166 research outputs found

    A Mobile App For Delirium Screening

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    Objective: The objective of this study is to describe the algorithm and technical implementation of a mobile app that uses adaptive testing to assess an efficient mobile app for the diagnosis of delirium. Materials and Methods: The app was used as part of a NIH-funded project to assess the feasibility, effectiveness, administration time, and costs of the 2-step delirium identification protocol when performed by physicians and nurses, and certified nursing assistants (CNA). The cohort included 535 hospitalized patients aged 79.7 (SD¼6.6) years enrolled at 2 different sites. Each patient was assessed on 2 consecutive days by the research associate who performed the reference delirium assessment. Thereafter, physicians, nurses, and CNAs performed adaptive delirium assessments using the app. Qualitative data to assess the experience of administering the 2-step protocol, and the app usability were also collected and analyzed from 50 physicians, 189 nurses, and 83 CNAs. We used extensible hypertext markup language (XHTML) and JavaScript to develop the app for the iOS–based iPad. The App was linked to Research Electronic Data Capture (REDCap), a relational database system, via a REDCap application programming interface (API) that sent and received data from/to the app. The data from REDCap were sent to the Statistical Analysis System for statistical analysis. Results: The app graphical interface was successfully implemented by XHTML and JavaScript. The API facilitated the instant updating and retrieval of delirium status data between REDCap and the app. Clinicians performed 881 delirium assessments using the app for 535 patients. The transmission of data between the app and the REDCap system showed no errors. Qualitative data indicated that the users were enthusiastic about using the app with no negative comments, 82% positive comments, and 18% suggestions of improvement. Delirium administration time for the 2-step protocol showed similar total time between nurses and physicians (103.9 vs 106.5 seconds). Weekly enrollment reports of the app data were generated for study tracking purposes, and the data are being used for statistical analyses for publications. Discussion: The app developed using iOS could be easily converted to other operating systems such as Android and could be linked to other relational databases beside REDCap, such as electronic health records to facilitate better data retrieval and updating of patient’s delirium status

    Delirium Incidence, Duration and Severity in Critically Ill Patients with COVID-19

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    Background: Delirium incidence, duration and severity in patients admitted to the intensive care unit (ICU) due to COVID-19 is not known. Methods: We conducted an observational study at two large urban academic Level 1 trauma centers. Consecutive patients admitted to the ICU with a positive SARS-CoV-2 nasopharyngeal swab polymerase chain reaction test from March 1st, 2020 to April 27, 2020, were included. Individuals younger than 18 years of age, without any documented delirium assessments (CAM-ICU), or without a discharge disposition were excluded. The primary outcomes were delirium rates and delirium duration and the secondary outcome was delirium severity. Outcomes were assessed for up to the first 14 days of ICU stay. Results: Of 243 consecutive patients with confirmed COVID-19 admitted to the ICU, 144 met eligibility criteria and were included in the analysis. Delirium occurred in 73.6% (106/144) and delirium or coma occurred in 76.4% (110/144). Sixty-three percent of patients were positive for delirium on the first CAM-ICU assessment. The median duration of delirium and coma was 7 days (IQR: 3-10), and the median delirium duration was 5 days (IQR: 2-7). The median CAM-ICU-7 score was 6 (IQR: 4-7) representing severe delirium. Mechanical ventilation was associated with greater odds of developing delirium (OR: 42.1, 95%CI: 13.0-137.1). Mortality was 26.4% in patients with delirium compared to 15.8% in patients without delirium. Conclusions: 73.6% of patients admitted to the ICU with COVID-19 experience delirium that persists for approximately 1 week. Invasive mechanical ventilation is significantly associated with odds of delirium. Clinical attention to prevent and manage delirium and reduce delirium duration and severity is urgently needed for patients with COVID-19.Babar Khan, Sujuan Gao, and Anthony Perkins are supported through NIA R01 AG 055391, R01 AG 052493 and NHLBI R01 HL131730. Anthony Perkins is also supported by NIA grants 1K23AG062555-01 and R01AG056325. Roberto Machado is supported by 1R01HL111656, 1R01HL127342 and 1R01HL133951. Sophia Wang is supported by K23AG062555-01. Edward Marcantonio is supported by grants R01AG044518 and K24AG035075 from the NIA. Malaz Boustani received funding from NIA R01AG034205 and disclosed that he has ownership equity in two for profit companies, Preferred Population Health Management and RestUp. The products and services of the two companies are not related to the research activities of the paper

    Higher C-reactive Protein Levels Predict Postoperative Delirium in Older Patients Undergoing Major Elective Surgery: A Longitudinal Nested Case-Control Study

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    Background—Delirium is a common, morbid, and costly postoperative complication.. We aimed to identify blood-based postoperative delirium markers in a nested case control study of older surgical patients using a proteomics approach followed by enzyme-linked immunosorbent assay (ELISA) validation. Methods and Materials—The Successful Aging after Elective Surgery Study enrolled dementia-free adults age ≥70 undergoing major scheduled non-cardiac surgery (N=566; 24% delirium). Plasma was collected at 4 timepoints: preoperatively (PREOP), post-anesthesia care unit (PACU), postoperative day 2 (POD2) and 1 month follow-up (PO1MO). Matched pairs were selected for the independent discovery (39 pairs) and replication cohorts (36 pairs), which were subsequently combined into the pooled cohort (75 pairs). iTRAQ-based relative quantitation mass spectrometry proteomics was performed to identify the strongest delirium-related protein, which was selected for ELISA validation. Using the ELISA results, statistical analyses using non-parametric signed-rank tests were performed in all cohorts examining the association between the identified protein and delirium. Results—C-reactive protein (CRP) emerged from the proteomics analysis as the strongest delirium-related protein. ELISA validation confirmed that compared to controls, cases had significantly higher CRP levels (*p\u3c.05, **p\u3c.01) in the discovery, replication, and pooled cohorts at PREOP (median paired difference [mg/L] 1.97*, 0.29, 1.56**, respectively), PACU (2.83, 2.22*, 2.53**, respectively) and POD2 (71.97**, 35.18*, 63.76**, respectively), but not PO1MO (2.72, −0.66, 1.10, respectively). Discussion—Elevated pre- and postoperative plasma levels of CRP were associated with delirium, suggesting that a pre-inflammatory state and heightened inflammatory response to surgery are potential pathophysiological mechanisms of delirium
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