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Malagù, M.;  Donazzan, L.;  Capanni, A.;  Sirugo, P.;  Rapezzi, C.;  Bertini, M. Cardiac Implantable Electronic Device Infection. Encyclopedia. Available online: https://encyclopedia.pub/entry/36118 (accessed on 15 April 2024).
Malagù M,  Donazzan L,  Capanni A,  Sirugo P,  Rapezzi C,  Bertini M. Cardiac Implantable Electronic Device Infection. Encyclopedia. Available at: https://encyclopedia.pub/entry/36118. Accessed April 15, 2024.
Malagù, Michele, Luca Donazzan, Andrea Capanni, Paolo Sirugo, Claudio Rapezzi, Matteo Bertini. "Cardiac Implantable Electronic Device Infection" Encyclopedia, https://encyclopedia.pub/entry/36118 (accessed April 15, 2024).
Malagù, M.,  Donazzan, L.,  Capanni, A.,  Sirugo, P.,  Rapezzi, C., & Bertini, M. (2022, November 23). Cardiac Implantable Electronic Device Infection. In Encyclopedia. https://encyclopedia.pub/entry/36118
Malagù, Michele, et al. "Cardiac Implantable Electronic Device Infection." Encyclopedia. Web. 23 November, 2022.
Cardiac Implantable Electronic Device Infection
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Infection is the most feared complication in patients with cardiac implantable electronic devices (CIED), with an incidence of 1–3% during the lifetime and a mortality rate of up to 27.5% at three years. Different strategies have been proposed to prevent infections. Strategies of proven efficacy include appropriate procedure timing, management of antithrombotic therapy, patient preparation, surgical technique, and adequate wound care. However, the most important defense against CIED infection (and the most studied in more than 40 years of clinical trials) is systemic antibiotic prophylaxis. In short, preoperative administration of antibiotics is clearly beneficial and represents the standard of care for all patients, recommended by international consensus, mostly with drugs covering Staphylococcus aureus species, such as beta-lactams or glycopeptides.
cardiac device CIED infection endocarditis pacemaker ICD CRT risk

1. Risk Factors for Cardiac Implantable Electronic Devices (CIED) Infections

Many risk factors for CIED infection have been identified in a multitude of studies during the last 50 years [1]. These factors may be classified according to patient, procedure, and device characteristics. Factors related to the patient include age, male sex, diabetes mellitus, heart failure, renal insufficiency, chronic obstructive pulmonary disease, active neoplasia, fever within 24 h, anticoagulation, corticosteroids, central venous catheter, previous device infection, and trauma at the site of implant [1][2][3][4][5][6][7][8][9][10]. Factors related to the procedure are a lack of antibiotic prophylaxis, replacement, revision, upgrade, early reintervention, temporary pacing, procedure duration, operator experience, lead dislodgement, and hematoma [1][3][10][11][12][13][14][15]. Factors related to the device include implantable cardioverter–defibrillator (ICD) or cardiac resynchronization therapy (CRT), more than two leads, epicardial leads, and abdominal pockets [1][10][16]. These factors have been considered differently in the different scores that have been proposed.

2. Risk Scores

2.1. PADIT

The PADIT risk score was developed by Birnie et al. using the population of the PADIT trial and is currently the only risk score not derived from retrospective analysis [17][18]. For the score’s development, 200 samples were initially bootstrapped for internal validation. Independent predictors were identified using multivariable logistic prediction modeling. The performance of the full prediction model and risk score model was assessed in terms of calibration-in-the-large, calibration slope, and the C-statistic.
Five easy-to-access, independent predictors were recognized, namely prior procedures (P), age (A), depressed renal function (D), immunocompromised (I), and procedure type (T), giving a score ranging from 0 to 15 points. This classified patients into low (0 to 4), intermediate (5 to 6), and high (≥7) risk, with rates of hospitalization for infection of 0.51%, 1.42%, and 3.41%, respectively.
It should be remarked that the subgroup analysis by PADIT infection risk score of the two antibiotic regimes (single dose or incremental) used in the PADIT trial showed no treatment effect (p for interaction = 0.37).
The risk score revealed high predictive power for reinfection, all-cause mortality, and hospitalization during the first year of follow-up, as well as cardiovascular mortality in patients submitted to lead extraction for CIED infection [19].
Moreover, the PADIT risk score showed a significant association with CIED infections, with overall modest prediction performance when tested in the RI-AIAC registry population [20]. There was no association with the occurrence of the composite clinical event of infection or all-cause death.
An independent validation of the score was performed in a data set extracted from U.S. healthcare claims by Ahmed et al [21]. In this population, the PADIT risk score served as a predictor of higher CIED infection risk. The risk of a major CIED infection increased by 28% for each one unit increase in PADIT risk score in a linear fashion. Furthermore, it was suggested that the use of prior CIED infection history to confer additional predictive value to the risk score.

2.2. SHARIFF

“SHARIFF” is a preoperative risk score developed to identify patients at high risk of CIED infection. It is calculated considering each of the following: diabetes mellitus, heart failure, oral anticoagulation, chronic corticosteroid use, renal insufficiency (serum creatinine >1.5 mg/dL), prior CIED infection, presence of more than two leads, presence of epicardial lead(s), temporary pacemaker at implantation, and replacement/upgrade procedure. Each factor counts for one point; therefore, the score ranges from 0 to 10. In the original study, a cohort of 1467 patients was retrospectively analyzed [10]. Occurrence of infection was compared between patients receiving an antibacterial envelope and a control group. At 6-month follow-up, a lower rate of infection was found in patients with SHARIFF score <3 (infection rate 1.0%) compared to those with SHARIFF score ≥3 (2.4%). A modified version of this score for first CIED implantation, evidently not considering prior CIED infection and replacement/upgrade, has been validated in a retrospective analysis of 1391 patients, in which a score ≥4 was an independent predictor of infection (relative risk 3.20, p = 0.029) [22]. The SHARIFF score was also used to stratify patient risk in the PRACTICE study, in which prolonged antibiotic prophylaxis was proposed for high-risk patients [3].

2.3. KOLEK

In 2013, Kolek et al. published a retrospective cohort study analyzing the outcomes of patients receiving an antibacterial envelope.The antibacterial envelope in patients considered at high risk for CIED infections were implanted, arbitrarily chosen as presenting at least two of the following: diabetes, renal insufficiency, anticoagulation, chronic corticosteroid use, fever or leukocytosis at the time of implantation, prior CIED infection, ≥3 leads, pacemaker dependency, or early pocket reentry. Patients with an antibacterial envelope were compared to a control group of patients, matched for the number of risk factors, with a CIED implanted before an antibacterial envelope became available. At a median follow-up of 18.7 ± 7.7 months, CIED infections were 20/899, 2.22%, significantly lower among patients receiving the antibacterial envelope compared to the control group (0.4% vs. 3%) [23].
In a subsequent study published by the same group, patients satisfying the presence of at least two of the same risk factors for CIED infections were divided into those receiving an absorbable antibacterial envelope (n = 135), those receiving a non-absorbable antibacterial envelope (n = 353), and those not receiving an antibacterial envelope (n = 636). The mean number of risk factors was 3.08 for the absorbable antibacterial envelope group, 3.20 for the non-absorbable antibacterial envelope group, and 3.09 for controls. The overall rate of CIED infection was 21/1124 (1.87%). Again, herein, it was showed a lower rate of infection in patients treated with antibacterial envelopes also after a propensity score-matched cohort of either envelope or controls (0% vs. 2.8%) [24].
In both of these studies, patients were considered at high risk of infection if presenting at least two factors from the prespecified list. According to the study design, patients considered at low infective risk were not included.

2.4. MITTAL

In 2014, a study was published retrospectively evaluating 2880 consecutive patients undergoing a CIED procedure, divided into the pre-antibacterial envelope era and envelope era [25]. Infections necessitating the removal of the device were considered at a follow-up of 6 months. The “MITTAL” score was developed in order to stratify the risk of CIED infection: the investigators created a model of seven independent risk factors, with a point score assigned based on their weighting in the logistic regression model. The seven risk factors were the need for early pocket re-exploration, male sex, diabetes, the need for an upgrade procedure, congestive heart failure, arterial hypertension, and glomerular filtration rate <60 mL/min. In the “pre-envelope era”, the infection rate was 1.0% in patients with a score of 0–7, 3.4% in patients with a score of 8–14, 11.1% in patients with scores >15. In the “envelope era”, 22% of patients (deemed at high risk) received the antibacterial envelope and the rate of infection was reduced to 0.7% and 0.0%, respectively, in patients with scores of 8–14 and 15–25.
Interestingly, the stratification of individual infective risk was used to determine which patients to treat with the antibacterial envelope, and this approach resulted in a significantly reduced rate of infection.

2.5. PACE DRAP

The PACE DRAP score was originally developed to estimate the risk of bleeding complications of CIED surgery among a cohort of 1100 consecutive patients [26]. Eight risk factors were identified at the multivariable analysis, corresponding to the acronym “PACE DRAP”: (P) presence of valvular prosthesis, (A) uncontrolled arterial hypertension (≥160/100 mmHg); (C) cancer (any malignancy diagnosed within the last 5 years); (E) elderly (≥75 years); (D) device type (CRT/ICD); (R) renal failure (glomerular filtration rate <60 mL/min/m2); (A) antiplatelets (clopidogrel, ticagrelor); and (P) procedure type (system upgrade). In a subsequent analysis, a PACE DRAP score ≥6 was able to identify patients at high risk of CIED infection (sensitivity 72%, specificity 71%, positive predictive value 4.4%, negative predictive value 99.3%, area under curve 0.72) [27]. In the multivariable regression model, age >75 years, system upgrade procedure, duration of surgery >1 h, the presence of significant pocket hematoma, and early reintervention within 1 month of the primary procedure were identified as independent predictors of CIED infection (final model area under curve 0.95).

2.6. RI-AIAC

In 2022, two different scores were developed with the purpose of providing an assessment of both the risk of CIED infection and risk of CIED infection + all-cause mortality [20]. Eighteen Italian centers enrolled a total of 2675 patients, which were followed up for 12 months. The following risk factors were associated with the occurrence of CIED infection and included in the “RI-AIAC Infection score”: any CIED replacement, revision/upgrade/reimplantation, diabetes mellitus, hospital-acquired infection. An RI-AIAC infection score ≥1 identified patients at higher risk of CIED infection (sensitivity 36%, specificity 90%) and was significantly associated with CIED infections (odds ratio (OR) 2.23, 95% confidence interval (CI) 1.02–4.85).
In parallel, the “RI-AIAC Event score” estimated the cumulative risk of CIED infection and all-cause death and was composed of the following: age, temporary pacing, renal failure, oral corticosteroids, hospital-acquired infection, and diabetes mellitus. An RI-AIAC event score ≥2 identified patients at higher risk of the composite clinical event (sensitivity 59%, specificity 69%).
Both scores were developed based on the multivariate logistic analysis of the study cohort and subsequently validated in an independent cohort of 1017 patients.

References

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