Kataoka T, Niinuma H, Shirahashi N. Risk factors for hypoxemia after surgery for acute type A aortic dissection. Surg Today. 2006;36(8):680–5.

    Article  PubMed  Google Scholar 

  37. Salome CM, King GG, Berend N. Physiology of obesity and effects on lung function. J Appl Physiol (1985). 2010;108(1):206–11.

    Article  PubMed  Google Scholar 

  38. Fantuzzi G. Adipose tissue, adipokines, and inflammation. J Allergy Clin Immunol. 2005;115(5):911–9 quiz 920.

    Article  CAS  PubMed  Google Scholar 

  39. Mohanty P, Hamouda W, Garg R, Aljada A, Ghanim H, Dandona P. Glucose challenge stimulates reactive oxygen species (ROS) generation by leucocytes. J Clin Endocrinol Metab. 2000;85(8):2970–3.

    Article  CAS  PubMed  Google Scholar 

  40. Wisse BE. The inflammatory syndrome: the role of adipose tissue cytokines in metabolic disorders linked to obesity. J Am Soc Nephrol. 2004;15(11):2792–800.

    Article  CAS  PubMed  Google Scholar 

  41. Zemel MB, Sun X, Sobhani T, Wilson B. Effects of dairy compared with soy on oxidative and inflammatory stress in overweight and obese subjects. Am J Clin Nutr. 2010;91(1):16–22.

    Article  CAS  PubMed  Google Scholar 

  42. Jo Y, Anzai T, Sugano Y, Naito K, Ueno K, Kohno T, Yoshikawa T, Ogawa S. Early use of beta-blockers attenuates systemic inflammatory response and lung oxygenation impairment after distal type acute aortic dissection. Heart Vessels. 2008;23(5):334–40.

    Article  PubMed  Google Scholar 

  43. Hosogai N, Fukuhara A, Oshima K, Miyata Y, Tanaka S, Segawa K, Furukawa S, Tochino Y, Komuro R, Matsuda M, et al. Adipose tissue hypoxia in obesity and its impact on adipocytokine dysregulation. Diabetes. 2007;56(4):901–11.

    Article  CAS  PubMed  Google Scholar 

  44. Furukawa S, Fujita T, Shimabukuro M, Iwaki M, Yamada Y, Nakajima Y, Nakayama O, Makishima M, Matsuda M, Shimomura I. Increased oxidative stress in obesity and its impact on metabolic syndrome. J Clin Invest. 2004;114(12):1752–61.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  45. Bazurro S, Ball L, Pelosi P. Perioperative management of obese patient. Curr Opin Crit Care. 2018;24(6):560–7.

    Article  PubMed  Google Scholar 

  46. Gottlieb DJ, Punjabi NM. Diagnosis and management of obstructive sleep apnea: A review. JAMA. 2020;323(14):1389–400.

    Article  PubMed  Google Scholar 

  47. Cozowicz C, Memtsoudis SG. Perioperative management of the patient with obstructive sleep apnea: A narrative review. Anesth Analg. 2021;132(5):1231–43.

    Article  PubMed  Google Scholar 

  48. Lyons PG, Mokhlesi B. Diagnosis and management of obstructive sleep apnea in the perioperative setting. Semin Respir Crit Care Med. 2014;35(5):571–81.

    Article  PubMed  Google Scholar 

  49. Trivedi D, Navid F, Balzer JR, Joshi R, Lacomis JM, Jovin TG, Althouse AD, Gleason TG. Aggressive Aortic Arch and Carotid Replacement Strategy for Type A Aortic Dissection Improves Neurologic Outcomes. Ann Thorac Surg. 2016;101(3):896–903 Discussion 903–895.

    Article  PubMed  Google Scholar 

  50. Yang Z, Yang S, Wang F, Hong T, Lai H, Wang C. Type A aortic dissection occurring after previous cardiac surgery. J Card Surg. 2015;30(11):830–5.

    Article  PubMed  Google Scholar 

  51. Nienaber CA, Fattori R, Mehta RH, Richartz BM, Evangelista A, Petzsch M, Cooper JV, Januzzi JL, Ince H, Sechtem U, et al. Gender-related differences in acute aortic dissection. Circulation. 2004;109(24):3014–21.

    Article  PubMed  Google Scholar 

  52. Maitusong B, Sun HP, Xielifu D, Mahemuti M, Ma X, Liu F, Xie X, Azhati A, Zhou XR, Ma YT. Sex-Related Differences Between Patients With Symptomatic Acute Aortic Dissection. Medicine (Baltimore). 2016;95(11): e3100.

    Article  PubMed  Google Scholar 

  53. Shih YC, Li HW, Chen YF. Are there gender differences in patients with acute type A aortic dissection? J Thorac Cardiovasc Surg. 2016;151(6):1771–2.

    Article  PubMed  Google Scholar 

  54. Gasser S, Stastny L, Kofler M, Krapf C, Bonaros N, Grimm M, Dumfarth J. Type A aortic dissection is more aggressive in women. Eur J Cardiothorac Surg. 2022;62(2):ezac040.

  55. Lawrence KW, Yin K, Connelly HL, Datar Y, Brydges H, Balasubramaniyan R, Karlson KJ, Edwards NM, Dobrilovic N. Sex-based outcomes in surgical repair of acute type A aortic dissection: A meta-analysis and meta-regression. J Thorac Cardiovasc Surg. 2022:S0022-5223(22)00129-5.

Download references

Funding

This work was sponsored by the National Natural Science Foundation of China (No.82200526 and No.81970328), the Shanghai Rising-Star Program (No.23QB1400900), the Shanghai “Rising Stars of Medical Talents” Youth Development Program (No.SHWRS2023-62), the Shanghai Sailing Program (No.20YF1405400), the Clinical Research Fund of Shanghai Municipal Health Commission (No.20224Y0286), and the Shanghai Special Research Project on Aging Population and Maternal and Child Health (No.2020YJZX010).

Author information

Authors and Affiliations

Authors

Contributions

Jinmiao Chen and Lai Wei designed and supervised this work. Wenyu Song, Jiani Liu and Lulu Pan performed literature research and data analysis. Wenyu Song wrote the original manuscript. Jinmiao Chen, Lai Wei, Jiani Liu, Guowei Tu, Lulu Pan, Yixiang Hong and Lieyang Qin revised the manuscript. All authors approved the final version of the manuscript.

Corresponding authors

Correspondence to Lai Wei or Jinmiao Chen.

Ethics declarations

Ethics approval and consent to participate

This work is a systematic review of literature and meta-analysis. Ethical and safety considerations are not appliable.

Consent for publication

Not appliable.

Competing interests

The authors declare no competing interests.

Additional information

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary Information

Additional file 1.

Additional file 2:

 Figure S1. Effect of BMI on perioperative mortality of ATAAD (exclude a low sample study).

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Song, W., Liu, J., Tu, G. et al. Impact of body mass index on perioperative mortality of acute stanford type A aortic dissection: a systematic review and meta-analysis. BMC Cardiovasc Disord 23, 531 (2023). https://doi.org/10.1186/s12872-023-03517-z

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1186/s12872-023-03517-z

Keywords