A Mediation Analysis Examining High Risk, Anticholinergic Medication Use, Delirium, and Dementia After Major Surgery.

INTRODUCTION: Anticholinergic medications are known to cause adverse cognitive effects in community-dwelling older adults and medical inpatients, including dementia. The prevalence with which such medications are prescribed in older adults undergoing major surgery is not well described nor is their mediating relationship with delirium and dementia. We sought to determine the prevalence of high-risk medication use in major surgery patients and their relationship with the subsequent development of dementia. METHODS: This was a retrospective cohort study which used data between January 2013 and December 2019, in a large midwestern health system, including sixteen hospitals. All patients over age 50 undergoing surgery requiring an inpatient stay were included. The primary exposure was the number of doses of anticholinergic medications delivered during the hospital stay. The primary outcome was a new diagnosis of Alzheimer's disease and related dementias at 1-y postsurgery. Regression methods and a mediation analysis were used to explore relationships between anticholinergic medication usage, delirium, and dementia. RESULTS: There were 39,665 patients included, with a median age of 66. Most patients were exposed to anticholinergic medications (35,957/39,665; 91%), and 7588/39,665 (19.1%) patients received six or more doses during their hospital stay. Patients with at least six doses of these medications were more likely to be female, black, and with a lower American Society of Anesthesiologists class. Upon adjusted analysis, high doses of anticholinergic medications were associated with increased odds of dementia at 1 y relative to those with no exposure (odds ratio 2.7; 95% confidence interval 2.2-3.3). On mediation analysis, postoperative delirium mediated the effect of anticholinergic medications on dementia, explaining an estimated 57.6% of their association. CONCLUSIONS: High doses of anticholinergic medications are common in major surgery patients and, in part via a mediating relationship with postoperative delirium, are associated with the development of dementia 1 y following surgery. Strategies to decrease the use of these medications and encourage the use of alternatives may improve long-term cognitive recovery.

Applied Artificial Intelligence in Healthcare: A Review of Computer Vision Technology Application in Hospital Settings.

Computer vision (CV), a type of artificial intelligence (AI) that uses digital videos or a sequence of images to recognize content, has been used extensively across industries in recent years. However, in the healthcare industry, its applications are limited by factors like privacy, safety, and ethical concerns. Despite this, CV has the potential to improve patient monitoring, and system efficiencies, while reducing workload. In contrast to previous reviews, we focus on the end-user applications of CV. First, we briefly review and categorize CV applications in other industries (job enhancement, surveillance and monitoring, automation, and augmented reality). We then review the developments of CV in the hospital setting, outpatient, and community settings. The recent advances in monitoring delirium, pain and sedation, patient deterioration, mechanical ventilation, mobility, patient safety, surgical applications, quantification of workload in the hospital, and monitoring for patient events outside the hospital are highlighted. To identify opportunities for future applications, we also completed journey mapping at different system levels. Lastly, we discuss the privacy, safety, and ethical considerations associated with CV and outline processes in algorithm development and testing that limit CV expansion in healthcare. This comprehensive review highlights CV applications and ideas for its expanded use in healthcare.

Advancing specificity in delirium: The delirium subtyping initiative.

BACKGROUND: Delirium, a common syndrome with heterogeneous etiologies and clinical presentations, is associated with poor long-term outcomes. Recording and analyzing all delirium equally could be hindering the field's understanding of pathophysiology and identification of targeted treatments. Current delirium subtyping methods reflect clinically evident features but likely do not account for underlying biology. METHODS: The Delirium Subtyping Initiative (DSI) held three sessions with an international panel of 25 experts. RESULTS: Meeting participants suggest further characterization of delirium features to complement the existing Diagnostic and Statistical Manual of Mental Disorders Fifth Edition Text Revision diagnostic criteria. These should span the range of delirium-spectrum syndromes and be measured consistently across studies. Clinical features should be recorded in conjunction with biospecimen collection, where feasible, in a standardized way, to determine temporal associations of biology coincident with clinical fluctuations. DISCUSSION: The DSI made recommendations spanning the breadth of delirium research including clinical features, study planning, data collection, and data analysis for characterization of candidate delirium subtypes. HIGHLIGHTS: Delirium features must be clearly defined, standardized, and operationalized. Large datasets incorporating both clinical and biomarker variables should be analyzed together. Delirium screening should incorporate communication and reasoning.

Serum proteomic analysis in esophagectomy patients with postoperative delirium: A case-control study.

BACKGROUND: Postoperative delirium occurs in up to 80% of patients undergoing esophagectomy. We performed an exploratory proteomic analysis to identify protein pathways that may be associated with delirium post-esophagectomy. OBJECTIVES: Identify proteins associated with delirium and delirium severity in a younger and higher-risk surgical population. METHODS: We performed a case-control study using blood samples collected from patients enrolled in a negative, randomized, double-blind clinical trial. English speaking adults aged 18 years or older, undergoing esophagectomy, who had blood samples obtained were included. Cases were defined by a positive delirium screen after surgery while controls were patients with negative delirium assessments. Delirium was assessed using Richmond Agitation Sedation Scale and Confusion Assessment Method for the Intensive Care Unit, and delirium severity was assessed by Delirium Rating Scale-Revised-98. Blood samples were collected pre-operatively and on post-operative day 1, and discovery proteomic analysis was performed. Between-group differences in median abundance ratios were reported using Wilcoxon-Mann-Whitney Odds (WMWodds1) test. RESULTS: 52 (26 cases, 26 controls) patients were included in the study with a mean age of 64 (SD 9.6) years, 1.9% were females and 25% were African American. The median duration of delirium was 1 day (IQR: 1-2), and the median delirium/coma duration was 2.5 days (IQR: 2-4). Two proteins with greater relative abundance ratio in patients with delirium were: Coagulation factor IX (WMWodds: 1.89 95%CI: 1.0-4.2) and mannosyl-oligosaccharide 1,2-alpha-mannosidase (WMWodds: 2.4 95%CI: 1.03-9.9). Protein abundance ratios associated with mean delirium severity at postoperative day 1 were Complement C2 (Spearman rs = -0.31, 95%CI [-0.55, -0.02]) and Mannosyl-oligosaccharide 1,2-alpha-mannosidase (rs = 0.61, 95%CI = [0.29, 0.81]). CONCLUSIONS: We identified changes in proteins associated with coagulation, inflammation, and protein handling; larger, follow-up studies are needed to confirm our hypothesis-generating findings.

Increasing Hospital at Home Enrollment Through Decentralization With Agile Science.

LEVEL OF EVIDENCE: 4, Descriptive quality improvement project.

Agile Mentorship: A Longitudinal Exploratory Analysis.

Effective mentorship relationships increase mentee academic success and satisfaction. However, existing mentorship models are limited by miscommunication, undefined roles, and mismatched goals. The agile mentorship process aims to address these limitations by leveraging insights from agile science and the existing evidence on effective mentorship models to support effective mentoring relationships in healthcare environments. To illustrate the agile mentorship process and the growth of a mentored clinician-scientist (H.L., first author), we describe the model and share qualitative findings generated from the independent analysis of 18 months of mentee reflections. In two iterative cycles, reflections (n = 56) were analyzed using exploratory content and relational analysis. Coauthors C.S. and B.T. employed inductive and deductive coding approaches to explore the data using an ontological lens. We discuss and share quotes representing the identified four main themes. Identification of shortcomings, adaptive perspective, managing relationships, and personal growth. In addition, personal growth had three subthemes: Awareness, continual reflection, and toolkit development. In summary, the reflections of one mentee within the agile mentorship process illustrated the growth process which occurred within an effective mentorship relationship. The agile mentorship process is a scalable and sustainable framework that is adaptable to various career development processes. Further evaluation is needed to understand the longitudinal impact of the model on mentee performance and satisfaction.

Who needs clinician attention first? A qualitative study of critical care clinicians' needs that enable the prioritization of care for populations of acutely ill patients.

BACKGROUND: To adequately care for groups of acutely ill patients, clinicians maintain situational awareness to identify the most acute needs within the entire intensive care unit (ICU) population through constant reappraisal of patient data from electronic medical record and other information sources. Our objective was to understand the information and process requirements of clinicians caring for multiple ICU patients and how this information is used to support their prioritization of care among populations of acutely ill patients. Additionally, we wanted to gather insights on the organization of an Acute care multi-patient viewer (AMP) dashboard. METHODS: We conducted and audio-recorded semi-structured interviews of ICU clinicians who had worked with the AMP in three quaternary care hospitals. The transcripts were analyzed with open, axial, and selective coding. Data was managed using NVivo 12 software. RESULTS: We interviewed 20 clinicians and identified 5 main themes following data analysis: (1) strategies used to enable patient prioritization, (2) strategies used for optimizing task organization, (3) information and factors helpful for situational awareness within the ICU, (4) unrecognized or missed critical events and information, and (5) suggestions for AMP organization and content. Prioritization of critical care was largely determined by severity of illness and trajectory of patient clinical status. Important sources of information were communication with colleagues from the previous shift, bedside nurses, and patients, data from the electronic medical record and AMP, and physical presence and availability in the ICU. CONCLUSIONS: This qualitative study explored ICU clinicians' information and process requirements to enable the prioritization of care among populations of acutely ill patients. Timely recognition of patients who need priority attention and intervention provides opportunities for improvement of critical care and for preventing catastrophic events in the ICU.

Evaluation of Digital Health Strategy to Support Clinician-Led Critically Ill Patient Population Management: A Randomized Crossover Study.

To investigate whether a novel acute care multipatient viewer (AMP), created with an understanding of clinician information and process requirements, could reduce time to clinical decision-making among clinicians caring for populations of acutely ill patients compared with a widely used commercial electronic medical record (EMR). DESIGN: Single center randomized crossover study. SETTING: Quaternary care academic hospital. SUBJECTS: Attending and in-training critical care physicians, and advanced practice providers. INTERVENTIONS: AMP. MEASUREMENTS AND MAIN RESULTS: We compared ICU clinician performance in structured clinical task completion using two electronic environments-the standard commercial EMR (Epic) versus the novel AMP in addition to Epic. Twenty subjects (10 pairs of clinicians) participated in the study. During the study session, each participant completed the tasks on two ICUs (7-10 beds each) and eight individual patients. The adjusted time for assessment of the entire ICU and the adjusted total time to task completion were significantly lower using AMP versus standard commercial EMR (-6.11; 95% CI, -7.91 to -4.30 min and -5.38; 95% CI, -7.56 to -3.20 min, respectively; p < 0.001). The adjusted time for assessment of individual patients was similar using both the EMR and AMP (0.73; 95% CI, -0.09 to 1.54 min; p = 0.078). AMP was associated with a significantly lower adjusted task load (National Aeronautics and Space Administration-Task Load Index) among clinicians performing the task versus the standard EMR (22.6; 95% CI, -32.7 to -12.4 points; p < 0.001). There was no statistically significant difference in adjusted total errors when comparing the two environments (0.68; 95% CI, 0.36-1.30; p = 0.078). CONCLUSIONS: When compared with the standard EMR, AMP significantly reduced time to assessment of an entire ICU, total time to clinical task completion, and clinician task load. Additional research is needed to assess the clinicians' performance while using AMP in the live ICU setting.

Association of delirium with increased short-term mortality among older emergency department patients: A cohort study.

STUDY OBJECTIVE: To evaluate the association between delirium and subsequent short-term mortality in geriatric patients presenting to the emergency department (ED). METHODS: This was an observational cohort study of adults age ≥75 years who presented to an academic ED and were screened for delirium during their ED visit. The Delirium Triage Screen followed by the Brief Confusion Assessment Method were used to ascertain the presence of delirium. In-hospital, 7-day, and 30-day mortality were compared between patients with and without ED delirium. Odds ratios with 95% confidence intervals (CIs) were calculated through logistic regression after adjusting for confounders including age, sex, history of dementia, ED disposition, and acuity. RESULTS: A total of 967 ED visits were included for analysis among which delirium was detected in 107 (11.1%). The median age of the cohort was 83 years (IQR 79, 88), 526 (54.4%) were female, 285 (29.5%) had documented dementia, and 171 (17.7%) had a high acuity Emergency Severity Index triage level 1 or 2. During the hospitalization, 5/107 (4.7%) of those with delirium and 4/860 (0.5%) of those without delirium died. Within 7 days of ED departure, 6/107 (5.6%) of those with delirium and 6/860 (0.7%) of those without delirium died (unadjusted OR 8.46, 95% CI 2.68-26.71). Within 30 days, 18/107 (16.8%) of those with delirium and 37/860 (4.3%) of those without delirium died (unadjusted OR 4.50, 95% CI 2.46-8.23). ED delirium remained associated with higher 7-day (adjusted OR 5.23, 95% CI 1.44-19.05, p = 0.008) and 30-day mortality (adjusted OR 2.82, 95% CI 1.45-5.46, p = 0.002). CONCLUSION: Delirium is an important prognostic factor that ED clinicians and nurses must be aware of to optimize delirium prevention, management, disposition, and communication with patients and families.

Relationship Among Clinically Obtained Biomarkers of Inflammation, Hypercoagulability, and Macrophage Activation, and Delirium in Critically Ill Patients With COVID-19.

Critically ill patients with COVID-19 experience high rates of delirium and coma. Whether delirium occurs through novel mechanisms in COVID-19 is not known. We analyzed the relationship among biomarkers of inflammation (C-reactive protein [CRP]), hypercoagulability (d-dimer), and lung macrophage activation (ferritin), and the primary composite outcome of delirium/coma next day. We also measured associations between biomarkers and next day delirium and coma independently, and delirium severity. DESIGN: Retrospective, observational cohort study. SETTING: ICUs at two large, urban, academic referral hospitals. PATIENTS: All consecutive adult patients admitted to the ICU from March 1, 2020, to June 7, 2020, with COVID-19 with clinical biomarkers and delirium assessments performed. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: Daily concentrations of CRP, d-dimer, and ferritin were obtained. Coma (assessed by Richmond Agitation-Sedation Scale) and delirium (assessed by Confusion Assessment Method for the ICU/Confusion Assessment Method for the ICU-7) were measured bid. A cohort of 197 ICU patients with COVID-19 were included. Higher d-dimer (odds ratio [OR], 1.57; 95% CI, 1.17-2.12; p < 0.01) and ferritin quartiles (OR, 1.36; 95% CI, 1.02-1.81; p < 0.01) were associated with greater odds of the composite outcome of delirium/coma next day. d-dimer was associated with greater odds of next day delirium (OR, 1.49; 95% CI, 1.14-1.94; p < 0.01) and coma independently (OR, 1.52; 95% CI, 1.08-2.14; p = 0.017). Higher ferritin quartiles were associated with greater odds of next day delirium (OR, 1.33; 95% CI, 1.04-1.70; p = 0.026) and coma independently (OR, 1.59; 95% CI, 1.14-2.23; p < 0.01). Higher CRP quartiles were associated with coma (OR, 1.36; 95% CI, 1.03-1.79; p = 0.030) and delirium severity the next day (ß = 0.30; se, 0.07; p ≤ 0.01). CONCLUSIONS: Our hypothesis-generating study found d-dimer and ferritin were associated with delirium/coma the following day, as well as delirium and coma independently. CRP was associated with next day coma and delirium severity. Larger studies to validate these results are needed.

Perioperative ischaemic brain injury and plasma neurofilament light: a secondary analysis of two prospective cohort studies.

BACKGROUND: Ischaemic brain infarction can occur without acute neurological symptoms (covert strokes) or with symptoms (overt strokes), both associated with poor health outcomes. We conducted a pilot study of the incidence of preoperative and postoperative (intraoperative or postoperative) covert strokes, and explored the relationship of postoperative ischaemic brain injury to blood levels of neurofilament light, a biomarker of neuronal damage. METHODS: We analysed 101 preoperative (within 2 weeks of surgery) and 58 postoperative research MRIs on postoperative days 2-9 from two prospective cohorts collected at the University of Wisconsin (NCT01980511 and NCT03124303). Participants were aged >65 yr and undergoing non-intracranial, non-carotid surgery. RESULTS: Preoperative covert stroke was identified in 2/101 participants (2%; Bayesian 95% confidence interval [CI], 0.2-5.4). This rate was statistically different from the postoperative ischaemic brain injury rate of 7/58 (12%, 4.9-21.3%; P=0.01) based on postoperative imaging. However, in a smaller group of participants with paired imaging (n=30), we did not identify the same effect (P=0.67). Patients with postoperative brain injury had elevated peak neurofilament light levels (median [inter-quartile range], 2.34 [2.24-2.64] log10 pg ml-1) compared with those without (1.86 [1.48-2.21] log10 pg ml-1; P=0.025). Delirium severity scores were higher in those with postoperative brain injury (19 [17-21]) compared with those without (7 [4-12]; P=0.01). CONCLUSION: Although limited by a small sample size, these data suggest that preoperative covert stroke occurs more commonly than previously anticipated. Plasma neurofilament light is a potential screening biomarker for postoperative ischaemic brain injury.

American Delirium Society 2022 Year in Review: Highlighting the Year's Most Impactful Delirium Research.

Background: Since 2015, the American Delirium Society (ADS) Research Committee has conducted an annual survey of the delirium literature for presentation in its year-in-review session. Our objectives were to describe the review process used for the 2021-2022 and to summarise the selected publications. Methods: Each member of the ADS Research Committee nominated up to 6 publications considered to be the most impactful primary delirium research published from September 1, 2021, to July 31, 2022. The 24 nominated studies were divided into three categories balanced by number of articles: medical intervention trials, non-medical intervention trials, and delirium detection/basic science studies. Each ADS Research Committee member ranked all studies in their assigned category for methodological rigor and for impact, each being scored as 0-10, for a total score of 0-20. It was decided a priori to select the top three highest-scoring articles in each category for presentation, with ties adjudicated by Committee consensus. Results: Nineteen Research Committee members served as reviewers. Scores for each category were similar: medical interventions mean (standard deviation) 12.8 (1.1), non-medical interventions 13.1 (1.1), and detection/basic science 12.6 (1.0). We summarise the results of the papers presented in the 2022 ADS year-in-review session. Conclusion: The diversity of studies presented for the 2022 ADS year-in-review session illustrates the breadth of the delirium field and the growing number of clinical trials. The dissemination of publications across a broad, diverse array of journals provides further justification of the need for delirium-specific journals.

Information and Data Visualization Needs among Direct Care Nurses in the Intensive Care Unit.

OBJECTIVES: Intensive care unit (ICU) direct care nurses spend 22% of their shift completing tasks within the electronic health record (EHR). Miscommunications and inefficiencies occur, particularly during patient hand-off, placing patient safety at risk. Redesigning how direct care nurses visualize and interact with patient information during hand-off is one opportunity to improve EHR use. A web-based survey was deployed to better understand the information and visualization needs at patient hand-off to inform redesign. METHODS: A multicenter anonymous web-based survey of direct care ICU nurses was conducted (9-12/2021). Semi-structured interviews with stakeholders informed survey development. The primary outcome was identifying primary EHR data needs at patient hand-off for inclusion in future EHR visualization and interface development. Secondary outcomes included current use of the EHR at patient hand-off, EHR satisfaction, and visualization preferences. Frequencies, means, and medians were calculated for each data item then ranked in descending order to generate proportional quarters using SAS v9.4. RESULTS: In total, 107 direct care ICU nurses completed the survey. The majority (46%, n = 49/107) use the EHR at patient hand-off to verify exchanged verbal information. Sixty-four percent (n = 68/107) indicated that current EHR visualization was insufficient. At the start of an ICU shift, primary EHR data needs included hemodynamics (mean 4.89 ± 0.37, 98%, n = 105), continuous IV medications (4.55 ± 0.73, 93%, n = 99), laboratory results (4.60 ± 0.56, 96%, n = 103), mechanical circulatory support devices (4.62 ± 0.72, 90%, n = 97), code status (4.40 ± 0.85, 59%, n = 108), and ventilation status (4.35 + 0.79, 51%, n = 108). Secondary outcomes included mean EHR satisfaction of 65 (0-100 scale, standard deviation = ± 21) and preferred future EHR user-interfaces to be organized by organ system (53%, n = 57/107) and visualized by tasks/schedule (61%, n = 65/107). CONCLUSION: We identified information and visualization needs of direct care ICU nurses. The study findings could serve as a baseline toward redesigning an EHR interface.

Effects of Image Quality on the Accuracy Human Pose Estimation and Detection of Eye Lid Opening/Closing Using Openpose and DLib.

OBJECTIVE: The application of computer models in continuous patient activity monitoring using video cameras is complicated by the capture of images of varying qualities due to poor lighting conditions and lower image resolutions. Insufficient literature has assessed the effects of image resolution, color depth, noise level, and low light on the inference of eye opening and closing and body landmarks from digital images. METHOD: This study systematically assessed the effects of varying image resolutions (from 100 × 100 pixels to 20 × 20 pixels at an interval of 10 pixels), lighting conditions (from 42 to 2 lux with an interval of 2 lux), color-depths (from 16.7 M colors to 8 M, 1 M, 512 K, 216 K, 64 K, 8 K, 1 K, 729, 512, 343, 216, 125, 64, 27, and 8 colors), and noise levels on the accuracy and model performance in eye dimension estimation and body keypoint localization using the Dlib library and OpenPose with images from the Closed Eyes in the Wild and the COCO datasets, as well as photographs of the face captured at different light intensities. RESULTS: The model accuracy and rate of model failure remained acceptable at an image resolution of 60 × 60 pixels, a color depth of 343 colors, a light intensity of 14 lux, and a Gaussian noise level of 4% (i.e., 4% of pixels replaced by Gaussian noise). CONCLUSIONS: The Dlib and OpenPose models failed to detect eye dimensions and body keypoints only at low image resolutions, lighting conditions, and color depths. CLINICAL IMPACT: Our established baseline threshold values will be useful for future work in the application of computer vision in continuous patient monitoring.

Delirium severity does not differ between medical and surgical intensive care units after adjusting for medication use.

Severe delirium is associated with an increased risk of mortality, institutionalization, and length of stay. Few studies have examined differences in delirium severity between different populations of critically ill patients. The objective of the study was to compare delirium severity and the presence of the four core features between adults in the surgical intensive care unit (SICU) and medical intensive care unit (MICU) while controlling for variables known to be associated with delirium. This is a secondary analysis of two parallel randomized multi-center trials conducted from March 2009 to January 2015 at 3 Indianapolis hospitals. A total of 474 adults with delirium were included in the analysis. Subjects were randomized in a 1:1 ratio in random blocks of 4 by a computer program. Patients were randomized to either haloperidol prescribing or de-prescribing regimen vs usual care. Delirium severity was assessed daily or twice-daily using the CAM-ICU-7 beginning after 24 h of ICU admission and until discharge from the hospital, death, or 30 days after enrollment. Secondary outcomes included hospital length of stay, hospital and 30-day mortality, and delirium-related adverse events. These outcomes were compared between SICU and MICU settings for this secondary analysis. Out of 474 patients, 237 were randomized to intervention. At study enrollment, the overall cohort had a mean age of 59 (SD 16) years old, was 54% female, 44% African-American, and 81% were mechanically ventilated upon enrollment. MICU participants were significantly older and severely ill with a higher premorbid cognitive and physical dysfunction burden. In univariate analysis, SICU participants had significantly higher mean total CAM-ICU-7 scores, corresponding to delirium severity, (4.15 (2.20) vs 3.60 (2.32), p = 0.02), and a lower mean RASS score (- 1.79 (1.28) vs - 1.53 (1.27), p < 0.001) compared to MICU participants. Following adjustment for benzodiazepines and opioids, delirium severity did not significantly differ between groups. The presence of Feature 3, altered level of consciousness, was significantly associated with the SICU participants, identifying as Black, premorbid functional impairment, benzodiazepines, opioids, and dexmedetomidine. In this secondary analysis examining differences in delirium severity between MICU and SICU participants, we did not identify a difference between participant populations following adjustment for administered benzodiazepines and opioids. We did identify that an altered level of consciousness, core feature 3 of delirium, was associated with SICU setting, identifying as Black, activities of daily living, benzodiazepines and opioid medications. These results suggest that sedation practice patterns play a bigger role in delirium severity than the underlying physiologic insult, and expression of core features of delirium may vary based on individual factors.Trial registration CT#: NCT00842608.

The Impact of Health Information Technology for Early Detection of Patient Deterioration on Mortality and Length of Stay in the Hospital Acute Care Setting: Systematic Review and Meta-Analysis.

OBJECTIVE: To evaluate the impact of health information technology (HIT) for early detection of patient deterioration on patient mortality and length of stay (LOS) in acute care hospital settings. DATA SOURCES: We searched MEDLINE and Epub Ahead of Print, In-Process & Other Non-Indexed Citations and Daily, Embase, Cochrane Central Register of Controlled Trials, Cochrane Database of Systematic Reviews, and Scopus from 1990 to January 19, 2021. STUDY SELECTION: We included studies that enrolled patients hospitalized on the floor, in the ICU, or admitted through the emergency department. Eligible studies compared HIT for early detection of patient deterioration with usual care and reported at least one end point of interest: hospital or ICU LOS or mortality at any time point. DATA EXTRACTION: Study data were abstracted by two independent reviewers using a standardized data extraction form. DATA SYNTHESIS: Random-effects meta-analysis was used to pool data. Among the 30 eligible studies, seven were randomized controlled trials (RCTs) and 23 were pre-post studies. Compared with usual care, HIT for early detection of patient deterioration was not associated with a reduction in hospital mortality or LOS in the meta-analyses of RCTs. In the meta-analyses of pre-post studies, HIT interventions demonstrated a significant association with improved hospital mortality for the entire study cohort (odds ratio, 0.78 [95% CI, 0.70-0.87]) and reduced hospital LOS overall. CONCLUSIONS: HIT for early detection of patient deterioration in acute care settings was not significantly associated with improved mortality or LOS in the meta-analyses of RCTs. In the meta-analyses of pre-post studies, HIT was associated with improved hospital mortality and LOS; however, these results should be interpreted with caution. The differences in patient outcomes between the findings of the RCTs and pre-post studies may be secondary to confounding caused by unmeasured improvements in practice and workflow over time.

Association between emergency department modifiable risk factors and subsequent delirium among hospitalized older adults.

STUDY OBJECTIVE: To evaluate the association between potential emergency department (ED)-based modifiable risk factors and subsequent development of delirium among hospitalized older adults free of delirium at the time of ED stay. METHODS: Observational cohort study of patients aged ≥75 years who screened negative for delirium in the ED, were subsequently admitted to the hospital, and had delirium screening performed within 48 h of admission. Potential ED-based risk factors for delirium included ED length of stay (LOS), administration of opioids, benzodiazepines, antipsychotics, or anticholinergics, and the placement of urinary catheter while in the ED. Odds ratios (OR) and mean differences (MD) with 95% confidence intervals (CIs) were calculated. RESULTS: Among 472 patients without delirium in the ED (mean age 84 years, 54.2% females), 33 (7.0%) patients developed delirium within 48 h of hospitalization. The ED LOS of those who developed delirium was similar to those who did not develop delirium (312.1 vs 325.6 min, MD -13.5 min, CI -56.1 to 29.0). Patients who received opioids in the ED were as likely to develop delirium as those who did not receive opioids (7.2% vs 6.9%: OR 1.04, CI 0.44 to 2.48). Patients who received benzodiazepines had a higher risk of incident delirium, the difference was clinically but not statistically significant (37.3% vs 6.5%, OR 5.35, CI 0.87 to 23.81). Intermittent urinary catheterization (OR 2.05, CI 1.00 to 4.22) and Foley placement (OR 3.69, CI 1.55 to 8.80) were associated with a higher risk of subsequent delirium. After adjusting for presence of dementia, only Foley placement in the ED remained significantly associated with development of in-hospital delirium (adjusted OR 3.16, CI 1.22 to 7.53). CONCLUSION: ED LOS and ED opioid use were not associated with higher risk of incident delirium in this cohort. Urinary catheterization in the ED was associated with an increased risk of subsequent delirium. These findings can be used to design ED-based initiatives and increase delirium prevention efforts.

Postoperative delirium and its relationship with biomarkers for dementia: a meta-analysis.

OBJECTIVES: This study seeks to identify Alzheimer's and related dementias (ADRD) biomarkers associated with postoperative delirium (POD) via meta-analysis. DESIGN: A comprehensive search was conducted. Studies met the following inclusion criteria: >18 years of age, identified POD with standardized assessment, and biomarker measured in the AT(N)-X (A = amyloid, T = tau, (N)=neurodegeneration, X-Other) framework. Exclusion criteria: focus on prediction of delirium, delirium superimposed on dementia, other neurologic or psychiatric disorders, or terminal delirium. Reviewers extracted and synthesized data for the meta-analysis. SETTING: Meta-analysis. PARTICIPANTS: Patients with POD. MEASUREMENTS: Primary outcome: association between POD and ATN-X biomarkers. Secondary outcomes involved sample heterogeneity. RESULTS: 28 studies were included in this meta-analysis. Studies focused on inflammatory and neuronal injury biomarkers; there were an insufficient number of studies for amyloid and tau biomarker analysis. Two inflammatory biomarkers (IL-6, and CRP) showed a significant relationship with POD (IL-6 n = 10, standardized mean difference (SMD): 0.53, 95% CI: 0.36-0.70; CRP n = 14, SMD: 0.53, 95% CI: 0.33-0.74). Two neuronal injury biomarkers (blood-based S100B and NfL) were positively associated with POD (S100B n = 5, SMD: 0.40, 95% CI: 0.11-0.69; NFL n = 2, SMD: 0.93, 95% CI: 0.28-1.57). Of note, many analyses were impacted by significant study heterogeneity. CONCLUSIONS: This meta-analysis identified an association between certain inflammatory and neuronal injury biomarkers and POD. Future studies will need to corroborate these relationships and include amyloid and tau biomarkers in order to better understand the relationship between POD and ADRD.