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Pulmonary disease prevalence increases with age and contributes to morbidity and mortality in older patients. Dyspnea in older patients is often ascribed to multiple etiologies such as medical comorbidities and deconditioning. Common pulmonary disorders are frequently overlooked as contributors to dyspnea in older patients. In addition to negative impacts on morbidity and mortality, quality of life is reduced in older patients with uncontrolled, undertreated pulmonary symptoms. The purpose of this review is to discuss the epidemiology of common pulmonary diseases, namely pneumonia, chronic obstructive pulmonary disease, asthma, lung cancer, and idiopathic pulmonary fibrosis in older patients. We will review common clinical presentations for these diseases and highlight differences between younger and older patients. We will also briefly discuss risk factors, treatment, and mortality associated with these diseases. Finally, we will address the relationship between comorbidities, pulmonary symptoms, and quality of life in older patients with pulmonary diseases. [ABSTRACT FROM PUBLISHER]

Introduction: We assessed smoking data from the Veterans Health Administration (VHA) electronic medical record (EMR) Health Factors dataset.Methods: To assess the validity of the EMR Health Factors smoking data, we first created an algorithm to convert text entries into a 3-category smoking variable (never, former, and current). We compared this EMR smoking variable to 2 different sources of patient self-reported smoking survey data: (a) 6,816 HIV-infected and -uninfected participants in the 8-site Veterans Aging Cohort Study (VACS-8) and (b) a subset of 13,689 participants from the national VACS Virtual Cohort (VACS-VC), who also completed the 1999 Large Health Study (LHS) survey. Sensitivity, specificity, and kappa statistics were used to evaluate agreement of EMR Health Factors smoking data with self-report smoking data.Results: For the EMR Health Factors and VACS-8 comparison of current, former, and never smoking categories, the kappa statistic was .66. For EMR Health Factors and VACS-VC/LHS comparison of smoking, the kappa statistic was .61.Conclusions: Based on kappa statistics, agreement between the EMR Health Factors and survey sources is substantial. Identification of current smokers nationally within the VHA can be used in future studies to track smoking status over time, to evaluate smoking interventions, and to adjust for smoking status in research. Our methodology may provide insights for other organizations seeking to use EMR data for accurate determination of smoking status. [ABSTRACT FROM AUTHOR]

With the introduction of highly active antiretroviral therapy (HAART), HIV has become a chronic disease. As HIV-infected patients are aging, they are at increased risk for comorbid diseases. These non-AIDS related diseases account for a growing proportion of intensive care unit (ICU) admissions in HIV-infected patients in recent studies. HIV-infected patients still present to the ICU with HIV-related conditions such as Pneumocystis jirovecii pneumonia (PCP), but these conditions are becoming less common. Respiratory failure remains the most common indication for ICU admission. Immune reconstitution inflammatory response syndrome and toxicities related to HAART may also result in ICU admission. While ICU survival has improved since the earliest era of the HIV epidemic, hospital mortality for HIV-infected patients admitted to the ICU remains around 30%. Risk factors for ICU mortality include poor functional status, weight loss, more than one year between HIV diagnosis and ICU admission, lower serum albumin, higher severity of illness, need for mechanical ventilation, and respiratory failure-particularly if due to PCP and accompanied by pneumothorax. The impact of HAART on ICU outcomes is unclear. HAART administration in the ICU can be challenging due to limited delivery routes, concern for viral resistance and medication toxicities. There are no data to determine the safety or efficacy of HAART initiation in the ICU. Future studies are needed to address the role of age, associated comorbidities and impact of HAART on outcomes of HIV-infected patients admitted to the ICU [ABSTRACT FROM PUBLISHER]

People over age 65 are the fastest growing segment of the population and account for 42% to 52% of the intensive care unit admissions in the United States. There are many physiologic changes that occur with aging which can impact on both the presentation and management of older patients with critical illness. Older patients have an increased risk for the development of sepsis, and age itself impacts on outcomes related to sepsis. Delirium is also very prevalent among older intensive care unit patients and is associated with adverse outcomes. While outcome studies suggest that chronologic age itself is not a risk factor for poor outcomes after adjusting for severity of illness, older patients clearly have physiologic changes which need to be considered when providing critical care. This article will review important physiologic changes of aging, as well as sepsis and delirium and outcomes of older ICU patients. [ABSTRACT FROM AUTHOR]

Introduction: Delirium is a serious and prevalent problem in intensive care units (ICUs). The purpose of this study was to develop a research algorithm to enhance detection of delirium in critically ill ICU patients using chart review to complement a validated clinical delirium instrument. Methods: A prospective cohort study was conducted in 178 patients aged 60 years and older who were admitted to the medical ICU. The Confusion Assessment Method for the ICU (CAM-ICU) and a validated chart review method for detecting delirium were performed daily. We assessed the diagnostic accuracy of the chart-based delirium method using the CAM-ICU as the 'gold standard'. We then used an algorithm to detect delirium first using the CAM-ICU ratings and then chart review when the CAM-ICU was unavailable. Results: When using both the CAM-ICU and the chart-based review, the prevalence of delirium was found to be 80% of patients (143 out of 178) or 64% of patient-days (929 out of 1,457). Of these patient-days, 292 were classified as delirium by the CAM-ICU. The remainder (637 patient-days) were classified as delirium by the validated chart review method when CAM-ICU was missing because the assessment was conducted for weekends or holidays (404 patient-days), when CAM-ICU was not performed because of stupor or coma (205 patient-days), and when the CAM-ICU was negative (28 patient-days). Sensitivity of the chart-based method was 64% and specificity was 85%. Overall agreement between chart and the CAM-ICU was 72%. Conclusion: Eight out of 10 patients in this cohort study developed delirium in the ICU. Although use of a validated delirium instrument with frequent direct observations is recommended for clinical care, this approach may not always be feasible, especially in a research setting. The algorithm proposed here comprises a more comprehensive method for detecting delirium in a research setting, taking into account the fluctuation that occurs with delirium, which is a key component of accurate determination of delirium status. Improving detection of delirium is of paramount importance both to advance delirium research and to enhance clinical care and patient safety.

Background: In medical intensive care unit (MICU) patients, the predictors of post-discharge sleep disturbance and functional disability are poorly understood. ICU delirium is a risk factor with a plausible link to sleep disturbance and disability. This study evaluated the prevalence of self-reported post-ICU sleep disturbance and increased functional disability, and their association with MICU delirium and other ICU factors.Methods: This was an observational cohort study of MICU patients enrolled in a biorepository and assessed upon MICU admission by demographics, comorbidities, and baseline characteristics. Delirium was assessed daily using the Confusion Assessment Method for the ICU. Telephone follow-up interview instruments occurred after hospital discharge and included the Pittsburgh Sleep Quality Index (PSQI), and basic and instrumental activities of daily living (BADLs, IADLs) for disability. We define sleep disturbance as a PSQI score > 5 and increased disability as an increase in composite BADL/IADL score at follow-up relative to baseline. Multivariable regression modeled the associations of delirium and other MICU factors on follow-up PSQI scores and change in disability scores.Results: PSQI and BADL/IADL instruments were completed by 112 and 122 participants, respectively, at mean 147 days after hospital discharge. Of those surveyed, 63% had sleep disturbance by PSQI criteria, and 37% had increased disability by BADL/IADL scores compared to their pre-MICU baseline. Total days of MICU delirium (p = 0.013), younger age (p = 0.013), and preexisting depression (p = 0.025) were significantly associated with higher PSQI scores at follow-up. Lower baseline disability (p < 0.001), older age (p = 0.048), and less time to follow-up (p = 0.024) were significantly associated with worsening post-ICU disability, while the occurrence of MICU delirium showed a trend toward association (p = 0.077).Conclusions: After adjusting for important covariates, total days of MICU delirium were significantly associated with increased post-discharge sleep disturbance. Delirium incidence showed a trend toward association with increased functional disability in the year following discharge. [ABSTRACT FROM AUTHOR]

The authors discuss the study "Incidence and short-term consequences of delirium in critically ill patients: a prospective observational cohort study" by M. van den Boogaard and colleagues, which found that screening methods can detect delirium, associated with adverse outcomes, in critical patients. They state that the study highlights the differences in delirium between intensive care unit (ICU) patient subgroups and the need for studies on delirium prevention and reducing delirium duration.

Background: Professional society guidelines recommend limiting the use of antipsychotics in older patients with postoperative delirium. How these recommendations affected the use of antipsychotics and other psychoactive drugs in the postoperative period has not been studied. Methods: This retrospective cohort study included patients 65 years or older without psychiatric diagnoses who underwent major surgery in community hospitals (CHs) and academic medical centers (AMCs) in the United States. The outcome was the rate of hospital days exposed to antipsychotics, antidepressants, antiepileptics, benzodiazepines, hypnotics, and selective alpha‐2 receptor agonist dexmedetomidine in the postoperative period by hospital type. Results: The study included 4,098,431 surgical admissions from CHs (mean age 75.0 [standard deviation, 7.1] years; 50.8% female) during 2008–2018 and 2,310,529 surgical admissions from AMCs (75.0 [7.4] years; 49.4% female) during 2009–2018. In the intensive care unit (ICU) setting, the number of exposed days per 1000 hospital‐days declined for haloperidol (CHs: 33–21 days [p < 0.01]; AMCs: 24–15 days [p < 0.01]) and benzodiazepines (CHs: 261–136 days [p < 0.01]; AMCs: 150–77 days [p < 0.01]). The use of atypical antipsychotics, antidepressants, antiepileptics, and dexmedetomidine increased, while hypnotic use varied by the hospital type. In the non‐ICU setting, the rate declined for haloperidol in CHs but not in AMCs (CHs: 10–6 days [p < 0.01]; AMCs: 4–3 days [p = 0.52]) and for benzodiazepines in both settings (CHs: 126–56 days [p < 0.01]; AMCs: 30–27 days [p < 0.01]). The use of antiepileptics and antidepressants increased, while the use of atypical antipsychotics and hypnotics varied by the hospital type. Conclusions: The use of haloperidol and benzodiazepines in the postoperative period declined at both CHs and AMCs. These trends coincided with the increasing use of other psychoactive drugs. [ABSTRACT FROM AUTHOR]

The article discusses how the 3-D CAM (computer-aided manufacturing) provides easy to use, specific delirium assessment tool for older hospitalised patients, with and without dementia. Topics discussed include in-depth patient assessment to serve as the reference standard for delirium detection, assessment of inter-rater reliability on 50 percent of participants, which was found to be excellent with 95 percent, and research priority to validate 3D-CAM in critically ill patients.

Antipsychotics are commonly used to manage postoperative delirium. Recent studies reported that haloperidol use has decreased and atypical antipsychotic use has increased over time. This study compared the risk for in-hospital adverse events associated with use of oral haloperidol versus atypical agents, including olanzapine, quetiapine, and risperidone, in older patients after major surgery. Visual Abstract. Comparative Safety Analysis of Oral Antipsychotics for In-Hospital Adverse Clinical Events in Older Adults After Major Surgery: Antipsychotics are commonly used to manage postoperative delirium. Recent studies reported that haloperidol use has decreased and atypical antipsychotic use has increased over time. This study compared the risk for in-hospital adverse events associated with use of oral haloperidol versus atypical agents, including olanzapine, quetiapine, and risperidone, in older patients after major surgery. Background: Antipsychotics are commonly used to manage postoperative delirium. Recent studies reported that haloperidol use has declined, and atypical antipsychotic use has increased over time. Objective: To compare the risk for in-hospital adverse events associated with oral haloperidol, olanzapine, quetiapine, and risperidone in older patients after major surgery. Design: Retrospective cohort study. Setting: U.S. hospitals in the Premier Healthcare Database. Patients: 17 115 patients aged 65 years and older without psychiatric disorders who were prescribed an oral antipsychotic drug after major surgery from 2009 to 2018. Interventions: Haloperidol (≤4 mg on the day of initiation), olanzapine (≤10 mg), quetiapine (≤150 mg), and risperidone (≤4 mg). Measurements: The risk ratios (RRs) for in-hospital death, cardiac arrhythmia events, pneumonia, and stroke or transient ischemic attack (TIA) were estimated after propensity score overlap weighting. Results: The weighted population had a mean age of 79.6 years, was 60.5% female, and had in-hospital death of 3.1%. Among the 4 antipsychotics, quetiapine was the most prescribed (53.0% of total exposure). There was no statistically significant difference in the risk for in-hospital death among patients treated with haloperidol (3.7%, reference group), olanzapine (2.8%; RR, 0.74 [95% CI, 0.42 to 1.27]), quetiapine (2.6%; RR, 0.70 [CI, 0.47 to 1.04]), and risperidone (3.3%; RR, 0.90 [CI, 0.53 to 1.41]). The risk for nonfatal clinical events ranged from 2.0% to 2.6% for a cardiac arrhythmia event, 4.2% to 4.6% for pneumonia, and 0.6% to 1.2% for stroke or TIA, with no statistically significant differences by treatment group. Limitation: Residual confounding by delirium severity; lack of untreated group; restriction to oral low-to-moderate dose treatment. Conclusion: These results suggest that atypical antipsychotics and haloperidol have similar rates of in-hospital adverse clinical events in older patients with postoperative delirium who receive an oral low-to-moderate dose antipsychotic drug. Primary Funding Source: National Institute on Aging. [ABSTRACT FROM AUTHOR]

Background: People aging with and without HIV (PWH and PWoH) want to avoid neurocognitive dysfunction, especially delirium. Continued use of alcohol in conjunction with neurocognitively active medications (NCAMs) may be a largely underappreciated cause, especially for PWH who experience polypharmacy a decade earlier than PWoH. We compare absolute and relative risk of delirium among PWH and PWoH by age, level of alcohol use, and exposure to NCAMs. Methods: Using the VACS cohort, we compare absolute and relative risk of inpatient delirium among PWH and PWoH by age, level of alcohol use, and exposure to NCAMs between 2007 and 2019. We matched each case based on age, race/ethnicity, sex, HIV, baseline year, and observation time with up to 5 controls. The case/control date was defined as date of admission for cases and the date corresponding to the same length of time on study for controls. Level of alcohol use was defined using Alcohol Use Disorder Identification Test–Consumption (AUDIT‐C). Medication exposure was measured from 45 to 3 days prior to index date; medications were classified as anticholinergic NCAM, non‐anticholinergic NCAM, or non NCAM and counts generated. We used logistic regression to determine odds ratios (ORs) for delirium associated with medication counts stratified by HIV status and adjusted for demographics, severity of illness, and related diagnoses. Results: PWH experienced a higher incidence of delirium (5.6, [95% CI 5.3–5.9/1000 PY]) than PWoH (5.0, [95% CI 4.8–5.1/1000 PY]). In multivariable analysis, anticholinergic and non‐anticholinergic NCAM counts and level of alcohol use demonstrated strong independent dose–response associations with delirium. Conclusions: Decreasing alcohol use and limiting the use of neurocognitively active medications may help decrease excess rates of delirium, especially among PWH. [ABSTRACT FROM AUTHOR]

Purpose: This study was designed to identify factors associated with persistent delirium in an older medical intensive care unit (ICU) population. Materials and Methods: This is a prospective cohort study of 309 consecutive medical ICU patients 60 years or older. Persistent delirium was defined as delirium occurring in the ICU and continuing upon discharge to the ward. The Confusion Assessment Method was used to assess for delirium. Patient demographics, severity of illness, and medication data were collected. Univariate and multivariate analysis were used to assess factors associated with persistent delirium. Results: Of 309 consecutive admissions to the ICU, 173 patients had ICU delirium, survived the ICU stay, and provided ward data. One-hundred patients (58%) had persistent delirium. In a multivariable logistic regression model, factors significantly associated with persistent delirium included age more than 75 years (odds ratio [OR], 2.52; 95% confidence interval [CI], 1.23-5.16), opioid (morphine equivalent) dose greater than 54 mg/d (OR, 2.90; 95% CI, 1.15-7.28), and haloperidol (OR, 2.88; 95% CI, 1.38-6.02); change in code status to “do not resuscitate” (OR, 2.62; 95% CI 0.95-7.35) and dementia (OR, 1.93; 95% CI 0.95-3.93) had less precise associations. Conclusions: Age, use of opioids, and haloperidol were associated with persistent delirium. Further research is needed regarding the use of haloperidol and opioids on persistent delirium. [Copyright &y& Elsevier]

Background Nicotine replacement therapy, bupropion, and varenicline are smoking cessation medications (SCMs) shown to be similarly effective in people with and without human immunodeficiency virus (PWH and PWoH, respectively), although rates of receipt of these medications are unknown. Methods We identified patients in the Veterans Aging Cohort Study with electronic health record-documented current smoking using clinical reminder data for tobacco use (2003–2018). We measured receipt of SCMs using Veterans Affairs pharmacy data for outpatient prescriptions filled 0–365 days after current smoking documentation. We used log-linear, Poisson-modified regression models to evaluate the relative risk (RR) for receiving SCM by human immunodeficiency virus (HIV) status, the annual rate of receipt, and rate difference among PWH relative to PWoH. Results The sample included 92 632 patients (29 086 PWH), reflecting 381 637 documentations of current smoking. From 2003 to 2018, the proportion receiving SCMs increased from 15% to 34% for PWH and from 17% to 32% among PWoH. There was no statistical difference in likelihood of receiving SCM by HIV status (RR, 1.010; 95% confidence interval [CI],.994–1.026). Annual rates of receiving SCM increased for PWH by 4.3% per year (RR, 1.043; 95% CI, 1.040–1.047) and for PWoH by 3.7% per year (RR, 1.037; 95% CI, 1.036–1.038; rate difference +0.6% [RR, 1.006; 95% CI, 1.004–1.009]). Conclusions In a national sample of current smokers, receipt of SCM doubled over the 16-year period, and differences by HIV status were modest. However, fewer than 35% of current smokers receive SCM annually. Efforts to improve SCM receipt should continue for both groups given the known dangers of smoking. [ABSTRACT FROM AUTHOR]

Background: The ability to determine which episodes of delirium are likely to lead to poor clinical outcomes has remained a major area of challenge.Objective: To quantify delirium severity and course over an entire hospitalization using several measures, and to evaluate their predictive validity for 30- and 90-day outcomes post-discharge.Design: Two prospective cohort studies.Participants: Analysis was conducted in two independent cohorts of adult patients aged ≥70.Main Measures: Nine delirium episode severity measures were examined: (1) measures reflecting delirium intensity (peak Confusion Assessment Method-Severity [CAM-S] and mean CAM-S score), (2) a measure reflecting delirium intensity and duration (sum of all CAM-S scores, sum of all CAM-S scores on delirium days only, peak CAM-S score x days with delirium), (3) measures requiring information on delirium duration and delirium at discharge (total number of delirium days, percentage of delirium days, delirium at discharge), and (4) a measure of cognitive change. Associations of the delirium episode severity measures with 30- and 90-day post-hospital outcomes (death, nursing home placement, and readmission) relevant to delirium were examined.Key Results: The delirium episode severity measure that required information on both delirium intensity and duration (sum of all CAM-S scores) was the most strongly associated with 30- and 90-day post-hospital outcomes. Using this measure, the relative risk [95 % confidence interval] for death at 30-days increased across levels of sum of all CAM-S scores from 1.0 (referent) to 2.1 [0.8, 5.4] for 'low,' to 2.9 [1.2, 7.1] for 'moderate,' to 6.4 [2.9, 14.0] for 'high' (p for trend <.01).Conclusions: The delirium episode severity measure that included both intensity and duration had the strongest association with important post-hospital outcomes. [ABSTRACT FROM AUTHOR]

There is now ample evidence that differences in sex and gender contribute to the incidence, susceptibility, presentation, diagnosis, and clinical course of many lung diseases. Some conditions are more prevalent in women, such as pulmonary arterial hypertension and sarcoidosis. Some life stages-such as pregnancy-are unique to women and can affect the onset and course of lung disease. Clinical presentation may differ as well, such as the higher number of exacerbations experienced by women with cystic fibrosis (CF), more fatigue in women with sarcoidosis, and more difficulty in achieving smoking cessation. Outcomes such as mortality may be different as well, as indicated by the higher mortality in women with CF. In addition, response to therapy and medication safety may also differ by sex, and yet, pharmacogenomic factors are often not adequately addressed in clinical trials. Various aspects of lung/sleep biology and pathobiology are impacted by female sex and female reproductive transitions. Differential gene expression or organ development can be impacted by these biological differences. Understanding these differences is the first step in moving toward precision medicine for all patients. This article is the second part of a state-of-the-art review of specific effects of sex and gender focused on epidemiology, disease presentation, risk factors, and management of selected lung diseases. We review the more recent literature and focus on guidelines incorporating sex and gender differences in pulmonary hypertension, CF and non-CF bronchiectasis, sarcoidosis, restless legs syndrome and insomnia, and critical illness. We also provide a summary of the effects of pregnancy on lung diseases and discuss the impact of sex and gender on tobacco use and treatment of nicotine use disorder. [ABSTRACT FROM AUTHOR]

Background: Critical illness often leads to persistent functional impairment among older Intensive Care Unit (ICU) survivors. Identification of high‐risk survivors prior to discharge from their ICU hospitalization can facilitate targeting for restorative interventions after discharge, potentially improving the likelihood of functional recovery. Our objective was to develop and validate a prediction model for persistent functional impairment among older adults in the year after an ICU hospitalization. Methods: The analytic sample included community‐living participants enrolled in the National Health and Aging Trends Study 2011 cohort who survived an ICU hospitalization through December 2017 and had a follow‐up interview within 1 year. Persistent functional impairment was defined as failure to recover to the pre‐ICU level of function within 12 months of discharge from an ICU hospitalization. We used Bayesian model averaging to identify the final predictors from a comprehensive set of 17 factors. Discrimination and calibration were assessed using area‐under‐the‐curve (AUC) and calibration plots. Results: The development cohort included 456 ICU admissions (2,654,685 survey‐weighted admissions) and the validation cohort included 227 ICU admissions (1,350,082 survey‐weighted admissions). In the development cohort, the median age was 81.0 years (interquartile range [IQR] 76.0, 86.0) and 231 (50.7%) participants were women; demographic characteristics were comparable in the validation cohort. The rates of persistent functional impairment were 49.3% (development) and 50.2% (validation). The final model included age, pre‐ICU disability, probable dementia, frailty, prior hospitalizations, vision impairment, depressive symptoms, and hospital length of stay. The model demonstrated good discrimination (AUC 71%, 95% confidence interval [CI] 0.66–0.76) and good calibration. When applied to the validation cohort, the model demonstrated comparable discrimination (AUC 72%, 95% CI 0.66–0.78) and good calibration. Conclusions: Application of the model prior to discharge from an ICU hospitalization may identify older adults at the highest risk of persistent functional impairment in the subsequent year, thereby facilitating targeted interventions and follow‐up. [ABSTRACT FROM AUTHOR]

Objective: Medical intensive care unit (MICU) admissions have been declining in people with HIV infection (PWH), but frequency of outpatient polypharmacy (prescription of ≥5 chronic medications) has increased. Among those hospitalized, we examined whether outpatient polypharmacy is associated with subsequent 1-year MICU admission or 10-year all-cause mortality, and if the association varies by HIV status. Design: Retrospective cohort study. Methods: Using a national electronic health record cohort of Veterans in care, we ascertained outpatient polypharmacy during fiscal year (FY) 2009 and followed patients for 1-year MICU admission and 10-year mortality. We assessed associations of any polypharmacy (yes/no and categorized ≤4, 5–7, 8–9, and ≥10 medications) with 1-year MICU admission and 10-year mortality using logistic and Cox regressions, respectively, adjusted for demographics, HIV status, substance use, and severity of illness. Results: Among 9898 patients (1811 PWH) hospitalized in FY2010, prior outpatient polypharmacy was common (51%). Within 1 year, 1532 (15%) had a MICU admission and within 10 years, 4585 (46%) died. Polypharmacy was associated with increased odds of 1-year MICU admission, in both unadjusted (odds ratio (OR) 1.36 95% CI: (1.22, 1.52)) and adjusted models, aOR (95% CI) = 1.28 (1.14, 1.43) and with 10-year mortality in unadjusted, hazard ratio (HR) (95% CI) = 1.40 (1.32, 1.48), and adjusted models, HR (95% CI) = 1.26 (1.19, 1.34). Increasing levels of polypharmacy demonstrated a dose-response with both outcomes and by HIV status, with a stronger association among PWH. Conclusions: Among hospitalized patients, prior outpatient polypharmacy was associated with 1-year MICU admission and 10-year all-cause mortality after adjusting for severity of illness in PWH and PWoH. [ABSTRACT FROM AUTHOR]

Purpose: The aim of this Intensive Care Medicine Rapid Practice Guideline (ICM‑RPG) was to formulate evidence‑based guidance for the use of dexmedetomidine for sedation in invasively mechanically ventilated adults in the intensive care unit (ICU). Methods: We adhered to the methodology for trustworthy clinical practice guidelines, including use of the Grading of Recommendations Assessment, Development, and Evaluation approach to assess the certainty of evidence, and the Evidence-to-Decision framework to generate recommendations. The guideline panel comprised 28 international panelists, including content experts, ICU clinicians, methodologists, and patient representatives. Through teleconferences and web‑based discussions, the panel provided input on the balance and magnitude of the desirable and undesirable effects, the certainty of evidence, patients' values and preferences, costs and resources, feasibility, acceptability, and research priorities. Results: The ICM‑RPG panel issued one weak recommendation (suggestion) based on overall moderate certainty of evidence: "In invasively mechanically ventilated adult ICU patients, we suggest using dexmedetomidine over other sedative agents, if the desirable effects including a reduction in delirium are valued over the undesirable effects including an increase in hypotension and bradycardia". Conclusion: This ICM-RPG provides updated evidence-based guidance on the use of dexmedetomidine for sedation in mechanically ventilated adults, and outlines uncertainties and research priorities. [ABSTRACT FROM AUTHOR]

• Cosinor analysis allows for the fitting of a cosine curve to data of known period and is frequently used in the analysis of circadian rhythm. • Parameters estimated by the model include time of minimum and maximum, curve amplitude and rhythm adjusted mean. • We are not aware of any published SAS procedures or macros which would facilitate these analyses. • To meet this gap, we describe a SAS macro which performs cosinor analyses and demonstrate the use of this macro with data from our research. Cosinor analysis, developed by Franz Hallberg and colleagues in the 1960s, allows for the fitting of a cosine curve to data of a known period. Cosinor analysis is frequently used in the analysis of biological rhythm data. While software exists to perform these analyses, we are not aware of any published SAS procedures or macros which would facilitate them. To meet this gap, we herein describe SAS macros which perform cosinor analyses that assume either normally or gamma distributed outcomes and fixed period. The macros can 1) produce datasets with cosinor parameters including acrophase, mesor, amplitude, nadir and test for rhythmicity 2) output datasets with fitted and observed values from the model, and 3) plot the resulting curve and underlying data. We demonstrate the use of these macros with data from our research on circadian rhythms of heart rate and sleep in critically ill patients. Cosinor analysis provides a parsimonious and intuitive set of estimates to summarize periodic data. We are hopeful that the publication of our macro will allow a wider spectrum of users to avail themselves of this technique. [ABSTRACT FROM AUTHOR]

The cosinor model, in which a cosine curve is fitted to periodic data within a regression model, is a frequently used method for describing patterns of cyclical activity such as circadian rhythms. For circadian variables of interest (eg, melatonin and heart rate) that do not take on negative values, the assumption of normally distributed residuals required by the general linear model, which is most commonly used for cosinor analysis, may not be appropriate. Alternatively, a generalized linear model with the gamma distribution (GZLM-gamma) is specifically defined to accommodate non-negative outcomes. Herein, we demonstrate the improved fit and gains of efficiency in detection of circadian rhythm afforded by using the GZLM-gamma in cosinor models of heart rate, actigraphic activity, and urinary 6-sulfatoxymelatonin. Notably, this improved detection of circadian rhythm allows retention of additional patients for downstream analyses, further improving study power. [ABSTRACT FROM AUTHOR]

Purpose: Our purpose was to create a content domain framework for delirium severity to inform item development for a new instrument to measure delirium severity.Methods: We used an established, multi-stage instrument development process during which expert panelists discussed best approaches to measure delirium severity and identified related content domains. We conducted this work as part of the Better ASsessment of ILlness (BASIL) study, a prospective, observational study aimed at developing and testing measures of delirium severity. Our interdisciplinary expert panel consisted of twelve national delirium experts and four expert members of the core research group. Over a one-month period, experts participated in two rounds of review.Results: Experts recommended that the construct of delirium severity should reflect both the phenomena and the impact of delirium to create an accurate, patient-centered instrument useful to interdisciplinary clinicians and family caregivers. Final content domains were Cognitive, Level of consciousness, Inattention, Psychiatric-Behavioral, Emotional dysregulation, Psychomotor features, and Functional. Themes debated by experts included reconciling clinical geriatrics and psychiatric content, mapping symptoms to one specific domain, and accurate capture of unclear clinical presentations.Conclusions: We believe this work represents the first application of instrument development science to delirium. The identified content domains are inclusive of various, wide-ranging domains of delirium severity and are reflective of a consistent framework that relates delirium severity to potential clinical outcomes. Our content domain framework provides a foundation for development of delirium severity instruments that can help improve care and quality of life for patients with delirium. [ABSTRACT FROM AUTHOR]