Gajic, Ognjen

Background Adherence to evidence-based care processes and patient outcomes in intensive care units (ICUs) can be influenced by staffing and resource availability. We aimed to evaluate if there is a weekend effect on adherence to evidence-based care processes, and hospitalization outcomes and whether a checklist implementation could mitigate potential differences. Methods Post hoc analysis of the Checklist for Early Recognition and Treatment of Acute Illness and Injury (CERTAIN) study dataset collected before and after checklist implementation in 34 ICUs across 15 countries (2013-2017). Admission days were classified as ‘weekend/holidays’ or ‘weekdays’ according to local work schedules and public holidays. The primary outcome was the omission of 10 evidence-based care processes addressed in the checklist. Mortality and length of stay differences between weekend/holiday and weekday admissions were evaluated as secondary outcomes. Results 4256 patients contributed 1141 weekend versus 3501 weekday observation days pre-intervention, and 2014 versus 6507 post-intervention. Pre-intervention, peptic ulcer prophylaxis was omitted more frequently on weekends/holidays than weekdays (adjusted rate ratio [aRR], 0.58 [95%–confidence interval [CI] 0.38-0.88), whereas head-of-bed elevation was omitted more often on weekdays than on weekends/holidays (aRR, 3.17 [1.14-8.86]). Post-intervention, peptic ulcer prophylaxis omission rates became similar (aRR, 1.03 [0.68-1.56], but head-of-bed elevation became omitted more often on weekends than on weekdays (aRR, 0.63 [0.45-0.88]). Post-intervention, oral care was omitted more frequently on weekends/holidays than in weekdays (aRR, 0.63 [0.45-0.9]), and central catheter removal was more frequent on weekdays than in weekends/holidays (aRR, 1.11 [1.02-1.21]). No significant differences in mortality or length of stay were found. Conclusion A weekend effect influenced adherence to some care processes. While checklist implementation improved overall adherence, some disparities diminished, while new ones emerged. Organizational, cultural, and temporal factors should be further studied to optimize care delivery across all times and settings. Clinical Trial Registration Number NCT01973829

Acute respiratory distress syndrome (ARDS) is a common and highly heterogeneous condition in the critically ill. The association between hyper- and hypo-inflammatory subphenotypes and clinical outcomes has generated significant interest in precise ARDS management. The value of identifying biomarkers to guide treatment and enrollment in future ARDS trials is undisputable. We describe multiple factors complicating the search for subphenotypes and their treatable traits. The observed heterogeneity seen in the clinical course of ARDS is dynamic and influenced by factors beyond lung pathophysiology, including variations in the delivery of best critical care practices, patient comorbidities, and functional status, and patient or family preferences. Current subphenotype definitions lack strong biological plausibility and without clear evidence of benefit from targeted treatments, their use in clinical practice is currently unwarranted.

Abstract Background Doxycycline is a frequently used alternative treatment for community-acquired pneumonia (CAP) in hospitalized patients; however, the evidence base is limited. We aimed to compare outcomes in CAP patients treated with doxycycline or azithromycin in combination with beta-lactams. Methods We evaluated patients with CAP admitted to Mayo Clinic hospitals from May 2018 to September 2022 and treated with either azithromycin or doxycycline in combination with a beta-lactam. Patients who received both antibiotics or were on either antibiotic as chronic therapy prior to admission were excluded. The primary outcome was mortality. Patients were 1-to-1 matched according to the presence of congestive heart failure, coronary artery disease, chronic obstructive pulmonary disease, human immunodeficiency virus infection, recent immunosuppressant use, and pneumonia severity index class. Results Among 8492 patients (5810 for azithromycin, 2682 for doxycycline), 2671 doxycycline-treated patients were matched with azithromycin-treated patients. In-hospital mortality was significantly lower in the azithromycin group than in the doxycycline group (odds ratio, 0.71; 95% confidence interval [CI], .56–.9), as was 90-day mortality (hazard ratio, 0.83; 95% CI, .73–.95). Patients on azithromycin also had significantly more hospital-free days (HFDs) than those on doxycycline (estimate, 1.37; 95% CI, .99–1.74). Conclusions Among hospitalized patients with CAP, azithromycin was associated with lower mortality and more HFDs compared with doxycycline in combination with beta-lactams. Randomized, controlled trials are needed to assess the effectiveness of each regimen and to compare their potential side effects.

Abstract Objective: Patients with Opioid Use Disorder (OUD) are prone to Multidrug-Resistant Organism (MDRO) colonization and infections, thus at risk for worse outcomes during critical illness. Understanding the prevalence and predictors of MDRO infections is essential to optimize interventions and treatments. Design: Retrospective cohort study. Methods: The study evaluated the prevalence of MDRO isolation among adults with OUD admitted to an intensive care unit (ICU) between January 1, 2018, and July 31, 2023. It included adults admitted to an ICU with bacterial infections and positive cultures obtained within 48 hours of admission. Demographics, clinical traits, and MDRO isolation rates were analyzed using descriptive statistics, univariate methods, and Least Absolute Shrinkage and Selection Operator (LASSO) regression. Results: MDRO isolation occurred in 178 of 790 patients (22.5%), with methicillin-resistant Staphylococcus aureus as the most frequently isolated organism. LASSO regression identified housing insecurity (OR: 1.79, 95% CI 1.09–2.93, P = .022), no receipt of medications for OUD treatment (OR: 1.56, 95% CI 1.06–2.29, P = .023), positive hepatitis C virus (HCV) status (OR: 2.19, 95% CI 1.19–4.03, P = .012), and intravenous antibiotic use in the prior 90 days (OR: 1.04 per 24 h, 95% CI 1.01–1.07, P = .007) as significant predictors of MDRO isolation. Conclusions: The study highlights a high prevalence of MDRO isolation in critically ill OUD patients admitted for infection-related issues with positive cultures obtained within 48 hours of admission, influenced by factors like housing insecurity, no receipt of medications for OUD treatment, HCV status, and prior antibiotic use.

Abstract Background The opioid crisis and the increasing prevalence of multi-drug resistant organism (MDRO) infections pose a threat to public health. Opioid Use Disorder (OUD) patient are prone to MDRO colonization and infections, thus potentially leading to adverse outcomes during periods of critical illness. Understanding the prevalence and predictors of MDRO infections within this vulnerable population is critical to improving patient outcomes by optimizing interventions and treatment plans. Methods We conducted a retrospective, multicenter, cohort study to evaluate the prevalence of MDRO isolation among adults with OUD admitted to an intensive care unit (ICU) with an infection across four Mayo Clinic regions. Patients were classified to the MDRO cohort if an MDRO was isolated from standard cultures or rapid diagnostic testing within 48 hours of admission. We utilized descriptive statistics, univariate and multivariate least absolute shrinkage and selection operator (LASSO) regression analysis including random effect to account for site variability, to analyze demographic data, clinical characteristics, and outcomes. Results 790 critically ill adult OUD patients with infection-related admission were included in the study cohort. The prevalence of MDRO isolation was 22.5% (n=178), with MRSA being the predominant isolated MDRO. In LASSO regression analyses, we identified homelessness (OR: 1.79, p = 0.022), no Medications for OUD (MOUD) treatment (OR: 1.56, p=0.023), and positive Hepatitis C Virus (HCV) status (OR: 2.19, p = 0.012) as significant predictors for isolation of an MDRO. Intravenous (IV) antibiotic use in the preceding 90 days was also positively associated (OR: 1.04 per 24 hours, p = 0.007), alongside mental health disorders (OR: 2.03, p < 0.001) and diabetes (OR: 1.54, p = 0.023). Conclusion The high prevalence of MDRO isolation in critically ill OUD patients with infection is associated with complex social and clinical factors. Disclosures All Authors: No reported disclosures

ABSTRACT Understanding clinical trajectories of sepsis patients is crucial for prognostication, resource planning, and to inform digital twin models of critical illness. This study aims to identify common clinical trajectories based on dynamic assessment of cardiorespiratory support using a validated electronic health record data that covers retrospective cohort of 19,177 patients with sepsis admitted to intensive care units (ICUs) of Mayo Clinic Hospitals over 8-year period. Patient trajectories were modeled from ICU admission up to 14 days using an unsupervised machine learning two-stage clustering method based on cardiorespiratory support in ICU and hospital discharge status. Of 19,177 patients, 42% were female with a median age of 65 (interquartile range [IQR], 55–76) years, The Acute Physiology, Age, and Chronic Health Evaluation III score of 70 (IQR, 56–87), hospital length of stay (LOS) of 7 (IQR, 4–12) days, and ICU LOS of 2 (IQR, 1–4) days. Four distinct trajectories were identified: fast recovery (27% with a mortality rate of 3.5% and median hospital LOS of 3 (IQR, 2–15) days), slow recovery (62% with a mortality rate of 3.6% and hospital LOS of 8 (IQR, 6–13) days), fast decline (4% with a mortality rate of 99.7% and hospital LOS of 1 (IQR, 0–1) day), and delayed decline (7% with a mortality rate of 97.9% and hospital LOS of 5 (IQR, 3–8) days). Distinct trajectories remained robust and were distinguished by Charlson Comorbidity Index, The Acute Physiology, Age, and Chronic Health Evaluation III scores, as well as day 1 and day 3 SOFA ( P < 0.001 ANOVA). These findings provide a foundation for developing prediction models and digital twin decision support tools, improving both shared decision making and resource planning.

ABSTRACT Objective: The aim of the study is to develop a predictive model for in-hospital mortality in critically ill patients with cirrhosis and sepsis, using clinical and laboratory data. Design: This is a retrospective cohort study. Setting: Medical and mixed intensive care units (ICUs) of a tertiary medical center. Patients: Cirrhotic adults were admitted with sepsis to the ICUs from January of 2007 to May of 2017. Interventions: None. Measurements and Main Results: Of 2,595 ICU admissions of patients with cirrhosis, 277 with first ICU admission for sepsis were included in the analysis, and 37% died in the hospital. Patients who stayed in the ICU for at least 6 h (n = 275) were considered for the multivariate model. Ten-fold cross-validation was used to estimate best parameter values and model performance, and the final model was chosen as the model maximizing area under the receiver-operating characteristic curve. Variables in order of impact were Acute Physiology and Chronic Health Evaluation (APACHE) III score, initial serum lactate, conjugated bilirubin, serum creatinine, model for end-stage liver disease score, age, body mass index, and serum hemoglobin. The final best model from cross-validation presented an area under the receiver operator characteristic curve (AUC) of 0.75, using a cut-point of 50% estimated probability, sensitivity and specificity were 0.46 and 0.90, respectively, with positive predictive value of 0.72 and negative predictive value of 0.74. These results were similar to the APACHE III only model (AUC = 0.74, sensitivity = 0.43, specificity = 0.89, positive predictive value = 0.69, negative predictive value = 0.73). Conclusion: The combination of initial serum lactate level, conjugated bilirubin, initial serum creatinine, model for end-stage liver disease score, age, body mass index, and serum hemoglobin did not yield meaningful improvement in the AUC and did not provide advantage over the APACHE III score for the prediction of in-hospital mortality in critically ill patients with cirrhosis and sepsis.

Abstract Background Critically ill patients, particularly those treated with extracorporeal devices or at extremes of weight, experience pharmacokinetic variability which can compromise beta-lactam (BL) antibiotic target attainment and treatment response. Therapeutic drug monitoring (TDM) for BL antibiotics can improve precision pharmacotherapy but has had limited implementation. The objective of this study was to evaluate the frequency of BL target attainment among adult intensive care unit (ICU) patients who underwent TDM. Methods This observational study evaluated adults treated with cefepime, piperacillin/tazobactam or meropenem in ICUs at the Mayo Clinic in Rochester, Minnesota who underwent TDM from June-September 2022. During the study timeframe, multidisciplinary teams were encouraged to perform BL TDM on patients requiring extracorporeal membrane oxygenation, continuous kidney replacement therapy, or at an extreme of body weight (weight &lt; 40 kg or &gt;120 kg or BMI &lt; 18 kg/m2 or &gt; 40 kg/m2). Percentage of patients with initial serum trough concentrations within the therapeutic range was calculated (Table 1). Results During the study timeframe, 59 trough concentrations were performed on critically ill patients, of which 5 were excluded due to uninterpretable results. Of the remaining 54 BL trough concentrations analyzed, 49 (91%) were initial troughs during the antibiotic course, and 5 (9%) were repeat troughs. Thirty-six (73%) of the initial trough concentrations were within the therapeutic range. Among the trough concentrations outside the therapeutic range, 10 (77%) were too high, and 3 (23%) were too low (Table 2). Dose adjustment occurred in 19 (39%) of initial trough evaluations, including 6 which were adjusted despite a level within the therapeutic range. All of the repeat trough concentrations drawn during the same antibiotic course were within the therapeutic range (n = 5/5; 100%). Conclusion One-fourth of initial BL trough concentrations were outside of the therapeutic range. BL levels outside the therapeutic range prompted dose adjustment to improve the potential for effectiveness or limit the potential for toxicity. BL TDM appears to be a promising strategy to enhance precision pharmacotherapy in the critically ill. Disclosures Sara Ausman, PharmD, Gilead: Honoraria Christina G. Rivera (O'Connor), Pharm.D, Gilead Sciences: Advisor/Consultant|Gilead Sciences: Board Member|Gilead Sciences: Grant/Research Support|Gilead Sciences: Honoraria

ABSTRACT Objective: To identify and describe characteristics of patients with sepsis who could be treated with minimally invasive sepsis (MIS) approach without intensive care unit (ICU) admission and to develop a prediction model to select candidates for MIS approach. Methods: A secondary analysis of the electronic database of patients with sepsis at Mayo Clinic, Rochester, MN. Candidates for the MIS approach were adults with septic shock and less than 48 hours of ICU stay, who did not require advanced respiratory support and were alive at hospital discharge. Comparison group consisted of septic shock patients with an ICU stay of more than 48 hours without advanced respiratory support at the time of ICU admission. Results: Of 1795 medical ICU admissions, 106 patients (6%) met MIS approach criteria. Predictive variables (age >65 years, oxygen flow >4 L/min, temperature <37°C, creatinine >1.6 mg/dL, lactate >3 mmol/L, white blood cells >15 × 109/L, heart rate >100 beats/min, and respiration rate >25 breaths/min) selected through logistic regression were translated into an 8-point score. Model discrimination yielded the area under the receiver operating characteristic curve of 79% and was well fitted (Hosmer-Lemeshow P = 0.94) and calibrated. The MIS score cutoff of 3 resulted in a model odds ratio of 0.15 (95% confidence interval, 0.08–0.28) and a negative predictive value of 91% (95% confidence interval, 88.69–92.92). Conclusions: This study identifies a subset of low-risk septic shock patients who can potentially be managed outside the ICU. Once validated in an independent, prospective sample our prediction model can be used to identify candidates for MIS approach.