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\begin{document}

\title{Prognostic factors of hospital mortality for unplanned re-exploration
after cardiovascular surgery}



\author[1]{Jianying Deng}%
\author[1]{Qianjin Zhong}%
\affil[1]{Affiliation not available}%


\vspace{-1em}



  
  \date{May 27, 2024}


\begingroup
\let\center\flushleft
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\maketitle
\endgroup





\selectlanguage{english}
\begin{abstract}
Objective To explore the prognostic factors of hospital mortality for
unplanned re-exploration after cardiovascular surgery. Methods We
retrospectively analyzed the data of 100 patients who underwent
unplanned re-exploration after cardiovascular surgery in our hospital
between May 2010 and May 2020. There were 77 males and 23 females, aged
(55.1\selectlanguage{ngerman}±15.2) years. Demographic characteristics, operation information,
perioperative complications were collected to set up a database. The
patients were divided into survival group and non-survival group
according to hospital mortality. Logistic regression was used for
multivariable analysis to explore the prognostic factors of hospital
mortality. These statistically significant indicators were selected for
drawing the receiver operating characteristic curve of the evaluation
model, calculating the area under the curve(AUC) and evaluating the
effectiveness of the new model with Hosmer-Lemeshow C-statistic. Results
Hospital mortality was 26.0\% (26/100). Multivariate logistics
regression revealed that the operation time of unplanned re-exploration,
the worst blood creatinine within 48h before the re-exploration, the
worst lactate within 24h after the re-exploration, cardiac
insufficiency, respiratory insufficiency, and acute kidney injury were
independent prognostic factors (p\textless{}0.05). The AUC of the new
assessment model constituted by these prognostic factors was 0.910, and
the Hosmer-Lemeshow C-statistic was 4.153 (P= 0.762). Conclusions The
operation time of unplanned re-exploration, the worst blood creatinine
value within 48h before the re-exploration, the worst lactate value
within 24h after the re-exploration, cardiac insufficiency, respiratory
insufficiency, and acute kidney injury were independent prognostic
factors of hospital mortality for unplanned re-exploratio after
cardiovascular surgery.%
\end{abstract}\selectlanguage{ngerman}%



\sloppy


Prognostic factors of hospital mortality for unplanned re-exploration
after cardiovascular surgery

Jianying Deng,\textsuperscript{1} M.D. Qianjin Zhong\textsuperscript{2},
M.D.

\textsuperscript{1}Department of Cardiovascular Surgery,Chongqing
Kanghua Zhonglian Cardiovascular Hospital,

Chong Qing 400015, China

\textsuperscript{2}Department of Cardiovascular Surgery, Army Medical
Center of PLA, Chong Qing 400020, China

Correspondence: Jianying Deng, Department Of Cardiovascular
Surgery,Chongqing Kanghua Zhonglian Cardiovascular Hospital, No. 168,
Haier Road, District of Jiang Bei, Chong Qing 400015, China. e-mail:
65673171@qq.com

{[}\textbf{Abstract} {]} \textbf{Objective} To explore the prognostic
factors of hospital mortality for unplanned re-exploration after
cardiovascular surgery. \textbf{Methods} We retrospectively analyzed the
data of 100 patients who underwent unplanned re-exploration after
cardiovascular surgery in our hospital between May 2010 and May 2020.
There were 77 males and 23 females, aged (55.1\selectlanguage{ngerman}±15.2) years. Demographic
characteristics, operation information, perioperative complications were
collected to set up a database. The patients were divided into survival
group and non\selectlanguage{english}-survival group according to hospital mortality. Logistic
regression was used for multivariable analysis to explore the prognostic
factors of hospital mortality. These statistically significant
indicators were selected for drawing the receiver operating
characteristic curve of the evaluation model, calculating the area under
the curve(AUC) and evaluating the effectiveness of the new model with
Hosmer\selectlanguage{english}-Lemeshow C\selectlanguage{english}-statistic. \textbf{Results} Hospital mortality was
26.0\% (26/100). Multivariate logistics regression revealed that the
operation time of unplanned re-exploration, the worst blood creatinine
value within 48h before the re-exploration, the worst lactate value
within 24h after the re-exploration, cardiac insufficiency, respiratory
insufficiency, and acute kidney injury were independent prognostic
factors (\emph{p} \textless{}0.05). The AUC of the new assessment model
constituted by these prognostic factors was 0.910, and the
Hosmer\selectlanguage{english}-Lemeshow C\selectlanguage{english}-statistic was 4.153 (\emph{P=}
0.762).\textbf{Conclusions} The operation time of unplanned
re-exploration, the worst blood creatinine value within 48h before the
re-exploration, the worst lactate value within 24h after the
re-exploration, cardiac insufficiency, respiratory insufficiency, and
acute kidney injury were independent prognostic factors of hospital
mortality for unplanned re-exploratio after cardiovascular surgery. To
identify thess factors can promote preventive measures effectively and
improve the prognosis of patients.

{[}Key words{]} cardiovascular surgery; re-exploration; hospital
mortality; prognostic factor

Unplanned re-exploration is a serious adverse event after cardiovascular
surgery, which will prolong the patient's hospital stay, ICU stay,
mechanical ventilation time, and ultimately lead to an increase in the
incidence of complications{[}1-3{]}. The study showed that hospital
mortality rate of patients underwend unplanned re-exploration was
8\%-25\% {[}4{]}, which was far higher than that of patients who did not
underwent secondary thoracotomy. A large number of previous studies have
mostly focused on patients with severe bleeding or cardiac arrest after
cardiac surgery, focusing on the factors related to the second open
thoracotomy after cardiovascular surgery. These results showed that
elderly age, low body mass index, long cardiopulmonary bypass time, and
secondary surgery are independent prognostic factors for patients who
require a redo thoracotomy after cardiovascular surgery {[}5-7{]}. On
the basis of previous research, combined with the characteristics of our
hospital, we took patients who underwent unplanned re\selectlanguage{english}-exploration after
cardiac and aortic surgery as the research objectives, and explored the
prognostic factors of hospital mortality after re-exploration. In order
to better screen critically ill patients after redo thoracotomy, improve
the clinical treatment effectively, and improve the prognosis of
patients.

Materials and Methods

Research objective We retrospectively analyzed the data of consecutive
patients who underwent cardiac and aortic surgery in our hospital
between May 2010 and May 2020. Inclusion criteria: (1) accepted cardiac
and aortic surgery; (2) stayed in the ICU after the operation; (3)
performed unplanned re-exploration for exploratory surgery. Exclusion
criteria: Accept minimally invasive surgery, including robotic heart
surgery. A total of 4 329 patients undergoing cardiac and aortic surgery
were admitted during the period, of which 110 patients were stranded in
the ICU after unplanned re-exploration after cardiovascular surgery, and
10 minimally invasive surgery were excluded. Thererfor, a total of 100
patients were included in the analysis. There were 77 males and 23
females, aged (55.1+-15.2) years (range: 15 to 75 years), and body mass
index was (22.2+-3.0) kg/m\textsuperscript{2} (range: 17.1 to 35.2
kg/m\textsuperscript{2}). Fifty-five patients had a history of
hypertension, and 17 patients had a history of diabetes.

This study is a retrospective study, with informed consent from patients
or one of family members. This study has been approved by the ethics
committee of the Chongqing Kanghua Zhonglian Cardiovascular Hospital and
Army Medical Center of PLA, and has been recognized as exempt from
ethical review.

Research methods 2.1 Information Collection Collect the patient's
demographic characteristics, operation information, postoperative
information and perioperative complications. Demographic characteristics
includes age, sex, body mass index, high blood pressure and diabetes
history. Operation information includes operation time, operation
methods (including, coronary artery bypass grafting, valve surgery,
aortic surgery and other operations), whether it is an emergency
operation, whether it is a second operation, and whether it is an
extracorporeal bypass operation. The postoperative information includes
the reason and time of the re-exploration and the re-operation time, the
liver and kidney indexes (serum creatinine, urea nitrogen, AST, ALT,
total bilirubin, direct bilirubin) of the patient within 48 hours, the
worst blood lactate and blood potassium values within 24 hours, whether
intra-aortic balloon pump (IABP) is required, whether extracorporeal
membrane oxygenation (ECMO) therapy or continuous renal replacement
therapy (CRRT) is required. Perioperative complications mainly including
cardiac insufficiency (New York Heart Association grade
\selectlanguage{english}III\textasciitilde{}\selectlanguage{english}IV), acute kidney injury, perioperative liver
insufficiency, respiratory insufficiency, lung and blood infection,
craniocerebral complications (brain infarction, cerebral hemorrhage,
coma, delirium and confusion), atrial fibrillation and ventricular
fibrillation. 2.2 Establish an assessment model of inpatient mortality
The end of the observation was the hospital mortality of the patients.
The differences between the variables of the survival group and the
death group were compared, and meaningful variables of univariate
analysis were incorporated into the Logistics regression model for
multivariate analysis to clarify the prognostic factors that affect the
patient's death in hospital, and construct a scoring model based on the
prognostic factors. 2.3 Test the evaluation performance of the model
These statistically significant indicators were selected for plotting
the receiver operation characteristic curves, calculating the area under
the curve(AUC). The Hosmer\selectlanguage{english}-Lemeshow C\selectlanguage{english}-statistic was used to evaluate the
efficiency of the new model.

Statistical analysis SPSS 22.0 statistical software was used to analyze
the data. The quantitative data of the normal distribution is expressed
as \selectlanguage{english}?x +- s, and the independent sample t test is used for the comparison
between groups; the quantitative data of the non-normal distribution is
expressed as M (QR), and the non-parametric Mann-Whitney U test is used
for the comparison between groups.Frequency and percentage are
expressed, and comparisons between groups are performed by \selectlanguage{greek}χ\selectlanguage{ngerman}² test or
Fisher's exact probability method. Univariate analysis\emph{P}
\textless{}0.05 variables were included in the Logistics regression
model for multivariate analysis to determine the prognostic factors of
the patient's hospital mortality, and based on the results of the
multivariate analysis, the receiver operating characteristic curve was
drawn and the AUC was calculated. The difference was statistically
significant with \emph{P} \textless{}0.05.

Results

In this study, the hospital mortality of unplanned re-exploration was
2.5\% (110/4 329), and the hospital mortality of the enrolled patients
was 26.0\% (26/100). The results of univariate analysis showed that
there were statistically significant differences in the operation time,
whether it was a cardiopulmonary bypass operation, and whether it was an
emergency operation between the survival group and the non\selectlanguage{english}-survival
group (Table 1).

Compared with patients in the survival group, patients in the
non-survival group had a lower rate of re-exploration due to excessive
drainage, however, a higher rate of re-exploration due to ventricular
fibrillation and unexplained circulatory instability. In non-survival
group, the second thoracotomy exploratory operation time is longer, and
the ratio of ECMO and CRRT before and after the second exploratory is
higher. The differences in the worst liver and kidney function indexes
within 48 hours before and after the re-exploration and the worst blood
lactic acid value and the worst serum potassium value within 24 hours
before and after the re-exploration between the two groups were
statistically significant (Table 2). The incidence of cardiac
insufficiency (New York Heart Association grade \selectlanguage{english}III\textasciitilde{}\selectlanguage{english}IV),
respiratory insufficiency, acute kidney injury, perioperative liver
insufficiency, blood infection, and craniocerebral complications in the
non-survival group after the re-exploration was significantly higher
than that of survival group of patients (Table 3).

The statistically significant variables in the univariate analysis were
incorporated into the Logistics regression model for multivariate
analysis. The results showed that the worst blood creatinine value
within 48h before the re-exploration, the worst blood lactate value
within 24h after the re-exploration, cardiac insufficiency, respiratory
insufficiency, and acute kidney injury are the prognostic factors of
hospital mortality in patients undergoing re-exploration after
cardiovascular surgery (Table 4). Based on these prognostic factors, the
evaluation model of hospital mortality of patients with re-exploration
after cardiovascular surgery was constructed. The AUC of this model was
0.910, and the evaluation efficiency was good
(\selectlanguage{greek}χ\selectlanguage{english}\textsuperscript{2}=4.153, \emph{P} =0.762).

In addition, according to the reasons for the re-exploration, the
patients are divided into A (ventricular fibrillation + unexplained
circulatory instability re-exploration patients) and B (different
drainage + pericardial tamponade + re-exploration patients with other
reasons) group. The time of the re-exploration in group A was 3.0 (3.0)
h, which was longer than 2.0 (0.5)h in group B (\emph{Z} =
-5.929,\emph{P} =0.000); the ICU retention time was 5 (7) d, which was
longer than 3 (5) d in group B (\emph{Z} = -2.148, \emph{P} =0.032);
mechanical ventilation time was 111.0 (170.6) min, which was longer than
76.0 (101.3) min in group B (\emph{Z} = -2.065, \emph{P} =0.039).

Discussion

Cardiac and aortic surgery is the main treatment for cardiovascular
disease. Postoperative bleeding and cardiac arrest are the main
complications that lead to early postoperative death or serious adverse
events. When these complications are difficult to correct through
conservative treatment, in order to avoid further deterioration of the
disease, patients often need to undergo secondary thoracotomy
exploration. The re-exploration will bring the patient a large amount of
foreign blood products, the risk of mediastinal and deep soft tissue
infections, and it is a prognostic factor for severe postoperative
complications {[}8-10{]}. The surgical trauma of the second thoracotomy
exploration and the perioperative volume control of the patient make the
body prone to heart and kidney dysfunction, respiratory insufficiency,
and even multiple organ dysfunction syndrome, which seriously affects
the patient's prognosis.

In this study, the second thoracotomy exploratory operation time of
patients in the non-survival group was significantly higher than that of
patients in the survival group. Research results show that the operation
time is obviously related to postoperative complications. Every time of
the operation time is extended by 1 hour, the risk of complications will
increase accordingly {[}11-13{]}. However, in addition to the operation
method itself, the severity of the patient's disease and the level of
the surgeon will also affect the operation time {[}14{]}. In the future,
it is necessary to further explore the reasons for the prolonged
operation time in order to better clarify the relationship between it
and the patient outcome.

Blood lactic acid level is also a prognostic factor for hospital
mortality after cardiac surgery, and it can more sensitively reflect the
state of hypoperfusion and insufficient oxygen supply in the early stage
{[}15-16{]}. The hemodynamics of cardiacr surgery patients are not
stable within 24 hours after operation, which is likely to cause lactic
acid accumulation. Therefore, it is very important to closely monitor
the changes of lactic acid within 24 hours after operation. Once
abnormal blood lactic acid is found, if it can effectively improve
tissue perfusion and oxygenation in a short period of time, it will
significantly improve the clinical treatment effect of cardiac surgery
patients.

Acute kidney injury is a common serious complication after cardiac
surgery and an independent prognostic factor of hospital mortality after
cardiac surgery. Serum creatinine is closely related to changes in renal
function after cardiac surgery. A slight increase in this index
(\textgreater{}0.017 mmol/L) will significantly prolong hospital stay
and mortality {[}17-18{]}. The results of our study showed that the
worst serum creatinine value in the non-survival group within 48 hours
before the second thoracotomy exploration was significantly higher than
that of the survival group, suggesting that monitoring of serum
creatinine during the perioperative period has a certain value in
evaluating the outcome of patients. The AUC of this model is 0.910, and
the evaluation performance is good (\selectlanguage{greek}χ\selectlanguage{english}\textsuperscript{2}=4.153,\emph{P}
=0.762), which further shows that these prognostic factors have a high
evaluation value for the hospital mortality of patients with
re-exploration. Additonally, there is a good degree of fit between the
data and the patient's outcome. To clarify the prognostic factors of
hospital mortality in patients with re-exploration can effectively guide
us to timely screen critically ill patients after cardiaovascular
surgery, adjust clinical treatment strategies in time, and improve the
prognosis of patients.

Among the 100 patients in this study, 25 patients had a re-exploration
due to unexplained circulatory instability and ventricular fibrillation.
Among them, 48.0\% (12/25) patients died. This group hostital mortality
(48.0\%) was much higher than that of patients hostital mortality
{[}18.7\% (14/75){]} who had re-exploration due to large drainage and
other reasons. Compared with the former, the purpose of the second
exploratory thoracotomy in the latter group is clear. It can effectively
relieve the symptoms of patients and improve the prognosis through
timely and effective second exploratory thoracotomy to stop bleeding and
place drainage. When the patient undergoes a second exploratory
thoracotomy due to circulatory instability or ventricular fibrillation
caused by an unknown reason, the purpose and method of the operation
before re-exploration are not clear. Secondary exploratory thoracotomy
is often only used as a rescue operation. It is necessary to choose
cardiopulmonary resuscitation, application of mechanical assistance, or
another surgical treatment such as coronary artery bypass grafting
according to the patient's intraoperative situation, which makes the
re-operation time relatively prolonged and seriously affects the
prognosis of patients. However, since this study only included patients
who underwent secondary thoracotomy due to ventricular fibrillation or
circulatory instability, the pros and cons of the treatment results
compared with patients who did not undergo secondary thoracotomy are
still uncertain, and further analysis is needed in the future.
Clarifying the purpose of surgery and the reason for re-exploration has
high clinical value for evaluating the patient's condition and
formulating precise treatment plans.

Conclusions

This study still has some limitations. First of all, whether
anticoagulant drugs are used before re-exploration, the type of
anticoagulant drugs used and the time of application have a greater
impact on postoperative bleeding and the prognosis of patients
{[}19-20{]}. In addition, due to the lack of original data, the
corresponding analysis of anticoagulant drugs could not be performed in
this study. Secondly, this study is a single-center retrospective study
with a small sample size, which reduces the scientific nature of the
research results. In the future, we need to collect more complete case
data while expanding the sample size, and further verify the results
through multi-center studies.

\textbf{Data availabity statement} : all data used during this study can
be shared.

\textbf{Funding} : None.

\textbf{Conflict of interest:} All authors declare that there is no
conflict of interest.

\textbf{Ethical review:} This study has been approved by the ethics
committee of the Chongqing Kanghua Zhonglian Cardiovascular Hospital and
Army Medical Center of PLA, and has been recognized as exempt from
ethical review.

\textbf{Informed consent (or waiver) statemen} t: This study is a
retrospective study, with informed consent from patients or one of
family members.

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