To retrospectively observe procalcitonin (PCT) and antibiotic ordering practices in patients hospitalized with community-acquired pneumonia (CAP).

Retrospective, exact matched, multicenter cohort study from October 1, 2018 – March 31, 2023.

All hospitals across the Mayo Clinic Enterprise.

Adult patients with CAP, identified using pneumonia diagnosis codes and receipt of systemic antibiotics with an indication of “respiratory tract infection” within 48 hours of hospitalization.

PCT testing within the first 7 days of hospitalization was compared to non-PCT care (nPCT). The primary outcomes were treatment duration, antibiotic days of therapy (DOT), and length of stay (LOS).

15364 patients met inclusion criteria. PCT testing occurred in 42.4% (6515/15364) of encounters, totaling 8214 PCT results. 12880 unique patient encounters were matched 1:1, 6440 in each group. Treatment duration was longer in the PCT group compared to the nPCT group (5.1 vs 4.6 days, respectively, P < 0.001). Patients in the PCT group also received more DOT (8.6 vs 7.6 DOT, P < 0.001) and had a longer LOS (6.8 vs 5.9 days, P < 0.001), respectively. There was no difference in 30-day all-cause mortality or C. difficile infection between groups. In a sensitivity analysis of nPCT patients compared to those with a peak value <0.25 ng/mL (i.e. normal result) there was no difference in treatment duration (4.6 days nPCT vs 4.7 days normal PCT, P = 0.104) or LOS (5.9 days nPCT vs 6.0 days normal PCT, P = 0.134).

PCT testing in patients hospitalized with CAP was not associated with reduced antimicrobial utilization, LOS, or 30-day all-cause mortality.

Intensive care units (ICUs) and high-dependency units (HDUs) care for critically ill patients, many of whom have multi-drug-resistant (MDR) bacteria. We investigated the prevalence and distribution of MDR bacteria on the surfaces of patient medical files in three ICUs and two HDUs in Kampala.

We conducted a cross-sectional study that used simple random sampling to select patient medical files through unique codes recorded in a health information electronic system. MDR was defined as laboratory confirmation of the WHO priority pathogens following the 33rd edition of the Clinical Laboratory Standards Institute on Antimicrobial Susceptibility testing guidelines for antibiotic susceptibility interpretation. Quantitative data was descriptively analyzed, while qualitative was thematically analyzed.

Six of 33 files (18.2%) had MDR bacteria on their surfaces. Contamination was significantly associated with the type of medical diagnosis (p=0.014) and the file storage location (p=0.010). The MDR pathogens identified were Fastidious Acinetobacter (5/33; 15.2%) and methicillin-resistant Staphylococcus aureus (1/33; 3%).

Nearly one in five patient medical files in ICUs and HDUs were contaminated with MDR bacteria. Most contaminated files belonged to patients treated with aminoglycoside or glycopeptide-based regimens.

Hospital-onset bacteremia and fungemia (HOB) has been suggested as a suitable and automatable surveillance target to include in surveillance programs, however differences in definitions across studies limit interpretation and large-scale implementation. We aimed to apply an automated surveillance system for HOB in multiple hospitals using a consensus definition, and describe HOB rates.

Retrospective cohort study in four Dutch hospitals: 1 tertiary hospital and 3 secondary hospitals.

All patients admitted for at least one overnight stay between 2017 and 2021 were included, except patients in psychiatry wards.

Data from the electronic health records and laboratory information system were used to identify HOBs based on the PRAISE consensus definition. HOB rates were calculated at ward and micro-organism-level.

Hospital-wide HOB rates varied from 1.0 to 1.9, and ICU rates varied from of 8.2 to 12.5 episodes per 1000 patient days. The median time between admission and HOB was 8–13 days. HOBs were predominantly caused by Enterobacterales, Enterococci, S. aureus and coagulase-negative staphylococci. Longitudinal HOB surveillance detected differences over time at ward and micro-organism level; for example increased HOB rates were observed during the COVID-19 pandemic. Sensitivity analyses demonstrated the impact of assumptions regarding the collection of confirmatory blood cultures for common commensals.

Applying a fully automated definition for HOB surveillance was feasible in multiple centers with different data infrastructures, and enabled detection of differences over time at ward and micro-organism-level. HOB surveillance may lead to prevention initiatives in the future.

Asymptomatic patients colonized with toxigenic Clostridioides difficile are at risk of progressing to C. difficile infection (CDI), but risk factors associated with progression are poorly understood. The objectives of this study were to estimate the incidence and identify risk factors to progression of hospital-onset CDI (HO-CDI) among colonized patients.

This was a nested case-control study at an academic medical center including adult patients colonized with toxigenic C. difficile, detected via polymerase chain reaction (PCR) on a rectal swab collected on admission from 2017 to 2020. Patients with prior CDI or symptoms on admission, neutropenia, prior rectal surgery, or hospitalization less than 24 hours were excluded. Colonized patients that developed HO-CDI were matched 1:3 to colonized patients who did not based on PCR test date. Bivariate and multivariable-adjusted Cox regression analyses were used to identify risk factors.

Of 2,150 colonized patients, 109 developed HO-CDI, with an incidence of 5.1%. After exclusions, 321 patients (69 with HO-CDI) were included, with an estimated incidence of 4.2%. Risk factors included cirrhosis (aHR 1.94), ICU admission (aHR 1.76), malignancy (aHR 1.88), and hospitalization within six months (aHR 1.6). Prior antibiotic exposure in the past three months (aHR 2.14) and receipt of at-risk antibiotics were also identified as potential risk factors (aHR 2.17).

Progression to HO-CDI among colonized patients was not uncommon. This study highlights key risk factors associated with progression, underscoring the importance of enhanced monitoring and prevention efforts tailored to high-risk populations to mitigate HO-CDI.

Restricting infectious healthcare workers (HCWs) from the workplace is an important infection prevention strategy. The duration of viral shedding or symptoms are often used as proxies for the infectious period in adults but may not accurately estimate it.

To determine the risk period for transmission among previously healthy adults infected with SARS-CoV-2 omicron variant (omicron) or influenza A (influenza) by examining the duration of shedding and symptoms, and day of symptom onset in secondary cases of transmission pairs.

Rapid review

This rapid review adhered to PRISMA-ScR; five databases were searched. The cumulative daily proportion of participants with an outcome of interest was calculated for each study and summarized.

Forty-three studies were included. Shedding resolved among ≥ 70% of participants by the end of day nine post symptom onset for omicron, and day seven for influenza; and for ≥ 90% of participants, by the end of day 10 for omicron and day nine for influenza. Two studies suggested shedding continues > 24 hours post-fever resolution for both viruses. Symptom onset occurred in ≥ 80% of secondary cases by the end of day seven post-primary case symptom onset for omicron and day six for influenza.

Omicron shedding is consistent with previous recommendations to exclude infected HCWs from work for 10 days; and influenza follows a similar trend. Earlier symptom onset in most secondary cases for both pathogens indicates that, despite persistent viral shedding, most transmission occurs earlier; and the cumulative serial interval might better approximate the duration of infectiousness.

To evaluate the hospital-reported cost of care, clinical burden, and incidence of hospital-onset bacteremia and fungemia (HOB) for hospital admissions with surgical site infections (SSI).

A cross-sectional study of 38 acute-care hospital admissions with a procedure under the National Healthcare Safety Network (NHSN) surveillance for SSI was conducted. SSI admissions were identified through NHSN reporting by the hospital. Clinical outcomes were estimated for SSI compared to no SSI controls using propensity matching and multivariable adjusted models that controlled for patient and hospital demographics; these endpoints were also compared for SSI admissions with and without HOB co-occurrence.

The rate of hospital-reported SSI was 0.15 per 100 admissions with a procedure under surveillance for SSI. Admissions with SSI compared to no SSI had significantly higher incremental hospital-reported cost of $30,689 and length of stay (LOS) was 11.6 days higher. The incidence of HOB was 6-fold higher in admissions with SSI compared to no SSI. For SSI admissions with HOB vs. no HOB, HOB added $28,049 to cost of care and 6.5 days to the LOS.

Hospital-reported SSIs were associated with higher clinical and economic burden. Patients with SSI and HOB had even more deleterious outcomes. These data may inform programs to augment infection prevention bundles targeting SSIs and downstream complications or comorbidities like HOB.

To compare the risk and exposure-adjusted central line-associated bloodstream infection (CLABSI) rates between racial and ethnic groups.

Retrospective cohort study.

15 network hospitals in Illinois and Michigan (Part of OSF HealthCare).

Patients of all age groups who had a central line inserted and removed during the same hospitalization between 01/2018 and 06/2023.

CLABSI rates/1000 Central line days of the four major racial and ethnic categories (Hispanic, non-Hispanic White [NHW], non-Hispanic Black [NHB], and non-Hispanic others) were analyzed by generalized Poisson regression. Confounding variables included in the regression model based on a directed acyclic graph and included age group, insurance class, language, ICU admission, diagnostic cohorts (obesity, diabetes, dialysis, cancer, neutropenia), and line usage (blood products, chemotherapy, total parenteral nutrition).

27,674 central lines (244,889 catheter days) on 23,133 unique patients (median age 64 years, 8% pediatric patients) were included in the analysis. Overall, the CLABSI rate was 1.070/1000 Central line days. 76% of the study population was NHW, 17% NHB, and 4% Hispanic. After adjusting for confounding variables, Hispanic patients had higher CLABSI rates than NHW (IRR 1.89, 95% CI 1.15–3.10, P = .013). No significant difference was observed in the CLABSI rates between NHW and NHB patients.

Disparities in hospital-associated conditions persist even after controlling for patient-level risk factors and exposures, with Hispanic patients at the highest risk.

Antimicrobial resistance is increased by antibiotic overuse, so it’s crucial for stewardship programs to monitor and control their use. Pneumonia, particularly prevalent among older adults in Japan, is requiring higher rates of medical treatment. This study aimed to develop an improved method for benchmarking broad-spectrum antibiotic use in the empiric treatment of pneumonia in older adult inpatients by applying the “smoothed” observed-to-expected (O/E) ratio which adjusts for hospital-level variations and minimizes the effect of extreme values.

Using nationwide data from the Diagnosis Procedure Combination research group, pneumonia patients between April 1st 2018 and March 31st 2020 were analyzed. The primary outcome was the smoothed O/E ratio of the broad-spectrum antibiotic use for hospitals. It was calculated from the predicted values of broad-spectrum antibiotic use that were obtained through multilevel logistic regression using patient characteristics as predictors from data clustered by hospitals. The analysis investigated the risk-adjusted use of broad-spectrum antibiotics among hospitals.

A total of 244,747 patients from 958 hospitals were included, with a mean age of 81 (±8.30) years. The proportion of broad-spectrum antibiotic use was 35.3% (n = 86,316). The prediction model showed a C-statistic of 0.722. There was a noticeable variation in the O/E ratio among hospitals with values ranging from 0.13 (95% CI: 0.09–0.20) to 2.81 (95% CI: 2.64–2.97).

Using a risk-adjusted smoothed O/E ratio, we assessed the use of broad-spectrum antibiotics across hospitals, identifying those with high O/E ratios that may indicate a need for improvement.

To quantify the impact of patient- and unit-level risk adjustment on infant hospital-onset bacteremia (HOB) standardized infection ratio (SIR) ranking.

A retrospective, multicenter cohort study.

Infants admitted to 284 neonatal intensive care units (NICUs) in the United States between 2016 and 2021.

Expected HOB rates and SIRs were calculated using four adjustment strategies: birthweight (model 1), birthweight and postnatal age (model 2), birthweight and NICU complexity (model 3), and birthweight, postnatal age, and NICU complexity (model 4). Sites were ranked according to the unadjusted HOB rate, and these rankings were compared to rankings based on the four adjusted SIR models.

Compared to unadjusted HOB rate ranking (smallest to largest), the number and proportion of NICUs that left the fourth quartile (worst-performing) following adjustments were as follows: adjusted for birthweight (16, 22.5%), birthweight and postnatal age (19, 26.8%), birthweight and NICU complexity (22, 31.0%), birthweight, postnatal age and NICU complexity (23, 32.4%). Comparing NICUs that moved into the better-performing quartiles after birthweight adjustment to those that remained in the better-performing quartiles regardless of adjustment, the median percentage of low birthweight infants was 17.1% (Interquartile Range (IQR): 15.8, 19.2) vs 8.7% (IQR: 4.8, 12.6); and the median percentage of infants who died was 2.2% (IQR: 1.8, 3.1) vs 0.5% (IQR: 0.01, 12.0), respectively.

Adjusting for patient and unit-level complexity moved one-third of NICUs in the worst-performing quartile into a better-performing quartile. Risk adjustment may allow for a more accurate comparison across units with varying levels of patient acuity and complexity.

Bloodstream infections (BSI) are associated with high mortality rates, particularly when caused by resistant pathogens. Reducing the delay in diagnosis and initiation of appropriate treatment is crucial for improving clinical outcomes. The implementation of polymerase chain reaction (PCR) tests in the diagnostic process offers a promising approach to achieving quicker identification of pathogens, thereby potentially reducing mortality associated with BSI.

A difference-in-differences analysis was performed within a New York City hospital system, comparing mortality risk between patients with enterococcal BSI before and after the adoption of BCID2 PCR testing, using as control those with methicillin-sensitive S. aureus BSI, for which diagnostic protocol has been unchanged.

The study included 548 inpatients; 164 diagnosed with vancomycin-resistant enterococci (VRE) BSI and 384 with MSSA BSI. The mean 30-day mortality risk difference in the period post-intervention estimated in our difference-in-differences model was -6.03 per 100 (95% CI: -10.35 to -1.7), with event study plots suggesting minimal deviation from parallel trends in the pre-treatment period.

Findings suggest that introduction of BCID2 PCR testing for enterococcal bloodstream infections (BSI) may be associated with a reduction in mortality, however, interpretation of the effects must be approached with caution given the relative imprecision of estimates. Further research with larger samples is essential to establish a definitive conclusion on the impact of rapid PCR testing on mortality in BSI. This is an innovative approach using causal methods to evaluate interventions aimed at the improvement of infection control and antimicrobial treatment strategies.

Validate a public health model identifying patients at high risk for carbapenem-resistant Enterobacterales (CRE) on admission and evaluate performance across a healthcare network.

Retrospective case-control studies

Adults hospitalized with a clinical CRE culture within 3 days of admission (cases) and those hospitalized without a CRE culture (controls).

Using public health data from Atlanta, GA (1/1/2016–9/1/2019), we validated a CRE prediction model created in Chicago. We then closely replicated this model using clinical data from a healthcare network in Atlanta (1/1/2015–12/31/2021) (“Public Health Model”) and optimized performance by adding variables from the healthcare system (“Healthcare System Model”). We frequency-matched cases and controls based on year and facility. We evaluated model performance in validation datasets using area under the curve (AUC).

Using public health data, we matched 181 cases to 764,408 controls, and the Chicago model performed well (AUC 0.85). Using clinical data, we matched 91 cases to 384,013 controls. The Public Health Model included age, prior infection diagnosis, number of and mean length of stays in acute care hospitalizations (ACH) in the prior year. The final Healthcare System Model added Elixhauser score, antibiotic days of therapy in prior year, diabetes, admission to the intensive care unit in prior year and removed prior number of ACH. The AUC increased from 0.68 to 0.73.

A CRE risk prediction model using prior healthcare exposures performed well in a geographically distinct area and in an academic healthcare network. Adding variables from healthcare networks improved model performance.