The Association Between Central Line-Associated Bloodstream Infection and Central Line Access* : Critical Care Medicine

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The Association Between Central Line-Associated Bloodstream Infection and Central Line Access*

Ward, Andrew PhD1; Chemparathy, Augustine MS2,3; Seneviratne, Martin MD4; Gaskari, Shabnam PharmD3; Mathew, Roshni MD3; Wood, Matthew PhD3; Donnelly, Lane F. MD3; Lee, Grace M. MD, MPH3; Scheinker, David PhD5; Shin, Andrew Y. MD3,6

Author Information
Critical Care Medicine 51(6):p 787-796, June 2023. | DOI: 10.1097/CCM.0000000000005838



Question: Is the number of central line (CL) accesses per day associated with increased risk for central line-associated bloodstream infections (CLABSIs) and can a significant fraction of CL access be substituted with peripheral routes?

Findings: In this retrospective cohort study of 138,411 eligible CL device days across 6,543 unique patients, the number of per-day CL accesses was significantly associated with increased risk of CLABSI in the next 3 days (adjusted odds ratio, 1.007 d). Of medications administered through CLs, 88% were candidates for delivery through a peripheral line.

Meaning: The number of daily CL accesses is independently associated with CLABSI, and most medications administered through CLs are safely divertible to alternate routes.

Central line-associated bloodstream infections (CLABSIs) in hospitalized patients are a significant source of preventable morbidity, mortality, and healthcare waste. The annual consequences of CLABSIs are estimated at 28,000 deaths in ICUs and up to $2.3 billion annually, and CLABSIs are the most common healthcare-associated condition in pediatric patients (1,2). National adult and pediatric rates average 0.8–1.2 and 0.3–1.3 per 1,000 central line (CL) device days, respectively (3,4).

In 2006, the Institute for Healthcare Improvement advocated “care bundles” to improve patient safety (5). The current Central Line Maintenance Bundle for reducing CLABSI rates focuses on seven practices surrounding CL insertion, removal, and maintenance (6,7). These guidelines have proven broadly effective at reducing CLABSIs among patients with CLs (8–15).

Over the past decade, CLABSI rates still remain susceptible to system-level stressors, and there remains a question of whether additional interventions beyond the bundle could further reduce the burden of CLABSIs (16). Current guidelines do not sufficiently address the potential association between CL access and the risk for CLABSI, largely due to inadequate evidence. Detailed information on the characteristics of CL accesses and a potential association with CLABSI could inform practice improvements aimed at eradicating CLABSI. We leveraged techniques in high-throughput analytics to build a uniquely large, rich dataset of CL utilization practices to study the relationship between CL access and risk for CLABSI.

We hypothesize that the number of CL accesses per day is associated with an increased risk for CLABSI. We hypothesize further that a significant fraction of CL access may be substituted with non-CL routes and are thus a potentially modifiable risk factor.


Study Population

We designed a retrospective, single-center, observational cohort study performed at Lucile Packard Children’s Hospital at Stanford University Medical Center. All patients admitted to the hospital between January 1, 2015, and December 31, 2019, were evaluated for inclusion. Patients without an instance of CL utilization during their hospitalization were excluded. Standardized needleless connecting systems are employed across the hospital. Additionally, CL tubings are systematically changed every 96 hours. A nonalcohol chlorhexidine system is employed as standard disinfecting practice prior to and after CL access. This study was approved by the Institutional Review Board at Stanford University Medical Center (protocol 25561; approved August 29, 2019; “The Use of High Throughput Analytic Programming to Predict Adverse Events”). Procedures were followed in accordance with the ethical standards of the responsible committee on human experimentation (institutional or regional) and with the Helsinki Declaration of 1975 and the requirement for written informed consent was waived.

CL Device Days

For this study, we considered each CL day for each patient as a separate observation. An eligible CL is defined as a central catheter device which has been inserted or accessed in an in-patient location (17). A CL day was any part of any calendar day on which a patient had an eligible CL, as per National Healthcare Safety Network (NHSN) criteria (4). We previously reported an electronic method for conducting automated, hospital-wide counts of CL days, which was used in this study. This automatic method was developed iteratively by pulling patient CL data, comparing to manual chart review, and validating the electronic counts (18). For patients with a CLABSI, all CL days up to but not including the CLABSI date were included. Supplementary Figure 1 ( details how patient CL days were evaluated for inclusion in the study.


The diagnosis of CLABSI was made utilizing the NHSN criteria (19) in effect during the defined study period. Mucosal barrier injury laboratory-confirmed bloodstream infections were excluded. Because the infection window period for CLABSI includes the 3 calendar days before a laboratory test confirming diagnosis (19), the 3 days before the date on which the CLABSI was identified treated as positive observations in our statistical analyses; all other CL days not within 3 days of a CLABSI were treated as negative observations in our statistical analyses.

CL Access

For each patient and each eligible CL day, we recorded all CL accesses. We defined access as any laboratory blood draw from the CL or any medication administration given through the CL. Each time a medication was administered to a patient, clinical staff documented in the electronic health record (EHR) whether a central or peripheral route was used. Laboratory draws were not linked to specific catheters within the dataset, so we considered any laboratory draw done for a patient with a CL as a CL laboratory draw.

Each type of medication was classified as a “CL-preferred medication” (“CL medication”) or as a “peripheral line (PL)-preferred medication” (“PL medication”) based on the preferred route of access as defined by our pharmacy formulary, which is consistent with the medications’ manufacturer’s directive (Supplementary Table 1, Unless a medication was recommended to be administered through a CL based on drug type and dose concentration, it was classified as a PL medication. Each administration of a medication was counted as a separate line access. For medications which included a saline flush, the saline flushes were counted as independent accesses. This methodology provides a reproducible metric for quantifying the number of daily line accesses.

To explore the possibility of utilizing noncentral routes for medication administration, we recorded the presence and medical utilization of PLs. For each patient and for each CL access for a PL medication, we determined whether a PL was present at the time the PL medication was administered through the CL.

Other Risk Factors

Demographic features (age, sex) and patient’s unit/service line were recorded. Patients’ level of care (e.g., critical care) and admission via an external care facility were recorded. Other variables with known associations with CLABSI, including the number of previously elapsed CL days and the number of CLs present on each day, were determined. For a given CL day observation, the number of elapsed CL days was defined as the total number of consecutive days for which a patient had a CL present for any part of the day, including the current CL day (19).

Statistical Analysis

Patient-level variables were aggregated at the patient-visit level and reported for each hospital unit/service line. For each patient visit, the number of average daily CLs, CL accesses, and PL medication accesses were averaged across all eligible CL days in that visit. These values and other patient characteristics were then averaged across all patients with CLs in each unit.

Bivariate analyses were conducted to describe the differences between those CL device days that were and were not within 3 days of an identified CLABSI. Unadjusted odds ratios and 95% CIs were calculated using univariate logistic regression. p values were determined using t tests or chi-square tests, as appropriate.

Using each eligible CL device day as an observation, a mixed-effects logistic regression model was used to estimate the association between CLABSI within the next 3 days and the number of daily CL accesses. Patient-level mixed effects were used to account for the dependence between observations (Supplementary Figs. 2 and 3, Patient demographic and clinical factors, including known CLABSI risk factors outlined above (age, sex, unit/service, level of care, external admission, elapsed CL days, number of CLs present), and the number of PL medication accesses, were controlled for in the regression analysis. To ensure model parsimony, only unit/service variables with a p value of less than 0.05 in the bivariate analysis were included in the multivariate analysis. To mitigate the effects of outliers, a logarithmic transformation was applied to the number of elapsed CL days for the multivariate analysis.

The average change in daily risk associated with CL accesses for PL medications for an average patient was estimated as the adjusted odds ratio (aOR) of a CL access raised to the power of the mean number of daily CL accesses for PL medications. Analysis was completed in R Version 3.5.1 (R Foundation for Statistical Computing, Vienna, Austria) and Python Version 3.7 ( Mixed-effects models were run on an Amazon EC2 M5.24xlarge instance ( with 96 virtual central processing units and 384 gigabytes of memory.

CL Medication Analysis

CL medication accesses were further characterized in an exploratory data analysis broken down by unit. The number of times CLs were accessed to administer each individual medication were determined. Medications were categorized into medication types and aggregated at the unit level.


There were 149,370 unique patients (560,690 unique in-patient encounters) from 2015 to 2020. Of these, 6,543 patients (11,942 in-patient encounters) had eligible instances of CL utilization during their hospitalization and patients acquired a CLABSI in 217 of these hospitalizations. Across all in-patient encounters, there were 138,411 eligible CL days; 639 of these were within 3 days of a CLABSI.

The CLABSI rate across the entire study was 1.57 per 1,000 CL days. The highest CLABSI rates were in stem cell (3.97/1,000 CL device days) and Hematology/Oncology (1.94/1,000 CL device days) patients. The cardiovascular ICU (CVICU) had the highest average number of CLs per patient visit (1.43 [± 0.54] lines). The number of CL accesses per patient per line day (8.51 [± 6.11] accesses) was mostly composed of accesses due to PL medications (6.58 [± 5.09] accesses). This ratio of CL accesses for PL medications to total CL accesses was highest in Hematology/Oncology (0.901) and lowest in the neonatal ICU (0.666) (Supplementary Table 2,

In the bivariate analysis, variables significantly associated with CLABSI within 3 days included more hospital days and CL days, greater percentage being cared for by the Hematology/Oncology or stem cell service lines, and more total CL accesses. Among the categories of CL accesses, the number of accesses due to laboratory draws and the number of accesses due to PL medications were independently associated with CLABSI within 3 days. The number of PL accesses for medications and being cared for in the pediatric acute care unit were associated with a lower risk of CLABSI within 3 days (Table 1).

TABLE 1. - Values for All Variables Considered As Potential Risk Factors, Averaged Over All Eligible Central Line Device Days Which Were Not Within 3 Days of a Central Line-Associated Bloodstream Infection and Those Which Were Within 3 Days of a Central Line-Associated Bloodstream Infection
Variable No CLABSI CLABSI Total Unadjusted OR (95% CI) p
CL days, n 137,772 639 138,411
Age, yr 6.91 ± 7.69 6.59 ± 7.91 6.91 ± 7.69 0.994 (0.984–1.005) 0.283
Female, n (%) 61,793 (45) 309 (48) 62,102 (45) 1.151 (0.986–1.345) 0.082
Days since admission, median (IQR) 12 (4.5–30) 16 (8–46) 12 (4.5–30) 1.004 (1.002–1.005) < 0.001
Cardiovascular ICU patient, n (%) 25,203 (18) 110 (17) 25,313 (18) 0.929 (0.756–1.141) 0.482
Hematology/Oncology patient, n (%) 24,050 (17) 132 (21) 24,182 (17) 1.231 (1.016–1.492) 0.038
Neonatal ICU patient, n (%) 26,592 (19) 123 (19) 26,715 (19) 0.997 (0.818–1.214) 0.973
Pediatric acute care patient, n (%) 32,241 (23) 60 (9.4) 32,301 (23) 0.339 (0.260–0.443) < 0.001
PICU patient, n (%) 18,133 (13) 89 (14) 18,222 (13) 1.068 (0.853–1.336) 0.568
Stem cell patient, n (%) 9,787 (7.1) 125 (20) 9,912 (7.2) 3.180 (2.613–3.871) < 0.001
Other department patient, n (%) 1,200 (0.87) 0 (0) 1,200 (0.87) NA NA
External admit patient, n (%) 45,733 (33) 205 (32) 45,938 (33) 0.951 (0.805–1.123) 0.551
Critical care patient, n (%) 65,828 (48) 309 (48) 66,137 (48) 1.023 (0.876–1.196) 0.802
Number of CLs 1.29 ± 0.64 1.30 ± 0.60 1.29 ± 0.64 1.018 (0.903–1.148) 0.771
Elapsed CL days, median (IQR) 13 (4.1–51) 25 (7.3–67) 13 (4.1–52) 1.130 (1.081–1.182) < 0.001
CL accesses 10.85 ± 10.58 13.01 ± 10.91 10.86 ± 10.58 1.016 (1.010–1.022) < 0.001
CL accesses (laboratory draws) 1.44 ± 2.23 1.75 ± 2.32 1.44 ± 2.23 1.047 (1.020–1.074) < 0.001
CL accesses (CL medications) 1.11 ± 1.75 1.06 ± 1.50 1.11 ± 1.75 0.980 (0.936–1.027) 0.401
CL accesses (PL medications) 8.29 ± 8.77 10.21 ± 9.46 8.30 ± 8.77 1.020 (1.013–1.027) < 0.001
PL medication accesses 1.93 ± 5.26 0.87 ± 3.40 1.92 ± 5.26 0.931 (0.905–0.957) < 0.001
CL = central line, CLABSI = central line-associated bloodstream infection, IQR = interquartile range, NA = not applicable, OR = odds ratio, PL = peripheral line.
Unless otherwise noted, values are presented as mean ± sd.
Also shown are the unadjusted odds ratio, 95% CI, and p value from the univariate analysis for each variable.

After controlling for potential confounding variables and modeling each individual patient as a random effect, the number of daily CL accesses (aOR, 1.007; 95% CI, 1.003–1.012), female gender (aOR, 1.238; 95% CI, 1.102–1.392), the natural logarithm of the total elapsed CL days (aOR, 1.329; 95% CI, 1.300–1.359), and being cared for in the stem cell service line (aOR, 2.851; 95% CI, 2.372–3.426) were significantly associated with CLABSI within 3 days (Supplementary Fig. 4, Patient age in years (aOR, 0.972; 95% CI, 0.964–0.980), the number of PL accesses for medications (aOR, 0.931; 95% CI, 0.906–0.956), number of CLs (aOR, 0.736; 95% CI, 0.695–0.780), and being cared for in the pediatric acute care unit (aOR, 0.404; 95% CI, 0.312–0.525) were associated with lower probability of CLABSI within 3 days (Fig. 1).

Figure 1.:
Results of the mixed-effects multivariate logistic regression analysis, including adjusted odds ratios, 95% CIs, and p values for each variable used. Each eligible central line device day was considered as a separate observation. The outcome was whether a patient contracted a central line-associated bloodstream infection (CLABSI) in the 3 d after the current device day. Each patient was modeled as a separate random effect. *The adjusted odds ratio presented for elapsed central line days corresponds to the natural logarithm of the total elapsed central line days (to mitigate the effect of outliers). Hem/Onc = Hematology/Oncology.

We observed that administration of PL medication (i.e., medications whose recommended route is not via CL) accounted for 76% of all CL accesses and 88% of CL-administered medications. We found that 42% of all CL accesses (4.6 CL accesses per CL device day, on average) were for administration of PL medications while the patient had a PL present. This includes 58% and 52% of CL accesses in the CVICU and PICU, respectively (Fig. 2). In characterizing the types of CL access by medication (Table 2). neurosedatives (analgesics and sedatives) were the category of medications most frequently administered through CLs (Supplementary Table 3,

TABLE 2. - Total Number of Central Line Accesses Attributed to Individual Medication Categories, for Each Unit and in Total
Cardiovascular ICU Hematology/Oncology PICU Stem Cell
Medication Name n Medication Name n Medication Name n Medication Name n
Neurosedatives/analgesics 92,560 Antimicrobials 27,289 Neurosedatives/analgesics 86,233 Antimicrobials 34,041
Dextrose/electrolytes 49,606 Anticoagulation/line maintenance 21,105 Antimicrobials 27,273 Dextrose/electrolytes 17,644
Miscellaneous 28,739 Dextrose/electrolytes 18,413 Dextrose/electrolytes 25,380 Anticoagulation/line maintenance 17,125
Diuretics 26,553 Neurosedatives/analgesics 12,875 Anticoagulation/line maintenance 16,933 Miscellaneous 15,860
Parenteral nutrition 22,412 Miscellaneous 11,232 Parenteral nutrition 11,172 Neurosedatives/analgesics 13,488
Antimicrobials 15,291 Parenteral nutrition 2,358 Diuretics 8,447 Parenteral nutrition 6,662
Diuretics 1,150 Miscellaneous 3,742 Diuretics 2,583
Neonatal ICU Pediatric Acute Care Other Department Total
Medication Name n Medication Name n Medication Name n Medication Name n
Neurosedatives/analgesics 32,143 Anticoagulation/line maintenance 56,126 Miscellaneous 5,358 Neurosedatives/analgesics 210,526
Parenteral nutrition 31,744 Antimicrobials 31,214 Antimicrobials 4,295 Antimicrobials 139,153
Antimicrobials 25,486 Neurosedatives/analgesics 17,713 Dextrose/electrolytes 3,753 Anticoagulation/line maintenance 119,728
Diuretics 13,367 Dextrose/electrolytes 15,822 Anticoagulation/line maintenance 2,982 Miscellaneous 110,536
Miscellaneous 12,230 Parenteral nutrition 15,642 Parenteral nutrition 1,674 Dextrose/electrolytes 97,190
Dextrose/electrolytes 10,082 Miscellaneous 12,875 Neurosedatives/analgesics 1,348 Parenteral nutrition 91,664
Diuretics 3,202 Diuretics 57,022
Central line access counts for individual medications are given in Supplementary Table 2 (

Figure 2.:
Average daily counts of each separate type of central line access by unit and service line. The subset of central line accesses due to peripheral line (PL) medications for which the patient had an existing PL in place is also illustrated. Hem/Onc = Hematology/Oncology, N = number.


During a 5-year study period, we analyzed and characterized over 1,500,000 CL accesses across seven distinct clinical populations and quantified an increased risk in the development of CLABSI by a factor of 1.007 associated with each incremental CL access. Notably, 76% of all CL accesses were for medications compatible with alternative routes (namely, peripheral IV injection, infusion, or oral) and the utilization of PLs for medication access was associated with lower risk of CLABSI. The risk associated with CL accesses due to PL medications was independently observed after controlling for multiple service lines and a variety of host risk factors known to be associated with the development of CLABSI. CL accesses due to PL medications were associated with an average daily increase of 6.3% in the risk of developing a CLABSI.

Our estimates of the association between CL access and risk for CLABSI are similar to or smaller than those previously published (20,21). These previous studies had smaller study sizes, more select patient populations (neonates and patients with hemodialysis catheters, respectively) and significantly different risk adjustment methodologies. Our study is novel in the broad consideration of all types of pediatric hospitalizations and the quantification of the immediate, 3-day risk for CLABSI based on CL utilization patterns controlling for patient mix and traditional CLABSI risk factors (Supplementary Table 4, Additionally, we further characterized medication types to help determine the degree of necessity for each CL access and identify opportunities to reduce CLABSI risk by modifying practice.

In the critical care units where most of the CLs are employed, a majority of medications compatible with alternative routes were administered through the CL while the patient had a concomitant PL in place. Most CL medication accesses were for the delivery of neurosedative/analgesic and antimicrobial medications. Apart from vancomycin which can be caustic to peripheral veins, these medications are rated as generally safe to deliver peripherally. These findings imply that CL access for PL-preferred medications may be a modifiable risk factor and reducing these accesses may reduce CLABSI risk.

The findings presented here may be one of many “missing links” toward the sustainable elimination of CLABSI, particularly in high-risk patients. Consistent with several sentinel and landmark studies (6,20–24), we found younger age (25,26), duration of CL device days, and critically ill patients are important risk factors for CLABSI. Yet, despite widespread national dissemination of evidence-based bundle recommendations, CLABSIs continue to pose a significant cost to the healthcare system. The goal to eradicate healthcare-associated conditions, such as CLABSI, has been a consistent narrative of academic and industry research (1,27–29). The persistence of CLABSI may suggest there are additional poorly understood healthcare practices that contribute to CLABSI. One such factor may be the presence of multiple CLs, which have recently been shown to have nearly a two-fold increased risk of CLABSI (23,30). In our study, we found an inverse relationship between the risk of CLABSI and the presence of multiple CLs. We surmise this is due to patient population differences (pediatrics vs adult patients) and important differences in the utilization and prevalence of concomitant CLs. For example, multiple concomitant CLs are routinely employed in children recovering from cardiac surgery (CVICU) independent of severity of illness. Thus, the relationship between concomitant CLs and CLABSI were inconsistent from previous reports perhaps due to important differences in case mix.

We also found that female gender was independently associated with a risk of CLABSI. There is little consistency in previous reports (31,32) as to the relationship between gender and risk for hospital-acquired bloodstream infections. Although many hypotheses exist such as skin flora differences and the influence of gender-biased medical conditions (e.g., urinary tract infections), further analysis is required to understand the individual-level characteristics that form our population-based findings.

These findings introduce several possibilities for impactful interventions. The knowledge of frequent medication types administered through CLs can be used to develop targeted diversion strategies (such as daily rounding checklists or EHR-based alerts [33]) to PL administration. Differentiating by service lines and units lends these interventions to be uniquely tailored and targeted to specific patient populations. Given that an important number of medications were neurosedatives and analgesics, additional benefits may arise from adopting strategies to use existing smart syringe pumps and/or nursing-controlled or patient-controlled analgesia to minimize multiple CL accesses. These interventions, while carefully considering other priorities such as patient comfort, are relatively low-cost and would not require additional expensive technologies. More importantly, the principal concept behind reducing avoidable CL accesses should be considered a broadly applicable component of contemporary CLABSI prevention bundles.

This study should be interpreted in the context of its limitations. First, this was a single-center, retrospective cohort study; causation cannot be inferred and the findings may not be generalizable to institutions with different case mixes and different CL utilization patterns. However, we found that the risk for CLABSI by CL access was consistent across a diversity of service lines and case mix complexities, while the use of a PL was protective for the development of CLABSI. Second, we did not perform a validation study to document the medical necessity of medications given through CLs. We cannot conclusively report that an important number of medications are, in fact, divertible toward alternative routes of administration without knowing the clinical circumstances for medical and/or social reasons. Although we found a majority of medications administered via CL access can be safely and routinely administered through PLs, which were present for several patients in our study, careful consideration of various clinical priorities should be undertaken as part of any intervention. Third, the number of CL laboratory draws had to be heuristically derived; a proportion of these laboratories may have been drawn from PLs. Despite the possibility of this being an overestimate of the true number of CL laboratory draws, there was still an association between CL access and CLABSI. Therefore, our results likely represent an underestimate of the association between CL laboratory draws and risk for CLABSI. This suggests that batching noncritical laboratory draws or increasing utilization of noncentral routes could mitigate the risk of CLABSI. Finally, to characterize CL utilizations, we used the EHR, which may contain important errors in charting or documentation. Despite this, we are reassured by the observation that our findings are consistent between and agnostic to the heterogeneity of service lines where there is little overlap of nursing and physician teams. In fact, we contend our study is an example of secondary use of the EHR, where data can be used to identify improvement opportunities. With increasing economic pressure to contain cost growth, our efforts to invest in data acquisition and high-throughput analytics led to important insights and knowledge generation toward accountable care.


This cohort study provides a robust analysis characterizing an important risk for CLABSI associated with CL access. We found the number of CL accesses was significantly associated with an increased risk of CLABSI and that most access instances are potentially preventable. This provides evidence that efforts to reduce CL accesses may be an important strategy to include in contemporary CLABSI-prevention bundles.


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catheterization; central venous catheters; electronic health records; iatrogenic disease; informatics

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