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Background Esophagectomy is associated with postoperative delirium, but its pathophysiology is not well defined. We conducted this study to measure the relationship among serum biomarkers of inflammation and neuronal injury and delirium incidence and severity in a cohort of esophagectomy patients. Methods Blood samples were obtained from patients preoperatively and on postoperative days 1 and 3 and were analyzed for S100 calcium-binding protein B, C-reactive protein (CRP), interleukin (IL) 8 and IL-10, tumor necrosis factor-α, and insulin-like growth factor 1. Delirium was assessed twice daily using the Richmond Agitation Sedation Scale and Confusion Assessment Method for Intensive Care Unit. Delirium severity was assessed once daily with the Delirium Rating Scale–Revised-98. Results Samples from 71 patients were included. Preoperative biomarker concentrations were not associated with postoperative delirium. Significant differences in change in concentrations from preoperatively to postoperative day 1 were seen in IL-8 (delirium, 38.6; interquartile range [IQR], 29.3-69.8; no delirium, 24.8; IQR, 16.0-41.7, P = .022), and IL-10 (delirium, 26.1; IQR, 13.9-36.7; no delirium, 12.4; IQR, 7.7-25.7; P = .025). Greater postoperative increase in S100 calcium-binding protein B (Spearman r = 0.289, P = .020) and lower levels of insulin-like growth factor 1 were correlated with greater delirium severity (Spearman r = −0.27, P = .040). Greater CRP change quartiles were associated with higher delirium incidence adjusting for severity of illness (odds ratio, 1.68; 95% confidence interval, 1.03-2.75; P = .037) or comorbidities (odds ratio, 1.70; 95% confidence interval, 1.05-2.76, P = .030). Conclusions Differences in change in serum CRP, IL-8, and IL-10 concentrations were associated with postoperative delirium, suggesting biomarker measurement early in the postoperative course is associated with delirium.

Coronavirus disease (COVID-19), also known as Severe acute respiratory syndrome (SARS-COV2) and it has imposed deep concern on public health globally. Based on its fast-spreading breakout among the people exposed to the wet animal market in Wuhan city of China, the city was indicated as its origin. The symptoms, reactions, and the rate of recovery shown in the coronavirus cases worldwide have been varied. The number of patients is still rising exponentially, and some countries are now battling the third wave. Since the most effective treatment of this disease has not been discovered so far, early detection of potential COVID-19 patients can help isolate them socially to decrease the spread and flatten the curve. In this study, we explore state-of-the-art research on coronavirus disease to determine the impact of this illness among various age groups. Moreover, we analyze the performance of the Decision tree (DT), K-nearest neighbors (KNN), Naive bayes (NB), Support vector machine (SVM), and Logistic regression (LR) to determine COVID-19 in the patients based on their symptoms. A dataset obtained from a public repository was collected and pre-processed, before applying the selected Machine learning (ML) algorithms on them. The results demonstrate that all the ML algorithms incorporated perform well in determining COVID-19 in potential patients. NB and DT classifiers show the best performance with an accuracy of 93.70%, whereas other algorithms, such as SVM, KNN, and LR, demonstrate an accuracy of 93.60%, 93.50%, and 92.80% respectively. Hence, we determine that ML models have a significant role in detecting COVID-19 in patients based on their symptoms.

Background Delirium prevention requires optimal management of pain and anxiety. Given the limitations of current pharmacologic interventions, evaluation of novel non-pharmacological interventions is required. Virtual reality (VR) stimulation may be a promising intervention because of its capability to reduce psychophysiological stress, pain, and anxiety and to restore cognitive and attentional capacities. Objective To ascertain patients’ and providers’ perceptions of acceptability and safety of VR intervention in the intensive care unit (ICU). Methods We enrolled a cohort of 15 ICU patients and 21 health care providers to administer a 15-minute session showing a relaxing beach scene with VR headsets and nature sound effects. Participants were then asked to rate their experiences on a Likert scale survey. Results The majority of patients (86%, 12 of 14) rated the headsets as moderately to very comfortable. All had moderate or greater sense of presence in the virtual environment, and 79% (11 of 14) rated their overall experience at 3 or greater (5 indicating that they enjoyed it very much). Seventy-one percent (10 of 14) of the patients felt that their anxiety was better with VR, and 57% (8 of 14) did not notice a change in their pain or discomfort. All health care providers found the headset to be at least moderately comfortable and felt a moderate or greater sense of presence. All providers concluded that VR therapy should be available for their patients. Both groups experienced minimal side effects. Conclusion In this prospective study of perceptions of VR therapy for ICU patients and health care providers, there was a high level of acceptance, with minimal side effects, for both groups despite their low levels of prior experience with virtual reality and video gaming.

Background Between 30% and 80% of survivors of critical illness experience cognitive impairment, but the underlying mechanisms remain unknown. Objective To determine whether intensive care unit (ICU) delirium biomarkers align with the National Institute on Aging–Alzheimer’s Association (NIA-AA) research framework for diagnostic biomarkers for Alzheimer disease and other related dementias (ADRD). Methods Ovid MEDLINE, PsycInfo, Embase, and the Cochrane Library were systematically searched for articles published between January 1, 2000, and February 20, 2020, on the relationship between delirium and biomarkers listed in the NIA-AA framework. Only studies that addressed delirium in the ICU setting and fluid biomarkers were included in these analyses. Results Of 61 256 records screened, 38 studies met inclusion criteria, 8 of which were suitable for meta-analysis. In pooled analysis, significant associations were found between ICU delirium and amyloid β-peptide 1-40 (standard mean difference [SMD], 0.42; 95% CI, 0.09-0.75), interleukin (IL)-1 receptor antagonist (SMD, 0.58; 95% CI, 0.21-0.94), and IL-6 (SMD, 0.31; 95% CI, 0.06-0.56). No significant association was observed in pooled analyses between ICU delirium and the other biomarkers. Few studies have examined ICU delirium and pathologic tau or neurodegeneration biomarkers. Conclusions Inflammatory biomarkers and amyloid β are associated with ICU delirium and point to potential overlapping mechanisms between delirium and ADRD. Critical care providers should consider integrating diagnostic approaches used in ADRD in their assessment of post–ICU cognitive dysfunction.

Background Our goal was to determine the county-level effect of in-person primary and secondary school reopening on daily cases of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in Indiana. Methods In this county-level, population-based study, we used a panel data regression analysis of the proportion of in-person learning to evaluate an association with community-wide daily new SARS-CoV-2 cases. The study period was 12 July 2020–6 October 2020. We included 73 of 92 (79.3%) Indiana counties in the analysis, accounting for 85.7% of school corporations and 90.6% of student enrollment statewide. The primary exposure was the proportion of students returning to in-person instruction. The primary outcome was the daily new SARS-CoV-2 cases per 100 000 residents at the county level. Results There is a statistically significant relationship between the proportion of students attending K-12 schools in-person and the county level daily cases of SARS-CoV-2 28 days later. For all ages, the coefficient of interest (β) is estimated at 3.36 (95% confidence interval, 1.91 to 4.81; P Conclusions In-person primary and secondary school is associated with a statistically significant but proportionally small increase in the spread of SARS-CoV-2 cases.

Background: The corona virus disease also known as COVID-19 has opened gates to a lot of research about detection, treatment and prevention in the last past year due to lack of information regarding the SARS-CoV-2 virus. PCR corona via nasopharyngeal swab is the standard method of detection in our set-up. Materials and methods: Nasopharyngeal swabs were taken by ENT department using precautions and following proper SOPs. Swabs were sent for rRT-PCR tests. Data was collected and analyzed. All the subjects meeting the inclusion criteria were included in study. Data was analyzed using SPSS version 20. Frequency and percentage was calculated for gender. Positivity rate was calculated using CDC formula. Study design: - Descriptive studies Place and Duration of Study: - Government General Hospital, Ghulam Muhammadabad, Faisalabad. 889 samples were taken from 7.1.2020 to 6.12.2020. Results: Standard PCR for corona test by nasopharyngeal route was taken of suspected corona patients and of patients with contact with corona positive patients. 894 samples were taken from 7.1.2020 to 6.12.2020. 263 were positive for corona. The calculated positive rate is 29.41%. Conclusions: Calculation of positive rates is a very easy metric to give us a quick overview of the spread of the virus. Keywords: COVID-19, Positive rates, PCR-Corona

Objectives To identify whether delirium biomarkers aligned with the National Institute on Aging-Alzheimer's Association (NIA-AA) research framework, a conceptual model that describes the use of diagnostic biomarkers for Alzheimer's disease and other related dementias (ADRD). Design Systematic review following Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Setting Acute care and outpatient settings. Participants Adults diagnosed with delirium. Methods and measurements MEDLINE, PsycInfo, Embase, and the Cochrane Library were searched for English-language studies published from January 2010 to February 2020. Studies included adults older than 18 years, identified delirium with a standardized assessment tool, and measured an ADRD biomarker. Independent reviewers determined whether an association between delirium and ADRD biomarker was found, the quality of biomarker data based on the REMARK (REporting recommendations for tumor MARKer prognostic studies) checklist, and the study bias based on the Newcastle-Ottawa Scale. Results A total of 61,256 citations were identified; 113 studies were included. Most studies did not examine amyloid, tau, or neurodegeneration biomarkers. Delirium may be associated with neurodegeneration biomarkers, but few to no studies found an association with amyloid and tau biomarkers. Delirium was not consistently associated with inflammatory biomarkers. The quality of biomarker data was moderate, and the risk of bias was moderate to high. Studies often did not collect prehospital and posthospital cognitive data. Conclusion Most delirium diagnostic biomarker studies did not measure amyloid, tau, and/or neurodegenerative biomarkers, making characterization of the relationship between delirium and ADRD difficult. Future delirium biomarker diagnostic studies could improve the understanding of pathophysiologic links between delirium with other conditions affecting cognition.

Background: After critical illness, new or worsening impairments in physical, cognitive, and/or mental health function are common among patients who have survived. Who should be screened for long-term impairments, what tools to use, and when remain unclear. Objectives: Provide pragmatic recommendations to clinicians caring for adult survivors of critical illness related to screening for postdischarge impairments. Participants: Thirty-one international experts in risk-stratification and assessment of survivors of critical illness, including practitioners involved in the Society of Critical Care Medicine’s Thrive Post-ICU Collaboratives, survivors of critical illness, and clinical researchers. Design: Society of Critical Care Medicine consensus conference on post-intensive care syndrome prediction and assessment, held in Dallas, in May 2019. A systematic search of PubMed and the Cochrane Library was conducted in 2018 and updated in 2019 to complete an original systematic review and to identify pre-existing systematic reviews. Meeting Outcomes: We concluded that existing tools are insufficient to reliably predict post-intensive care syndrome. We identified factors before (e.g., frailty, preexisting functional impairments), during (e.g., duration of delirium, sepsis, acute respiratory distress syndrome), and after (e.g., early symptoms of anxiety, depression, or post-traumatic stress disorder) critical illness that can be used to identify patients at high-risk for cognitive, mental health, and physical impairments after critical illness in whom screening is recommended. We recommend serial assessments, beginning within 2–4 weeks of hospital discharge, using the following screening tools: Montreal Cognitive Assessment test; Hospital Anxiety and Depression Scale; Impact of Event Scale-Revised (post-traumatic stress disorder); 6-minute walk; and/or the EuroQol-5D-5L, a health-related quality of life measure (physical function). Conclusions: Beginning with an assessment of a patient’s pre-ICU functional abilities at ICU admission, clinicians have a care coordination strategy to identify and manage impairments across the continuum. As hospital discharge approaches, clinicians should use brief, standardized assessments and compare these results to patient’s pre-ICU functional abilities (“functional reconciliation”). We recommend serial assessments for post-intensive care syndrome-related problems continue within 2–4 weeks of hospital discharge, be prioritized among high-risk patients, using the identified screening tools to prompt referrals for services and/or more detailed assessments.

Rationale: Delirium severity and duration are independently associated with higher mortality and morbidity. No studies to date have described a delirium trajectory by integrating both severity and duration. Objectives: The primary aim was to develop delirium trajectories by integrating symptom severity and duration. The secondary aim was to investigate the association among trajectory membership, clinical characteristics, and 30-day mortality. Methods: A secondary analysis of the PMD (Pharmacologic Management of Delirium) randomized control trial (ClinicalTrials.gov Identifier: NCT00842608; N = 531) was conducted. The presence of delirium and symptom severity were measured at least daily for 7 days using the Confusion Assessment Method for the intensive care unit (CAM-ICU) and CAM-ICU-7 (on a scale of 0–7, with 7 being the most severe). Delirium trajectories were defined using an innovative, data-driven statistical method (group-based trajectory modeling [GBTM]) and SAS v9.4. Results: A total of 531 delirious participants (mean age 60 yr [standard deviation = 16], 55% female, and 46% African American) were analyzed. Five distinct delirium trajectories were described (CAM-ICU-7: mean [standard deviation]); mild-brief (CAM-ICU-7: 0.5 [0.5]), severe-rapid recovers (CAM-ICU-7: 2.1 [1.0]), mild-accelerating (CAM-ICU-7: 2.2 [0.9]), severe-slow recovers (CAM-ICU-7: 3.9 [0.9]), and severe-nonrecovers (CAM-ICU-7: 5.9 [1.0]). Baseline cognition and race were associated with trajectory membership. Trajectory membership independently predicted 30-day mortality while controlling for age, sex, race, cognition, illness severity, and comorbidities. Conclusions: This secondary analysis described five distinct delirium trajectories based on delirium symptom severity and duration using group-based trajectory modeling. Trajectory membership predicted 30-day mortality.

Objectives: One of the defining features of the novel coronavirus disease 2019 infection has been high rates of venous thromboses. The present study aimed to describe the prevalence of venous thromboembolism in critically ill patients receiving different regimens of prophylactic anticoagulation. Design: Single-center retrospective review using data from patients with confirmed severe acute respiratory syndrome coronavirus 2 requiring intubation. Setting: Tertiary-care center in Indianapolis, IN, United States. Patients: Patients hospitalized at international units Health Methodist Hospital with severe acute respiratory syndrome coronavirus 2 requiring intubation between March 23, 2020, and April 8, 2020, who underwent ultrasound evaluation for venous thrombosis. Interventions: None. Measurements and Main Results: A total of 45 patients were included. Nineteen of 45 patients (42.2%) were found to have deep venous thrombosis. Patients found to have deep venous thrombosis had no difference in time to intubation (p = 0.97) but underwent ultrasound earlier in their hospital course (p = 0.02). Sequential Organ Failure Assessment scores were similar between the groups on day of intubation and day of ultrasound (p = 0.44 and p = 0.07, respectively). d-dimers were markedly higher in patients with deep venous thrombosis, both for maximum value and value on day of ultrasound (p < 0.01 for both). Choice of prophylactic regimen was not related to presence of deep venous thrombosis (p = 0.35). Ultrasound evaluation is recommended if d-dimer is greater than 2,000 ng/mL (sensitivity 95%, specificity 46%) and empiric anticoagulation considered if d-dimer is greater than 5,500 ng/mL (sensitivity 53%, specificity 88%). Conclusions: Deep venous thrombosis is very common in critically ill patients with coronavirus disease 2019. There was no difference in incidence of deep venous thrombosis among different pharmacologic prophylaxis regimens, although our analysis is limited by small sample size. d-dimer values are elevated in the majority of these patients, but there may be thresholds at which screening ultrasound or even empiric systemic anticoagulation is indicated.

OBJECTIVES Mean arterial pressure is critically important in patients with cirrhosis in the ICU, however, there is limited data to guide therapies and targets. DESIGN Retrospective observational study. SETTING Tertiary care ICU. PATIENTS Two hundred and seventy-three critically ill patients with cirrhosis. INTERVENTIONS None. MEASUREMENTS AND MAIN RESULTS We performed a comprehensive time-weighted mean arterial pressure analysis (time-weighted-average-mean arterial pressure and cumulative-time-below various mean arterial pressure-thresholds) during the first 24-hours after ICU admission (median: 25 mean arterial pressure measurements per-patient). Time-weighted-average-mean arterial pressure captures both the severity and duration of hypotension below a mean arterial pressure threshold and cumulative-time-below is the total time spent below a mean arterial pressure threshold. Individual univariable and multivariable logistic regression models were assessed for each time-weighted-average-mean arterial pressure and cumulative-time-below mean arterial pressure threshold (55, 60, 65, 70, and 75 mm Hg) for ICU-mortality. Time-weighted-average-mean arterial pressure: for 1 mm Hg decrease in mean arterial pressure below 75, 70, 65, 60, and 55 mm Hg, the odds for ICU-mortality were 14%, 18%, 26%, 41%, and 74%, respectively (p < 0.01, all thresholds). The association between time-weighted-average-mean arterial pressure and ICU-mortality for each threshold remained significant after adjusting for model for end-stage liver disease-sodium score, mechanical ventilation, vasopressor use, renal replacement therapy, grade 3/4 hepatic encephalopathy, WBC count, and albumin. Cumulative-time-below: odds for ICU-mortality were 4%, 6%, 10%, 12%, and 12% for each-hour spent below 75, 70, 65, 60, and 55 mm Hg, respectively. In the adjusted models, significant associations only remained for mean arterial pressure less than 65 mm Hg (odds ratio, 1.07; 95% CI, 1.00-1.14; p = 0.05) and < 60 mm Hg (odds ratio, 1.10; 95% CI, 1.01-1.18; p = 0.04). CONCLUSIONS These data suggest that maintaining a mean arterial pressure of greater than 65 mm Hg may be a reasonable target in patients with cirrhosis admitted to the ICU. However, further prospective randomized trials are needed to determine the optimal mean arterial pressure-targets in this patient population.

Objectives Both delirium duration and delirium severity are associated with adverse patient outcomes. Serum biomarkers associated with delirium duration and delirium severity in ICU patients have not been reliably identified. We conducted our study to identify peripheral biomarkers representing systemic inflammation, impaired neuroprotection, and astrocyte activation associated with delirium duration, delirium severity, and in-hospital mortality. Design Observational study. Setting Three Indianapolis hospitals. Patients Three-hundred twenty-one critically ill delirious patients. Interventions None. Measurements and main results We analyzed the associations between biomarkers collected at delirium onset and delirium-/coma-free days assessed through Richmond Agitation-Sedation Scale/Confusion Assessment Method for the ICU, delirium severity assessed through Confusion Assessment Method for the ICU-7, and in-hospital mortality. After adjusting for age, gender, Acute Physiology and Chronic Health Evaluation II score, Charlson comorbidity score, sepsis diagnosis and study intervention group, interleukin-6, -8, and -10, tumor necrosis factor-α, C-reactive protein, and S-100β levels in quartile 4 were negatively associated with delirium-/coma-free days by 1 week and 30 days post enrollment. Insulin-like growth factor-1 levels in quartile 4 were not associated with delirium-/coma-free days at both time points. Interleukin-6, -8, and -10, tumor necrosis factor-α, C-reactive protein, and S-100β levels in quartile 4 were also associated with delirium severity by 1 week. At hospital discharge, interleukin-6, -8, and -10 retained the association but tumor necrosis factor-α, C-reactive protein, and S-100β lost their associations with delirium severity. Insulin-like growth factor-1 levels in quartile 4 were not associated with delirium severity at both time points. Interleukin-8 and S-100β levels in quartile 4 were also associated with higher in-hospital mortality. Interleukin-6 and -10, tumor necrosis factor-α, and insulin-like growth factor-1 were not found to be associated with in-hospital mortality. Conclusions Biomarkers of systemic inflammation and those for astrocyte and glial activation were associated with longer delirium duration, higher delirium severity, and in-hospital mortality. Utility of these biomarkers early in delirium onset to identify patients at a higher risk of severe and prolonged delirium, and delirium related complications during hospitalization needs to be explored in future studies.

Background The effect of delirium on physical function in patients undergoing noncardiac thoracic surgery has not been well described and may differ from that in other surgical populations. Objective To determine the effects of delirium on muscle strength and functional independence. The primary end point was change in Medical Research Council sum score (MRC-SS) by delirium status. Methods A secondary analysis of data from a clinical trial involving English-speaking adults aged 18 years or older who were undergoing major noncardiac thoracic surgery. Exclusion criteria were history of schizophrenia, Parkinson disease, dementia, alcohol abuse, or neuroleptic malignant syndrome; haloperidol allergy; being pregnant or nursing; QT prolongation; and taking levodopa or cholinesterase inhibitors. Delirium was assessed twice daily using the Confusion Assessment Method for the Intensive Care Unit. Preoperatively and postoperatively, muscle strength was assessed using the modified MRC-SS and functional independence was assessed using the Katz scale of activities of daily living. Changes in MRC-SS and Katz score by delirium status were analyzed using the Fisher exact test. Results Seventy-three patients were included in the analysis. Median (interquartile range) MRC-SS and Katz score before surgery did not differ significantly between patients without and with delirium (MRC-SS: 30 [30-30] vs 30 [30-30], P > .99; Katz score: 6 [6-6] vs 6 [6-6], P = .63). The percentage of patients with a change in MRC-SS was similar in patients without and with delirium (17% vs 13%, respectively; P > .99). More patients in the delirium group had a change in Katz score (13% vs 0%, P = .04). Conclusions Postoperative delirium was not associated with change in muscle strength. Follow-up studies using other muscle measures may be needed.

Background Management of delirium in intensive care units is challenging because effective therapies are lacking. Music is a promising nonpharmacological intervention. Objectives To determine the feasibility and acceptability of personalized music (PM), slow-tempo music (STM), and attention control (AC) in patients receiving mechanical ventilation in an intensive care unit, and to estimate the effect of music on delirium. Methods A randomized controlled trial was performed in an academic medical-surgical intensive care unit. After particular inclusion and exclusion criteria were applied, patients were randomized to groups listening to PM, relaxing STM, or an audiobook (AC group). Sessions lasted 1 hour and were given twice daily for up to 7 days. Patients wore noise-canceling headphones and used mp3 players to listen to their music/audiobook. Delirium and delirium severity were assessed twice daily by using the Confusion Assessment Method for the Intensive Care Unit (CAM-ICU) and the CAM-ICU-7, respectively. Results Of the 1589 patients screened, 117 (7.4%) were eligible. Of those, 52 (44.4%) were randomized, with a recruitment rate of 5 patients per month. Adherence was higher in the groups listening to music (80% in the PM and STM groups vs 30% in the AC group; P = .01), and 80% of patients surveyed rated the music as enjoyable. The median number (interquartile range) of delirium/coma-free days by day 7 was 2 (1-6) for PM, 3 (1-6) for STM, and 2 (0-3) for AC (P = .32). Median delirium severity was 5.5 (1-7) for PM, 3.5 (0-7) for STM, and 4 (1-6.5) for AC (P = .78). Conclusions Music delivery is acceptable to patients and is feasible in intensive care units. Further research testing use of this promising intervention to reduce delirium is warranted.

Background In-hospital respiratory outcomes of non-surgical patients with undiagnosed obstructive sleep apnea (OSA), particularly those with significant comorbidities are not well defined. Undiagnosed and untreated OSA may be associated with increased cardiopulmonary morbidity. Study objectives Evaluate respiratory failure outcomes in patients identified as at-risk for OSA by the Berlin Questionnaire (BQ). Methods This was a retrospective study conducted using electronic health records at a large health system. The BQ was administered at admission to screen for OSA to medical-service patients under the age of 80 years old meeting the following health system criteria: (1) BMI greater than 30; (2) any of the following comorbid diagnoses: hypertension, heart failure, acute coronary syndrome, pulmonary hypertension, arrhythmia, cerebrovascular event/stroke, or diabetes. Patients with known OSA or undergoing surgery were excluded. Patients were classified as high-risk or low-risk for OSA based on the BQ score as follows: low-risk (0 or 1 category with a positive score on the BQ); high-risk (2 or more categories with a positive score on BQ). The primary outcome was respiratory failure during index hospital stay defined by any of the following: orders for conventional ventilation or intubation; at least two instances of oxygen saturation less than 88% by pulse oximetry; at least two instances of respiratory rate over 30 breaths per minute; and any orders placed for non-invasive mechanical ventilation without a previous diagnosis of sleep apnea. Propensity scores were used to control for patient characteristics. Results Records of 15,253 patients were assessed. There were no significant differences in the composite outcome of respiratory failure by risk of OSA (high risk: 11%, low risk: 10%, p = 0.55). When respiratory failure was defined as need for ventilation, more patients in the low-risk group experienced invasive mechanical ventilation (high-risk: 1.8% vs. low-risk: 2.3%, p = 0.041). Mortality was decreased in patients at high-risk for OSA (0.86%) vs. low risk for OSA (1.53%, p Conclusions Further prospective studies are needed to understand the contribution of undiagnosed OSA to in-hospital respiratory outcomes.

Background Admissions to the ICU related to alcohol, prescription drugs, and illicit drugs are shown to be widespread and costly. In 1993, a study revealed 28% of ICU admissions at Johns Hopkins Hospital were related to substance abuse and accrued 39% of costs. Since then, health-care expenditures have increased, and substance abuse treatment admissions have risen. We conducted a study to provide updated data on ICU utilization and costs related to licit and illicit abuse at a large county hospital in Indianapolis, Indiana. Methods All admissions to the medical ICU at Eskenazi Hospital from March to October 2017 were reviewed. Demographics, reason for admission, relation to substance abuse and specific substance, ICU and hospital length of stay, Acute Physiology and Chronic Health Evaluation II (APACHE II) scores, mortality, insurance status, and hospital charges were collected based on chart review. Results A total of 611 admissions generated $74,587,280.35 in charges. A total of 25.7% of admissions related to substance abuse accounted for 23.1% of total charges. Illicit drugs were 13% of total admissions, generating 11% of charges. Alcohol-related admissions were 9.5% of total admissions, generating 7.6% of charges. Prescription drugs were 2.9% of admissions, generating 4.2% of charges. Of the substance abuse admissions, patients were generally men and 40 to 64 years of age, with longer ICU stay, higher APACHE II scores, and higher mortality. Conclusions Substance abuse admissions make up almost a one-quarter of resources used by our ICU. Patients tend to be younger and sicker with a higher risk of death. Identifying and accurately describing the landscape of this current health crisis will help us take appropriate action in the future.

Infrared thermography (IRT) has been widely used in detecting the subsurface delamination of bridge deck. However, IRT inspection on delamination zones of the bridge deck which have limited exposure to direct solar radiation (e.g., the bottom surface of the bridge deck) is rather challenging due to the relatively low thermal contrast (∆T) development in these zones. Therefore, the purpose of this study is to conduct a series of experimental studies in conjunction with numerical modeling for investigating the effectiveness of IRT in delamination detection of bridge deck components which are normally not exposed to direct solar radiation. Specially, the effects of different environmental conditions, thickness of bridge deck, and defect characteristics on the absolute thermal contrast (∆T) development were systematically investigated. The results show that IRT can effectively detect the subsurface delamination of concrete bridge deck located in regions that are not exposed to the direct solar radiation. In addition, the development of detectable thermal contrast (>0.5°C) is much dependent on the rate of change in ambient temperature with a suitable detection period between 8 am and 4 pm. Furthermore, it shows that the value of ∆T increases with the increase of bridge deck thickness and delamination size.

Background The COVID-19 pandemic has highlighted the inability of health systems to leverage existing system infrastructure in order to rapidly develop and apply broad analytical tools that could inform state- and national-level policymaking, as well as patient care delivery in hospital settings. The COVID-19 pandemic has also led to highlighted systemic disparities in health outcomes and access to care based on race or ethnicity, gender, income-level, and urban-rural divide. Although the United States seems to be recovering from the COVID-19 pandemic owing to widespread vaccination efforts and increased public awareness, there is an urgent need to address the aforementioned challenges. Objective This study aims to inform the feasibility of leveraging broad, statewide datasets for population health–driven decision-making by developing robust analytical models that predict COVID-19–related health care resource utilization across patients served by Indiana’s statewide Health Information Exchange. Methods We leveraged comprehensive datasets obtained from the Indiana Network for Patient Care to train decision forest-based models that can predict patient-level need of health care resource utilization. To assess these models for potential biases, we tested model performance against subpopulations stratified by age, race or ethnicity, gender, and residence (urban vs rural). Results For model development, we identified a cohort of 96,026 patients from across 957 zip codes in Indiana, United States. We trained the decision models that predicted health care resource utilization by using approximately 100 of the most impactful features from a total of 1172 features created. Each model and stratified subpopulation under test reported precision scores >70%, accuracy and area under the receiver operating curve scores >80%, and sensitivity scores approximately >90%. We noted statistically significant variations in model performance across stratified subpopulations identified by age, race or ethnicity, gender, and residence (urban vs rural). Conclusions This study presents the possibility of developing decision models capable of predicting patient-level health care resource utilization across a broad, statewide region with considerable predictive performance. However, our models present statistically significant variations in performance across stratified subpopulations of interest. Further efforts are necessary to identify root causes of these biases and to rectify them.

Supplemental Digital Content is available in the text., Importance: Delirium severity has been associated with a higher risk of mortality and an increasing morbidity burden. Recently defined delirium severity trajectories were predictive of 30-day mortality in a critically ill patient population. No studies to date have examined associations between delirium severity trajectories and 2-year mortality and healthcare utilization outcomes. Objectives: To examine the associations between recently defined delirium severity trajectories and 2-year healthcare utilization outcomes of emergency department visits, rehospitalizations, and mortality. Design, Setting, and Participants: This is a secondary analysis using data from the randomized controlled clinical trial Pharmacological Management of Delirium in the Intensive Care Unit and Deprescribing in the Pharmacologic Management of Delirium trial conducted from 2009 to 2015. Patients who were greater than or equal to 18 years old, were in the ICU for greater than or equal to 24 hours, and had a positive delirium assessment (Confusion Assessment Method for the ICU) were included in the original trial. Participants were included in the secondary analysis if 2-year healthcare utilization and mortality data were available (n = 431). Main Outcomes and Measures: Healthcare utilization data within 2 years of the initial discharge date were pulled from the Indiana Network for Patient Care. Data over a 2-year period on emergency department visits (days to first emergency department visit, number of emergency department visits), inpatient hospitalizations (days to first hospitalizations, number of hospitalizations), and mortality (time to death) were extracted. Univariate relationships, Cox proportional hazard models, and competing risk modeling were used to examine statistical relationships in SAS v9.4. Results: The overall sample (n = 431) had a mean age of 60 (sd, 16), 56% were females, and 49% African-Americans. No significant associations were identified between delirium severity trajectories and time to event for emergency department visit, mortality, or rehospitalization within 2 years of the index hospital discharge. Conclusions and Relevance: This secondary analysis did not identify a significant relationship between delirium severity trajectories and healthcare utilization or mortality within 2 years of hospital discharge.

Background:As many as 70% of intensive care unit (ICU) survivors suffer from long-term physical, cognitive, and psychological impairments known as post-intensive care syndrome (PICS). We describe how the first ICU survivor clinic in the United States, the Critical Care Recovery Center (CCRC), was designed to address PICS using the principles of Agile Implementation (AI).Methods:The CCRC was designed using an eight-step process known as the AI Science Playbook. Patients who required mechanical ventilation or were delirious ≥48 hours during their ICU stay were enrolled in the CCRC. One hundred twenty subjects who completed baseline HABC-M CG assessments and had demographics collected were included in the analysis to identify baseline characteristics that correlated with higher HABC-M CG scores. A subset of patients and caregivers also participated in focus group interviews to describe their perceptions of PICS.Results:Quantitative analyses showed that the cognitive impairment was a major concern of caregivers. Focus group data also confirmed that caregivers of ICU survivors (n = 8) were more likely to perceive cognitive and mental health symptoms than ICU survivors (n = 10). Caregivers also described a need for ongoing psychoeducation about PICS, particularly cognitive and mental health symptoms, and for ongoing support from other caregivers with similar experiences.Conclusions:Our study demonstrated how the AI Science Playbook was used to build the first ICU survivor clinic in the United States. Caregivers of ICU survivors continue to struggle with PICS, particularly cognitive impairment, months to years after discharge. Future studies will need to examine whether the CCRC model of care can be adapted to other complex patient populations seen by health-care professionals.

Background Postoperative delirium affects up to 50% of patients undergoing esophagectomy and is associated with negative outcomes. The perioperative risk factors for delirium in this population are not well understood. We conducted this study to assess perioperative risk factors for postoperative delirium among esophagectomy patients. Methods We performed a secondary data analysis of patients enrolled in a randomized controlled trial evaluating the efficacy of haloperidol prophylaxis postoperatively in reducing delirium among esophagectomy patients. Postoperative delirium was assessed twice daily using the Confusion Assessment Method for the ICU. Univariate and logistic regression analyses were performed to examine the association between perioperative variables and development of postoperative delirium. Results Of 84 consecutive esophagectomy patients, postoperative delirium developed in 27 (32%). These patients had higher Acute Physiology and Chronic Health Evaluation II scores (22.1 [SD, 6.5] vs 17.4 [SD, 6.8]; p = 0.003), longer mechanical ventilation days (1.7 [SD, 1.4] days vs 1.0 [SD, 1.1] days; p = 0.001), and longer intensive care unit (ICU) days (5.1 [SD, 2.6] days vs 2.6 [SD, 1.6] days; p Conclusions ICU length of stay was significantly associated with postoperative delirium. Other perioperative factors, including duration of procedure, blood loss, and hemoglobin levels, were not significantly associated with postoperative delirium.

Rationale Red blood cells (RBC) undergo morphologic and biochemical changes during storage which may lead to adverse health risks upon transfusion. In prior studies, the effect of RBC age on health outcomes has been conflicting. We designed the study to assess the effects of RBC units’ storage duration on health outcomes specifically for hospitalized patients undergoing hip fracture surgery or coronary artery bypass grafting (CABG) surgery. Methods Using International Classification of Diseases (ICD) 9 codes, hip fracture surgery and CABG surgery patients, who received RBC transfusions between 2008 and 2013, were retrospectively identified from the electronic medical records system. Hip fracture surgery and CABG cohorts were sub-divided into 3 blood age groups based upon RBC unit age at the time of transfusion: young blood (RBC units stored less than or equal to 14 days), old blood (RBC units were stored for greater than or equal to 28 days), or mixed blood for the remaining patients. Outcome variables were 30-day, 90-day, and inpatient mortality as well as hospital length of stay. Results A total of 3,182 patients were identified: 1,121 with hip fractures and 2,061 with CABG. Transfusion of old blood was associated with higher inpatient mortality in the hip fracture surgery cohort (OR 166.8, 95% CI 1.067-26064.7, p = 0.04) and a higher 30-day mortality in the CABG cohort (OR 4.55, 95% CI 1.01–20.49, p = 0.03). Conclusions Transfusing RBC units stored for greater than or equal to 28 days may be associated with a higher mortality for patients undergoing hip fracture or CABG.

Background Sleep disturbances in critically ill patients are associated with poorer long-term clinical outcomes and quality of life. Studies are needed to better characterize associations and risk factors for persistent sleep disturbances after intensive care unit (ICU) discharge. Psychiatric disorders are frequently associated with sleep disturbances, but the role of psychiatric symptoms in sleep disturbances in ICU survivors has not been well-studied. Objective To examine the association between psychiatric symptoms and sleep disturbances in ICU survivors. Methods 112 adult ICU survivors seen from July 2011 to August 2016 in the Critical Care Recovery Center, an ICU survivor clinic at the Eskenazi Hospital in Indianapolis, IN, USA, were assessed for sleep disturbances (insomnia, hypersomnia, difficulty with sleep onset, difficulty with sleep maintenance, and excessive daytime sleepiness) and psychiatric symptoms (trauma-related symptoms and moderate to severe depressive symptoms) 3 months after ICU discharge. A multivariate logistic regression model was performed to examine the association between psychiatric symptoms and sleep disturbances. Analyses were controlled for age, hypertension, history of depression, and respiratory failure. Results ICU survivors with both trauma-related and depression symptoms (OR 16.66, 95% CI 2.89-96.00) and trauma-related symptoms alone (OR 4.59, 95% CI 1.11-18.88) had a higher likelihood of sleep disturbances. Depression symptoms alone were no longer significantly associated with sleep disturbances when analysis was controlled for trauma-related symptoms. Conclusion Trauma-related symptoms and trauma-related plus moderate to severe depressive symptoms were associated with a higher likelihood of sleep disturbances. Future studies are needed to determine whether psychiatric symptoms are associated with objective changes on polysomnography and actigraphy and whether adequate treatment of psychiatric symptoms can improve sleep disturbances.

Objective To quantify in-hospital systolic blood pressure variability among patients with intracerebral hemorrhage, determine the association between high systolic blood pressure variability (HSBPV) and 90-day severe disability or death, and examine the association between pre-hospital factors and HSBPV. Methods Adult, radiologically confirmed, intracerebral hemorrhage patients enrolled in a multi-site cohort were included. Using a semi-automated algorithm, systolic blood pressure values recorded from routine non-invasive systolic blood pressure monitoring in critical and acute care settings were extracted for the duration of hospitalization. Inter and intra-patient systolic blood pressure variability was quantified using generalized estimating equation methods. Modified Poisson and logistic regression models were fit to determine the association between HSBPV and 90-day severe disability or death and between pre-hospital characteristics and HSBPV, respectively. Results A total of 566 patients managed at four certified stroke centers were included. Over 120,000 systolic blood pressure readings were analyzed, and a standard deviation (SD) of 13.0 was parameterized as a cut-off point to categorize HSBPV. Patients with HSBPV had a greater risk of 90-day severe disability or death (relative risk: 1.20, 95% confidence interval: 1.04–1.39), after controlling for age, pre-morbid functional status, and other disease severity measures. Greater likelihood of in-hospital HSBPV was independently observed in elderly, female patients, and in patients with high admission systolic blood pressure. Conclusion Quantification of HSBPV is feasible utilizing routinely collected systolic blood pressure readings, and a singular cut-off parameter for systolic blood pressure variability demonstrated association with 90-day severe disability or death. Elderly, female, and patients with high admission systolic blood pressure may be more likely to demonstrate HSBPV during hospitalization.

Background/objective Delirium in the intensive care units (ICUs) is prevalent, with both delirium duration and delirium severity associated with adverse outcomes. We designed a pragmatic trial to test the efficacy of a pharmacological management of delirium (PMD) bundle in improving delirium/coma-free days and reducing delirium severity among ICU patients. Design A randomized pragmatic clinical trial. Setting Medical, surgical, and progressive ICUs of three tertiary care hospitals. Participants A total of 351 critically ill patients. Intervention A multicomponent PMD bundle consisting of reducing the exposure to 20 definite anticholinergic medications and benzodiazepines and prescribing low-dose haloperidol. Measurements The primary outcomes were delirium/coma-free days, measured through the Richmond Agitation-Sedation Scale and the Confusion Assessment Method for the ICU (CAM-ICU), and delirium severity, measured through Delirium Rating Scale-Revised-98 and the CAM-ICU-7. Secondary outcomes were in-hospital and posthospital discharge 30-day mortality, ICU and hospital lengths of stay, and delirium-related hospital complications. Results We randomized 351 critically ill delirious patients (mean age = 59.3 years [SD = 16.9 years]; 52% female, 42% African Americans) to receive the PMD bundle or usual care. There were no significant differences in median delirium/coma-free days at day 8 (PMD vs usual care = 4 [interquartile range {IQR} = 2-7] days vs 5 [IQR = 1-7] days; P = .888) or at day 30 (PMD vs usual care = 26 [IQR 19-29] days vs 26 [IQR, 14-29] days; P = .991). There were no significant differences for decrease in delirium severity at day 8, but at hospital discharge, the intervention group showed a greater reduction in delirium severity (mean decrease in CAM-ICU-7 score for PMD vs usual care = 3.2 [SD = 3.3] vs 2.5 [SD = 3.2]; P = .046). No differences were observed between groups for ICU and hospital lengths of stay, mortality, and delirium-related hospital complications. Similar results were observed when analyses were limited to patients 65 years or older and 75 years or older. Conclusion and relevance Implementing the PMD bundle in the ICU did not reduce delirium duration or severity among critically ill patients. Trial registration clinicaltrials.gov Identifier: NCT00842608. J Am Geriatr Soc 67:1057-1065, 2019.

Objective Benzodiazepines and anticholinergics are risk factors for delirium in the intensive care unit (ICU). We tested the impact of a deprescribing intervention on short-term delirium outcomes. Design Multisite randomized clinical trial. Setting ICUs of three large hospitals. Participants Two hundred adults aged 18 years or older and admitted to an ICU with delirium, according to the Richmond Agitation-Sedation Scale and the Confusion Assessment Method for the ICU (CAM-ICU). Participants had a contraindication to haloperidol (seizure disorder or prolonged QT interval) or preference against haloperidol as a treatment for delirium, and were excluded for serious mental illness, stroke, pregnancy, or alcohol withdrawal. Participants were randomized to a deprescribing intervention or usual care. The intervention included electronic alerts combined with pharmacist support to deprescribe anticholinergics and benzodiazepines. Measurements Primary outcomes were delirium duration measured by the CAM-ICU and severity measured by the Delirium Rating Scale Revised-98 (DRS-R-98) and the CAM-ICU-7; secondary outcomes included adverse events and mortality. Results Participants had a mean age of 61.8 (SD = 14.3) years, 59% were female, and 52% were African American, with no significant differences in baseline characteristics between groups. No differences between groups were identified in the number exposed to anticholinergics (P = .219) or benzodiazepines (P = .566), the median total anticholinergic score (P = .282), or the median total benzodiazepine dose in lorazepam equivalents (P = .501). Neither median delirium/coma-free days (P = .361) nor median change in delirium severity scores (P = .582 for DRS-R-98; P = .333 for CAM-ICU-7) were different between groups. No differences in adverse events or mortality were identified. Conclusions When added to state-of-the-art clinical services, this deprescribing intervention had no impact on medication use in ICU participants. Given the age of the population, results of clinical outcomes may not be easily extrapolated to older adults. Nonetheless, improved approaches for deprescribing or preventing anticholinergics and benzodiazepines should be developed to determine the impact on delirium outcomes. J Am Geriatr Soc 67:695-702, 2019.

Introduction: Severe COVID-19 is associated with high rates of intensive care unit (ICU) delirium and prolonged mechanical ventilation due to acute respiratory distress syndrome. We hypothesize that COVID-19 ICU survivors are at high risk for developing post-intensive care syndrome (PICS), namely long-term cognitive, psychiatric, and physical impairments which persist after ICU hospitalization. Methods: We conducted a prospective observational study at two sites of 49 patients who met the following inclusion criteria: age 18 or older, admitted to the medical ICU, had a positive COVID-19 nasopharyngeal swab, and attended at least one outpatient visit at the Indiana University School of Medicine's Critical Care Recovery Center (CCRC). Patients were administered assessments by trained personnel of cognition (Mini Mental State Exam [MMSE] or Montreal Cognitive Assessment [MoCA]) and self-reported scales for depression (Patient Health Questionarre-9 [PHQ-9]), anxiety (General Anxiety Disorder-7 [GAD-7]), post-traumatic stress disorder (Post Traumatic Symptom Scale-10 [PTSS-10]), quality of life and physical functioning (EuroQol-5D Quality of Life questionnaire [EQ5D QoL], EuroQol-5D5L [EQ5D5L], Healthy Age Brain Care Monitor Self Report [HABC-SR]). Descriptive statistics were computed as frequency, mean, and standard deviation using SPSS. Results: A total of 49 patients were included in the study with 30.6% female, mean age of 51.89 (SD 13.95). Nearly all patients (93.9%) required mechanical ventilation while hospitalized. The average hospital length of stay was 23.06 days (SD 12.3) and the mean days from discharge to initial evaluation in the CCRC was 87.3 (SD 43.2). Scores suggestive of mild cognitive impairment were seen in 23.3% (n = 36) of patients who performed the MMSE and in 37.5% (n = 16) of patients who completed the MoCA. Of the patients who participated in the PHQ-9, 33.3% (n = 36) had an abnormal score consistent with at least mild depression. 21.1% (n = 47) of the patients had abnormal scores on the functional subscale of the HABC-SR. Most notably, the mean quality of life score was 67.8 (SD 19.08) using the EQ5D QoL. Conclusions: ICU hospitalization for severe COVID-19 symptoms may be associated with long-term impairments in cognition, mental health, and physical function consistent with PICS. Larger observational cohort studies are needed to have a deeper understanding of COVID-19-related PICS, risk factors for COVID-19 PICS, and factors affecting recovery from PICS. These results emphasize the importance of continued focused assessment of ICU survivors to help identify and treat impairments in these domains in order to improve quality of life.

BackgroundTo determine the county-level effect of in-person primary and secondary school reopening on daily cases of SARS-CoV-2 in Indiana.MethodsThis is a county-level population-based study using a panel data regression analysis of the proportion of in-person learning to evaluate an association with community-wide daily new SARS-CoV-2 cases. The study period was July 12-October 6, 2020. We included 73 out of 92 (79.3%) Indiana counties in the analysis, accounting for 85.7% of school corporations and 90.6% of student enrollement statewide. The primary exposure was the proportion of students returning to in-person instruction. The primary outcome was the daily new SARS-CoV-2 cases per 100,000 residents at the county level.ResultsThere is a statistically significant relationship between the proportion of students attending K-12 schools in-person and the county level daily cases of SARS-CoV-2 28 days later. For all ages, the coefficient of interest (β) is estimated at 3.36 (95% CI: 1.91—4.81; p < 0.001). This coefficient represents the effect of a change the proportion of students attending in-person on new daily cases 28 days later. For example, a 10 percentage point increase in K-12 students attending school in-person is associated with a daily increase in SARS-CoV-2 cases in the county equal to 0.336 cases/100,000 residents of all ages.ConclusionIn-person primary and secondary school is associated with a statistically significant but proportionally small increase in the spread of SARS-CoV-2 cases.

Roads are among the most important assets in the world. Road structure improvements make a crucial contribution to economic development and growth and bring important social benefits. Automation in structural health monitoring allow the accurate prediction of ongoing damage caused by long-term traffic loading. This permits optimal road structure management and ensures the longevity and safety of road structures. This chapter discusses a variety of advanced automation techniques in structural health monitoring of road structures, such as data acquisition, data processing, and life-cycle assessment. It demonstrates that the implementation of automation in road asset management can increase the productivity and extend the service life of road structures, and enhance the durability of crucial road structures and increase transport infrastructure sustainability.

In 2004, it was estimated that there were 13–20 million mechanically ventilated patients, 1.2–5.5 million patients with ARDS and 15–19 million patients with sepsis worldwide. These patients who are admitted to intensive care units (ICUs) each year are at risk of developing long-term cognitive, functional, and psychological impairments, collectively known as postintensive care syndrome (PICS). ICU hospitalization and post-ICU recovery can also have a psychological impact on family members and other caregivers. Post-ICU recovery clinics can offer these patients and their caregivers a comprehensive personalized care plan for a meaningful recovery. In this chapter, we will discuss the various methods of postdischarge recovery in ICU survivors and their families, with a particular emphasis on the mobile ICU. Limited access to traditional outpatient clinics is a major barrier to implementation of recovery programs. The mobile critical care recovery programs bring healthcare services to patients’ homes and have the potential to be widely implemented. Further work will be needed to optimize the design and patient engagement in these programs and to develop effective and appropriate outcome measures for both patients and healthcare providers. Integrating innovative delivery systems such as telemedicine interventions, smartphone applications, and mobile ICU recovery teams into traditional clinic models for post-ICU care have the potential to enhance post-ICU recovery and reduce healthcare utilization.

Background: COVID-19 is associated with severe respiratory failure and high mortality in critically ill patients.2,4,5 Neurologic manifestations of the disease, including delirium and coma, may also be associated with poor clinical outcomes. Delirium is associated with prolonged mechanical ventilation and mortality.3 this study sought to describe the rates, duration, and severity of delirium in patients admitted to the ICU with COVID-19. Methods: A retrospective, observational study was conducted from March 1stto April 27th, 2020, at Indiana University Health Methodist and Eskenazi Health Hospitals. The delirium measurements were extracted in the first 14 days of the ICU stay, using the Richmond Agitation and Sedation Scale (RASS) and the CAM-ICU and CAM-ICU7, for those with a positive COVID-19 diagnosis. The primary outcomes were delirium rates and duration; the secondary outcome was delirium severity. Descriptive statistics and median group comparisons were done using SAS v9.4. Results: Of 144 patients in the study, 73.6% experienced delirium and 76.4% experienced delirium or coma. The median delirium or coma duration 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: 2-7) signifying severe delirium. Mechanical ventilation was associated increased risk of developing delirium (OR: 22.65, 95% CL: 5.24-97.82). Mortality was also more likely in patients experiencing delirium: 26.4% compared to 15.8% in patients without delirium. Conclusion: Of the 144 patients included, 73.6% experienced delirium lasting on average 5 days: the median delirium score being severe. Mechanical ventilation was also associated with greater odds of developing delirium. Because Covid-19 is associated with high rates of delirium, leading to increased rates of functionality disability, more resources and attention are needed to prevent and manage delirium in patients.1 References Brummel NE, Jackson JC, Pandharipande PP, et al. Delirium in the ICU and subsequent long-term disability among survivors of mechanical ventilation. Critical Care Medicine. 2014;42(2):369-377. Grasselli G, Pesenti A, Cecconi M. Critical Care Utilization for the COVID-19 Outbreak in Lombardy, Italy: Early Experience and Forecast During an Emergency Response. JAMA. 2020. Hayhurst CJ, Pandharipande PP, Hughes CG. Intensive Care Unit Delirium: A Review of Diagnosis, Prevention, and Treatment. Anesthesiology. 2016;125(6):1229-1241. Li YC, Bai WZ, Hashikawa T. The neuroinvasive potential of SARS-CoV2 may play a role in the respiratory failure of COVID-19 patients. J Med Virol. 2020. Wu Y, Xu X, Chen Z, et al. Nervous system involvement after infection with COVID-19 and other coronaviruses. Brain, behavior, and immunity. 2020:S0889-1591(0820)30357-30353.

Background: The pathophysiology of postoperative delirium in patients undergoing esophagectomy is not well understood but has been hypothesized to involve neuroinflammation. Inflammatory biomarkers may therefore be associated with delirium incidence and severity. We conducted this study to measure the association between serum inflammatory biomarkers and postoperative delirium and delirium severity. Methods: Blood samples were obtained from patients enrolled in a randomized double-blind placebo-controlled trial undergoing elective esophagectomy at Indiana University Health University Hospital. S100 calcium-binding protein B, C-Reactive Protein (CRP), interleukins 8, 10, tumor necrosis factor-alpha, and insulin like growth factor 1 (IGF1) were analyzed at preoperative, and postoperative days 1 and 3 timepoints. Delirium status and severity were assessed using the Confusion Assessment Method for Intensive Care Unit and Delirium Rating Scale (DRS-R-98), respectively. Results: Samples from 71 patients were included. Higher median CRP values were associated with delirium incidence at post-operative day 1 (no delirium: 22.7 IQR:2.2, 42.7; delirium: 35.4 IQR:25.0, 50.0, p=0.031) but not at post-operative day 3. Median CRP S100B serum values were correlated with mean delirium severity (-0.289, p=0.020). IGF-1 serum values were associated with delirium severity on post-operative day 1 (0.270, p=0.040). Conclusion: Postoperative delirium incidence was associated with higher median CRP values at POD1. The findings of this study provide evidence for the early measurement of post-operative serum biomarkers to ascertain likely incidence and severity of delirium.

Background: Delirium is a common post-operative complication for patients who undergo esophagectomy. The pathophysiology of delirium is poorly understood, limiting therapeutic options. To advance our pathophysiologic understanding, we conducted this study to evaluate the association of protein expression with postoperative delirium. Methods: A case-control study was performed using blood samples from the PEPOD randomized clinical control trial (NCT02213900). 52 patients (26 cases with delirium, 26 control) who were >18 years old, spoke English, and underwent esophagectomy were included, while those with schizophrenia, Parkinson’s, alcohol abuse, neuroleptic malignant syndrome, haloperidol allergy, and severe dementia were excluded. Samples were from pre-op and post-op day 1. Delirium was assessed for using the Confusion Assessment Method for the Intensive Care Unit and Richmond Agitation Sedation Scale, while the severity was assessed using DRS-R-68. Proteomic analysis was performed using TMT 10ples isobaric labels. Proteome Discoverer and STRING web-based tools were used for bioinformatic analyses, and the Wilcoxon-Mann-Whitney Odds (WMWodds) test was used to report between-group differences in protein abundance ratios. Results: 52 samples (26 cases, 26 controls) were analyzed for this study. Elevated protein abundance ratios of Coagulation factor IX (Median (IQR): 1.18 (1.08-1.28) p=0.047) and Mannosyl-oligosaccharide 1,2-alpha-mannosidase (Median (IQR): 1.50 (1.35-1.60) p=0.049) were noted in patients that developed delirium. Elevated protein abundance ratios of angiotensinogen (Median (IQR): 1.19 (1.14-1.23) p=0.038), ceruloplasmin (Median (IQR): 1.02 (0.98-1.08) p=0.038), and Complement C2 (Median (IQR): 1.01 (0.96-1.08) p=0.016) were noted in control patients. Protein abundance ratios for 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]) were associated with the severity of delirium in case patients. Conclusions: Changes in proteins associated with coagulation, inflammation, and protein handling were identified. These could be evaluated in future studies to develop tools for predicting onset and severity of post-operative delirium.

Background/Objective: High mortality rates among mechanically ventilated COVID-19 intensive care unit (ICU) patients have raised concerns regarding use of mechanical ventilation in management of patients with COVID-19. Additional data is needed in this discussion to better understand treatment strategies for this vulnerable population. We conducted a study to examine length of stay, duration of mechanical ventilation, mortality, and risk factors for death in critically ill patients with COVID-19. Methods: Observational study in patients admitted to Eskenazi Health and Indiana University Health Methodist ICUs. Participants were 18 years and older patients admitted to the ICU from March 1 2020 to April 27, 2020 who tested positive for COVID-19. Primary outcomes for this study were in-hospital mortality, duration of mechanical ventilation, and the length of stay in the ICU. Results: The study cohort was made up of 242 patients. The mortality rate was 19.8% (48/242) for the overall cohort and 20.5% (38/185) for mechanically ventilated patients. Age was a significant risk factor for in-hospital mortality [increased hazard in in-hospital mortality: age 65-74 years (HR: 3.1, 95%Cl=1.2-7.9, p=0.021), age 75+ (HR: 4.1, 95%CI=1.6-10.5, p=0.003) compared to those younger than 65]. In our Cox’s proportional hazard model, ESRD (HR:5.9, 95%CI=1.3-26.9, p=0.021) along with age were the only risk factors with statistical significance. The median duration of mechanical ventilation in the overall cohort was 9.3 days (IQR=-5.7-13.7). In patients that died, median ICU length of stay was 8.7 days (IQR=4.0-14.9), compared to 9.2 days (IQR=4.0-14.0) in those discharged alive. Conclusion/Clinical Impact: We found lower mortality rates and longer length of stays in our cohort than in previous studies. While more data is needed, this study supports continued use of mechanical ventilation ARDS recommendations for treating patients with ARDS from COVID-19. Further, this data potentially shows a benefit to not having a strained healthcare system.

Natural Language Processing (NLP) is an argument that provokes territory of figural manner for motorized scrutiny and depiction of humane language. Research in it unfolded from the term of punch cards till the age of intelligent examination engines which takes less than a second to Figure out millions of web pages and digital documents. In the web, pieces of evidence and end-users produced content to have formerly stimulated text. The obligation of advantageous and astute content driving is decisive forthwith. Consequently, the web is being treated as a foremost source of evidence brought about the extensive extent of a probe to perceive the compass of the machine. Considering the democratization of online content formulation, it has skeptically influenced the information resurgence and eradication. This paper pulls contemporary developments in the NLP probe to perceive the scope of machine learning in a modern era to avoid ramification of adverse instructions.

Supplemental Digital Content is available in the text., Objectives: ICU is a multifaceted organization where multiple teams care for critically ill patients. In the current era, collaboration between teams and efficient workflows form the backbone of value-based care. Geographical cohorting is a widespread model for hospitalist rounding, but its role in ICUs is unclear. This study evaluates the outcomes of geographical cohorting in a large ICU of an Academic Health Center. Design: This is a retrospective analysis of quality metrics collected 12 months pre- and post-implementation of geographical cohorting. Setting: A total of 130 bedded ICU at tertiary academic health center in Midwest. Patients: All patients admitted to the ICU. Interventions: Our institution piloted the geographical cohorting model for critical care physician rounding on September 1, 2018. Measurements: The quality metrics were categorized as ICU harm events and ICU hospital metrics. Team of critical care providers were surveyed 12 months after implementation. Main Results: The critical care utilization in the pre- and post-implementation numbers were similar for patient days (pre = 34,839, post = 35,155), central-line days (pre = 17,648, post = 19,224), and Foley catheter days (pre = 18,292, post = 17,364). The ICU length of stay was similar (4.9 d) in both pre- and post-intervention periods. Significant reduction in the incidence of Clostridium difficile infection (relative risk, –0.50; 95% CI, 0.25–0.96; p = 0.039), hospital-acquired pressure injury (relative risk, –0.60; 95% CI, 0.39–0.92; p = 0.020), central line-associated bloodstream infection incidence (relative risk, –0.19; 95% CI, 0.05–0.52; p = 0.008), and catheter-associated urinary tract infection (relative risk, –0.52; 95% CI, 0.29–0.93; p = 0.027). Healthcare providers perceived optimal utilization of their time, reduced interruptions, and improved coordination of care with geographical rounding. Conclusions: Geographical cohorting improves coordination of care, physician workflow, and critical care quality metrics in very large ICUs.

Background Critical care patients with delirium are at an increased risk of functional decline and mortality long term. Objective To determine the relationship between delirium severity in the intensive care unit and mortality and acute health care utilization within 2 years after hospital discharge. Methods A secondary data analysis of the Pharmacological Management of Delirium and Deprescribe randomized controlled trials. Patients were assessed twice daily for delirium or coma using the Richmond Agitation-Sedation Scale and the Confusion Assessment Method for the Intensive Care Unit (CAM-ICU). Delirium severity was measured using the CAM-ICU-7. Mean delirium severity (from time of randomization to discharge) was categorized as rapidly resolving, mild to moderate, or severe. Cox proportional hazards regression was used to model time to death, first emergency department visit, and rehospitalization. Analyses were adjusted for age, sex, race, Charlson Comorbidity Index, Acute Physiology and Chronic Health Evaluation II score, discharge location, diagnosis, and intensive care unit type. Results Of 434 patients, those with severe delirium had higher mortality risk than those with rapidly resolving delirium (hazard ratio 2.21; 95% CI, 1.35-3.61). Those with 5 or more days of delirium or coma had higher mortality risk than those with less than 5 days (hazard ratio 1.52; 95% CI, 1.07-2.17). Delirium severity and number of days of delirium or coma were not associated with time to emergency department visits and rehospitalizations. Conclusion Increased delirium severity and days of delirium or coma are associated with higher mortality risk 2 years after discharge.

BackgroundDelirium incidence, duration and severity in patients admitted to the intensive care unit (ICU) due to COVID-19 is not known.MethodsWe 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.ResultsOf 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.Conclusions73.6% 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.

Supplemental Digital Content is available in the text., Objectives: To characterize the risk of long-term cognitive impairment associated with delirium in acute neurologic injury patients. Design: We analyzed a 10-year cohort of adult acute neurologic injury patients (stroke and traumatic brain injury) without preexisting mild cognitive impairment or dementia, utilizing administrative databases. Patients were followed for in-hospital delirium and mild cognitive impairment or dementia. We report incidence and adjusted hazard ratios for mild cognitive impairment or dementia associated with delirium. Subgroups analyzed include acute neurologic injury categories, dementia subtypes, repeated delirium exposure, and age strata. Setting: We used state emergency department and state inpatient databases for New York, Florida, and California. All visits are included in the databases regardless of payer status. Patients: We included adult patients with diagnosis of stroke and traumatic brain injury as acute neurologic injury. Patients with preexisting mild cognitive impairment or dementia were excluded. Interventions: None. Measurements and Main Results: Among 911,380 acute neurologic injury patients, 5.2% were diagnosed with delirium. Mild cognitive impairment or dementia incidence among delirium patients was approximately twice that of nondelirium patients. In adjusted models, risk of mild cognitive impairment or dementia was higher among patients with delirium (adjusted hazard ratio, 1.58). Increased risk was observed across all subgroups including patients less than or equal to 55 years old. Conclusions: Identification, management, and prevention of in-hospital delirium could potentially improve long-term cognitive outcomes in acute neurologic injury patients.

Delamination is a serious form of deterioration in concrete bridge decks. Infrared thermography (IRT) is an advance non‐destructive testing method for concrete bridge deck delamination detection by capturing the absolute thermal contrast (ΔT) on the concrete surface caused by the disruption in heat flow due to subsurface defects. However, as the ambient environmental conditions (e.g. wind velocity and solar radiation) of a bridge could significantly affect the measurement outcomes of IRT, the optimal times for infrared data collection are still unclear. In this paper, a series of experimental and numerical studies were carried out to investigate the effects of the rate of heat flux and wind velocity on ΔT on the surface of bridge decks with the aim of identifying the optimal inspection times for different geometry characteristics of delamination (i.e. size and depth). The developed model is firstly validated by the experimental data and then a series of parametric studies were carried out. The result shows that the heat flux rate plays an important role in the development of ΔT on concrete surface, especially for a relatively shallow and small size delamination. However, the influence of heat flux rate gradually diminishes with the increase in size and depth of delamination. In addition, it demonstrates that there is a positive linear correlation between the total heat energy (external irradiation) and square of the delamination depth. The current research represents an important step towards the development of an effective and efficient way for defect detection using IRT.

Despite rapidly expanding experience in the prevention and treatment of delirium in various care environments, no pharmacologic agent is approved for the prevention or treatment of delirium. Non-pharmacologic approaches, which address many of the risk factors for delirium, have shown reductions in delirium incidence in general medical wards. In critically ill populations, protocols combining aggressive physical and occupational therapy, daily awakening, and reduced sedation exposure reduced duration of delirium. Studies employing pharmacologic agents such as antipsychotics, statins, acetylcholinesterase inhibitors, and alpha-2 agonists have not generated acceptable data supporting a recommendation for the prevention or treatment of delirium in all patient populations. The current state of literature is highlighted by many gaps in the knowledge of delirium prevention and treatment strategies. Future research will clarify whether pharmacologic interventions can be added to non-pharmacologic interventions and whether these interventions impact short-term and/or long-term outcomes.

Objectives To assess the efficacy of haloperidol in reducing postoperative delirium in individuals undergoing thoracic surgery. Design Randomized double‐blind placebo‐controlled trial. Setting Surgical intensive care unit (ICU) of tertiary care center. Participants Individuals undergoing thoracic surgery (N=135). Intervention Low‐dose intravenous haloperidol (0.5 mg three times daily for a total of 11 doses) administered postoperatively. Measurements The primary outcome was delirium incidence during hospitalization. Secondary outcomes were time to delirium, delirium duration, delirium severity, and ICU and hospital length of stay. Delirium was assessed using the Confusion Assessment Method for the ICU and delirium severity using the Delirium Rating Scale‐Revised. Results Sixty‐eight participants were randomized to receive haloperidol and 67 placebo. No significant differences were observed between those receiving haloperidol and those receiving placebo in incident delirium (n=15 (22.1%) vs n=19 (28.4%); p = .43), time to delirium (p = .43), delirium duration (median 1 day, interquartile range (IQR) 1‐2 days vs median 1 day, IQR 1‐2 days; p = .71), delirium severity, ICU length of stay (median 2.2 days, IQR 1–3.3 days vs median 2.3 days, IQR 1‐4 days; p = .29), or hospital length of stay (median 10 days, IQR 8–11.5 days vs median 10 days, IQR 8‐12 days; p = .41). In the esophagectomy subgroup (n = 84), the haloperidol group was less likely to experience incident delirium (n=10 (23.8%) vs n=17 (40.5%); p = .16). There were no differences in time to delirium (p = .14), delirium duration (median 1 day, IQR 1‐2 days vs median 1 day, IQR 1‐2 days; p = .71), delirium severity, or hospital length of stay (median 11 days, IQR 10‐12 days vs median days 11, IQR 10‐15 days; p = .26). ICU length of stay was significantly shorter in the haloperidol group (median 2.8 days, IQR 1.1–3.8 days vs median 3.1 days, IQR 2.1–5.1 days; p = .03). Safety events were comparable between the groups. Conclusion Low‐dose postoperative haloperidol did not reduce delirium in individuals undergoing thoracic surgery but may be efficacious in those undergoing esophagectomy. J Am Geriatr Soc 66:2289–2297, 2018.

Background Obstructive sleep apnea (OSA) is associated with higher rates of postoperative delirium. The relationship between preoperative OSA risk and postoperative delirium and coma in thoracic surgery patients hospitalized in the intensive care unit (ICU) is not well understood. This study tests the hypothesis that thoracic surgery patients hospitalized in ICU with a higher preoperative risk for OSA are more likely to develop postoperative delirium and coma, resulting in longer hospital stays. Methods Preoperative OSA risk was measured using the STOP-BANG questionnaire. STOP-BANG scores of greater than or equal to 3 were defined as intermediate-high risk for OSA; 128 patients who underwent major thoracic surgery completed the STOP-BANG questionnaire preoperatively. The Richmond Agitation and Sedation Scale was used to assess level of consciousness. The Confusion Assessment Method for the ICU was used to assess for delirium. Linear regression was used to assess the relationship between risk of OSA and outcome measures. Results were adjusted for age, sex, body mass index, Charlson Comorbidity Index, instrumental activities of daily living, and surgery type. Results A total of 96 of 128 patients (76%) were in the intermediate–high-risk OSA group. Adjusted analyses showed that the intermediate–high-risk OSA group had a longer duration of postoperative ICU delirium and coma compared with the low-risk OSA group (1.4 ± 1.3 days versus 0.9 ± 1.4 days; P = 0.04). Total number of hospital days was not significantly different. Conclusions Higher preoperative risk for OSA in thoracic surgery patients was associated with a longer duration of postoperative delirium and coma.

Problem Despite the more than $32 billion the National Institutes of Health has invested annually, evidence-based health care services are not reliably implemented, sustained, or distributed in health care delivery organizations, resulting in suboptimal care and patient harm. New organizational approaches and frameworks that reflect the complex nature of health care systems are needed to achieve this goal. Approach To guide the implementation of evidence-based health care services at their institution, the authors used a number of behavioral theories and frameworks to develop the Agile Implementation (AI) Playbook, which was finalized in 2015. The AI Playbook leverages these theories in an integrated approach to selecting an evidence-based health care service to meet a specific opportunity, rapidly implementing the service, evaluating its fidelity and impact, and sustaining and scaling up the service across health care delivery organizations. The AI Playbook includes an interconnected eight-step cycle: (1) identify opportunities; (2) identify evidence-based health care services; (3) develop evaluation and termination plans; (4) assemble a team to develop a minimally viable service; (5) perform implementation sprints; (6) monitor implementation performance; (7) monitor whole system performance; and (8) develop a minimally standardized operating procedure. Outcomes The AI Playbook has helped to improve care and clinical outcomes for intensive care unit survivors and is being used to train clinicians and scientists in AI to be quality improvement advisors. Next Steps The authors plan to continue disseminating the details of the AI Playbook and illustrating how health care delivery organizations can successfully leverage it.

OBJECTIVE: This study evaluates the roles of medical and social complexity in health care use outcomes in cystic fibrosis (CF) after transfer from pediatric to adult care. METHODS: Retrospective cohort design included patients with CF who were transitioned into adult care at Indiana University from 2005 to 2015. Predictor variables included demographic and comorbidity data, age at transition, treatment complexity score (TCS), and an objective scoring measure of their social complexity (Bob’s Level of Social Support, BLSS). Outcome variables included outpatient visit rates and hospitalization rates. Pearson’s correlations and linear regression were used to analyze the data. RESULTS: The median age of the patients (N=133) at the time of transition was 20 (IQR 19–23) years. The mean FEV(1) % predicted at transition was 69 ± 24%. TCS correlated with outpatient visit rates (r = 0.3, p = 0.003), as well as hospitalization rates (r = 0.4, p < 0.001); while the BLSS only correlated with hospitalization rates (r = 0.7, p < 0.001). After adjusting for covariates, the strongest predictors of post-transfer hospitalizations are BLSS (p