Josh F. Peterson

Lorazepam Is an Independent Risk Factor for Transitioning to Delirium in Intensive Care Unit Patients

Background:Delirium has recently been shown as a predictor of death, increased cost, and longer duration of stay in ventilated patients. Sedative and analgesic medications relieve anxiety and pain but may contribute to patients’ transitioning into delirium. Methods:In this cohort study, the authors designed a priori an investigation to determine whether sedative and analgesic medications independently increased the probability of daily transition to delirium. Markov regression modeling (adjusting for 11 covariates) was used in the evaluation of 198 mechanically ventilated patients to determine the probability of daily transition to delirium as a function of sedative and analgesic dose administration during the previous 24 h. Results:Lorazepam was an independent risk factor for daily transition to delirium (odds ratio, 1.2 [95% confidence interval, 1.1–1.4]; P = 0.003), whereas fentanyl, morphine, and propofol were associated with higher but not statistically significant odds ratios. Increasing age and Acute Physiology and Chronic Health Evaluation II scores were also independent predictors of transitioning to delirium (multivariable P values < 0.05). Conclusions:Lorazepam administration is an important and potentially modifiable risk factor for transitioning into delirium even after adjusting for relevant covariates.

Intensive care unit delirium is an independent predictor of longer hospital stay: a prospective analysis of 261 non-ventilated patients

IntroductionDelirium occurs in most ventilated patients and is independently associated with more deaths, longer stay, and higher cost. Guidelines recommend monitoring of delirium in all intensive care unit (ICU) patients, though few data exist in non-ventilated patients. The study objective was to determine the relationship between delirium and outcomes among non-ventilated ICU patients.MethodA prospective cohort investigation of 261 consecutively admitted medical ICU patients not requiring invasive mechanical ventilation during hospitalization at a tertiary-care, university-based hospital between February 2002 and January 2003. ICU nursing staff assessed delirium and level of consciousness at least twice per day using the Confusion Assessment Method for the ICU (CAM-ICU) and Richmond Agitation-Sedation Scale (RASS). Cox regression with time-varying covariates was used to determine the independent relationship between delirium and clinical outcomes.ResultsOf 261 patients, 125 (48%) experienced at least one episode of delirium. Patients who experienced delirium were older (mean ± SD: 56 ± 18 versus 49 ± 17 years; p = 0.002) and more severely ill as measured by Acute Physiology and Chronic Health Evaluation II (APACHE II) scores (median 15, interquartile range (IQR) 10–21 versus 11, IQR 6–16; p < 0.001) compared to their non-delirious counterparts. Patients who experienced delirium had a 29% greater risk of remaining in the ICU on any given day (compared to patients who never developed delirium) even after adjusting for age, gender, race, Charlson co-morbidity score, APACHE II score, and coma (hazard ratio (HR) 1.29; 95% confidence interval (CI) 0.98–1.69, p = 0.07). Similarly, patients who experienced delirium had a 41% greater risk of remaining in the hospital after adjusting for the same covariates (HR 1.41; 95% CI 1.05–1.89, p = 0.023). Hospital mortality was higher among patients who developed delirium (24/125, 19%) versus patients who never developed delirium (8/135, 6%), p = 0.002; however, time to in-hospital death was not significant the adjusted (HR 1.27; 95% CI 0.55–2.98, p = 0.58).ConclusionDelirium occurred in nearly half of the non-ventilated ICU patients in this cohort. Even after adjustment for relevant covariates, delirium was found to be an independent predictor of longer hospital stay.

Delirium and Its Motoric Subtypes: A Study of 614 Critically Ill Patients

OBJECTIVES: To describe the motoric subtypes of delirium in critically ill patients and compare patients aged 65 and older with a younger cohort.

Adverse Drug Events Occurring Following Hospital Discharge

OBJECTIVE: To describe the incidence of adverse drug events (ADEs), preventable ADEs, and ameliorable ADEs occurring after hospital discharge and their associated risk factors.DESIGN: Prospective cohort study.SETTING: Urban academic health sciences center.PATIENTS: Consecutive patients discharged home from the general medical service.INTERVENTIONS: We determined posthospital outcomes approximately 24 days following discharge by performing a chart review and telephone interview. Using the telephone interview, we identified new or worsening symptoms, the patient’s health system use, and recollection of processes of care. Posthospital outcomes were judged by 2 internists independently.RESULTS: Four hundred of 581 potentially eligible patients were evaluated. Of the 400 patients, 45 developed an ADE (incidence, 11%; 95% confidence interval [CI], 8% to 14%). Of these, 27% were preventable and 33% were ameliorable. Injuries were significant in 32 patients, serious in 6, and life threatening in 7. Patients were less likely to experience an ADE if they recalled having side effects of prescribed medications explained (OR, 0.4; 95% CI, 0.2 to 0.8). The risk of ADE per prescription was highest for corticosteroids, anticoagulants, antibiotics, analgesics, and cardiovascular medications. Risk increased with prescription number. Failure to monitor was an especially common cause of preventable and ameliorable ADEs.CONCLUSION: Following discharge, ADEs were common and many were preventable or ameliorable. Medication side effects should be discussed, and interventions should include better monitoring and target patients receiving specific drug classes or multiple medications.

Operational Implementation of Prospective Genotyping for Personalized Medicine: The Design of the Vanderbilt PREDICT Project

The promise of “personalized medicine” guided by an understanding of each individuals genome has been fostered by increasingly powerful and economical methods to acquire clinically relevant information. We describe the operational implementation of prospective genotyping linked to an advanced clinical decision‐support system to guide individualized health care in a large academic health center. This approach to personalized medicine entails engagement between patient and health‐care provider, identification of relevant genetic variations for implementation, assay reliability, point‐of‐care decision support, and necessary institutional investments. In one year, approximately 3,000 patients, most of whom were scheduled for cardiac catheterization, were genotyped on a multiplexed platform that included genotyping for CYP2C19 variants that modulate response to the widely used antiplatelet drug clopidogrel. These data are deposited into the electronic medical record (EMR), and point‐of‐care decision support is deployed when clopidogrel is prescribed for those with variant genotypes. The establishment of programs such as this is a first step toward implementing and evaluating strategies for personalized medicine.

Large-scale implementation of sedation and delirium monitoring in the intensive care unit

Objective:To implement sedation and delirium monitoring via a process-improvement project in accordance with Society of Critical Care Medicine guidelines and to evaluate the challenges of modifying intensive care unit (ICU) organizational practice styles. Design:Prospective observational cohort study. Setting:The medical ICUs at two institutions: the Vanderbilt University Medical Center (VUMC) and a community Veterans Affairs hospital (York-VA). Subjects:Seven hundred eleven patients admitted to the medical ICUs for >24 hrs and followed over 4,163 days during a 21-month study period. Interventions:Unit-wide nursing documentation was changed to accommodate a sedation scale (Richmond Agitation-Sedation Scale) and delirium instrument (Confusion Assessment Method for the ICU). A 20-min introductory in-service was performed for all ICU nurses, followed by graded, staged educational interventions at regular intervals. Data were collected daily for compliance, and randomly 40% of nurses each day were chosen for accuracy spot-checks by reference raters. An implementation survey questionnaire was distributed at 6 months. Measurements and Main Results:The implementation project involved 64 nurses (40 at VUMC and 24 at York-VA). Sedation and delirium monitoring data were recorded for 711 patients (614 at VUMC and 97 at York-VA). Compliance with the Richmond Agitation-Sedation Scale was 94.4% (21,931 of 23,220) at VUMC and 99.7% (5,387 of 5,403) at York-VA. Compliance with the Confusion Assessment Method for the ICU was 90% (7,323 of 8,166) at VUMC and 84% (1,571 of 1,871) at York-VA. The Confusion Assessment Method for the ICU was performed more often than requested on 63% of shifts (5,146 of 8,166) at VUMC and on 8% (151 of 1871) of shifts at York-VA. Overall weighted-&kgr; between bedside nurses and references raters for the Richmond Agitation-Sedation Scale were 0.89 (95% confidence interval, 0.88 to 0.92) at VUMC and 0.77 (95% confidence interval, 0.72 to 0.83) at York-VA. Overall agreement (&kgr;) between bedside nurses and reference raters using the Confusion Assessment Method for the ICU was 0.92 (95% confidence interval, 0.90–0.94) at VUMC and 0.75 (95% confidence interval, 0.68–0.81) at York-VA. The two most-often-cited barriers to implementation were physician buy-in and time. Conclusions:With minimal training, the compliance of bedside nurses using sedation and delirium instruments was excellent. Agreement of data from bedside nurses and a reference-standard rater was very high for both the sedation scale and the delirium assessment over the duration of this process-improvement project.

Commonly used surrogates for baseline renal function affect the classification and prognosis of acute kidney injury

Studies of acute kidney injury usually lack data on pre-admission kidney function and often substitute an inpatient or imputed serum creatinine as an estimate for baseline renal function. In this study, we compared the potential error introduced by using surrogates such as (1) an estimated glomerular filtration rate of 75 ml/min per 1.73 m(2) (suggested by the Acute Dialysis Quality Initiative), (2) a minimum inpatient serum creatinine value, and (3) the first admission serum creatinine value, with values computed using pre-admission renal function. The study covered a 12-month period and included a cohort of 4863 adults admitted to the Vanderbilt University Hospital. Use of both imputed and minimum baseline serum creatinine values significantly inflated the incidence of acute kidney injury by about half, producing low specificities of 77-80%. In contrast, use of the admission serum creatinine value as baseline significantly underestimated the incidence by about a third, yielding a low sensitivity of 39%. Application of any surrogate marker led to frequent misclassification of patient deaths after acute kidney injury and differences in both in-hospital and 60-day mortality rates. Our study found that commonly used surrogates for baseline serum creatinine result in bi-directional misclassification of the incidence and prognosis of acute kidney injury in a hospital setting.

Design and anticipated outcomes of the eMERGE-PGx project: a multicenter pilot for preemptive pharmacogenomics in electronic health record systems.

We describe here the design and initial implementation of the eMERGE‐PGx project. eMERGE‐PGx, a partnership of the Electronic Medical Records and Genomics Network and the Pharmacogenomics Research Network, has three objectives: (i) to deploy PGRNseq, a next‐generation sequencing platform assessing sequence variation in 84 proposed pharmacogenes, in nearly 9,000 patients likely to be prescribed drugs of interest in a 1‐ to 3‐year time frame across several clinical sites; (ii) to integrate well‐established clinically validated pharmacogenetic genotypes into the electronic health record with associated clinical decision support and to assess process and clinical outcomes of implementation; and (iii) to develop a repository of pharmacogenetic variants of unknown significance linked to a repository of electronic health record–based clinical phenotype data for ongoing pharmacogenomics discovery. We describe site‐specific project implementation and anticipated products, including genetic variant and phenotype data repositories, novel variant association studies, clinical decision support modules, clinical and process outcomes, approaches to managing incidental findings, and patient and clinician education methods.

Clinical Pharmacogenetics Implementation Consortium (CPIC) Guidelines for CYP3A5 Genotype and Tacrolimus Dosing

Tacrolimus is the mainstay immunosuppressant drug used after solid organ and hematopoietic stem cell transplantation. Individuals who express CYP3A5 (extensive and intermediate metabolizers) generally have decreased dose‐adjusted trough concentrations of tacrolimus as compared with those who are CYP3A5 nonexpressers (poor metabolizers), possibly delaying achievement of target blood concentrations. We summarize evidence from the published literature supporting this association and provide dosing recommendations for tacrolimus based on CYP3A5 genotype when known (updates at www.pharmgkb.org).

Electronically Screening Discharge Summaries for Adverse Medical Events

Objective: Detecting adverse events is pivotal for measuring and improving medical safety, yet current techniques discourage routine screening. The authors hypothesized that discharge summaries would include information on adverse events, and they developed and evaluated an electronic method for screening medical discharge summaries for adverse events. Design: A cohort study including 424 randomly selected admissions to the medical services of an academic medical center was conducted between January and July 2000. The authors developed a computerized screening tool that searched free-text discharge summaries for trigger words representing possible adverse events. Measurements: All discharge summaries with a trigger word present underwent chart review by two independent physician reviewers. The presence of adverse events was assessed using structured implicit judgment. A random sample of discharge summaries without trigger words also was reviewed. Results: Fifty-nine percent (251 of 424) of the discharge summaries contained trigger words. Based on discharge summary review, 44.8% (327 of 730) of the alerted trigger words indicated a possible adverse event. After medical record review, the tool detected 131 adverse events. The sensitivity and specificity of the screening tool were 69% and 48%, respectively. The positive predictive value of the tool was 52%. Conclusion: Medical discharge summaries contain information regarding adverse events. Electronic screening of discharge summaries for adverse events using keyword searches is feasible but thus far has poor specificity. Nonetheless, computerized clinical narrative screening methods could potentially offer researchers and quality managers a means to routinely detect adverse events.