Mortality in Surgical Site Infections Post-cardiac Surgery - a Prospective, International Id-iri Study

doi:10.21203/rs.3.rs-4281241/v1

OBJECTIVES

Surgical site infections (SSIs) after cardiac surgery increase morbidity and mortality. This multi-center study aimed to identify mortality risk factors associated with SSIs following heart surgery.

METHODS

Conducted from January to March 2023, this prospective study included 167 patients aged > 16 with post-heart surgery SSIs. The primary focus was on 30-day mortality. Univariate analysis and a multivariate logistic regression model, utilizing the Backward elimination method, were employed to establish the final model.

RESULTS

A number of factors had substantial correlations to death. These included urinary catheterization [OR 14.197 (90% CI 12.198–91.721)], emergent surgery [OR 8.470 (90% CI 2.028–35.379)], valvular replacement [OR 4.487 (90% CI 1.001–20.627)], higher qSOFA scores [OR 3.147 (90% CI 1.450–6.827)], advancing age [OR 1.075 (90% CI 1.020–1.132)] and postoperative re-interventions within 30 days following SSI [OR 14.832 (90% CI 2.684–81.972)]. No pathogen was isolated from wound cultures in 53 (31.7%) patients. 43.1% of SSIs (n = 72) were due to Gram-positive microorganisms, while 27.5% of cases (n = 46) involved Gram-negatives. Among Gram-positives, Staphylococci (n = 30, 17.9%) were the predominant microorganisms, while Klebsiellae (n = 16, 9.6%), Escherichia coli (n = 9, 5.4%), Pseudomonas aeruginosa (n = 7, 4.2%), and were the most prevalent among Gram-negatives. Colonization with VRE, MRSA, carbapenem resistant enteric bacteria on admission was detected in 9 (6.1%) cases.

CONCLUSION

To mitigate mortality following heart surgery, stringent infection control measures, preoperative screening, and effective surgical antisepsis are crucial. Timely detection of bloodstream infections and the clinical progression of the disease reflected by qSOFA score, and effective treatment are other essential components of SSI management.

Surgical site infection

CABG

sternotomy

infection

mortality

cardiac surgery

Surgical site infections (SSIs) can result in serious consequences for patients who undergo cardiac surgery. Infections can lead to prolonged hospital stays, additional medical treatments, reoperations, increased morbidity and mortality, and raised costs [1]. In addition, cardiac surgery patients are often elders with pre-existing medical conditions, making them more vulnerable to complications from SSIs [2]. Hence, infections can compromise the success of the cardiac surgery itself.

Identifying the characteristics of patients with SSIs and exploring factors predicting mortality is crucial for the optimization of the patient management. Thus, this prospective observational international study aimed to analyze patients with SSIs after cardiac surgery and investigated factors leading to mortality.

This multi-center study was conducted prospectively between January 1^st 2023 and March 31^st 2023.

Inclusion criteria: Adult patients (>16 years of age) who developed SSIs after cardiac surgery following sternotomy were enrolled into the study.

Definitions

Antibiotic de-escalation: This is a strategy to reduce the spectrum of administered antibiotics, either by stopping one or more components of combination therapy, changing an antimicrobial for another with a narrower spectrum [3,4].

Antibiotic escalation: This is a strategy in which the initial broad-spectrum antibiotic treatment is increased [3,4].

Multidrug resistant (MDR) isolates: MDR bacteria were described elsewhere [5].

Surgical site infection: SSIs were defined according to CDC criteria [6].

Outcome measure: The outcome was 30-day postoperative mortality.

Data collection: The data were collected from 29 centers in 12 countries (Afghanistan, Bosnia-Herzegovina, Croatia, Egypt, Iran, Italy, Poland, Saudi Arabia, Serbia, Pakistan, North Macedonia, Türkiye) through a web-based case report form. The parameters related to demographic, clinical, laboratory, and therapeutic parameters, prior prophylaxis, and 30-day mortality data were recorded.

Ethical consent: The ethical consent of the study was approved/registered by the Istanbul Medeniyet University, School of Medicine at 23.11.2022 (No: 20220672). The centers obtained the local approvals if deemed necessary.

Statistical Analysis: The assumption of normal distribution for parametric tests was examined with the Shapiro-Wilk test, and it was observed that continuous variables have not have a normal distribution. For the comparison of the survivors and those who died of SSI in terms of unadjusted effects of these variables, the Mann-Whitney U test was used. The association between categorical variables and mortality was investigated using the Pearson chi-square test. Candidate variables for estimating the risk of death in the multivariate model to be established were selected based on univariate tests, with a P-value less than 0.10. Multiple binary logistic regression models and classification and regression tree (CART) algorithms, one of the machine learning algorithms, were used to obtain the adjusted effects. The internal validity of the logistic regression model and CART algorithm was assessed using the 5-fold cross-validation method. Furthermore, their performances were evaluated using some metrics such as area under the curve (AUC), false positive and false negative, sensitivity, specificity, positive predictive value, and classification accuracy. Due to the small total number of deceased cases (n=11) and the unbalanced distribution between survivors and patients who died, determining the significant effects of risk factors in multivariate models could be challenging. Therefore, a statistical significance level of P<0.10 was accepted, and SPSS (ver. 23) and Orange (ver. 3.35.0) programs were used for calculations.

The data of 275 patients were received from the participating centers, but 108 of these cases were excluded from the study either because they were ineligible or due to missing data. Surgical procedures were as follows: CABG (n=131), valvular replacement (n=50), surgery of the aorta (n=7), ASD closure (n=3), heart transplantation (n=1). Eleven patients died of SSIs while an additional six patients who underwent CABG died due to causes unrelated to SSIs and were consequently excluded from the analysis. Hence, 161 patients were included and analyzed for SSI related mortality.

Types and findings of SSIs: Patients with SSIs were categorized into superficial incisional (n=115, 68.9%), deep incisional (n=32, 20.9%), and organ/space SSIs (n=20, 12%). Local findings were:

Localized swelling, redness, heat, or fever, and the incision is opened deliberately or spontaneously dehisces (n=80, 47.9%)
Purulent drainage from the superficial fascia (n=76, 45.5%), deep fascia (n=40, 23.9%), muscles (n=14, 8.3%), organ or space component of the surgical site (n=17, 10.2%)
Abscess formation (n=16, 9.6%)
Organ space infection [(n=20, 12%), mediastinitis (n=9), retrosternal infection (n=6), endocardial infection on prosthetic valves after surgery (n=2), graft infection (n=2), transplanted heart infection after surgery (n=1)].

Coexisting infections: Coexisting other foci of hospital-acquired infections were identified in 37 patients, representing 22.2% of the total cases. Pneumonia (n=17, 10.2%), catheter associated urinary tract infection (n=14, 8.3%), central line associated blood stream infections (n=10, 6%), decubitus infection (n=1, 0.6%), endocarditis (n=1, 0.6%).

Microbiological data: In 53 (31.7%) patients, no microorganism was isolated from wound cultures. Gram-negatives were recovered in 46 (27.5%) patients, while Gram-positive microorganisms were recovered in 72 (43.1%) patients. In two patients, two microorganisms were recovered (Pseudomonas aeruginosa and Staphylococcus aureus in one, and Escherichia coli plus Enterococcus faecium in the other). The isolated microorganisms in descending order were as follows: Coagulase negative Staphylococci (CoNS) [n=30, 17.9% (Staphylococcus epidermidis; n=21), (Staphylococcus haemolyticus; n=1), (untyped CoNS; n=8)], Klebsiellae [n=16, 9.6% (Klebsiella pneumoniae; n=12), (Klebsiella aerogenes; n=3), (Klebsiella oxytoca; n=1)], E. coli (n=9), P. aeruginosa (n=7), Enterococci [n=5, 3% (Enterococcus faecalis, n=3), (E. faecium n=2)], Serratia marcescens (n=4), Corynebacterium striatum (n=3), Proteus spp [n=3, 1.8% (P. mirabilis; n=2), (P. vulgaris; n=1)], Acinetobacter baumannii (n=2), Streptococcus anginosus (n=1), Cutibacterium acnes (n=1), Morganella morganii (n=1).

Preoperative MDR colonization: In 148 patients MDR colonization were screened for vancomycin resistant enterococci (VRE), methicillin-resistant Staphylococcus aureus (MRSA), and carbapenem resistant enteric bacteria (CRE). There were 9 (6.1%) MDR bacteria colonized patients [Vancomycin resistant E. faecium (n=2), MRSA (n=5), carbapenem resistant enteric bacteria (n=2)].

Empirical antimicrobial treatment: Single-antibiotic regimens were employed in 73 patients (43.7%), double-antibiotic combinations were administered in 94 cases (56.3%), and triple-antibiotic combinations were empirically given in 2 patients (1.2%). The antibiotics used in the empirical treatment of SSIs in descending order were piperacillin-tazobactam (n=33; 19.8%), imipenem/meropenem (n=29; 17.4%), clindamycin/lincomycin (n=29; 17.4%), ampicillin-sulbactam (n=23; 13.8%), vancomycin (n=23; 9%), cefazolin (n=14; 8.4%), ceftriaxone/cefotaxime (n=12; 7.2%), linezolid (n=11; 6.6%), gentamicin (n=10; 6%), ciprofloxacin (n=8; 4.8%), metronidazole (n=4; 2.4%), cefepime (n=3; 1.8%), ceftazidime (n=3; 1.8%), amikacin (n=3; 1.8%), cefuroxime (n=2; 1.2%), colistin/polymyxin-B (n=2; 1.2%), daptomycin (n=2; 1.2%), ertapenem (n=1; 0.6%), meropenem-vaborbactam (n=1; 0.6%), cloxacillin (n=1; 0.6%), amoxicillin-clavulanic acid (n=1; 0.6%), micafungin (n=1; 0.6%).

Therapeutic suitability: Appropriate treatment was given empirically in 71 (42.5%) patients while inappropriate treatment was given 43 (25.7%). In the remaining 53 (31.7%) patients, cultures were negative.

Antibiotic modification: It was done in 76 (44.5%) patients. Treatment was escalated in 52 (31.1%) patients while de-escalation was done in 24 (14.4%) patients.

Results of univariate analysis: For the 11 patients died of SSI, the average survival time was 18.6 ± 16.15 days with a median value of 11 (IQR=7-28). Table-1 illustrates the distribution of categorical features, while Table-2 presents descriptive statistics for numerical characteristics of patients who experienced mortality (n=11, 6.6%) and those who survived (n=150, 89.8%). Both tables contain comparative results of survivors and patients who died, assessed through univariate tests.

Results of multivariate logistic regression model: Significant variables with a P value of P<0.10 in Table-1 and Table-2 were examined using a multivariate logistic regression model with the Backward elimination method. This model includes the adjusted effects of variables and was used to predict the risk of death. The final model results were presented in the Table-3. Upon evaluating the results, it was seen that in individuals undergoing emergent surgery, those with valvular replacement, as the qSOFA score increases, in individuals with urinary catheter at the time of SSI, and when postoperative re-intervention done within 30 days after SSI, there was a significant increase in the risk of death (P<0.10) (Table-3).

The prediction model: In this model, the predicted probabilities of each individual are between 0-1, and when those with a probability greater than 0.10 are classified as "dead" and those with a lower probability are classified as "survived", the diagnostic success criteria were obtained as shown in Table-4.

Where;

X₁: Surgery classification is elective, otherwise this value equal to “0”
X₂: qSOFA Score
X₃: Urinary catheter is Yes, otherwise this value equal to “0”
X₄: Was postop re-intervention done within 30 days of SSI is Yes, otherwise this value equal to “0”
X₅: Age
X₆: Valvular replacement is present, otherwise this value equal to “0”

The nomogram of the logistic regression model, which makes it easier for researchers to calculate the death risk of any person was provided (Figure-1). ROC curve of predicted probabilities from the logistic regression were shown in Figure-2. When the cut-off value of the predictions of death probabilities obtained from the final model was accepted as 0.10 due to the unbalanced distribution in the number of survivors and deaths, the numbers of correctly and incorrectly classified patients and model performance metrics are presented in the Table-4. Ten of 11 (90.9%) patients who actually died were classified as dead according to the logistic regression model. Of the 150 patients who were actually alive, fifteen (10%) were predicted to have died also according to the logistic regression model.

SSIs observed after cardiac surgeries can lead to delayed healing, pain and discomfort, prolonged hospitalization, more profound infections affecting tissues, bones, or implanted devices such as pacemakers or stents, necessitating further surgical procedures or interventions. In addition, systemic infections like sepsis and a high risk of mortality can also result from SSIs in cardiac surgery cases. In this prospective study, we found significant increases in death risk among patients with SSIs developed after cardiac surgery like emergent surgery, valvular replacement, higher qSOFA scores, increasing age, urinary catheterization at the time of SSI, and postoperative re-interventions within 30 days after SSI.

While superficial SSIs are more common, organ/space SSIs are considered more serious [7]. In this study, although we found that organ/space infections were associated with significantly higher mortality in the univariate analysis, we could not establish such a correlation in the multivariate analyses, possibly due to the low numbers in this group. On the other, we found that postoperative re-intervention, which was identified as a predictor of mortality, may involve addressing deep-seated infections where surgical drainage of the infected cavity is the common approach [8]. However, despite being regarded as less serious, superficial incisional SSIs can still result in discomfort for the patient, a delay in the healing of the wound, higher costs, and excessive complications if left untreated. In addition, patients who undergo valvular replacement have a higher likelihood of mortality when SSIs occur. Although data elucidating the higher mortality rates in SSIs among patients undergoing valvular replacement is lacking, it is noted that minimally invasive valve surgery can decrease the likelihood of deep wound infections compared to the standard thoracotomy procedure [9], which is the preferred approach in our patient cohort. Thus, despite the absence of a direct correlation between deep-wound infections and mortality, the use of valvular replacement and postoperative re-intervention as indicators of mortality for SSIs were significant.

Hospitalized patients with bloodstream infections are known to be at an increased risk of complications and death [10, 11]. While the univariate analysis showed a notable connection, our final model did not reveal a clear association between mortality and bacteremia, likely influenced by variations in blood culture practices across surgical departments. Additionally, although coexistent pneumonia was found to be significant in initial analyses, its predictive power for mortality was limited, potentially because of the small number of cases involved.

Our study found that emergency surgery was linked to a higher risk of mortality compared to elective surgery. Previous research has shown that preoperative optimization and adequate preparation are crucial for surgical outcomes [12]. Therefore, it is possible that disruptions in the antisepsis chain may have contributed to SSIs caused by aggressive and drug-resistant hospital-acquired pathogens, rather than harmless skin colonizers. This, in turn, may have led to increased mortality rates. Consequently, the high mortality rate associated with emergency surgery may serve as an indicator of inadequate preoperative optimization, raising concerns about patient safety and ethics.

Patients who had a qSOFA score of 1 or less were more likely to survive. The recognized utility of qSOFA in predicting mortality in sepsis and critical infections aligns with the favorable prognosis associated with a qSOFA score of 1 or lower [13]. The result that patients with higher qSOFA scores are likely to die highlights how crucial it is to identify and treat patients at risk of worsening as soon as possible.

We found that the development of SSIs after cardiac surgery was significantly associated with increased mortality, particularly in older patients. This is consistent with previous research that has identified age as a major risk factor for mortality in patients who develop SSIs after surgery. Increasing age is linked to a weakening of the immune system, rendering older patients more vulnerable to infections, especially when coupled with a high burden of comorbidities [14, 15]. Therefore, it is crucial to implement effective infection control strategies to prevent SSIs in older patients undergoing cardiac surgery.

The findings of this study provide important information about the microbial makeup of SSIs following sternotomy. Gram-negative microorganisms were found in 27.5% of patients with SSIs, whereas Gram-positive microorganisms were more prevalent, accounting for 43.1%. Other epidemiological studies reported the higher prevalence of Gram-positive bacteria following major cardiac surgery in general [16, 17] or MRSA in particular [18]. While staphylococci were the dominant Gram-positives, K. pneumoniae, E. coli, P. aeruginosa were the leading Gram-negatives in this study. In addition, 6.1% of our patients were previously colonized with VRE, MRSA, and CRE on admission to hospital. Therefore, the presence of these highly resistant pathogens colonizing cardiac surgery patients underscores the urgent requirement for rigorous infection control measures, and urges the implementation of screening strategies prior to cardiac surgery.

Managing SSIs, along with a negative culture report in routine medical practices poses a formidable challenge, constituting over 30% of cases worldwide, as supported by our data [19]. Accordingly, one-third of SSIs in this study had negative cultures, which could be due to early start of antimicrobial treatment before taking cultures. Additionally, common colonizers like CoNS, Corynebacterium, and Acinetobacter spp.[20] were identified in two-fifths of the cultures, further complicating the interpretation of microbiological results for targeted therapy. Accordingly, the lack of specific pathogen identification and their antibiotic susceptibility in certain number of post-cardiac surgery SSI cases impeded our capacity to evaluate the statistical effectiveness of targeted antimicrobial treatment in this study. According to our data, piperacillin-tazobactam, carbapenems, and lincosamides were the most common antibiotics used in the empirical treatment. Among cases where antibiotic susceptibility data were ultimately available, only two-thirds received suitable initial empirical therapy while the remaining one-third needed adjustments to their antimicrobial treatments after obtaining the susceptibility data. Since rational antimicrobial therapy stands as the cornerstone for treating critical infections [21], the identification of the pathogen alongside its antibiotic susceptibility data is pivotal in managing SSIs [22]. Overall, antibiotic modification was done in 44.5% of the patients whom was escalated in two-thirds and de-escalated in one-third emphasizing the importance of microbiological input in optimizing therapy.

The strengths of this study are its prospective design and inclusion of patients solely with major cardiac surgery, and exclusion of patients with missing data aggressively. In addition, our model successfully forecasted the death with an easy-to-use nomogram (figure-1). In summary, the results of this study provide key insights into the relationships between various risk factors and mortality. Emergent surgery, and qSOFA score should be identified to help healthcare providers identify patients who are more likely to die. In an era marked by extensive antibiotic resistance, the surgeon conducting cardiac surgery should utilize every possible means to obtain microbiological data, especially before commencing antimicrobial treatment. In addition, SSIs following valvular replacement, presence of urinary catheter at the time of SSI, and requirement of postoperative re-interventions should alert the treating surgeon on the potential poor outcomes. Our study provides a core understanding into effective prevention, early detection, and rational management of SSIs following major cardiac surgery.

Funding: None to declare.

Conflict of interest: None to declare.

Data Availability

All data and analytical methods will be made available upon reasonable request.

Author contributions

Hakan Erdem, Handan Ankarali designed the study. Farouq Dayyaband Abdulwahab Al-Khalifacontributed the design. Handan Ankarali performed the statistical analysis. Hulya Caskurluobtained the ethical approval. All other authors managed and followed the patients with SSIs, collected and submitted the data. Hakan Erdem, Jaffar A. Al-Tawfiq, Handan Ankarali wrote the paper. All the authors have agreed on the manuscript submitted.

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Table-1. Descriptive statistics of the categorical characteristics of patients died of SSI and the survivors

Risk Factors		Survived (n=150)		Death (n=11)
Risk Factors		n	%	n	%	P*
Gender	Female	42	89.4	5	10.6	0.219
Surgery classification	Emergency	29	80.6	7	19.4	0.001
Diabetes mellitus	Absent	59	88.1	8	11.9	0.030
Acute renal failure	Present	8	80.0	2	20.0	0.088
Chronic renal failure	Present	11	91.7	1	8.3	0.830
Hypertension	Absent	32	88.9	4	11.1	0.248
Chronic respiratory disease	Present	16	84.2	3	15.8	0.099
Congestive Heart failure	Absent	129	92.8	10	7.2	0.647
Hyperlipidaemia	Absent	140	92.7	11	7.3	0.386
Coronary arterial bypass grafting	Absent	31	88.6	4	11.4	0.223
Valvular replacement	Present	42	85.7	7	14.3	0.013
Surgery of the Aorta	Present	6	85.7	1	14.3	0.424
Rational antimicrobial treatment	No	37	90.2	4	9.8	0.218
	Yes	63	91.3	6	8.7
	Unknown	50	98.0	1	2.0
Use of antibiotic prophylaxis	Yes	148	93.1	11	6.9	0.700
The number of prophylactic regimens	Single-drug	86	92.5	7	7.5	0.683
Surgical prophylaxis with
Cefazolin	Yes	68	89.5	8	10.5	0.079
Cefuroxime	No	118	91.5	11	8.5	0.087
Cefotaxime/Ceftriaxone	No	114	91.2	11	8.8	0.065
Ciprofloxacin/Levofloxacin	No	131	92.3	11	7.7	0.209
Ampicillin-Sulbactam/Amoxicillin-Clavulanate	Yes	2	66.7	1	33.3	0.066
Piperacillin Tazobactam	No	147	93.0	11	7.0	0.636
Linezolid	No	149	93.1	11	6.9	0.783
Clindamycin	No	148	93.1	11	6.9	0.700
Vancomycin	Yes	9	81.8	2	18.2	0.122
IMP/MER	Yes	4	80.0	1	20.0	0.236
Gentamicin	No	139	92.7	11	7.3	0.352
Azithromycin	No	131	92.3	11	7.7	0.209
Postoperative MV	Yes	112	91.8	10	8.2	0.225
Re-exploration after surgery for non-infectious causes like bleeding	Yes	14	82.4	3	17.6	0.062
SSI Type
Organ space infection	Yes	15	78.4%	4	21.7%	0.016
Deep incisional	Yes	28	90.3%	3	9.7%
Superficial	Yes	107	96.4%	4	3.6%
Coexisting infections
Catheter associated urinary tract infection	No	136	92.5	11	7.5	0.289
Pneumonia	Yes	11	78.6	3	21.4	0.023
Blood stream infections	Yes	5	55.6	4	44.4	0.001
Endocarditis	No	149	93.1	11	6.9	0.786
Decubitus infection	No	149	93.1	11	6.9	0.786
Indwelling catheters
Central venous catheter	Yes	86	89.6	10	10.4	0.049
Urinary catheter	Yes	74	89.2	9	10.8	0.037
Arterial line	Yes	19	86.4	3	13.6	0.173
Postoperative re-intervention done within 30 days after SSI	Yes	52	85.2	9	14.8	0.003
Re-intervention related to sternal incision. and the need for sternal bone debridement	Yes	11	78.6	3	21.4	0.023

*: Chi-Square test

Table-2. Descriptive statistics of numerical characteristics related to the patients died of SSI and the survivors

	Survived						Died
		Mean	SD	Percentiles				Mean	SD	Percentiles
	N	Mean	SD	25th	Median	75th	N	Mean	SD	25th	Median	75th	P*
Age	150	60.58	13.60	55.00	63.00	68.25	11	66.73	8.27	64.00	66.00	74.0	0.118
Body mass index	150	29.01	5.90	24.70	27.90	32.53	11	30.74	8.03	25.80	27.50	33.0	0.743
Pre-op ejection fraction	150	51.57	10.73	45.00	55.00	60.0	11	49.27	12.41	36.00	50.0	60.0	0.480
qSOFA Score	150	0.59	0.78	0	0	1.0	11	1.55	1.21	0	2.0	3.00	0.005
Duration of surgery in minutes	148	250.1	89.9	180.0	240.0	302.0	11	254.36	98.8	180.0	240.0	300.0	0.940
Total hospital stays (duration in days)	150	22.6	17.85	11.0	15.0	28.0	11	13.64	10.67	4.0	10.0	20.0	0.025
Preoperative stay in days	150	5.55	6.29	2.0	3.0	7.00	11	2.09	2.02	1.0	2.0	3.0	0.013
Duration of prophylaxis after surgery (days)	150	6.03	8.91	2.0	3.5	7.00	11	4.55	4.89	2.0	3.0	6.0	0.688

*: Mann-Whitney U test

Table-3. Final predictive model for mortality in cardiac surgery patients with surgical site infections

	OR	90% C.I. for OR
	OR	Lower	Upper	P
Surgery classification *(Emergency vs Elective)*	8.470	2.028	35.379	0.014
qSOFA Score	3.147	1.450	6.827	0.015
Valvular replacement (Present vs Absent)	4.487	1.001	20.627	0.090
Urinary catheter *(Yes vs No)*	14.197	2.198	91.721	0.019
Was postop re-intervention done within 30 days after SSI *(Yes vs No)* ?	14.832	2.684	81.972	0.009
Age	1.075	1.020	1.132	0.022
Constant	0.000001			<0.001

*: Multiple binary logistic regression model

Table-4. Classification results and metrics

FINAL MODEL		Predicted from the model
Actual		Survived	Died	Total
	*Survived*	135	15	150
	*Dead*	1	10	11
	Total	136	25	161
		Classification metrics
Cut-off		0.10
AUC±SE		0.957±0.017
Classification Accuracy		90.1%
Precision (PPV)		40.0%
Recall (sensitivity)		90.9%
Specifity		90.0%
False Positive		10.0%
False Negative		9.1%
FINAL MODEL				Predicted from the model
Actual				Survived	Died	Total
	*Survived*			135	15	150
	*Dead*			1	10	11
	Total			136	25	161
				Classification metrics
Cut-off				0.10
AUC±SE				0.957±0.017
Classification Accuracy				90.1%
Precision (PPV)				40.0%
Recall (sensitivity)				90.9%
Specificity				90.0%
False Positive				10.0%
False Negative				9.1%

*: FN: False negative; FP: False positive; PPV: Positive predictive value; Positive group is Death, Negative group is the Survivors

No competing interests reported.

Mortality in Surgical Site Infections Post-cardiac Surgery - a Prospective, International Id-iri Study

Status:

Version 1

Abstract

OBJECTIVES

METHODS

RESULTS

CONCLUSION

Figures

INTRODUCTION

METHODS

RESULTS

DISCUSSION

Declarations

References

Tables

Additional Declarations

Status:

Version 1