Aggressive Antimicrobial Initiation for Suspected Intensive Care Unit-Acquired Infection Is Associated with Decreased Long-Term Survival after Critical Illness

Antibiotic Exposure of Critically Ill Children at a Tertiary Care Paediatric Intensive Care Unit in Switzerland

Antibiotic overtreatment fosters multidrug-resistance that threatens healthcare systems worldwide as it increases patient morbidity and mortality. Contemporary data on antibiotic usage on tertiary care paediatric intensive care units for in- and external benchmarking are scarce. This was a single-centre retrospective quality control study including all patients with antibiotic treatment during their hospitalization at a paediatric intensive care unit in the time period 2019-2021. Antibiotic treatment was calculated as days of therapy (DOT) per 100 patient days (DOT/100pd). Further, the variables PIM II score, length of stay in intensive care (LOS), gender, age, treatment year, reason for intensive care unit admission, and death were assessed. Two thousand and forty-one cases with a median age of 10 months [IQR 0-64] were included; 53.4% were male, and 4.5% of the included patients died. Median LOS was 2.73 days [0.07-5.90], and PIM II score was 1.98% [0.02-4.86]. Overall, the antibiotic exposure of critically ill children and adolescents was 59.8 DOT/100pd. During the study period, the antibiotic usage continuously increased (2019: 55.2 DOT/100pd; 2020: 59.8 DOT/100pd (+8.2%); 2021: 64.5 DOT/100pd (+8.0%)). The highest antibiotic exposure was found in the youngest patients (0-1 month old (72.7 DOT/100pd)), in patients who had a LOS of >2-7 days (65.1 DOT/100pd), those who had a renal diagnosis (98 DOT/100pd), and in case of death (91.5 DOT/100pd). Critically ill paediatric patients were moderately exposed to antibiotics compared to data from the previously published literature. The current underreporting of antimicrobial prescription data in this cohort calls for future studies for better internal and external benchmarking.

Fever and infections in surgical intensive care: an American Association for the Surgery of Trauma Critical Care Committee clinical consensus document

The evaluation and workup of fever and the use of antibiotics to treat infections is part of daily practice in the surgical intensive care unit (ICU). Fever can be infectious or non-infectious; it is important to distinguish between the two entities wherever possible. The evidence is growing for shortening the duration of antibiotic treatment of common infections. The purpose of this clinical consensus document, created by the American Association for the Surgery of Trauma Critical Care Committee, is to synthesize the available evidence, and to provide practical recommendations. We discuss the evaluation of fever, the indications to obtain cultures including urine, blood, and respiratory specimens for diagnosis of infections, the use of procalcitonin, and the decision to initiate empiric antibiotics. We then describe the treatment of common infections, specifically ventilator-associated pneumonia, catheter-associated urinary infection, catheter-related bloodstream infection, bacteremia, surgical site infection, intra-abdominal infection, ventriculitis, and necrotizing soft tissue infection.

Antibiotic Initiation Timing and Mortality in Trauma Patients With Ventilator-Associated Pneumonia

BACKGROUND

Early antibiotic initiation is considered a cornerstone in the management of ventilator-associated pneumonia (VAP). However, recent data suggests that early antibiotic initiation may not be necessary in all cases. Additionally, the benefits of early antibiotic administration for infection have not been studied in a dedicated trauma population. This study's aim was to evaluate the impact of antibiotic administration timing on in-hospital mortality in trauma patients with VAP.

METHODS

This retrospective case-control study identified all trauma patients at a single level 1 academic trauma center from 2016 to 2020. Patients with a TQIP-defined VAP were included and stratified into 2 subgroups by in-hospital mortality. Time interval between airway culture and antibiotic initiation was gathered. Baseline measures of injury and illness severity were collected. Univariate analysis of the data was performed.

RESULTS

Forty-five patients met inclusion criteria. Overall, 80% of patients survived admission (n = 36) and 20% of patients did not survive admission (n = 9). There were no significant differences in baseline characteristics or cultured organism between survivors and non-survivors. The median time interval between airway culture and antibiotic initiation was 2 hours (IQR 0-4.5) for survivors, and 0 hours (IQR 0-0) for non-survivors (P = .07). Antibiotics were administered within 1 hour of airway culture for 33.3% of survivors, and 77.8% of non-survivors (P = .02).

CONCLUSIONS

In a population of trauma patients with VAP, survivors had antibiotics initiated in more delayed fashion than non-survivors. These findings question the primacy of early antibiotic administration for suspected infection.

Advanced Statistics: Multiple Logistic Regression, Cox Proportional Hazards, and Propensity Scores

Background: Randomized controlled trials (RCTs) are generally regarded as the gold standard for demonstrating causality because they effectively mitigate bias from both known and unknown confounders. However, conducting an RCT is not always feasible because of logistical and ethical considerations. This is especially true when evaluating surgical interventions, and non-randomized study designs must be utilized instead. Methods: Statistical methods that adjust for baseline differences in non-randomized studies were reviewed. Results: The three methods used most commonly to adjust for confounding factors are multiple logistic regression, Cox proportional hazard, and propensity scoring. Multiple logistic regression (MLR) is implemented to analyze the influence of categorical and/or continuous variables on a single dichotomous outcome. The model controls for multiple covariates while also quantifying the magnitude of each covariate's influence on the outcome. Selecting which variables to include in a model should be the most important consideration, and authors must report how and why variables were chosen. Cox proportional hazards modeling is conceptually similar to logistic regression and is used when analyzing survival data. When applied to survival curves, Cox proportional hazards can adjust for baseline group differences and provide a hazard ratio to quantify the effect that any single factor contributes to the survival curve. Propensity scores (PS) range from zero to one and are defined as the probability of receiving an intervention based on observed baseline characteristics. Propensity score matching (PSM) is especially useful when the outcome of interest is a rare event. Treated and untreated subjects with similar propensity scores are paired, forming balanced samples for further analysis. Conclusions: The method by which to address confounding should be selected according to the data format and sample size. Reporting of methods should provide justification for selected covariates, confirmation that data did not violate model assumptions, and measures of model performance.

Long-term outcome of prolonged critical illness: A multicentered study in North Brisbane, Australia

Background

Although critical illness is usually of high acuity and short duration, some patients require prolonged management in intensive care units (ICU) and suffer long-term morbidity and mortality.

Objective

To describe the long-term survival and examine determinants of death among patients with prolonged ICU admission.

Methods

A retrospective cohort of adult Queensland residents admitted to ICUs for 14 days or longer in North Brisbane, Australia was assembled. Comorbid illnesses were classified using the Charlson definitions and all cause case fatality established using statewide vital statistics.

Results

During the study a total of 28,742 adult Queensland residents had first admissions to participating ICUs of which 1,157 (4.0%) had prolonged admissions for two weeks or longer. Patients with prolonged admissions included 645 (55.8%), 243 (21.0%), and 269 (23.3%) with ICU lengths of stay lasting 14–20, 21–27, and ≥28 days, respectively. Although the severity of illness at admission did not vary, pre-existing comorbid illnesses including myocardial infarction, congestive heart failure, kidney disease, and peptic ulcer disease were more frequent whereas cancer, cerebrovascular accidents, and plegia were less frequently observed among patients with increasing ICU lengths of stay lasting 14–20, 21–27, and ≥28 days. The ICU, hospital, 90-day, and one-year all cause case-fatality rates were 12.7%, 18.5%, 20.2%, and 24.9%, respectively, and were not different according to duration of ICU stay. The median duration of observation was 1,037 (interquartile range, 214–1888) days. Although comorbidity, age, and admitting diagnosis were significant, neither ICU duration of stay nor severity of illness at admission were associated with overall survival outcome in a multivariable Cox regression model.

Conclusions

Most patients with prolonged stays in our ICUs are alive at one year post-admission. Older age and previous comorbidities, but not severity of illness or duration of ICU stay, are associated with adverse long-term mortality outcome.

Clinical Diagnosis of Infection in Surgical Intensive Care Unit: You're Not as Good as You Think!

Background: Because of the everincreasing costs and the complexity of institutional medical reimbursement policies, the necessity for extensive laboratory work-up of potentially infected patients has come into question. We hypothesized that intensivists are able to differentiate between infected and non-infected patients clinically, without the need to pan-culture, and are able to identify the location of the infection clinically in order to administer timely and appropriate treatment. Methods: Data collected prospectively on critically ill patients suspected of having an infection in the surgical intensive care unit (SICU) was obtained over a six-month period in a single tertiary academic medical center. Objective evidence of infection derived from laboratory or imaging data was compared with the subjective answers of the three most senior physicians' clinical diagnoses. Results: Thirty-nine critically ill surgical patients received 52 work-ups for suspected infections on the basis of signs and symptoms (e.g., fever, altered mental status). Thirty patients were found to be infected. Clinical diagnosis differentiated infected and non-infected patients with only 61.5% accuracy (sensitivity 60.3%; specificity 64.4%; p = 0.0049). Concordance between physicians was poor (κ = 0.33). Providers were able to predict the infectious source correctly only 60% of the time. Utilization of culture/objective data and SICU antibiotic protocols led to overall 78% appropriate initiation of antibiotics compared with 48% when treatment was based on clinical evaluation alone. Conclusion: Clinical diagnosis of infection is difficult, inaccurate, and unreliable in the absence of culture and sensitivity data. Infection suspected on the basis of signs and symptoms should be confirmed via objective and thorough work-up.

Recent Anti-Microbial Exposure Is Associated with More Complications after Elective Surgery

BACKGROUND

Recent anti-microbial exposure has been associated with poor outcomes after infection in a mixed population. We hypothesized that recent anti-microbial exposure would be associated with poor outcomes of elective surgery.

METHODS

From August 2015 to August 2016, all elective surgical patients were questioned prospectively about anti-microbial exposure during the prior three months. Multivariable models were used to calculate risk-adjusted odds ratios for anti-microbial exposure controlling for surgeon influence. Primary outcomes were any serious complication, any complication, any infection, and surgical site infection. Secondary outcomes were length of stay, C. difficile infection, and death. A separate analysis of patients excluding those having colorectal surgery who had undergone an oral antibiotic bowel preparation also was performed.

RESULTS

Ninety-four percent of eligible patients (n = 1,538) answered the exposure question, with a three-month anti-microbial exposure rate of 34.1%. Colorectal surgery patients had the highest exposure rate, whereas hernia patients had the lowest. Exposed patients had higher rates of any complication, any infection, and surgical site infection, as well as a median two-day longer hospital stay. There were no differences in C. difficile infection or death between the groups. After risk adjustment, anti-microbial exposure was independently associated with any serious complication for all patients as well as with complications and infection in patients having an operation other than colorectal surgery.

CONCLUSION

Recent anti-microbial exposure is associated with more complications of elective surgery. Anti-microbial drug-induced alterations in microbiome-related inflammatory responses may play a role, highlighting an opportunity for pre-surgical intervention in this at-risk population.