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Additional file 1. Summary of adjusted cohort studies and RCTs evaluating the relationship between ICU delirium and mortality and how each have each have incorporated common confounders affecting this relationship. Table comparing and contrasting previous studies evaluating association between ICU delirium and mortality, with a focus on confounder adjustment.

Additional file 4. Sensitivity analyses excluding length of stay and mechanical ventilation. Additional analyses conducted to explore the impact of mechanical ventilation and ICU length of stay as mediators or confounders.

Additional file 5. Sensitivity analyses controlling for duration of mechanical ventilation. Additional analyses conducted to look at the effect of duration of mechanical ventilation on the associations of interest.

Additional file 3. Sensitivity analyses evaluating coma occurring in the first 48 h. Previous studies have reported an association between coma occurring in the first 48 h and mortality. This table presents the results of a similar analysis within this patient population.

Additional file 2. Sensitivity analyses exploring an interaction between neurologic status and REDUCE trial arm. This table presents the results of the sensitity analyses exploring whether an interaction exists between the REDUCE trial arm and neurologic status (delirium or coma) for each of the 8 models.

Cognitive function is often impaired during hospitalization, but whether this impairment resolves or persists after discharge is unknown.We enrolled (April 2011-May 2013) and interviewed during hospitalization and 1-month post-discharge 1521 nondemented acute coronary syndrome survivors enrolled in TRACE (Transitions, Risks and Actions in Coronary Events). Cognitive function was assessed using the Telephone Interview of Cognitive Status (range: 0-41) at both time points. Patients reported demographic and psychosocial characteristics and medical records were abstracted. Using the Telephone Interview of Cognitive Status cut point of ≤28, we defined 4 groups of cognitive change based on cognitive status during hospitalization and 1 month later: consistently impaired, transiently impaired, newly impaired, and consistently nonimpaired. Characteristics associated with cognitive change categories were examined using multinomial logistic regression. Participants were 67% male, 84% non-Hispanic white, with mean age±SD 62±11 years; 16% (n=237) were cognitively impaired during hospitalization, and 11% (n=174) were impaired 1 month after discharge. Overall, 80% were consistently nonimpaired, 9% transiently impaired, 7% consistently impaired, and 4% newly impaired. Lower education level, minority status, low health literacy and numeracy, and higher severity of disease were independently associated with cognitive impairment during and after hospitalization. Male sex was associated with increased risk of cognitive impairment after hospital discharge.Cognitive function changes during the transition from hospital to home after acute coronary syndrome are less favorable for men and those with psychosocial vulnerability. Assessing cognitive status both in hospital and post-discharge is important for detecting patients who could benefit from tailored transitional care including early follow-up and booster discharge instructions.

Atrial fibrillation (AF) is one of the most common types of cardiac arrhythmia, particularly among older adults. AF confers a 5-fold risk for thromboembolic stroke as well as a 2-fold higher risk for congestive heart failure, morbidity, and mortality. Although stroke remains an important and impactful complication of AF, recent studies have shown that AF is independently associated with other neurological disorders, including cognitive impairment and dementia, even after adjusting for prior ischemic stroke. We performed a review of the published literature on the association between AF and cognitive status. Further, we reviewed studies investigating the underlying mechanisms for this association and/or reporting the impact of AF treatment on cognitive function. While most published studies demonstrate associations between AF and impaired cognition, no AF treatment has yet been associated with a reduced incidence of cognitive decline or dementia.

BackgroundAge-related dementia, most commonly caused by Alzheimer disease or cerebrovascular factors (vascular dementia), is a major public health threat. Chronic arterial hypertension is a well-established risk factor for both types of dementia, but the link between hypertension and its treatment and cognition remains poorly understood. In this scientific statement, a multidisciplinary team of experts examines the impact of hypertension on cognition to assess the state of the knowledge, to identify gaps, and to provide future directions.MethodsAuthors with relevant expertise were selected to contribute to this statement in accordance with the American Heart Association conflict-of-interest management policy. Panel members were assigned topics relevant to their areas of expertise, reviewed the literature, and summarized the available data.ResultsHypertension disrupts the structure and function of cerebral blood vessels, leads to ischemic damage of white matter regions critical for cognitive function, and may promote Alzheimer pathology. There is strong evidence of a deleterious influence of midlife hypertension on late-life cognitive function, but the cognitive impact of late-life hypertension is less clear. Observational studies demonstrated a cumulative effect of hypertension on cerebrovascular damage, but evidence from clinical trials that antihypertensive treatment improves cognition is not conclusive.ConclusionsAfter carefully reviewing the literature, the group concluded that there were insufficient data to make evidence-based recommendations. However, judicious treatment of hypertension, taking into account goals of care and individual characteristics (eg, age and comorbidities), seems justified to safeguard vascular health and, as a consequence, brain health.

To derive and validate a method for scoring delirium severity using a recently validated, brief, structured diagnostic interview for Confusion Assessment Method (CAM)-defined delirium (3D-CAM) and to demonstrate its agreement with the CAM Severity short form (CAM-S SF) as the reference standard.Derivation and validation analysis in a prospective cohort study.Two academic medical centers.Individuals aged 70 and older enrolled in the Successful Aging after Elective Surgery Study undergoing major elective noncardiac surgery (N = 566).The sample was randomly divided into a derivation dataset (n = 377) and an independent validation dataset (n = 189). These datasets were used to develop a severity scoring method using the 3D-CAM based on the four-item CAM-S SF (3D-CAM-S) and evaluate agreement between the 3D-CAM-S and the traditional CAM-S SF using weighted kappa statistics.A method for scoring severity using 3D-CAM items was developed that achieved good agreement with the CAM-S SF in the derivation dataset (κ = 0.94, 95% confidence interval (CI) = 0.93-0.95). The 3D-CAM-S achieved nearly identical agreement in the independent validation dataset (κ = 0.93, 95% CI = 0.92-0.95), and 100% of 3D-CAM-S scores were within 1 point of the CAM-S SF score in both datasets. The 3D-CAM-S also strongly predicts clinical outcomes.A newly developed method for scoring delirium severity using the 3D-CAM (the 3D-CAM-S) has excellent agreement with the CAM-S SF. This new methodology enables clinicians and researchers using the 3D-CAM for surveillance to measure delirium severity and monitor its course simultaneously by tracking changes over time. The 3D-CAM-S expands the utility of the 3D-CAM as an important tool for delirium recognition and management.

Preoperative pain and depression predispose patients to delirium. Our goal was to determine whether pain and depressive symptoms interact to increase delirium risk.We enrolled 459 persons without dementia aged ≥70 years scheduled for elective orthopedic surgery. At baseline, participants reported their worst and average pain within seven days and current pain on a 0-10 scale. Depressive symptoms were assessed using the 15-item Geriatric Depression Scale and chart. Delirium was assessed with the Confusion Assessment Method and chart. We examined the relationship between preoperative pain, depressive symptoms and delirium using multivariable analysis of pain and delirium stratified by presence of depressive symptoms.Delirium, occurring in 23% of the sample, was significantly higher in those with depressive symptoms at baseline than those without (relative risk, RR, 1·6, 95% confidence interval, CI, 1·2-2·3). Preoperative pain was associated with an increased adjusted risk for delirium across all pain measures (RR from 1·07-1·08 per point of pain). In stratified analyses, patients with depressive symptoms had a 21% increased risk for delirium for each one-point increase in worst pain score, demonstrating a significant interaction (Preoperative pain and depressive symptoms demonstrated increased risk for delirium independently and with substantial interaction, suggesting a cumulative impact. Thus, pain and depression are vulnerability factors for delirium that should be assessed before surgery.U.S. National Institute on Aging.

To identify and describe the validity of algorithms used to detect heart failure (HF) using administrative and claims data sources.A systematic review of PubMed and Iowa Drug Information Service searches of the English language was performed to identify studies published between 1990 and 2010 that evaluated the validity of algorithms for the identification of patients with HF using and claims data. Abstracts and articles were reviewed by two study investigators to determine their relevance on the basis of predetermined criteria.The initial search strategy identified 887 abstracts. Of these, 499 full articles were reviewed and 35 studies included data to evaluate the validity of identifying patients with HF. Positive predictive values (PPVs) were in the acceptable to high range, with most being very high (90%). Studies that included patients with a primary hospital discharge diagnosis of International Classification of Diseases, Ninth Revision, code 428.X had the highest PPV and specificity for HF. PPVs for this algorithm ranged from 84% to 100%. This algorithm, however, may compromise sensitivity because many HF patients are managed on an outpatient basis. The most common 'gold standard' for the validation of HF was the Framingham Heart Study criteria.The algorithms and definitions used to identify HF using administrative and claims data perform well, particularly when using a primary hospital discharge diagnosis. Attention should be paid to whether patients who are managed on an outpatient basis are included in the study sample. Including outpatient codes in the described algorithms would increase the sensitivity for identifying new cases of HF.

To perform a systematic review of the validity of algorithms for identifying cerebrovascular accidents (CVAs) or transient ischemic attacks (TIAs) using administrative and claims data.PubMed and Iowa Drug Information Service searches of the English language literature were performed to identify studies published between 1990 and 2010 that evaluated the validity of algorithms for identifying CVAs (ischemic and hemorrhagic strokes, intracranial hemorrhage, and subarachnoid hemorrhage) and/or TIAs in administrative data. Two study investigators independently reviewed the abstracts and articles to determine relevant studies according to pre-specified criteria.A total of 35 articles met the criteria for evaluation. Of these, 26 articles provided data to evaluate the validity of stroke, seven reported the validity of TIA, five reported the validity of intracranial bleeds (intracerebral hemorrhage and subarachnoid hemorrhage), and 10 studies reported the validity of algorithms to identify the composite endpoints of stroke/TIA or cerebrovascular disease. Positive predictive values (PPVs) varied depending on the specific outcomes and algorithms evaluated. Specific algorithms to evaluate the presence of stroke and intracranial bleeds were found to have high PPVs (80% or greater). Algorithms to evaluate TIAs in adult populations were generally found to have PPVs of 70% or greater.The algorithms and definitions to identify CVAs and TIAs using administrative and claims data differ greatly in the published literature. The choice of the algorithm employed should be determined by the stroke subtype of interest.