Effectiveness of a Multi-component Delirium Prevention Program Implemented on General Medicine Hospital Units: an Interrupted Time Series Analysis.

BACKGROUND: Delirium is among the most prevalent harmful events in hospitals that is associated with an elevated risk for severe outcomes such as functional decline, falls, longer length of stay, and increased mortality. OBJECTIVE: To evaluate the impact of the implementation of a multi-component delirium program on the prevalence of delirium and the incidence of falls among patients staying on general medicine inpatient hospital units. DESIGN: A pre-post intervention study using retrospective chart abstraction and interrupted time series analysis. COHORT: Patients were selected from adult patients that stayed at least 1 day on one of the five general medicine units in a large community hospital in Ontario, Canada. A total of 16 random samples of 50 patients per month for 8 consecutive months pre-intervention (October 2017 to May 2018) and 8 months post intervention (January 2019 to August 2019) were selected for a total of 800 patients. There were no exclusion criteria. INTERVENTION: The delirium program included multiple components: education of staff and hospital leadership, twice per day bed-side screen for delirium, non-pharmacological and pharmacological prevention, and intervention strategies and a delirium consultation team. MEASUREMENT: Delirium prevalence was assessed using the evidence-based delirium chart abstraction method, CHART-del. Demographic data as well as fall incidence were also collected. RESULT: Our evaluation showed that the implementation of a multicomponent delirium program led to a reduction in delirium prevalence and fall incidences. The reduction in both delirium and falls was the largest for patients in the ages between 72 and 83 years old and varied across inpatient units. CONCLUSION: A multi-component delirium program to improve the prevention, recognition, and management of delirium reduces the prevalence of delirium and fall incidence among patients in general medicine units.

Medication clusters at hospital discharge and risk of adverse drug events at 30 days postdischarge: A population-based cohort study of older adults.

AIMS: Certain combinations of medications can be harmful and may lead to serious adverse drug events (ADEs). Identifying potentially problematic medication clusters could help guide prescribing and/or deprescribing decisions in hospital. The aim of this study is to characterize medication prescribing patterns at hospital discharge and determine which medication clusters were associated with an increased risk of ADEs in the 30-day posthospital discharge. METHODS: All residents of the province of Ontario in Canada aged 66 years or older admitted to hospital between March 2016 and February 2017 were included. Identification of medication clusters prescribed at hospital discharge was conducted using latent class analysis. Cluster identification and categorization were based on medications dispensed up to 30-day posthospitalization. Multivariable logistic regression was used to assess the potential association between membership to a particular medication cluster and ADEs postdischarge, while also evaluating other patient characteristics. RESULTS: In total, 188 354 patients were included in the study cohort. Median age (interquartile range) was 77 (71-84) years, and patients had a median (IQR) (interquartile range [IQR]) of 9 (6-13) medications dispensed prior to admission. Within the study population, 6 separate clusters of dispensing patterns were identified: cardiovascular (14%), respiratory (26%), complex care needs (12%), cardiovascular and metabolic (15%), infection (10%), and surgical (24%). Overall, 12 680 (7%) patients had an ADE in the 30 days following discharge. After considering other patient characteristics, those belonging to the respiratory cluster had the highest risk of ADEs (adjusted odds ratio: 1.12, 95% confidence interval: 1.08-1.17) compared with all the other clusters, while those in the complex care needs cluster had the lowest risk (adjusted odds ratio: 0.82, 95% confidence interval: 0.77-0.87). CONCLUSION: This study suggests that ADEs post hospital discharge can be linked with identifiable medication clusters. This information may help clinicians and researchers better understand patient populations that are more or less likely to benefit from peri-hospital discharge interventions aimed at reducing ADEs.

Physician antimicrobial prescribing and patient outcomes on general medical wards: a multicentre retrospective cohort study.

BACKGROUND: Variability in antimicrobial prescribing may indicate an opportunity for improvement in antimicrobial use. We sought to measure physician-level antimicrobial prescribing in adult general medical wards, assess the contribution of patient-level factors to antimicrobial prescribing and evaluate the association between antimicrobial prescribing and clinical outcomes. METHODS: Using the General Medicine Inpatient Initiative (GEMINI) database, we conducted a retrospective cohort study of physician-level volume and spectrum of antimicrobial prescribing in adult general medical wards in 4 academic teaching hospitals in Toronto, Ontario, between April 2010 and December 2019. We stratified physicians into quartiles by hospital site based on volume of antimicrobial prescribing (days of therapy per 100 patient-days and antimicrobial-free days) and antibacterial spectrum (modified spectrum score). The modified spectrum score assigns a value to each antibacterial agent based on the breadth of coverage. We assessed patient-level differences among physician quartiles using age, sex, Laboratory-based Acute Physiology Score, discharge diagnosis and Charlson Comorbidity Index. We evaluated the association of clinical outcomes (in-hospital 30-day mortality, length of stay, intensive care unit [ICU] transfer and hospital readmission) with antimicrobial volume and spectrum using multilevel modelling. RESULTS: The cohort consisted of 124 physicians responsible for 124 158 hospital admissions. The median physician-level volume of antimicrobial prescribing was 56.1 (interquartile range 51.7-67.5) days of therapy per 100 patient-days. We did not find any differences in baseline patient characteristics by physician prescribing quartile. The difference in mean prescribing between quartile 4 and quartile 1 was 15.8 days of therapy per 100 patient-days (95% confidence interval [CI] 9.6-22.0), representing 30% higher antimicrobial prescribing in the fourth quartile than the first quartile. Patient in-hospital deaths, length of stay, ICU transfer and hospital readmission did not differ by physician quartile. In-hospital mortality was higher among patients cared for by prescribers with higher modified spectrum scores (odds ratio 1.13, 95% CI 1.04-1.24). INTERPRETATION: We found that physician-level variability in antimicrobial prescribing was not associated with differences in patient characteristics or outcomes in academic general medicine wards. These findings provide support for considering the lowest quartile of physician antimicrobial prescribing within each hospital as a target for antimicrobial stewardship.

Association Between Delayed Discharge From Acute Care and Rehabilitation Outcomes and Length of Stay: A Retrospective Cohort Study.

OBJECTIVE: To examine the association between discharge delays from acute to rehabilitation care because of capacity strain in the rehabilitation units, patient length of stay (LOS), and functional outcomes in rehabilitation. DESIGN: Retrospective cohort study using an instrumental variable to remove potential biases because of unobserved patient characteristics. SETTING: Two campuses of a hospital network providing inpatient acute and rehabilitation care. PARTICIPANTS: Patients admitted to and discharged from acute care categories of Medicine and Neurology/Musculoskeletal (Neuro/MSK) and subsequently admitted to and discharged from inpatient rehabilitation between 2013 and 2019 (N=10486). INTERVENTIONS: None. MAIN OUTCOME MEASURES: Rehabilitation LOS, FIM scores at admission and discharge, and rehabilitation efficiency defined as FIM score improvement per day of rehabilitation. RESULTS: The final cohort contained 3690 records for Medicine and 1733 for Neuro/MSK categories. For Medicine, 1 additional day of delayed discharge was associated with an average 5.1% (95% confidence interval [CI], 3%-7.3%) increase in rehabilitation LOS and 0.08 (95% CI, 0.03-0.13) reduction in rehabilitation efficiency. For Neuro/MSK, 1 additional day of delayed discharge was associated with an average 11.6% (95% CI, 2.8%-20.4%) increase in rehabilitation LOS and 0.08 (95% CI, -0.07 to 0.23) reduction in rehabilitation efficiency. CONCLUSIONS: Delayed discharge from acute care to rehabilitation because of capacity strain in rehabilitation had a strong association with prolonged LOS in rehabilitation. An important policy implication of this "cascading" effect of delays is that reducing capacity strain in rehabilitation could be highly effective in reducing discharge delays from acute care and improving rehabilitation efficiency.

An inhibitor of complement C5 provides structural insights into activation.

The complement system is a crucial part of innate immune defenses against invading pathogens. The blood-meal of the tick Rhipicephalus pulchellus lasts for days, and the tick must therefore rely on inhibitors to counter complement activation. We have identified a class of inhibitors from tick saliva, the CirpT family, and generated detailed structural data revealing their mechanism of action. We show direct binding of a CirpT to complement C5 and have determined the structure of the C5-CirpT complex by cryoelectron microscopy. This reveals an interaction with the peripheral macro globulin domain 4 (C5_MG4) of C5. To achieve higher resolution detail, the structure of the C5_MG4-CirpT complex was solved by X-ray crystallography (at 2.7 Å). We thus present the fold of the CirpT protein family, and provide detailed mechanistic insights into its inhibitory function. Analysis of the binding interface reveals a mechanism of C5 inhibition, and provides information to expand our biological understanding of the activation of C5, and thus the terminal complement pathway.

Outcomes in patients with and without disability admitted to hospital with COVID-19: a retrospective cohort study.

BACKGROUND: Disability-related considerations have largely been absent from the COVID-19 response, despite evidence that people with disabilities are at elevated risk for acquiring COVID-19. We evaluated clinical outcomes in patients who were admitted to hospital with COVID-19 with a disability compared with patients without a disability. METHODS: We conducted a retrospective cohort study that included adults with COVID-19 who were admitted to hospital and discharged between Jan. 1, 2020, and Nov. 30, 2020, at 7 hospitals in Ontario, Canada. We compared in-hospital death, admission to the intensive care unit (ICU), hospital length of stay and unplanned 30-day readmission among patients with and without a physical disability, hearing or vision impairment, traumatic brain injury, or intellectual or developmental disability, overall and stratified by age (≤ 64 and ≥ 65 yr) using multivariable regression, controlling for sex, residence in a long-term care facility and comorbidity. RESULTS: Among 1279 admissions to hospital for COVID-19, 22.3% had a disability. We found that patients with a disability were more likely to die than those without a disability (28.1% v. 17.6%), had longer hospital stays (median 13.9 v. 7.8 d) and more readmissions (17.6% v. 7.9%), but had lower ICU admission rates (22.5% v. 28.3%). After adjustment, there were no statistically significant differences between those with and without disabilities for in-hospital death or admission to ICU. After adjustment, patients with a disability had longer hospital stays (rate ratio 1.36, 95% confidence interval [CI] 1.19-1.56) and greater risk of readmission (relative risk 1.77, 95% CI 1.14-2.75). In age-stratified analyses, we observed longer hospital stays among patients with a disability than in those without, in both younger and older subgroups; readmission risk was driven by younger patients with a disability. INTERPRETATION: Patients with a disability who were admitted to hospital with COVID-19 had longer stays and elevated readmission risk than those without disabilities. Disability-related needs should be addressed to support these patients in hospital and after discharge.

Characteristics and outcomes of hospital admissions for COVID-19 and influenza in the Toronto area.

BACKGROUND: Patient characteristics, clinical care, resource use and outcomes associated with admission to hospital for coronavirus disease 2019 (COVID-19) in Canada are not well described. METHODS: We described all adults with COVID-19 or influenza discharged from inpatient medical services and medical-surgical intensive care units (ICUs) between Nov. 1, 2019, and June 30, 2020, at 7 hospitals in Toronto and Mississauga, Ontario. We compared patient outcomes using multivariable regression models, controlling for patient sociodemographic factors and comorbidity level. We validated the accuracy of 7 externally developed risk scores to predict mortality among patients with COVID-19. RESULTS: There were 1027 hospital admissions with COVID-19 (median age 65 yr, 59.1% male) and 783 with influenza (median age 68 yr, 50.8% male). Patients younger than 50 years accounted for 21.2% of all admissions for COVID-19 and 24.0% of ICU admissions. Compared with influenza, patients with COVID-19 had significantly greater in-hospital mortality (unadjusted 19.9% v. 6.1%, adjusted relative risk [RR] 3.46, 95% confidence interval [CI] 2.56-4.68), ICU use (unadjusted 26.4% v. 18.0%, adjusted RR 1.50, 95% CI 1.25-1.80) and hospital length of stay (unadjusted median 8.7 d v. 4.8 d, adjusted rate ratio 1.45, 95% CI 1.25-1.69). Thirty-day readmission was not significantly different (unadjusted 9.3% v. 9.6%, adjusted RR 0.98, 95% CI 0.70-1.39). Three points-based risk scores for predicting in-hospital mortality showed good discrimination (area under the receiver operating characteristic curve [AUC] ranging from 0.72 to 0.81) and calibration. INTERPRETATION: During the first wave of the pandemic, admission to hospital for COVID-19 was associated with significantly greater mortality, ICU use and hospital length of stay than influenza. Simple risk scores can predict in-hospital mortality in patients with COVID-19 with good accuracy.

Value of routine echocardiography in the management of stroke.

BACKGROUND: Transthoracic echocardiography is routinely performed in patients with stroke or transient ischemic attack (TIA) to help plan secondary stroke management, but recent data evaluating its usefulness in this context are lacking. We sought to evaluate the value of echocardiography for identifying clinically actionable findings for secondary stroke prevention. METHODS: We conducted a multicentre cohort study of patients admitted to hospital with stroke or TIA between 2010 and 2015 at 2 academic hospitals in Toronto, Ontario, Canada. Clinically actionable echocardiographic findings for secondary stroke prevention included cardiac thrombus, patent foramen ovale, atrial myxoma or valvular vegetation. We identified patient characteristics associated with clinically actionable findings using logistic regression. RESULTS: Of the 1862 patients with stroke or TIA we identified, 1272 (68%) had at least 1 echocardiogram. Nearly all echocardiograms were transthoracic; 1097 (86%) were normal, 1 (0.08%) had an atrial myxoma, 2 (0.2%) had a valvular vegetation, 11 (0.9%) had a cardiac thrombus and 66 (5.2%) had a PFO. Patent foramen ovale was less likely among patients older than 60 years (adjusted odds ratio [OR] 0.34, 95% confidence interval [CI] 0.20-0.57), with prior stroke or TIA (adjusted OR 0.31, 95% CI 0.09-0.76) or with dyslipidemia (adjusted OR 0.39, 95% CI 0.15-0.84). Among the 130 patients with cryptogenic stroke who had an echocardiogram (n = 110), a PFO was detected in 19 (17%) on transthoracic echocardiogram. INTERPRETATION: Most patients with stroke or TIA had a normal echocardiogram, with few having clinically actionable findings for secondary stroke prevention. Clinically actionable findings, specifically PFO, were more common in patients with cryptogenic stroke.

Prevalence and Costs of Discharge Diagnoses in Inpatient General Internal Medicine: a Multi-center Cross-sectional Study.

BACKGROUND: Understanding the most common and costly conditions treated by inpatient general medical services is important for implementing quality improvement, developing health policy, conducting research, and designing medical education. OBJECTIVE: To determine the prevalence and cost of conditions treated on general internal medicine (GIM) inpatient services. DESIGN: Retrospective cross-sectional study involving 7 hospital sites in Toronto, Canada. PARTICIPANTS: All patients discharged between April 1, 2010 and March 31, 2015 who were admitted to or discharged from an inpatient GIM service. MAIN MEASURES: Hospital administrative data were used to identify diagnoses and costs associated with admissions. The primary discharge diagnosis was identified for each admission and categorized into clinically relevant and mutually exclusive categories using the Clinical Classifications Software (CCS) tool. KEY RESULTS: Among 148,442 admissions, the most common primary discharge diagnoses were heart failure (5.1%), pneumonia (5.0%), urinary tract infection (4.6%), chronic obstructive pulmonary disease (4.5%), and stroke (4.4%). The prevalence of the 20 most common conditions was significantly correlated across hospitals (correlation coefficients ranging from 0.55 to 0.95, p ≤ 0.01 for all comparisons). No single condition represented more than 5.1% of all admissions or more than 7.9% of admissions at any hospital site. The costliest conditions were stroke (median cost $7122, interquartile range 5587-12,354, total cost $94,199,422, representing 6.0% of all costs) and the group of delirium, dementia, and cognitive disorders (median cost $12,831, IQR 9539-17,509, total cost $77,372,541, representing 4.9% of all costs). The 10 most common conditions accounted for only 36.2% of hospitalizations and 36.8% of total costs. The remaining hospitalizations included 223 different CCS conditions. CONCLUSIONS: GIM services care for a markedly heterogeneous population but the most common conditions were similar across 7 hospitals. The diversity of conditions cared for in GIM may be challenging for healthcare delivery and quality improvement. Initiatives that cut across individual diseases to address processes of care, patient experience, and functional outcomes may be more relevant to a greater proportion of the GIM population than disease-specific efforts.

Analysis of mRNA deadenylation by multi-protein complexes.

Poly(A) tails are found at the 3' end of almost every eukaryotic mRNA and are important for the stability of mRNAs and their translation into proteins. Thus, removal of the poly(A) tail, a process called deadenylation, is critical for regulation of gene expression. Most deadenylation enzymes are components of large multi-protein complexes. Here, we describe an in vitro deadenylation assay developed to study the exonucleolytic activities of the multi-protein Ccr4-Not and Pan2-Pan3 complexes. We discuss how this assay can be used with short synthetic RNAs, as well as longer RNA substrates generated using in vitro transcription. Importantly, quantitation of the reactions allows detailed analyses of deadenylation in the presence and absence of accessory factors, leading to new insights into targeted mRNA decay.

Caractéristiques et issues des hospitalisations pour les cas de COVID-19 et d'influenza dans la région de Toronto.

CONTEXTE: Les caractéristiques des patients, les soins cliniques, l'utilisation des ressources et les issues cliniques des personnes atteintes de la maladie à coronavirus 2019 (COVID-19) hospitalisées au Canada ne sont pas bien connus. MÉTHODES: Nous avons recueilli des données sur tous les adultes hospitalisés atteints de la COVID-19 ou de l'influenza ayant obtenu leur congé d'unités médicales ou d'unités de soins intensifs médicaux et chirurgicaux entre le 1er novembre 2019 et le 30 juin 2020 dans 7 centres hospitaliers de Toronto et de Mississauga (Ontario). Nous avons comparé les issues cliniques des patients à l'aide de modèles de régression multivariée, en tenant compte des facteurs sociodémographiques et de l'intensité des comorbidités. Nous avons validé le degré d'exactitude de 7 scores de risque mis au point à l'externe pour déterminer leur capacité à prédire le risque de décès chez les patients atteints de la COVID-19. RÉSULTATS: Parmi les hospitalisations retenues, 1027 patients étaient atteints de la COVID-19 (âge médian de 65 ans, 59,1 % d'hommes) et 783 étaient atteints de l'influenza (âge médian de 68 ans, 50,8 % d'hommes). Les patients âgés de moins de 50 ans comptaient pour 21,2 % de toutes les hospitalisations dues à la COVID-19 et 24,0 % des séjours aux soins intensifs. Comparativement aux patients atteints de l'influenza, les patients atteints de la COVID-19 présentaient un taux de mortalité perhospitalière (mortalité non ajustée 19,9 % c. 6,1 %; risque relatif [RR] ajusté 3,46 %, intervalle de confiance [IC] à 95 % 2,56­4,68) et un taux d'utilisation des ressources des unités de soins intensifs (taux non ajusté 26,4 % c. 18,0 %; RR ajusté 1,50, IC à 95 % 1,25­1,80) significativement plus élevés, ainsi qu'une durée d'hospitalisation (durée médiane non ajustée 8,7 jours c. 4,8 jours; rapport des taux d'incidence ajusté 1,45; IC à 95 % 1,25­1,69) significativement plus longue. Le taux de réhospitalisation dans les 30 jours n'était pas significativement différent (taux non ajusté 9,3 % c. 9,6 %; RR ajusté 0,98 %, IC à 95 % 0,70­1,39). Trois scores de risque utilisant un pointage pour prédire la mortalité perhospitalière ont montré une bonne discrimination (aire sous la courbe [ASC] de la fonction d'efficacité du récepteur [ROC] 0,72­0,81) et une bonne calibration. INTERPRÉTATION: Durant la première vague de la pandémie, l'hospitalisation des patients atteints de la COVID-19 était associée à des taux de mortalité et d'utilisation des ressources des unités de soins intensifs et à une durée d'hospitalisation significativement plus importants que les hospitalisations des patients atteints de l'influenza. De simples scores de risque peuvent prédire avec une bonne exactitude le risque de mortalité perhospitalière des patients atteints de la COVID-19.

SNS01-T modulation of eIF5A inhibits B-cell cancer progression and synergizes with bortezomib and lenalidomide.

The high rates of recurrence and low median survival in many B-cell cancers highlight a need for new targeted therapeutic modalities. In dividing cells, eukaryotic translation initiation factor 5A (eIF5A) is hypusinated and involved in regulation of protein synthesis and proliferation, whereas the non-hypusinated form of eIF5A is a potent inducer of cell death in malignant cells. Here, we demonstrate the potential of modulating eIF5A expression as a novel approach to treating B-cell cancers. SNS01-T is a nonviral polyethylenimine-based nanoparticle, designed to induce apoptosis selectively in B-cell cancers by small interfering RNA-mediated suppression of hypusinated eIF5A and plasmid-based overexpression of a non-hypusinable eIF5A mutant. In this study, we show that SNS01-T is preferentially taken up by malignant B cells, inhibits tumor growth in multiple animal models of B-cell cancers without damaging normal tissues, and synergizes with the current therapies bortezomib and lenalidomide to inhibit tumor progression. The results collectively demonstrate the potential of SNS01-T as a novel therapeutic for treatment of a diverse range of B-cell malignancies.

Long-Term Outcomes Following Fairly Brief Androgen Suppression and Stereotactic Radiation Therapy in High-Risk Prostate Cancer: Update From the FASTR/FASTR-2 Trials.

PURPOSE: There is limited data on the long-term outcomes of ultrahypofractionated radiation therapy in high-risk prostate cancer. The FASTR and FASTR-2 trials were designed to assess the tolerability of stereotactic ablative radiation therapy (SABR) in this context. Herein, the long-term results are reported. METHODS AND MATERIALS: Eligible patients had localized high-risk prostate cancer and were either ≥70 years old, had a score of ≥3 on the Vulnerable Elderly Scale, or declined standard therapy. Nineteen patients from a single institution were enrolled on FASTR between 2011 and 2015. They received 40 Gy to the prostate and 25 Gy to the pelvic lymph nodes in 5 weekly fractions, with 12 months of androgen deprivation therapy (ADT). Thirty patients from the same institution were enrolled on FASTR-2 between 2015 and 2017. They received 35 Gy to the prostate alone in 5 weekly fractions, with 18 months of ADT. Updated toxicity and outcomes were assessed retrospectively. Kaplan-Meier estimates were calculated for biochemical failure-free survival, freedom from distant metastases, prostate cancer-specific survival, and overall survival. RESULTS: Forty-four patients were eligible for analysis, 16 from FASTR and 28 from FASTR-2. Thirty-four patients (77%) were >70 years old. High-risk features included Gleason score ≥8 (n = 20, 46%), T3-T4 disease (n = 12, 27%), and baseline prostate-specific antigen > 20 (n = 22, 50%). Median follow-up was 6.4 years. The 5-year cumulative incidence of late grade ≥3 genitourinary/gastrointestinal toxicity was 32% in FASTR and 11% in FASTR-2. At 5 years, the combined rates of biochemical failure-free survival, freedom from distant metastases, prostate cancer-specific survival, and overall survival were 72%, 90%, 92%, and 83%, respectively. CONCLUSIONS: SABR can be safely delivered in high-risk prostate cancer by optimizing technical delivery, particularly with adherence to strict dose constraints for organs at risk. The clinical outcomes in FASTR and FASTR-2 were largely comparable to more standard fractionation schemes plus ADT, but further modifications may improve disease control. Larger randomized trials are necessary to better understand the efficacy and tolerability of this approach.

Characterizing medical patients with delirium: A cohort study comparing ICD-10 codes and a validated chart review method.

BACKGROUND: Delirium is a major cause of preventable mortality and morbidity in hospitalized adults, but accurately determining rates of delirium remains a challenge. OBJECTIVE: To characterize and compare medical inpatients identified as having delirium using two common methods, administrative data and retrospective chart review. METHODS: We conducted a retrospective study of 3881 randomly selected internal medicine hospital admissions from six acute care hospitals in Toronto and Mississauga, Ontario, Canada. Delirium status was determined using ICD-10-CA codes from hospital administrative data and through a previously validated chart review method. Baseline sociodemographic and clinical characteristics, processes of care and outcomes were compared across those without delirium in hospital and those with delirium as determined by administrative data and chart review. RESULTS: Delirium was identified in 6.3% of admissions by ICD-10-CA codes compared to 25.7% by chart review. Using chart review as the reference standard, ICD-10-CA codes for delirium had sensitivity 24.1% (95%CI: 21.5-26.8%), specificity 99.8% (95%CI: 99.5-99.9%), positive predictive value 97.6% (95%CI: 94.6-98.9%), and negative predictive value 79.2% (95%CI: 78.6-79.7%). Age over 80, male gender, and Charlson comorbidity index greater than 2 were associated with misclassification of delirium. Inpatient mortality and median costs of care were greater in patients determined to have delirium by ICD-10-CA codes (5.8% greater mortality, 95% CI: 2.0-9.5 and $6824 greater cost, 95%CI: 4713-9264) and by chart review (11.9% greater mortality, 95%CI: 9.5-14.2% and $4967 greater cost, 95%CI: 4415-5701), compared to patients without delirium. CONCLUSIONS: Administrative data are specific but highly insensitive, missing most cases of delirium in hospital. Mortality and costs of care were greater for both the delirium cases that were detected and missed by administrative data. Better methods of routinely measuring delirium in hospital are needed.

Modulation of eIF5A expression using SNS01 nanoparticles inhibits NF-κB activity and tumor growth in murine models of multiple myeloma.

Despite recent advances in the first-line treatment of multiple myeloma, almost all patients eventually experience relapse with drug-resistant disease. New therapeutic modalities are needed, and to this end, SNS01, a therapeutic nanoparticle, is being investigated for treatment of multiple myeloma. The antitumoral activity of SNS01 is based upon modulation of eukaryotic translation initiation factor 5A (eIF5A), a highly conserved protein that is involved in many cellular processes including proliferation, apoptosis, differentiation and inflammation. eIF5A is regulated by post-translational hypusine modification, and overexpression of hypusination-resistant mutants of eIF5A induces apoptosis in many types of cancer cells. SNS01 is a polyethylenimine (PEI)-based nanoparticle that contains both a B-cell-specific expression plasmid expressing a non-hypusinable mutant of eIF5A and a small interfering RNA (siRNA) which depletes endogenous hypusinated eIF5A. Reducing hypusine-modified eIF5A levels was found to inhibit phosphorylation and activity of ERK MAPK and nuclear factor-κB (NF-κB), and thus sensitize myeloma cells to apoptosis resulting from transfection of a plasmid expressing eIF5A(K50R). SNS01 exhibited significant antitumoral activity in both KAS-6/1 (95% inhibition; P < 0.05) and RPMI 8226 (59% inhibition; P < 0.05) multiple myeloma xenograft models following systemic administration. These results highlight the potential of using this approach as a new therapeutic strategy for multiple myeloma.

Use of eco-mapping in health services research: a scoping review protocol.

INTRODUCTION: People with complex health and social needs often require care from different providers and services. Identifying their existing sources of support could assist with addressing potential gaps and opportunities for enhanced service delivery. Eco-mapping is an approach used to visually capture people's social relationships and their linkages to the larger social systems. As it is an emerging and promising approach in the health services field, a scoping review on eco-mapping is warranted. This scoping review aims to synthesise the empirical literature that has focused on the application of eco-mapping by describing characteristics, populations, methodological approaches and other features of eco-mapping in health services research. METHODS AND ANALYSIS: This scoping review will follow the Joanna Briggs Institute methodology. From the date of database construction to 16 January 2023, the following databases in English will be searched: Ovid Medline, Ovid Embase, CINAHL Ultimate (EBSCOhost), Emcare (Ovid), Cochrane Central Register of Controlled Trials (Ovid) and Cochrane Database of Systematic Reviews (Ovid) Study/Source of Evidence selection. The inclusion criteria consist of empirical literature that uses eco-mapping or a related tool in the context of health services research. Two researchers will independently screen references against inclusion and exclusion criteria using Covidence software. Once screened, the data will be extracted and organised according to the following research questions: (1) What research questions and phenomena of interest do researchers address when using eco-mapping? (2) What are the characteristics of studies that use eco-mapping in health services research? (3) What are the methodological considerations for eco-mapping in health services research? ETHICS AND DISSEMINATION: This scoping review does not require ethical approval. The findings will be disseminated through publications, conference presentations and stakeholder meetings. TRIAL REGISTRATION NUMBER: https://doi.org/10.17605/OSF.IO/GAWYN.

The Perceived Ease of Use and Perceived Usefulness of a Web-Based Interprofessional Communication and Collaboration Platform in the Hospital Setting: Interview Study With Health Care Providers.

BACKGROUND: Hospitalized patients with complex care needs require an interprofessional team of health professionals working together to support their care in hospitals and during discharge planning. However, interprofessional communication and collaboration in inpatient settings are often fragmented and inefficient, leading to poor patient outcomes and provider frustration. Health information technology can potentially help improve team communication and collaboration; however, to date, evidence of its effectiveness is lacking. There are also concerns that current implementations might further fragment communication and increase the clinician burden without proven benefits. OBJECTIVE: In this study, we aimed to generate transferrable lessons for future designers of health information technology tools that facilitate team communication and collaboration. METHODS: A secondary analysis of the qualitative component of the mixed methods evaluation was performed. The electronic communication and collaboration platform was implemented in 2 general internal medicine wards in a large community teaching hospital in Mississauga, Ontario, Canada. Fifteen inpatient clinicians in those wards, including nurses, physicians, and allied health care providers, were recruited to participate in semistructured interviews about their experience with a co-designed electronic communication and collaboration tool. Data were analyzed using the Technology Acceptance Model, and themes related to the constructs of perceived ease of use (PEOU) and perceived usefulness (PU) were identified. RESULTS: A secondary analysis guided by the Technology Acceptance Model highlighted important points. Intuitive design precluded training as a barrier to use, but lack of training may hinder participants' PEOU if features designed for efficiency are not discovered by users. Organized information was found to be useful for creating a comprehensive clinical picture of each patient and facilitating improved handovers. However, information needs to be both comprehensive and succinct, and information overload may negatively impact PEOU. The mixed paper and electronic practice environment also negatively impacted PEOU owing to unavoidable double documentation and the need for printing. Participants perceived the tool to be useful as it improved efficiency in information retrieval and documentation, improved the handover process, afforded another mode of communication when face-to-face communication was impractical, and improved shared awareness. The PU of this tool depends on its optimal use by all team members. CONCLUSIONS: Electronic tools can support communication and collaboration among interprofessional teams caring for patients with complex needs. There are transferable lessons learned that can improve the PU and PEOU of future systems.

Dual-center validation of using magnetic resonance imaging radiomics to predict stereotactic radiosurgery outcomes.

Background: MRI radiomic features and machine learning have been used to predict brain metastasis (BM) stereotactic radiosurgery (SRS) outcomes. Previous studies used only single-center datasets, representing a significant barrier to clinical translation and further research. This study, therefore, presents the first dual-center validation of these techniques. Methods: SRS datasets were acquired from 2 centers (n = 123 BMs and n = 117 BMs). Each dataset contained 8 clinical features, 107 pretreatment T1w contrast-enhanced MRI radiomic features, and post-SRS BM progression endpoints determined from follow-up MRI. Random decision forest models were used with clinical and/or radiomic features to predict progression. 250 bootstrap repetitions were used for single-center experiments. Results: Training a model with one center's dataset and testing it with the other center's dataset required using a set of features important for outcome prediction at both centers, and achieved area under the receiver operating characteristic curve (AUC) values up to 0.70. A model training methodology developed using the first center's dataset was locked and externally validated with the second center's dataset, achieving a bootstrap-corrected AUC of 0.80. Lastly, models trained on pooled data from both centers offered balanced accuracy across centers with an overall bootstrap-corrected AUC of 0.78. Conclusions: Using the presented validated methodology, radiomic models trained at a single center can be used externally, though they must utilize features important across all centers. These models' accuracies are inferior to those of models trained using each individual center's data. Pooling data across centers shows accurate and balanced performance, though further validation is required.

Predicting stereotactic radiosurgery outcomes with multi-observer qualitative appearance labelling versus MRI radiomics.

Qualitative observer-based and quantitative radiomics-based analyses of T1w contrast-enhanced magnetic resonance imaging (T1w-CE MRI) have both been shown to predict the outcomes of brain metastasis (BM) stereotactic radiosurgery (SRS). Comparison of these methods and interpretation of radiomics-based machine learning (ML) models remains limited. To address this need, we collected a dataset of n = 123 BMs from 99 patients including 12 clinical features, 107 pre-treatment T1w-CE MRI radiomic features, and BM post-SRS progression scores. A previously published outcome model using SRS dose prescription and five-way BM qualitative appearance scoring was evaluated. We found high qualitative scoring interobserver variability across five observers that negatively impacted the model's risk stratification. Radiomics-based ML models trained to replicate the qualitative scoring did so with high accuracy (bootstrap-corrected AUC = 0.84-0.94), but risk stratification using these replicated qualitative scores remained poor. Radiomics-based ML models trained to directly predict post-SRS progression offered enhanced risk stratification (Kaplan-Meier rank-sum p = 0.0003) compared to using qualitative appearance. The qualitative appearance scoring enabled interpretation of the progression radiomics-based ML model, with necrotic BMs and a subset of heterogeneous BMs predicted as being at high-risk of post-SRS progression, in agreement with current radiobiological understanding. Our study's results show that while radiomics-based SRS outcome models out-perform qualitative appearance analysis, qualitative appearance still provides critical insight into ML model operation.