Skip to main content
Download PDF

The prognostic significance of postoperative hyperbilirubinemia in cardiac surgery: systematic review and meta-analysis

Journal of Cardiothoracic Surgery volume 17, Article number: 129 (2022) Cite this article

Abstract

Background

Hyperbilirubinemia following cardiac surgery is a common phenomenon and is of emerging interest in prognostic factor research. This systematic review and meta-analysis evaluated the association between post-operative hyperbilirubinemia (PH) and mortality and morbidity in cardiac surgery patients.

Methods

Ovid Medline and Ovid Embase were searched from inception to July 2020 for studies evaluating the prognostic significance of PH following cardiac surgery. Maximally adjusted odds ratios (OR) with associated confidence intervals were obtained from each study and pooled using random effects inverse variance modelling to assess in-hospital mortality. Standardised mean differences were pooled to assess Intensive Care Unit (ICU) and hospital length of stay (LOS). Qualitative analysis was performed to assess ventilation requirements and long-term mortality. Meta-regression was used to assess inter- and intra-study heterogeneity.

Results

3251 studies satisfied the selection criteria, from which 12 studies incorporating 3876 participants were included. PH significantly predicted in-hospital mortality with a pooled OR of 7.29 (95% CI 3.53, 15.09). Multiple pre-defined covariates contributed to the prognostic significance of PH, however only aortic cross-clamp time (p < 0.0001) and number of transfusions (p = 0.0001) were significant effect modifiers. PH significantly predicted both ICU LOS (Mean difference 1.32 [95% CI 0.04–2.6]) and hospital LOS (Mean difference 1.79 [95% CI 0.36–3.21]). Qualitative analysis suggested PH is associated with increased post-operative ventilation requirements and reduced long-term survival rates.

Conclusions

Hyperbilirubinemia is a cost-effective, widely available prognostic marker of adverse outcomes following cardiac surgery, albeit with residual sources of heterogeneity.

Peer Review reports

Introduction

Post-operative hyperbilirubinemia (PH), generally described as > 3 mg/dL, is a common complication following cardiac surgery. PH incidence varies between 10 and 40% depending on the severity of underlying cardiac disease and the type of surgery performed [1,2,3,4]. Moreover, PH has been associated with adverse patient outcomes such as prolonged ICU stay, new onset infection, low-output syndrome, and increased requirements for invasive ventilation and renal replacement therapy [5].

The aetiology of PH is debated and thought to be multifactorial. Cardiopulmonary bypass (CPB) is a recognised risk factor that can lead to hypoperfusion, systemic inflammation and haemolysis [6,7,8]. Additional risk factors include patient age, heart failure status, postoperative sepsis, and intra-operative administration of blood products [2, 9,10,11].

Despite advancements in CPB and anaesthesia techniques, the incidence of hyperbilirubinemia after cardiac surgery has not decreased since the first report in 1967 [9, 11, 12]. A recent study reported a 10% incidence with an associated mortality of 17.4% [5]. This mortality rate rises to 90% in cases when progression to hepatic failure is observed [1, 3, 13]. Moreover, the timing of bilirubin elevation post-surgery is of clinical importance with late-onset hyperbilirubinemia (> 7 days) being associated with increased mortality [5].

Given that plasma bilirubin assays are routinely performed after cardiac surgery and may be a predictor of adverse patient outcome we conducted a systematic review and meta-analysis to evaluate the prognostic value of PH following cardiac surgery.

Methods

Study design and registration

This systematic review and meta-analysis was constructed in accordance with the Preferred Reporting Items for Systematic reviews and Meta-Analysis (PRISMA) Statement [14], and conducted according to methodological guidance [15]. Details of the protocol of this prognostic research review were registered prospectively (PROSPERO ID CRD42020206068). There were no protocol deviations.

Eligibility criteria

Eligible studies met the following criteria (a) randomized controlled trials, non-randomized controlled trials (case control or controlled cohort), observational studies (b) study population of adult patients (aged ≥ 18 years) (c) exposure to cardiopulmonary bypass for coronary artery bypass grafting (CABG), valvular surgery or combined CABG and valvular surgery (e) outcome measure of plasma bilirubin reported (f) outcome measure of mortality or morbidity measured. Studies involving organ transplant, ventricular assist devices, and extracorporeal membrane oxygenation were excluded.

Search strategy

OVID Medline and OVID Embase were searched from inception to July 2020 using a set of a validated and comprehensive keywords and medical subject headings (MeSH) relating to ‘cardiac surgery,’ ‘hyperbilirubinemia’ and ‘mortality and morbidity’ (see Additional file 1). Reference lists from published articles were hand searched for potentially relevant studies. No restrictions were placed on language or publication year. The reference lists of the included studies were separately searched for further potential citations.

Study selection

Two reviewers (DR and LP) independently screened titles and abstracts of all identified studies. Full text screening of potentially relevant studies was performed by the same reviewers with a third author (JPD) adjudicating any disagreements. The definition of hyperbilirubinemia was as defined by the authors in each study, if no definition was given a cut-off of 3 mg/dL (51.3 µmol/L) was used.

Data extraction and management

Two reviewers (DR and LP) independently extracted the following information onto standardised forms: Study designs, population demographics, co-morbidities, operative details, proportion with PH, timing of PH peak, conjugated vs unconjugated phenotype of PH, ICU length of stay (LOS), hospital LOS, post-operative ventilation time and mortality following discharge (see Additional file 2). Where provided, maximally adjusted odds ratio (OR) for short term survival were used. Mean differences were used for continuous outcomes. Where studies stratified patients into more than two groups (e.g. tertiles or quartiles) we compared the upper most quantile against the cumulative lowermost quantiles.

Assessment of methodological quality

The Prediction model Risk Of Bias Assessment Tool (PROBAST) was utilised to assess the methodological quality of the included studies. Assessment was performed by two review authors (DR and LAP) and disagreements were resolved through discussion with a third author (JPD). PROBAST is tailored for prognostic studies and assesses risk of bias across four domains: participants, predictors, outcome, and analysis [16, 17].

Statistical analysis and data synthesis

We tabulated the maximally adjusted OR with associated 95% confidence intervals for each study assessing in-hospital mortality and generated a pooled OR using mixed-methods (generalised linear) inverse variance modelling. For continuous outcomes such as ICU and hospital LOS, we generated mean differences with 95% confidence intervals. Analysis was of post-operative ventilation times or long-term mortality was not performed due to the low number of reporting studies.

Chi-square statistics were used to estimate statistical heterogeneity for each outcome. Where there were greater than 10 studies reporting an outcome, we conducted a meta-regression to explore sources of statistical heterogeneity by inputting the following covariates: study year, age, proportion of males, bilirubin threshold (as defined by study authors), day of bilirubin measurement, cardiopulmonary bypass time, clamp time, number units of blood transfused and proportion with pre-operative liver disease. Where there were fewer than 10 studies reporting on an outcome, potential sources of clinical and statistical heterogeneity were explored qualitatively.

Publication bias was formally assessed by generating funnel plots. Visual testing of skew was performed, and funnel plot asymmetry was analysed using the Classical Egger test, fixed- and mixed-effects meta-regression models with p values [18, 19]. To further examine for suppression of non-significant studies, we constructed a contour enhanced funnel plot [20]. All analyses were performed using the R statistical package ‘metafor’, with figures generated using ‘ggplot2’ [21, 22].

Results

Search results

The search returned 3878 citations and an additional four relevant citations were found from other sources. The removal of duplicates resulted in 3251 unique studies. After title and abstract screening, 84 studies underwent full text review of which 12 studies were selected (see Fig. 1).

Fig. 1
figure 1

Prisma Flow chart

Full size image

Description of included studies

Study design, patient demographics, operative details, days of bilirubin measurement, presence of preoperative liver disease and number of units of blood transfused are detailed in (see Table 1). The 12 studies were published between 1983 and 2017 and included a total of 3876 participants [23,24,25,26,27,28,29,30,31,32,33,34]. All included studies reported post-operative bilirubin measurements. Four studies were retrospective [25, 27,28,29], and the other eight studies were prospective. The mean age ranged from 32 to 71 years with a high proportion of the participants being male. The threshold for hyperbilirubinemia ranged from 2 to 3 mg/dL. Seven studies set a threshold of 3 mg/dL [23,24,25,26, 30, 32, 33], four studies at 2 mg/dL [27, 29, 31, 34], and one study at 2.8 mg/dL [28]. Nine studies reported post-operative bilirubin levels for at least 7 days following surgery [23, 24, 26,27,28, 30, 31, 33, 34]. Two studies reported measurements up to 2 and 5 days respectively [25, 29], with one study not specifying the days of measurement [32]. Several of the pre-specified modifier covariates were inconsistently reported and are provided as an online supplement.

Table 1 Characteristics of Included Studies
Full size table

Maximally adjusted OR for in-hospital mortality was reported in two studies [29, 32], unadjusted data were extracted from the remaining ten studies. We calculated standardised mean differences for ICU LOS from six studies [23,24,25, 27, 29, 30, 32, 33], and hospital LOS from four studies [26, 28, 31, 34].

Methodological quality

The overall methodological quality of the studies was poor with only 2 studies having low risk of bias [28, 32], and 10 studies having high risk of bias (see Fig. 2). Studies reporting only unadjusted data such as frequency of deaths observed were deemed high risk due to the potential for unaccounted for significant confounding variables. The complete table of PROBAST scores for each included study is available in the (see Additional file 3).

Fig. 2
figure 2

PROBAST risk of bias graph

Full size image

Meta-analysis

Quantitative analysis

In-hospital mortality

All studies reported on hospital mortality. PH was strongly associated with in-hospital mortality following cardiac surgery (OR 7.29 [95% CI 3.53, 15.09]) (see Fig. 3). Between-study statistical heterogeneity was substantial (I2 73.8%) with aortic cross clamp time and transfusion requirements being significant effect modifies on meta-regression analysis (see Table 2). The remaining pre-specified covariates were either not significant or not included in the meta-regression due to insufficient reporting (see Additional file 2). The variability introduced by the covariates and other study and patient-level factors partially contributes to the residual heterogeneity and the wide confidence interval. The mortality rates in the PH group was 13.08% (9.35) versus 2.21% (2.38) in the non-PH group (see Additional file 4).

Fig. 3
figure 3

Forest plot for PH predicting in-hospital mortality. Arrowheads indicate continuing confidence intervals

Full size image
Table 2 In-hospital mortality meta-regression results
Full size table
ICU LOS

Six studies inclusive of 1974 patients reported ICU LOS [23, 26, 27, 31, 33, 34]. PH was associated with longer ICU LOS, albeit with marked heterogeneity (Mean difference 1.32 [95% CI 0.04, 2.6], I2 = 99.26%).) (see Fig. 4).

Fig. 4
figure 4

Forest plot for PH predicting ICU LOS

Full size image
Hospital LOS

Four studies inclusive of 1979 patients reported hospital LOS [26, 28, 31, 34]. PH was associated with a longer hospital LOS, albeit with marked heterogeneity (Mean difference 1.79 [95% CI 0.36, 3.21], I 2= 99.03%) (see Fig. 5).

Fig. 5
figure 5

Forest plot for PH predicting hospital LOS

Full size image

Qualitative analysis

Ventilation time

Two studies involving a total of 862 patients reported the relationship between PH and duration of mechanical ventilation [23, 31]. Both studies reported longer duration of mechanical ventilation in patients with PH; (25.3 ± 13.3 h vs 16.5 ± 9.2 h, p < 0.05) [23] and (23.92 ± 45.93 h vs 15.55 ± 34.32 h, p = 0.0001) [31].

Long term mortality

Diab et al. [25] reported 5-year mortality in 285 patients following surgery for infective endocarditis. Five-year survival was lowest in patients with preoperative liver dysfunction (20.1%) compared to 37.1% in patients with PH and 57% in patients with normal pre-operative liver function and no PH.

Kraev et al. [28] reported 2 year mortality in 826 patients following CPB. Patients were categorised into tertiles according to post-operative plasma bilirubin: group 1 (normal bilirubin levels), group 2 (1.4–2.8 mg/dL) and group 3 (> 2.8 mg/dL). Mortality at 24 months was 3.7% in patients with normal post-operative bilirubin and 16.7% in the upper tertile of plasma bilirubin (p < 0.001).

Phenotype of hyperbilirubinemia

PH incidence is higher in patients undergoing valvular surgeries compared to CABG only, and this finding is pronounced when multiple valves are operated on [23, 24, 26, 30, 31, 33, 34]. Most of the included studies differentiated between conjugated and unconjugated PH. Some attribute the observed PH as being predominantly conjugated bilirubin [24, 30], while others point to unconjugated bilirubin [33, 34]. The remaining studies suggest a mixed picture.

Mortality rates

All studies except for two studies reported on the mortality rates observed in PH group vs non-PH group (see Additional file 4). The mean mortality rate in the PH group was 13.08% ± 9.35. The mean mortality rate in the non-PH group was 2.21% ± 2.38.

Publication bias

Publication bias was detected with the fixed-effects meta-regression model (p = 0.0152), but not the mixed-effects regression model for funnel asymmetry (p = 0.752) or the classical Egger test (p = 0.248). Visual inspection of asymmetry however shows slight asymmetry (see Additional file 5). Contour-enhanced funnel plot indicates suppression of studies reporting non-significant findings (see Fig. 6).

Fig. 6
figure 6

Contour Enhanced Funnel Plot

Full size image

Discussion

In this systematic review and meta-analysis, we found PH to be a promising prognostic biomarker for increased mortality and morbidity in cardiac surgery patients. The key finding of this study is that PH increases the odds of in-hospital mortality by sevenfold, especially in patients demonstrating persistent or late PH (POD > 7). The observed mortality rates were comparable to the figures reported by Australian and New Zealand Society of Cardiac and Thoracic Surgeons' Cardiac Surgery (ANZCTS) and the Society of Thoracic Surgeons (STS) [35, 36]. PH is also associated with longer ICU and hospital lengths of stay. Other covariates such as study year, age, bilirubin threshold, bilirubin monitoring period, CPB time, gender, proportion of CABG and proportion with existing pre-operative liver disease were not identified as significant modifiers. The overall methodological quality was poor due to high risk of bias and between-study heterogeneity was considerable, these factors may limit the generalisability of our findings, therefore further needed research will likely change our understanding of PH.

The meta-regression identified that the prognostic value of PH for in-hospital mortality increases with aortic cross-clamp time and number of blood units transfused. Longer cross-clamp times during cardiac surgery expose the patient to greater risks of low cardiac output, hypoxia and hypothermia which exacerbate hepatic injury [25, 26, 28, 30]. It is interesting to note that although total cross-clamp time was found to be a significant covariate in predicting in-hospital mortality, CPB time was not. Some studies provide support for this by demonstrating no significant difference in CPB time when comparing those that developed PH and those who did not [33]. Bilirubin accumulation from RBC hemolysis following perioperative blood transfusion can also increase risk of PH. Although this is reflected in our meta-regression, our observed transfusion requirements are marginally higher than what is indicated by current literature [5]. The inclusion of further studies with well-reported covariates are needed to increase the generalisability of our findings.

Several studies demonstrated preoperative liver disease to be a strong risk factor for PH, mortality, and morbidity [23,24,25, 27, 30, 31, 33, 34]. Our meta-regression did not detect a significant relationship between preoperative liver disease and the pooled odds ratio for in-hospital mortality. This may be due to the variability amongst authors in defining preoperative liver disease. Some defined preoperative liver disease using total bilirubin, others used aminotransferase derangements, and some used Model for End-Stage Liver Disease (MELD) scores. Similarly, there was variability amongst authors in how they obtained and defined the threshold value for hyperbilirubinemia. Consequently, we were unable to detect an effect-modifier relationship between hyperbilirubinemia threshold and the pooled odds ratio.

Qualitative analysis showed that patients with early PH characteristically demonstrate elevation of unconjugated bilirubin—most likely the result of the transient physiological insult by CPB, anaesthetics and blood transfusions [5]. These patients generally improve within 3 days[37]. The phenotype for patients with persistent or late PH (POD > 7) was predominantly conjugated. These patients were more likely to have long term hepatic dysfunction and multiple-organ failure due to systemic hypoperfusion, leading to increased mortality and morbidity [5, 10, 30]. The debate around the prognostic value of conjugated hyperbilirubinemia alone presents an interesting opportunity for future research. Only two studies reported on long term mortality, both suggesting PH is associated with poor long-term outcomes. More longitudinal studies are required to further investigate cause of death and morbidity in the long-term setting.

Limitations

Insufficient reporting of relevant data and inconsistencies in the data reported prevented the inclusion of all relevant studies. This is compounded by the possible publication bias. Therefore, the predictive value of PH may be overstated and external validity to current practice maybe limited.

Secondly, there is a high level of residual heterogeneity due to insufficient reporting of patient and study level covariates. This in turn reduced both the precision of the pooled statistics and our ability to reliably perform sub-group analyses.

Only two studies performed multivariable analyses to adjust for potential confounders [25, 28]. Consequently, most studies were classified as having high risk of bias.

The range of PH in our included studies was 9% to 51%, with 3 of the most recent studies reporting PH rates of 25% [25, 26, 31]. Although these rates are consistent with epidemiological literature [5], more research is needed to interpret the variable incidence rates of PH. The relatively high incidence could be explained by the observation that while a portion of patients with biochemical PH will have clinical manifestations of hyperbilirubinemia, some will be restricted to an isolated (and clinically occult) biochemical event.

The low rate of observed deaths in the included studies reduced the confidence of our summary estimates for in-hospital mortality, ICU LOS and hospital LOS. Therefore, larger cohort studies with greater statistical power are needed to improve the confidence and precision of summary estimates.

Implications for future research and practice

Qualitative analysis reveals CPB to be strong risk factor for PH and mortality, yet its complete effect on the human body remains to be understood. Therefore, additional CPB models should be developed to create safer and artificial circulation models.

The most widely ordered and investigated prognostic cardiac biomarkers are C-reactive protein (CRP), troponin, B-type natriuretic peptide (BNP), and N-terminal pro-BNP (Nt-pro-BNP) [38,39,40]. However, an array of new proteins, adhesion molecules and cytokines are also being investigated as potential prognostic biomarkers [41]. To our knowledge, this is the first systematic review and meta-analysis to synthesize the available evidence on the prognostic value of PH in cardiac surgery and to highlight the significance of early vs late PH peaks. The addition of PH to the list of newer prognostic haematological indices may aid in creating reliable predictive models for estimating mortality and morbidity in post-operative cardiac patients. Future research should focus on phenotyping PH as conjugated vs unconjugated and early vs delayed to determine which phenotypic profile confers the least and most favourable prognosis.

From a surgical standpoint, intra-operative considerations to prevent PH include aiming for reduced cross-clamp times and decreasing blood transfusion requirements. Patients with pre-existing heart failure or liver dysfunction require meticulous peri-operative planning and management [30]. Cardiac surgery is not recommended in patients with class C Child–Pugh cirrhosis [42]. Continual plasma bilirubin monitoring is paramount and persistent PH should prompt further investigations. Management of PH is mainly supportive with the main aim being the prevention of progression to hepatic failure, multi-organ failure and sepsis.

Conclusion

PH is a promising prognostication tool predictive of in-hospital mortality. The timing of PH peaks may help differentiate between patients with transient hyperbilirubinemia, warranting longer ICU stay, from those with hepatic dysfunction, warranting longer hospital stay. Persistent PH should alarm the clinician of impending hepatic failure. Further high-quality studies that consistently report on patient level and study level co-variates are needed to reduce statistical heterogeneity and improve precision of summary estimates.

Availability of data and materials

Generated data that is not already included as supplementary material are available from the corresponding author, DR, upon reasonable request.

Abbreviations

PH:

Post-operative hyperbilirubinemia

ICU:

Intensive care unit

CPB:

Cardiopulmonary bypass

PRISMA:

Preferred reporting items for systematic reviews and meta-analysis

PROBAST:

The prediction model risk of bias assessment tool

CABG:

Coronary artery bypass grafting

LD:

Liver dysfunction

LOS:

Length of stay

CB:

Conjugated bilirubin

UCB:

Unconjugated bilirubin

PICO:

Population intervention comparator outcome

References

  1. Chu CM, Chang CH, Liaw YF, Hsieh MJ. Jaundice after open heart surgery: a prospective study. Thorax. 1984;39(1):52–6.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  2. Hsu RB, Lin FY, Chen RJ, Chou NK, Ko WJ, Chi NH, et al. Incidence, risk factors, and prognosis of postoperative hyperbilirubinemia after heart transplantation. Eur J Cardiothorac Surg. 2007;32(6):917–22.

    Article  PubMed  Google Scholar 

  3. Michalopoulos A, Alivizatos P, Geroulanos S. Hepatic dysfunction following cardiac surgery: determinants and consequences. Hepatogastroenterology. 1997;44(15):779–83.

    CAS  PubMed  Google Scholar 

  4. Olsson R, Hermodsson S, Roberts D, Waldenstrom J. Hepatic dysfunction after open-heart surgery. Scand J Thorac Cardiovasc Surg. 1984;18(3):217–22.

    Article  CAS  PubMed  Google Scholar 

  5. Farag M, Veres G, Szabo G, Ruhparwar A, Karck M, Arif R. Hyperbilirubinaemia after cardiac surgery: the point of no return. ESC Heart Fail. 2019;6(4):694–700.

    Article  PubMed  PubMed Central  Google Scholar 

  6. Gardeback M, Settergren G, Brodin LA. Hepatic blood flow and right ventricular function during cardiac surgery assessed by transesophageal echocardiography. J Cardiothorac Vasc Anesth. 1996;10(3):318–22.

    Article  CAS  PubMed  Google Scholar 

  7. Kumle B, Boldt J, Suttner SW, Piper SN, Lehmann A, Blome M. Influence of prolonged cardiopulmonary bypass times on splanchnic perfusion and markers of splanchnic organ function. Ann Thorac Surg. 2003;75(5):1558–64.

    Article  PubMed  Google Scholar 

  8. Pintar T, Collard CD. The systemic inflammatory response to cardiopulmonary bypass. Anesthesiol Clin North Am. 2003;21(3):453–64.

    Article  CAS  PubMed  Google Scholar 

  9. Lockey E, McIntyre N, Ross DN, Brookes E, Sturridge MF. Early jaundice after open-heart surgery. Thorax. 1967;22(2):165–9.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  10. Mastoraki A, Karatzis E, Mastoraki S, Kriaras I, Sfirakis P, Geroulanos S. Postoperative jaundice after cardiac surgery. Hepatobiliary Pancreat Dis Int. 2007;6(4):383–7.

    PubMed  Google Scholar 

  11. Robinson JS, Cole FR, Gibson P, Simpson JA. Jaundice following cardiopulmonary bypass. Thorax. 1967;22(3):232–7.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  12. Sanderson RG, Ellison JH, Benson JA Jr, Starr A. Jaundice following open-heart surgery. Ann Surg. 1967;165(2):217–24.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  13. Arif R, Seppelt P, Schwill S, Kojic D, Ghodsizad A, Ruhparwar A, et al. Predictive risk factors for patients with cirrhosis undergoing heart surgery. Ann Thorac Surg. 2012;94(6):1947–52.

    Article  PubMed  Google Scholar 

  14. Moher D, Liberati A, Tetzlaff J, Altman DG, Group P. Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. PLoS Med. 2009;6(7):e1000097.

    Article  PubMed  PubMed Central  Google Scholar 

  15. Riley RD, Hayden JA, Steyerberg EW, Moons KG, Abrams K, Kyzas PA, et al. Prognosis research strategy (PROGRESS) 2: prognostic factor research. PLoS Med. 2013;10(2):e1001380.

    Article  PubMed  PubMed Central  Google Scholar 

  16. Moons KGM, Wolff RF, Riley RD, Whiting PF, Westwood M, Collins GS, et al. PROBAST: a tool to assess risk of bias and applicability of prediction model studies: explanation and elaboration. Ann Intern Med. 2019;170(1):W1–33.

    Article  PubMed  Google Scholar 

  17. Wolff RF, Moons KGM, Riley RD, Whiting PF, Westwood M, Collins GS, et al. PROBAST: a tool to assess the risk of bias and applicability of prediction model studies. Ann Intern Med. 2019;170(1):51–8.

    Article  PubMed  Google Scholar 

  18. Egger M, Davey Smith G, Schneider M, Minder C. Bias in meta-analysis detected by a simple, graphical test. BMJ. 1997;315(7109):629–34.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  19. Sterne J, Egger M. Publication bias in meta‐analysis: prevention, assessment and adjustments. In: Rothstein H, editor. Regression methods to detect publication and other bias in meta‐analysis: John Wiley & Sons, Ltd; 2005.

  20. Peters JL, Sutton AJ, Jones DR, Abrams KR, Rushton L. Contour-enhanced meta-analysis funnel plots help distinguish publication bias from other causes of asymmetry. J Clin Epidemiol. 2008;61(10):991–6.

    Article  PubMed  Google Scholar 

  21. Sterne J, Egger M. Funnel plots for detecting bias in meta-analysis: guidelines on choice of axis. J Clin Epidemiol. 2001;54(10):1046–55.

    Article  CAS  PubMed  Google Scholar 

  22. Viechtbauer W. Conducting meta-analyses in R with the metafor package. J Stat Softw. 2010;36(3):1–48.

    Article  Google Scholar 

  23. An Y, Xiao YB, Zhong QJ. Hyperbilirubinemia after extracorporeal circulation surgery: a recent and prospective study. World J Gastroenterol. 2006;12(41):6722–6.

    Article  PubMed  PubMed Central  Google Scholar 

  24. Collins JD, Bassendine MF, Ferner R, Blesovsky A, Murray A, Pearson DT, et al. Incidence and prognostic importance of jaundice after cardiopulmonary bypass surgery. Lancet. 1983;1(8334):1119–23.

    Article  CAS  PubMed  Google Scholar 

  25. Diab M, Sponholz C, von Loeffelholz C, Scheffel P, Bauer M, Kortgen A, et al. Impact of perioperative liver dysfunction on in-hospital mortality and long-term survival in infective endocarditis patients. Infection. 2017;45(6):857–66.

    Article  CAS  PubMed  Google Scholar 

  26. Golitaleb M, Kargar F, Aghai FG, Harorani M, Jadidi A, Abkenar HB, et al. Hyperbilirubinemia after open cardiac surgery. Iran Heart J. 2017;18(2):30–5.

    Google Scholar 

  27. Hosotsubo KK, Nishimura M, Nishimura S. Hyperbilirubinaemia after major thoracic surgery: comparison between open-heart surgery and oesophagectomy. Crit Care. 2000;4(3):180–7.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  28. Kraev AI, Torosoff MT, Fabian T, Clement CM, Perez-Tamayo RA. Postoperative hyperbilirubinemia is an independent predictor of longterm outcomes after cardiopulmonary bypass. J Am Coll Surg. 2008;206(4):645–53.

    Article  PubMed  Google Scholar 

  29. Leacche M, Winkelmayer WC, Paul S, Lin J, Unic D, Rawn JD, et al. Predicting survival in patients requiring renal replacement therapy after cardiac surgery. Ann Thorac Surg. 2006;81(4):1385–92.

    Article  PubMed  Google Scholar 

  30. Nishi H, Sakaguchi T, Miyagawa S, Yoshikawa Y, Fukushima S, Saito S, et al. Frequency, risk factors and prognosis of postoperative hyperbilirubinemia after heart valve surgery. Cardiology. 2012;122(1):12–9.

    Article  CAS  PubMed  Google Scholar 

  31. Sharma P, Ananthanarayanan C, Vaidhya N, Malhotra A, Shah K, Sharma R. Hyperbilirubinemia after cardiac surgery: an observational study. Asian Cardiovasc Thorac Ann. 2015;23(9):1039–43.

    Article  CAS  PubMed  Google Scholar 

  32. Vidal S, Richebe P, Barandon L, Calderon J, Tafer N, Pouquet O, et al. Evaluation of continuous veno-venous hemofiltration for the treatment of cardiogenic shock in conjunction with acute renal failure after cardiac surgery. Eur J Cardiothorac Surg. 2009;36(3):572–9.

    Article  PubMed  Google Scholar 

  33. Wang MJ, Chao A, Huang CH, Tsai CH, Lin FY, Wang SS, et al. Hyperbilirubinemia after cardiac operation. Incidence, risk factors, and clinical significance. J Thorac Cardiovasc Surg. 1994;108(3):429–36.

    Article  CAS  PubMed  Google Scholar 

  34. Chandra A, Gupta D, Saibaba SS, Dilip D, Kola S, Naidu MS. Hyperbilirubinemia after cardiopulmonary bypass: a prospective study. Asian Cardiovasc Thorac Ann. 1999;7(1):3–8.

    Article  Google Scholar 

  35. Shardey G, Tran L, WIlliams-Spence J, Solman N, Mclaren J, Marrow N, et al. The Australian and New Zealand society of cardiac and thoracic surgeons' cardiac surgery database program annual report 2020. Australia: Monash University, Department of Epidemiology and Preventive Medicine; 2021 Decemeber Report No.: 14.

  36. Bowdish ME, D’Agostino RS, Thourani VH, Desai N, Shahian DM, Fernandez FG, et al. The society of thoracic surgeons adult cardiac surgery database: 2020 update on outcomes and research. Ann Thorac Surg. 2020;109(6):1646–55.

    Article  PubMed  Google Scholar 

  37. Diaz GC, Renz JF. Cardiac surgery in patients with end-stage liver disease. J Cardiothorac Vasc Anesth. 2014;28(1):155–62.

    Article  PubMed  Google Scholar 

  38. Min JJ, Nam K, Kim TK, Kim HJ, Seo JH, Hwang HY, et al. Relationship between early postoperative C-reactive protein elevation and long-term postoperative major adverse cardiovascular and cerebral events in patients undergoing off-pump coronary artery bypass graft surgery: a retrospective study. Br J Anaesth. 2014;113(3):391–401.

    Article  CAS  PubMed  Google Scholar 

  39. Eikvar L, Pillgram-Larsen J, Skjaeggestad O, Arnesen H, Stromme JH. Serum cardio-specific troponin T after open heart surgery in patients with and without perioperative myocardial infarction. Scand J Clin Lab Invest. 1994;54(4):329–35.

    Article  CAS  PubMed  Google Scholar 

  40. Gasparovic H, Burcar I, Kopjar T, Vojkovic J, Gabelica R, Biocina B, et al. NT-pro-BNP, but not C-reactive protein, is predictive of atrial fibrillation in patients undergoing coronary artery bypass surgery. Eur J Cardiothorac Surg. 2010;37(1):100–5.

    Article  PubMed  Google Scholar 

  41. Preeshagul I, Gharbaran R, Jeong KH, Abdel-Razek A, Lee LY, Elman E, et al. Potential biomarkers for predicting outcomes in CABG cardiothoracic surgeries. J Cardiothorac Surg. 2013;8:176.

    Article  PubMed  PubMed Central  Google Scholar 

  42. Lin CH, Hsu RB. Cardiac surgery in patients with liver cirrhosis: risk factors for predicting mortality. World J Gastroenterol. 2014;20(35):12608–14.

    Article  PubMed  PubMed Central  Google Scholar 

Download references

Acknowledgements

Not applicable

Funding

This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.

Author information

Authors and Affiliations

  1. Department of Anaesthesia and Pain Management, Royal Melbourne Hospital, 300 Grattan St, Parkville, VIC, 3050, Australia

    Dev Raveendran, Reny Segal, Zhengyang Liu & Luke A. Perry

  2. Melbourne Medical School, University of Melbourne, Parkville, Australia

    Dev Raveendran & Zhengyang Liu

  3. Department of Surgery, School of Clinical Science, Monash University, Clayton, Australia

    Jahan C. Penny-Dimri & Julian A. Smith

  4. Department of Surgery, Barwon Health, Geelong, Australia

    Jahan C. Penny-Dimri

  5. Department of Cardiothoracic Surgery, Monash Health, Clayton, Australia

    Julian A. Smith

  6. Centre for Integrated Critical Care, University of Melbourne, Parkville, Australia

    Mark Plummer

  7. Intensive Care Unit, Royal Melbourne Hospital, Parkville, Australia

    Mark Plummer

Authors
  1. Dev Raveendran
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Jahan C. Penny-Dimri
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Reny Segal
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Julian A. Smith
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Mark Plummer
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Zhengyang Liu
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Luke A. Perry
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

LP conceived the idea. DR and LP performed the search strategy and data extraction. DR performed and wrote the systematic review and meta-analysis. J.C.P acted as third judicator and manuscript reviewer. RS, JS, MP, and ZL helped review and refine the manuscript. All authors read and approved the final manuscript.

Corresponding author

Correspondence to Dev Raveendran.

Ethics declarations

Ethics approval and consent to participate

Not applicable.

Consent for publication

Not applicable.

Competing interests

The authors declare that they have 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

. Search strategy (OVID Medline).

Additional file 2

. Table of summary characteristics.

Additional file 3

. Table of PROBAST assessment of Bias.

Additional file 4

. Table of Mortality Rates.

Additional file 5

. Funnel Plot for estimation of publication bias.

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

Verify currency and authenticity via CrossMark

Cite this article

Raveendran, D., Penny-Dimri, J.C., Segal, R. et al. The prognostic significance of postoperative hyperbilirubinemia in cardiac surgery: systematic review and meta-analysis. J Cardiothorac Surg 17, 129 (2022). https://doi.org/10.1186/s13019-022-01870-2

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1186/s13019-022-01870-2

Keywords

  • Cardiopulmonary bypass
  • Hyperbilirubinemia
  • Jaundice
  • Length of stay
  • Prognostic biomarkers

Journal of Cardiothoracic Surgery

ISSN: 1749-8090

Contact us