Unsupervised clustering of intensive care unit (ICU) medications may identify unique medication clusters (i.e., pharmacophenotypes) in critically ill adults. We performed an unsupervised analysis ...with Restricted Boltzmann Machine of 991 medications profiles of patients managed in the ICU to explore pharmacophenotypes that correlated with ICU complications (e.g., mechanical ventilation) and patient-centered outcomes (e.g., length of stay, mortality). Six unique pharmacophenotypes were observed, with unique medication profiles and clinically relevant differences in ICU complications and patient-centered outcomes. While pharmacophenotypes 2 and 4 had no statistically significant difference in ICU length of stay, duration of mechanical ventilation, or duration of vasopressor use, their mortality differed significantly (9.0% vs. 21.9%, p < 0.0001). Pharmacophenotype 4 had a mortality rate of 21.9%, compared with the rest of the pharmacophenotypes ranging from 2.5 to 9%. Phenotyping approaches have shown promise in classifying the heterogenous syndromes of critical illness to predict treatment response and guide clinical decision support systems but have never included comprehensive medication information. This first-ever machine learning approach revealed differences among empirically-derived subgroups of ICU patients that are not typically revealed by traditional classifiers. Identification of pharmacophenotypes may enable enhanced decision making to optimize treatment decisions.
This study aimed to evaluate the impact of American Heart Association (AHA) advanced cardiovascular life support (ACLS) education and training on long-term retention of ACLS knowledge and confidence ...in Doctor of Pharmacy (PharmD) students.
This multicenter study included PharmD students who received ACLS training through different means: 1-hour didactic lecture (didactic), 1-hour didactic lecture with 2-hour skills practice (didactic + skills), and comprehensive AHA ACLS certification through an elective course (elective-certification). Students completed a survey before training, immediately after training, and at least 6-12 months after training to assess demographics and ACLS confidence and knowledge. The primary outcome was a passing score, defined as ≥ 84% on the long-term knowledge assessment. Secondary outcomes included overall knowledge score and perceived confidence, assessed using the Dreyfus model.
The long-term assessment was completed by 160 students in the didactic group, 66 in the didactic + skills group, and 62 in the elective-certification group. Six (4%), 8 (12%), and 14 (23%) received a passing score on the long-term knowledge assessment in the didactic, didactic + skills, and elective-certification groups, respectively. The median (IQR) scores on the long-term knowledge assessment were 50% (40-60), 60% (50-70), and 65% (40-80) in the 3 groups. On the long-term assessment, confidence was higher in the elective-certification group, demonstrated by more self-ratings of competent, proficient, and expert, and fewer self-ratings of novice and advanced beginner.
Long-term retention of ACLS knowledge was low in all groups, but was higher in students who received AHA ACLS certification through an ACLS elective course.
What is known and objective
Advanced Cardiovascular Life Support (ACLS) is an integrated, team‐based approach to optimizing patient outcomes during acute cardiovascular events. Due to the fast‐paced, ...high‐stress environment, inherent strengths may impact performance and confidence with ACLS skills. The objective of this study was to assess pharmacist perceptions regarding strengths deemed important during emergency cardiovascular response.
Methods
An electronic survey was administered to members of the American College of Clinical Pharmacists Critical Care, Cardiology, Internal Medicine, Emergency Medicine and Pediatrics Practice and Research Network listservs. The survey assessed the top 5 strengths deemed important for being part of an emergency response team, a pharmacist's role in ACLS and a team leader's role in ACLS. The primary outcome was top strengths required for pharmacist involvement in ACLS. Descriptive statistics were used to present survey results.
Results
Of the 359 responses included, nearly all respondents had been certified by the American Heart Association in ACLS and/or Pediatric Advanced Life Support (PALS). The top CliftonStrengths® themes considered important for a pharmacist's role in ACLS were communication, adaptability, analytical, focus and responsibility. The top CliftonStrengths® themes considered important for the team leader's role in ACLS were communication, command, analytical, focus and adaptability. The top CliftonStrengths® themes important for an emergency response team were communication, adaptability, focus, analytical and command.
What is new and conclusions
By determining the personality traits perceived to be associated with high performance in ACLS, approaches can be taken to personalize student learning in order to train “practice‐ready” pharmacists that can be integral members of the ACLS team.
Previous research suggests that specific personality factors may be associated with high performance in critical care medicine. A survey of clinical pharmacists revealed that the CliftonStrengths® themes most important for a pharmacist's role in advanced cardiovascular life support (ACLS) are communication, adaptability, anlaytical, focus and responsibility. Future delivery of ACLS education can be personalized for students based on their posession of these strengths.
Catecholamine upregulation is a core pathophysiological feature in critical illness. Sustained catecholamine β-adrenergic induction produces adverse effects relevant to critical illness management. ...β-blockers (βB) have proposed roles in various critically ill disease states, including sepsis, trauma, burns, and cardiac arrest. Mounting evidence suggests βB improve hemodynamic and metabolic parameters culminating in decreased burn healing time, reduced mortality in traumatic brain injury, and improved neurologic outcomes following cardiac arrest. In sepsis, βB appear hemodynamically benign after acute resuscitation and may augment cardiac function. The emergence of ultra-rapid βB provides new territory for βB, and early data suggest significant improvements in mitigating atrial fibrillation in persistently tachycardic septic patients. This review summarizes the evidence regarding the pharmacotherapeutic role of βB on relevant pathophysiology and clinical outcomes in various types of critical illness.
Background:
Club cell secretory protein (CC16) has demonstrated utility as a lung-specific biomarker in predicting mortality in acute respiratory distress syndrome (ARDS). These findings have been ...observed in pre-clinical trials and a re-analysis of a large, randomized controlled trial of ARDS (Fluid and Catheter Treatment Trial (FACTT)).
Objectives:
The purpose of this study was to validate previous findings by evaluating CC16 level as a mortality predictor in patients from the albuterol to treat acute lung injury (ALTA) trial.
Design and Method:
In this secondary biomarker analysis, plasma CC16 level was measured from 100 ALTA subjects using enzyme-linked immunosorbent assay (ELISA). The rate of mortality was assessed in patients with high (⩾45 ng/mL) versus low CC16 (<45 ng/mL) levels. This cut-off level was applied based on our previous analysis from FACTT trial. Significance was assessed using Kaplan-Meier curves and a log-rank test.
Results:
Subjects were an average of 50 years old and 46% of them were females. Patients with high CC16 levels had higher 90-day mortality compared to those with low CC16 levels, (37.73% vs 8.95%, P < .001). Other clinical outcomes including ICU-free days, ventilator-free days, and organ failure free days were significantly different between the groups (All P < .05).
Conclusion:
In this validation study, we demonstrated that ARDS patients with high plasma CC16 concentration had a higher mortality rate than those with low CC16 levels, confirming previous findings that CC16 levels are associated with ARDS mortality.
Matrix metalloproteinase-3 (MMP-3) is a proteolytic enzyme involved in acute respiratory distress syndrome (ARDS) pathophysiology that may serve as a lung-specific biomarker in ARDS.
This study was a ...secondary biomarker analysis of a subset of Albuterol for the Treatment of Acute Lung Injury (ALTA) trial patients to determine the prognostic value of MMP-3. Plasma sample MMP-3 was measured by enzyme-linked immunosorbent assay. The primary outcome was the area under the receiver operating characteristic (AUROC) of MMP-3 at day 3 for the prediction of 90-day mortality.
A total of 100 unique patient samples were evaluated and the AUROC analysis of day three MMP-3 showed an AUROC of 0.77 for the prediction of 90-day mortality (95% confidence interval: 0.67-0.87), corresponding to a sensitivity of 92% and specificity of 63% and an optimal cutoff value of 18.4 ng/mL. Patients in the high MMP-3 group (≥ 18.4 ng/mL) showed higher mortality compared to the non-elevated MMP-3 group (< 18.4 ng/mL) (47% vs. 4%, p < 0.001). A positive difference in day zero and day three MMP-3 concentration was predictive of mortality with an AUROC of 0.74 correlating to 73% sensitivity, 81% specificity, and an optimal cutoff value of + 9.5 ng/mL.
Day three MMP-3 concentration and difference in day zero and three MMP-3 concentrations demonstrated acceptable AUROCs for predicting 90-day mortality with a cut-point of 18.4 ng/mL and + 9.5 ng/mL, respectively. These results suggest a prognostic role of MMP-3 in ARDS.
Critical care pharmacy has evolved rapidly over the last 50 years to keep pace with the rapid technological and knowledge advances that have characterized critical care medicine. The modern-day ...critical care pharmacist is a highly trained individual well suited for the interprofessional team-based care that critical illness necessitates. Critical care pharmacists improve patient-centered outcomes and reduce health care costs through three domains: direct patient care, indirect patient care, and professional service. Optimizing workload of critical care pharmacists, similar to the professions of medicine and nursing, is a key next step for using evidence-based medicine to improve patient-centered outcomes.
Fluid overload, while common in the ICU and associated with serious sequelae, is hard to predict and may be influenced by ICU medication use. Machine learning (ML) approaches may offer advantages ...over traditional regression techniques to predict it. We compared the ability of traditional regression techniques and different ML-based modeling approaches to identify clinically meaningful fluid overload predictors. This was a retrospective, observational cohort study of adult patients admitted to an ICU ≥ 72 h between 10/1/2015 and 10/31/2020 with available fluid balance data. Models to predict fluid overload (a positive fluid balance ≥ 10% of the admission body weight) in the 48-72 h after ICU admission were created. Potential patient and medication fluid overload predictor variables (n = 28) were collected at either baseline or 24 h after ICU admission. The optimal traditional logistic regression model was created using backward selection. Supervised, classification-based ML models were trained and optimized, including a meta-modeling approach. Area under the receiver operating characteristic (AUROC), positive predictive value (PPV), and negative predictive value (NPV) were compared between the traditional and ML fluid prediction models. A total of 49 of the 391 (12.5%) patients developed fluid overload. Among the ML models, the XGBoost model had the highest performance (AUROC 0.78, PPV 0.27, NPV 0.94) for fluid overload prediction. The XGBoost model performed similarly to the final traditional logistic regression model (AUROC 0.70; PPV 0.20, NPV 0.94). Feature importance analysis revealed severity of illness scores and medication-related data were the most important predictors of fluid overload. In the context of our study, ML and traditional models appear to perform similarly to predict fluid overload in the ICU. Baseline severity of illness and ICU medication regimen complexity are important predictors of fluid overload.
The high mortality of coronavirus disease 2019 (COVID-19) patients is due to their progression to cytokine-associated organ injuries, primarily the acute respiratory distress syndrome (ARDS). The ...uncertainties in the molecular mechanisms leading to the switch from the early virus infection to the advanced stage ARDS is a major gridlock in therapeutic development to reduce mortality. Previous studies in our laboratory have identified matrix metalloprotease-3 (MMP3) as an important mediator of bacterial lipopolysaccharide (LPS)-induced ARDS, particularly in the exudative phase. Our studies have also reported elevated plasma MMP3 activity levels in the ARDS patients and that inhibition of MMP3 can reduce the severity of LPS-induced ARDS in mice. Given these observations, targeting MMP3 could be a potential option to treat COVID-19 patients with ARDS, and measurement of MMP3 activity in the plasma may serve as a biomarker for the early detection of ARDS in COVID-19 patients.
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