Abstract
Background
Health-care associated infections (HAI) represent serious complications for patients within pediatric cardiac intensive care units (CICU). HAI are associated with increased morbidity, mortality, and resource utilization. There are few studies describing the epidemiology of HAI across the entire spectrum of patients (surgical and non-surgical) receiving care in dedicated pediatric CICUs.
Methods
Retrospective analyses of 22,839 CICU encounters from 10/2013–9/2016 across 22 North American CICUs contributing data to the Pediatric Cardiac Critical Care Consortium clinical registry.
Results
HAI occurred in 2.4% of CICU encounters at a rate of 3.3 HAI/1000 CICU days, with 73% of HAI occurring in children <1 year. Eighty encounters (14%) had ≥ 2 HAI. Aggregate rates for the four primary HAI: CLABSI 1.1/1000 line days; CAUTI 1.5/1000 catheter days; VAP 1.9/1000 ventilator days; SSI 0.81/100 operations. Surgical and non-surgical patients had similar HAI rates/1000 CICU days. Incidence was twice as high in surgical encounters, and increased with surgical complexity; postoperative infection occurred in 2.8% of encounters. Prematurity, younger age, presence of congenital anomaly, STAT 4–5 surgery, admission with an active medical condition, open sternum, and extracorporeal membrane oxygenation were independently associated with HAI. In univariable analysis, HAI was associated with longer hospital length of stay and durations of urinary catheter, central venous catheter, and ventilation. Mortality was 24.4% in patients with HAI vs. 3.4% in those without, p<0.0001.
Conclusions
We provide comprehensive multicenter benchmark data regarding rates of HAI within dedicated pediatric CICUs. We confirm that while rare, HAIs of all types are associated with significant resource utilization and mortality.
Keywords: infection, cardiac intensive care unit, healthcare-associated, HAC, pediatric surgery
Introduction
Health-care associated infections (HAI) are a well described burden in pediatric and neonatal intensive care units (1), even more so in developing countries where individual HAI rates are over eight times higher than United States ICUs (2). Quality improvement initiatives and other infection control measures have decreased the rates of individual infections, but HAI remain an important source of morbidity (3). The epidemiology of HAI is less well studied in critically ill children with cardiac disease; HAI are associated with increased morbidity and mortality, cost, and resource utilization in this population (4–11). Patients within the pediatric cardiac intensive care unit (CICU) may experience a prolonged critical illness period, which contributes to increased risk for HAI. Postoperative cardiac surgical patients incur significant HAI risk as result of surgical wounds, compromised immune function after cardiopulmonary bypass (CPB), and multiple invasive medical devices that bypass normal host defense mechanisms. The growing non-surgical patient population in CICUs (chronic heart failure, ventricular assist device patients, etc.) may have additional risks of acquiring HAI during critical illness, but far less is known about this unique subgroup.
The Centers for Disease Control and Prevention (CDC) defines four primary HAI applicable to pediatric CICU patients: central line associated bloodstream infections (CLABSI), ventilator associated pneumonia (VAP), catheter associated urinary tract infections (CAUTI), and surgical site infections (SSI) (12). In addition to the CDC guidelines for prevention of HAI, multiple single center studies have highlighted quality initiatives aimed at reducing HAI in the CICU, typically focusing on cardiac surgical patients. There are few studies describing the epidemiology of HAI across the entire spectrum of patients (surgical and non-surgical) receiving care in dedicated CICUs.
In this context, we aimed to describe the epidemiology of HAI across 22 North American CICUs contributing data to the Pediatric Cardiac Critical Care Consortium (PC4) clinical registry. We aimed to provide HAI epidemiologic data across multiple patient subgroups, such that individual CICUs can use these data as a quality benchmark. We secondarily sought to describe patient factors and outcomes associated with HAI. We view this study as a crucial initial step to inform initiatives aimed at reduction of HAI and improving overall quality of care and outcomes for children managed in contemporary CICUs.
Material and Methods
Data Source
PC4 is a quality improvement collaborative that collects data on all patients admitted to the CICU service of participating hospitals (13). PC4 maintains a clinical registry to support research and quality improvement initiatives. At time of analysis, 22 hospitals were submitting cases.
Each participating center has a trained data manager who collects and enters data in accordance with standardized PC4 data definitions. PC4 shares common terminology and definitions with the International Pediatric and Congenital Cardiac Code, Society of Thoracic Surgeons (STS) Congenital Heart Surgery Database, and American College of Cardiology Improving Pediatric and Adult Congenital Treatment Registry (13). Participating centers are audited on a regular schedule, with the most recent published results demonstrating 0.6% major discrepancy rate across 29,476 fields (14). The University of Michigan Institutional Review Board provides oversight for the PC4 Data Coordinating Center; this study was reviewed and approved with waiver of informed consent.
Inclusion and exclusion criteria
In this observational analytical study, all CICU encounters at PC4 hospitals from October 15, 2013 to September 23, 2016 were considered; excluded were no cardiac disease (n=138) and admission for hospice (n=9).
Definitions
“Surgical encounter” was defined as any encounter in which the patient underwent an index surgery with or without CPB. “Medical encounter” was defined as any encounter not meeting above criteria. We categorized medical encounters into two cohorts based on their primary reason for CICU admission: 1. “Medical condition” patients were those with underlying cardiac disease admitted with active medical diagnosis (cardiac, gastrointestinal, respiratory, infectious, neurologic, other) and 2. “Miscellaneous” medical encounter patients were those presenting for routine post-procedure (catheterization or non-cardiac surgery) intensive monitoring, or patients evaluated for structural heart disease and possible intervention.
The four primary HAI (CLABSI, CAUTI, SSI, VAP) were defined as per CDC guidelines (12); and pooled mean incidence density rates were calculated as detailed by the CDC’s National Healthcare Safety Network (NHSN) HAI data collection module (1). Rates were calculated as: CLABSI/1000 line days; CAUTI/1000 catheter days; VAP/1000 vent days; and SSI/100 index operations. One line day was defined as any calendar day with ≥1 central venous catheter or intracardiac line. No individual center rates or incidences were calculated. The four primary HAI must be adjudicated per CDC criteria by the local infection control personnel before data collectors could record the infection in the registry. Non-device associated (DA) UTI and non-DA pneumonia were defined/diagnosed by the clinical team and did not meet criteria for CAUTI or VAP. Pooled device utilization ratios were calculated as total device days/total CICU patient days.
Statistical analysis
Descriptive analyses (means, standard deviations (SD), medians, interquartile ranges (IQR), frequency distributions (%), and rates) described patient’s demographics and characteristics as appropriate. To assess univariable association between primary/secondary outcomes and potential risk factors we conducted Chi-square, Fisher exact, Mann-Whitney U, Student’s-t tests as appropriate. Multivariable analyses characterized per-admission risk factors associated with HAI, as the primary outcome variable. Variables with significant (p < 0.1) univariate association served as the predictor variables. Though there are several other clinical predictor variables that could be analyzed, (e.g. central venous line days, steroid exposure, etc.) we chose to focus on peri-admission patient variables as they are mostly independent of CICU practice and quality. We used generalized linear models with logit-link to assess the independent risk factors associated with the main outcome measure (HAI). We employed the generalized estimating equation method to account the correlations of observations within patient who had several admissions, and for clustering of patients within hospitals. To quantify effects of risk factors, we estimated odds ratios and 95% confidence intervals. All hypothesis tests were two-tailed with p-value <0.05 to indicate statistical significance. All analysis used SAS version 9.4 (Cary, NC).
Results
Patient characteristics and HAI rates
There were 20,732 hospitalizations and 22,839 CICU encounters (9,355 medical, 13,484 surgical) during the study dates. Patient and encounter characteristics are in Table 1, Supplemental Digital Content 1. HAI occurred in 2.4% of CICU encounters at a rate of 3.3/1000 CICU days. Of 554 encounters with HAI, 474 (86%) had one infection; while 80 (14%) had ≥2 infections.
Stratified HAI incidence and rates are presented in Table 1. Surgical encounters had almost twice the incidence of HAI compared to medical encounters, but similar HAI rate/1000 CICU days. Postoperative infection occurred in 2.8% of encounters. Incidence of HAI increased with decreasing age; children <1 year incurred 73% of HAI. Neonates had the highest incidence of HAI; infants had highest HAI rate/1000 CICU days. HAI incidence increases with surgical complexity; STAT 4-5 patients incur 54% of surgical encounter HAI, despite representing only 25% of the surgical population.
Table 1.
Incidence and Rates of HAI in Medical and Surgical CICU Encounters
| Encounters with HAI (%) | Rate per 1000 CICU days | |
|---|---|---|
| All Encounters (n=22841) | 554 (2.4) | 3.29 |
| Age groups | ||
| Neonate, 0–30 days (n=4070) | 191 (4.7) | 3.12 |
| Infant, 31–365 days (n=7241) | 211 (2.9) | 3.81 |
| Child, 1–18 years (n=9865) | 132 (1.3) | 2.85 |
| Adult, >18 years (n=1665) | 20 (1.2) | 3.35 |
| All Medical Encounters (n=9356) | 149 (1.6) | 2.93 |
| All Surgical Encounters (n=13485) | 405 (3.0) | 3.44 |
| STAT 1 (n=3846) | 32 (0.8) | 2.35 |
| STAT 2 (n=4291) | 81 (1.9) | 2.75 |
| STAT 3 (n=1689) | 56 (3.3) | 3.67 |
| STAT 4 (n=2828) | 167 (5.9) | 3.93 |
| STAT 5 (n=542) | 53 (9.8) | 3.99 |
| STAT not assigned (n=289) | 16 (5.5) | 4.17 |
HAI, hospital acquired infection; CICU, cardiac intensive care unit; STAT, Society of Thoracic Surgeons - European Association for Cardio-Thoracic Surgery Congenital Heart Surgery Mortality Categories
HAI types
Aggregate rates for the four primary HAI were: CLABSI 1.1/1000 line days; CAUTI 1.5/1000 catheter days; VAP 1.9/1000 ventilator days; SSI 0.81/100 index operations (Table 2, Supplemental Digital Content 2). Stratified rates by HAI types are presented in Table 2. Epidemiologic trends seen among the individual types of HAI are similar to that for all HAI in aggregate. Surgical encounters have higher incidence of HAI for every infection type; however, medical encounters have higher incidence density rates for all DA HAI. CLABSI represents the most frequent HAI across all strata. Neonatal encounters had twice the CLABSI incidence of infants, but rates/1000 line days were similar. STAT 4, 5 encounters account for 64% of surgical encounter CLABSI.
Table 2.
Distribution of Individual HAI types in Medical and Surgical CICU Encounters
| CLABSI | CAUTI | VAP | Deep SSI | Superficial SSI | Non-DA Pneumonia | Non-DA UTI | |
|---|---|---|---|---|---|---|---|
| All encounters, (n=22841) | 159 (0.70) | 70 (0.31) | 116 (0.51) | 38 (0.17) | 78 (0.34) | 65 (0.26) | 104 (0.46) |
| Age group | |||||||
| Neonate, 0–30d (n=4070) | 61 (1.50) | 15 (0.37) | 27 (0.66) | 13 (0.32) | 51 (1.25) | 7 (0.17) | 35 (0.86) |
| Infant, 31–365d (n=7241) | 62 (0.86) | 27 (0.37) | 54 (0.75) | 14 (0.19) | 16 (0.22) | 26 (0.36) | 50 (0.69) |
| Child, 1–18yr (n=9865) | 32 (0.32) | 24 (0.24) | 32 (0.32) | 8 (0.08) | 7 (0.07) | 31 (0.31) | 15 (0.15) |
| Adult, >18 yrs (n=1665) | 4 (0.24) | 4 (0.24) | 3 (0.18) | 3 (0.18) | 4 (0.24) | 1 (0.06) | 4 (0.24) |
| All medical encounters, (n=9355) | 53 (0.57) | 20 (0.21) | 35 (0.37) | 5 (0.05) | 5 (0.05) | 19 (0.20) | 25 (0.27) |
| All surgical encounters, (n=13484) | 106 (0.79) | 50 (0.37) | 81 (0.60) | 33 (0.24) | 73 (0.54) | 46 (0.34) | 79 (0.59) |
| STAT 1 (n=3846) | 8 (0.21) | 5 (0.13) | 7 (0.18) | 0 (0.00) | 3 (0.08) | 7 (0.18) | 10 (0.26) |
| STAT 2 (n=4291) | 15 (0.35) | 14 (0.33) | 17 (0.40) | 7 (0.16) | 10 (0.23) | 13 (0.30) | 14 (0.33) |
| STAT 3 (n=1689) | 11 (0.65) | 5 (0.30) | 11 (0.65) | 6 (0.36) | 8 (0.47) | 7 (0.41) | 16 (0.95) |
| STAT 4 (n=2827) | 48 (1.70) | 23 (0.81) | 32 (1.13) | 13 (0.46) | 35 (1.24) | 14 (0.50) | 30 (1.06) |
| STAT 5 (n=542) | 20 (3.69) | 1 (0.18) | 11 (2.03) | 5 (0.92) | 15 (2.77) | 3 (0.55) | 6 (1.11) |
| STAT not assigned (n=289) | 4 (1.38) | 2 (0.69) | 3 (1.04) | 2 (0.69) | 2 (0.69) | 2 (0.69) | 3 (1.04) |
Data presented as number (%)
HAI, Hospital associated infection; CICU, cardiac intensive care unit; CLABSI, central line-associated blood stream infection; CAUTI, catheter-associated urinary tract infection; VAP, ventilator-associated pneumonia; SSI, surgical site infection; Non-DA, non-device associated; UTI, urinary tract infection; STAT, Society of Thoracic Surgeons - European Association for Cardio-Thoracic Surgery Congenital Heart Surgery Mortality Categories
Multiple infections
63/80 encounters with multiple infections were surgical. Thirteen patients had ≥2 infections simultaneously (diagnosed ≤24 hours of each other); all were surgical patients. CLABSI and UTI combined in 7/13 patients; UTI and pneumonia combined in four patients; CLABSI and SSI in two patients. Of encounters diagnosed with HAI, 67/554 (12.1%) developed subsequent infection later in same encounter; 15% developed subsequent infection in same hospitalization.
Timing of Infection
For surgical encounters, 8% of HAI occurred in the preoperative period. For postoperative HAI, median time to diagnosis was 8 days (IQR 4, 20). Minority of infections (10%) were diagnosed within the first two postoperative days. When considering all encounters, CLABSI was diagnosed median 13 days (IQR 5, 29) after admission and CAUTI 6 days (IQR 3, 11). All other infection types occurred median eight to nine days after admission.
Risk factors for HAI
Table 3, Supplemental Digital Content 3 shows the univariate analysis of patient characteristics and early admission/postoperative factors associated with HAI development. In multivariable analysis prematurity, STAT 4-5 surgery, admission with a medical condition, open sternum, and extracorporeal membrane oxygenation were independently associated with HAI, Table 3.
TABLE 3.
Patient Characteristics with Independent HAI Association
| Outcomes | Odds Ratio | 95% Confidence Interval | P value |
|---|---|---|---|
| Congenital anomaly | 2.00 | 1.66–2.38 | <0.0001 |
| ECMO | 3.93 | 2.83–5.45 | <0.0001 |
| Open Sternum | 2.44 | 1.77–3.37 | <0.0001 |
| Age Group | |||
| Infant vs child | 1.91 | 1.52–2.41 | <0.0001 |
| Preterm neonate vs child | 2.62 | 1.72–4.00 | <0.0001 |
| Term neonate vs child | 1.70 | 1.25–2.32 | 0.0008 |
| Preterm vs term neonate | 1.54 | 1.04–2.28 | 0.0305 |
| Reason for Encounter | |||
| Medical condition+ vs Misc. Medical* | 3.15 | 2.08–4.79 | <0.0001 |
| STAT 1-3 vs Misc. Medical* | 2.31 | 1.53–3.50 | <0.0001 |
| STAT 4-5 vs Misc. Medical* | 4.86 | 3.14–7.53 | <0.0001 |
| STAT 4-5 vs STAT 1-3 | 2.10 | 1.61–2.74 | <0.0001 |
| Medical condition+ vs STAT 1-3 | 1.36 | 1.06–1.74 | 0.0134 |
| STAT 4-5 vs medical condition+ | 1.54 | 1.16–2.05 | 0.0028 |
Misc., miscellaneous;
Medical condition- medical encounter admitted with a medical condition; see methods section.
Neonate, <30 days; Infant, 30–365 days; Child, 1–18 years; HAI, hospital acquired infection; ECMO, extracorporeal membrane oxygenation; STAT, Society of Thoracic Surgeons - European Association for Cardio-Thoracic Surgery Congenital Heart Surgery Mortality Categories
Resource utilization and HAI outcomes
Pooled device utilization ratios were 0.78 for central venous lines, 0.25 for urinary catheters, and 0.32 for ventilator. In univariable analysis, HAI was associated with longer hospital length of stay (HLOS) [median 45 days (IQR 26, 99) vs. 7 (IQR 4, 14)], urinary catheter duration [6 days (IQR 3, 12) vs. 2 (IQR 0, 2)], central venous catheter line duration [26 days (IQR 14, 59) vs. 2 (IQR 0, 6)], and ventilation hours [319 (IQR 124, 754) vs. 1 (IQR 0, 26.5)]. Mortality for the entire cohort was 24.4% in patients with HAI vs. 3.4% in those without, p<0.0001. Table 4 demonstrates unadjusted mortality rates. Mortality dramatically increased with diagnosis of HAI within all strata evaluated, except adult age. Encounters with CLABSI (36.7%) and CAUTI (30%) had the highest mortality rates, Table 5.
Table 4.
Hospital acquired infection and mortality
| Cohort | Mortality, No HAI | Mortality, Any HAI | P value |
|---|---|---|---|
| All medical encounters (n=7450) | 394 (5.4) | 39 (32.8) | <0.0001 |
| All surgical encounters (n=13282) | 298 (2.3) | 94 (22.0) | <0.0001 |
| STAT 1 (n=3826) | 9 (0.2) | 3 (8.6) | 0.0001 |
| STAT 2 (n=4234) | 43 (1.0) | 15 (17.9) | <0.0001 |
| STAT 3 (n=1667) | 29 (1.8) | 11 (19.6) | <0.0001 |
| STAT 4 (n=2764) | 135 (5.2) | 41 (23.2) | <0.0001 |
| STAT 5 (n=539) | 70 (14.6) | 21 (36.2) | <0.0001 |
| STAT not assigned (n=252) | 12 (5.1) | 3 (17.7) | 0.0700 |
| Age | |||
| Neonates (n=3820) | 302 (8.4) | 66 (31.9) | <0.0001 |
| Infants (n=6173) | 164 (2.7) | 34 (18.0) | <0.0001 |
| Child (n=9177) | 177 (2.0) | 30 (23.8) | <0.0001 |
| Adult (n=1562) | 49 (3.2) | 3 (15.0) | 0.0266 |
Data presented as number (%)
Neonate, <30 days; Infant, 30–365 days; Child, 1–18 years; HAI, hospital acquired infection; STAT, Society of Thoracic Surgeons - European Association for Cardio-Thoracic Surgery Congenital Heart Surgery Mortality Categories
Table 5.
Type of Infection and mortality
| Infection type | Mortality: Yes n (%) |
|---|---|
| Central line associated blood stream infection (n=158) | 58 (36.7) |
| Catheter associated urinary tract infection (n=70) | 21 (30.0) |
| Ventilator associated pneumonia (n=115) | 28 (24.3) |
| Deep surgical site infection (n=38) | 8 (21.1) |
| Superficial surgical site infection (n=78) | 12 (15.4) |
| Non-ventilator associated pneumonia (n=65) | 9 (13.8) |
| Non-catheter associated urinary tract infection (n=104) | 21 (20.2) |
| No infection (n=20186) | 692 (3.4) |
Discussion
This analysis represents the first multicenter description of HAI across all patient encounters in contemporary pediatric CICUs. HAI occurred in 2.4% of CICU encounters at a rate of 3.3 HAI/1000 CICU days, with 73% of HAI occurring in children <1 year. Incidence was twice as high in surgical encounters, and increased with surgical complexity. Patients admitted with medical conditions were also at high risk for HAI. Our study confirms that HAI is associated with significantly increased mortality and increased resource utilization.
Previous studies of HAI in pediatric cardiac patients primarily include surgical patients, with incidence rates ranging from 3–24%, depending on the type(s) of infections evaluated (5,6,11,15,16). Postoperative HAI occurred in 2.8% of surgical encounters in our study. Recent studies of cardiac surgical patients found higher surgical complexity, longer CPB time, younger age, longer LOS, delayed sternal closure, cyanotic heart disease, postoperative steroids and red blood cell transfusion were associated with increased postoperative HAI risk (4–6,10,11,17). Our study confirms many of these findings. Novel findings of our analysis include: increased incidence of more than one concurrent infections in surgical patients compared to medical cardiac patients, and increased risk for developing subsequent HAI(s) after diagnosis of a first.
The CDC’s NHSN 2013 summary data of DA HAI for pediatric CICU demonstrated a CLABSI rate of 1.3 (43 centers), CAUTI rate of 1.2 (36 centers), and VAP rate of 0.4 (14 centers) (1). In this cohort, we saw similar CLABSI (1.1) and CAUTI (1.5) rates, but significantly higher VAP rate (1.9/1000 vent days). The explanation for the higher VAP rate in this cohort is not clear. In a report from the STS (5) database, the multicenter postoperative VAP rate was less than half of what we describe (0.4% vs. 0.94%). Ascertainment bias is a consideration; it is possible that combined identification and adjudication by the clinical team, PC4 clinical champion, and hospital safety officer may have increased VAP identification. In support of this supposition, single center studies focused on CICU VAP epidemiology reveal much higher VAP rates (4,10,18). HAI diagnosis rate may increase with the rigor of surveillance (19), and it is paramount that clinicians and infection control personnel work closely together to produce the most valid HAI data for future initiatives.
Similar to studies of post cardiac surgical patients (4–6,11,16), CLABSI was the most common HAI; however, the PC4 CLABSI incidence was much lower than previously reported. Analyses from the STS database report sepsis with positive blood culture in 1.9% and 2.6%, (5,6) whereas in our postoperative population, 0.8% had CLABSI, (this does not include secondary bloodstream infections). Perhaps the lower rate in the more contemporary PC4 data set reflects, in part, successes of quality initiatives aimed at decreasing CLABSI that have been commonplace in CICUs over the last several years. However, the PC4 central line utilization rate (0.78) is similar to that of CICUs in 2013 (0.72), (1) suggesting earlier removal of central lines may not be the key driver to the lower CLABSI rate. Importantly, over ⅓ of patients with CLABSI died. Although we cannot conclude causality, others have suggested blood stream infections to be risk factors for mortality (17). Quality initiatives aimed at decreasing CLABSI have been successful in the pediatric CICU (20,21), increasing the impetus for aggressive efforts to identify modifiable risk factors given the high rate of CLABSI associated morbidity and mortality. Multicenter data on CLABSI risk factors and outcomes from the PC4 database is forthcoming.
To our knowledge, we provide the first multicenter epidemiologic data regarding UTI in the pediatric CICU. Perhaps marginalized as a minor HAI in this population, UTI represents the most frequent HAI in our cohort (0.8% of all encounters and 1% of surgical encounters). Furthermore, patients with UTI were most likely to be diagnosed with a concomitant infection (CLABSI, seven times). Presence of UTI had univariable association with longer duration of catheter use, HLOS, and mortality (24%). In a single-center study, longer duration of catheter use is an independent risk factor for UTI after pediatric cardiac surgery (22). Further investigation into the risk factors and impact of this important HAI on outcomes is warranted.
An interesting novel finding is that admission to the CICU with a medical condition incurs a 36% higher risk of HAI when compared to lower risk cardiac surgery (STAT category 1–3), while STAT 4-5 surgical encounters have a 54% increased risk of HAI vs encounters admitted with a medical condition. Medical condition patients contain a high proportion of children with acute and/or chronic heart failure which are increasingly associated with mortality, morbidity and resource utilization (23). However, the incidence and rates of HAI for this patient population have not been specifically studied. Our data suggests the risk of HAI in this medical population is higher than most of the surgical population, and warrants further detailed study. STAT 4-5 likely have highest HAI rates as they consistently combine many of the innate and treatment factors identified as high risk for HAI, including prolonged exposure to invasive devices.
Limitations
The limitations of our study are inherent of any observational analysis using clinical registry data. Although the data integrity of the PC4 database has previously been demonstrated as excellent (14), adjudicating HAI is by nature a subjective process even for infection control teams and likely differs across hospitals. This study was not comprehensive of all HAI: we did not include meningitis, infective endocarditis, viral respiratory diseases, or infective gastroenteritis, but review of the existing PC4 data suggest these are rare events (24). HAI were only counted if diagnosed during the CICU encounter, and the database does not include infections diagnosed at non-PC4 hospitals. These limitations may be of particular importance in contextualizing the reported SSI rate, which are often diagnosed after CICU discharge. As such, our SSI rate was significantly lower (0.78%) than most other studies, including a recent multicenter study focused on SSI prevention (1.9%), which captured post-discharge SSI (25).
It was beyond the scope of our study to analyze all variables that may increase the risk of HAI, including center specific systems based variables -such as antibiotic prophylaxis, nurse staffing models, and specific quality improvement initiatives aimed at HAI reduction as well as resource utilization metrics (duration of medical device exposure and CICU LOS, etc.) and their dual role as risk factors and outcome for HAI. These analyses are best undertaken when focused on an individual infection type. Given the fact infection rates vary tremendously among centers (5), the impact of these modifiable management details on center risk-adjusted HAI rate are an important target for future study.
In summary, we provide comprehensive multicenter benchmark data regarding rates of HAI within dedicated pediatric CICUs. Additionally, we describe high risk subpopulations and time periods for HAI. This data can be used to guide local prevention strategies and plan quality improvement efforts to reduce the occurrence of HAI. We confirm that while rare, HAIs of all types are associated with significant resource utilization, morbidity and mortality. HAI may represent a modifiable target to improve overall outcomes in critically ill patients with cardiac disease.
Supplementary Material
Acknowledgments
We acknowledge the data collection teams at all of the participating centers.
This study was supported in part by funding from the University of Michigan Congenital Heart Center, CHAMPS for Mott, and the Michigan Institute for Clinical & Health Research (NIH/NCATS UL1TR002240).
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