Clinical Adjudication Research Articles

Prospective Validation of a Rapid Host Gene Expression Test to Discriminate Bacterial From Viral Respiratory Infection

Bacterial and viral causes of acute respiratory illness (ARI) are difficult to clinically distinguish, resulting in the inappropriate use of antibacterial therapy. The use of a host gene expression-based test that is able to discriminate bacterial from viral infection in less than 1 hour may improve care and antimicrobial stewardship. To validate the host response bacterial/viral (HR-B/V) test and assess its ability to accurately differentiate bacterial from viral infection among patients with ARI. This prospective multicenter diagnostic study enrolled 755 children and adults with febrile ARI of 7 or fewer days' duration from 10 US emergency departments. Participants were enrolled from October 3, 2014, to September 1, 2019, followed by additional enrollment of patients with COVID-19 from March 20 to December 3, 2020. Clinical adjudication of enrolled participants identified 616 individuals as having bacterial or viral infection. The primary analysis cohort included 334 participants with high-confidence reference adjudications (based on adjudicator concordance and the presence of an identified pathogen confirmed by microbiological testing). A secondary analysis of the entire cohort of 616 participants included cases with low-confidence reference adjudications (based on adjudicator discordance or the absence of an identified pathogen in microbiological testing). Thirty-three participants with COVID-19 were included post hoc. The HR-B/V test quantified the expression of 45 host messenger RNAs in approximately 45 minutes to derive a probability of bacterial infection. Performance characteristics for the HR-B/V test compared with clinical adjudication were reported as either bacterial or viral infection or categorized into 4 likelihood groups (viral very likely [probability score <0.19], viral likely [probability score of 0.19-0.40], bacterial likely [probability score of 0.41-0.73], and bacterial very likely [probability score >0.73]) and compared with procalcitonin measurement. Among 755 enrolled participants, the median age was 26 years (IQR, 16-52 years); 360 participants (47.7%) were female, and 395 (52.3%) were male. A total of 13 participants (1.7%) were American Indian, 13 (1.7%) were Asian, 368 (48.7%) were Black, 131 (17.4%) were Hispanic, 3 (0.4%) were Native Hawaiian or Pacific Islander, 297 (39.3%) were White, and 60 (7.9%) were of unspecified race and/or ethnicity. In the primary analysis involving 334 participants, the HR-B/V test had sensitivity of 89.8% (95% CI, 77.8%-96.2%), specificity of 82.1% (95% CI, 77.4%-86.6%), and a negative predictive value (NPV) of 97.9% (95% CI, 95.3%-99.1%) for bacterial infection. In comparison, the sensitivity of procalcitonin measurement was 28.6% (95% CI, 16.2%-40.9%; P < .001), the specificity was 87.0% (95% CI, 82.7%-90.7%; P = .006), and the NPV was 87.6% (95% CI, 85.5%-89.5%; P < .001). When stratified into likelihood groups, the HR-B/V test had an NPV of 98.9% (95% CI, 96.1%-100%) for bacterial infection in the viral very likely group and a positive predictive value of 63.4% (95% CI, 47.2%-77.9%) for bacterial infection in the bacterial very likely group. The HR-B/V test correctly identified 30 of 33 participants (90.9%) with acute COVID-19 as having a viral infection. In this study, the HR-B/V test accurately discriminated bacterial from viral infection among patients with febrile ARI and was superior to procalcitonin measurement. The findings suggest that an accurate point-of-need host response test with high NPV may offer an opportunity to improve antibiotic stewardship and patient outcomes.

Diagnostic accuracy of major stroke types in Chinese adults: A clinical adjudication study involving 40,000 stroke cases

SummaryBackgroundWidespread use of brain imaging in suspected stroke cases in Chinese adults has prompted the need for clinical adjudication studies of stroke types. We conducted a clinical adjudication study to assess the reporting and diagnostic accuracy of major stroke types.MethodsThe prospective China Kadoorie Biobank recruited >512,000 adults (mean age 52 years, 59% women) from 10 urban and rural areas in China during 2004–2008, and recorded 45,859 first-ever incident stroke cases during an 11-year follow-up. Medical records were retrieved in ∼85%, and clinical details were recorded using a handheld computer for specialist physician adjudicators who applied conventional WHO clinical criteria for diagnosis of stroke. The positive predictive value (PPV) for reported and adjudicated stroke cases was examined for major stroke types (ischaemic stroke [IS], intracerebral haemorrhage [ICH], subarachnoid haemorrhage [SAH]), calendar year, area, and hospital type.FindingsOf 38,823 cases with retrieved medical records, the PPV for reported strokes was 91%. Among 29,952 adjudicated cases, the PPV for adjudicated cases was 81%, with higher PPV for ICH (n = 3391; 98%) and SAH (364; 98%) than for IS (20,473; 79%). Of 5504 cases with a verified IS diagnosis that was refuted on adjudication, 3763 (68%) had silent lacunar infarcts (LACI). The proportion of cases with silent LACI increased from 7.1% in 2004–2008 to 18.2% in 2016–2017. If cases with silent LACI were classified as IS, as advocated by new International Classification of Diseases (ICD-11) diagnostic criteria for stroke involving imaging and clinical rather than clinical criteria alone, the PPV increased to 93%.InterpretationWhile the overall reporting and diagnostic accuracy of stroke types in Chinese adults is high, the recent implementation of new diagnostic criteria for IS has important implications for contemporary clinical practice and research on stroke in Chinese populations.FundingKadoorie Charitable Foundation, Hong Kong, China, UK Wellcome Trust (212946/Z/18/Z, 202922/Z/16/Z, 104085/Z/14/Z, 088158/Z/09/Z), Chinese National Natural Science Foundation (91843302), and the National Key Research and Development Program of China (2016YFC0900500, 2016YFC0900501, 2016YFC0900504, 2016YFC1303904). British Heart Foundation, and UK Medical Research Council, and Cancer Research UK.

Temporal trends in clinical outcomes after percutaneous coronary intervention: a systematic review of 66,327 patients from 25 all-comers trials.

With the improvements of percutaneous coronary intervention (PCI) technology and post-PCI patient management, several registry studies reported temporal trends in post-PCI clinical outcomes. However, their results are inconclusive, potentially reflecting region-specific trends, based on site-reported events without external validity. This study aimed to investigate temporal trends in post-PCI clinical outcomes in all-comers randomised controlled trials (RCTs) involving coronary stents. We performed a systematic review identifying RCTs comparing a clinical outcome as a primary endpoint among different coronary stents with an all-comers design and independent clinical event adjudication, extracting the study start year, patient baseline characteristics, and one- and five-year clinical outcomes. Temporal trends in clinical outcomes (cardiac death, myocardial infarction [MI], target lesion revascularisation [TLR], stent thrombosis [ST]) were assessed using random-effects meta-regression analyses, estimating the relationship between clinical outcomes and study start year. Overall, 25 all-comers trials (51 device arms, 66,327 patients) conducted between 2003 and 2018 fulfilled the eligibility criteria. Random-effects meta-regression analysis revealed significant decreasing trends in one- and five-year cardiac death, one-year TLR, and five-year ST incidences (relative risk per 10-year increase: 0.69 [0.51-0.92], 0.66 [0.44-0.98], 0.60 [0.41-0.88], and 0.18 [0.07-0.44], respectively). There was no significant trend in myocardial infarction incidences. This is the first attempt to clarify and quantify the temporal trends of post-PCI outcome incidence. The 15-year improvements in PCI therapy and post-therapeutic patient management are associated with reduced incidences of cardiac death and PCI-related adverse events.

Incidence and Predictive Factors Associated with Beta-Lactam Neurotoxicity in the Critically Ill: A Retrospective Cohort Study.

Beta-lactam neurotoxicity is a relatively uncommon yet clinically significant adverse effect in critically ill patients. This study sought to define the incidence of neurotoxicity, derive a prediction model for beta-lactam neurotoxicity, and then validate the model in an independent cohort of critically ill adults. This retrospective cohort study evaluated critically ill patients treated with ≥ 48h of cefepime, piperacillin/tazobactam, or meropenem. Two separate cohorts were created: a derivation cohort and a validation cohort. Patients were screened for beta-lactam neurotoxicity by using search terms and diagnosis codes, followed by clinical adjudication using a standardized adverse event scoring tool. Multivariable regression models and least absolute shrinkage and selection operator were used to identify surrogates for neurotoxicity and develop a multivariable prediction model. The overall incidence of beta-lactam neurotoxicity was 2.6% (n/N = 34/1323) in the derivation cohort and 2.1% in the validation cohort (n/N = 16/767). The final multivariable neurotoxicity assessment tool included weight, Charlson comorbidity score, age, and estimated creatinine clearance as predictors of neurotoxicity. Incidence of neurotoxicity reached 4% in those with a body mass index more than 30kg/m2. Use of the candidate variables in the neurotoxicity assessment tool suggested that a score more than 35 would identify a patient at high risk for neurotoxicity with 75% sensitivity and 54% specificity. In this single center cohort of critically ill patients, beta-lactam neurotoxicity was demonstrated less frequently than previously reported. We identified obesity as a novel risk factor for the development of neurotoxicity. The prediction model needs to be further refined before it can be used in clinical practice as a tool to avoid drug-related harm.

Update of the permanent clinical impairment adjudication guide for occupational mental diseases in France

Update of the permanent clinical impairment adjudication guide for occupational mental diseases in France

Clinical events classification (CEC) in clinical trials: Report on the current landscape and future directions — proceedings from the CEC Summit 2018

Clinical events adjudication is pivotal for generating consistent and comparable evidence in clinical trials. The methodology of event adjudication is evolving, but research is needed to develop best practices and spur innovation. A meeting of stakeholders from regulatory agencies, academic and contract research organizations, pharmaceutical and device companies, and clinical trialists convened in Chicago, IL, for Clinical Events Classification (CEC) Summit 2018 to discuss key topics and future directions. Formal studies are lacking on strategies to optimize CEC conduct, improve efficiency, minimize cost, and generally increase the speed and accuracy of the event adjudication process. Major challenges to CEC discussed included ensuring rigorous quality of the process, identifying safety events, standardizing event definitions, using uniform strategies for missing information, facilitating interactions between CEC members and other trial leadership, and determining the CEC's role in pragmatic trials or trials using real-world data. Consensus recommendations from the meeting include the following: (1) ensure an adequate adjudication infrastructure; (2) use negatively adjudicated events to identify important safety events reported only outside the scope of the primary endpoint; (3) conduct further research in the use of artificial intelligence and digital/mobile technologies to streamline adjudication processes; and (4) emphasize the importance of standardizing event definitions and quality metrics of CEC programs. As novel strategies for clinical trials emerge to generate evidence for regulatory approval and to guide clinical practice, a greater understanding of the role of the CEC process will be critical to optimize trial conduct and increase confidence in the data generated.

Comparison of the Accuracy and Completeness of Records of Serious Vascular Events in Routinely Collected Data vs Clinical Trial–Adjudicated Direct Follow-up Data in the UK

Routinely collected data could substantially decrease the cost of conducting trials. To assess the accuracy and completeness of UK routine data for ascertaining serious vascular events (SVEs) compared with adjudicated follow-up data. This was a secondary analysis of a randomized clinical trial. From June 24, 2005, to July 28, 2011, the ASCEND (A Study of Cardiovascular Events in Diabetes) primary prevention trial used mail-based methods to randomize people with diabetes without evidence of atherosclerotic vascular disease using a 2 × 2 factorial design to aspirin and/or ω-fatty acids vs matching placebo in the UK. Direct participant mail-based follow-up was the main source of outcome data, with more than 90% of the primary outcome events undergoing adjudication. Follow-up was completed on July 31, 2017. In parallel, more than 99% of participants were linked to routinely collected hospital admission and death registry data (ie, routine data), enabling post hoc randomized comparisons of different sources of outcome data (conducted from September 1, 2018, to October 1, 2021). Random allocation to 100 mg of aspirin once daily vs matching placebo and separately to 1 g of ω-3 fatty acids once daily vs placebo. The primary outcome consisted of SVEs (a composite of nonfatal myocardial infarction, ischemic stroke, transient ischemic attack [TIA], or vascular death, excluding hemorrhagic stroke). A total of 15 480 participants were randomized (mean [SD] age, 63 [9] years; 9684 [62.6%] men) and followed up for a mean (SD) of 7.4 (1.8) years. For SVEs, agreement between adjudicated direct follow-up and routine data sources was strong (1401 vs 1127 events; κ = 0.78 [95% CI, 0.76-0.80]; sensitivity, 72.0% [95% CI, 69.7%-74.4%]; specificity, 99.2% [95% CI, 99.0%-99.3%]), and sensitivity improved for SVEs excluding transient ischemic attack (1129 vs 1026 events; sensitivity, 80.6% [95% CI, 78.3%-82.9%]). Rate ratios for the aspirin-randomized comparison for adjudicated direct follow-up vs follow-up solely through routine data alone were 0.88 (95% CI, 0.79-0.97) vs 0.91 (95% CI, 0.81-1.02) for the primary outcome and 0.92 (95% CI, 0.82-1.03) vs 0.91 (95% CI, 0.80-1.02) for SVEs excluding TIA. Results were similar for the ω-3 fatty acid comparison, and adjudication did not seem to markedly change rate ratios. Post hoc analyses of the ASCEND trial suggest that routinely collected hospital admission and death registry data in the UK could be used as the sole method of follow-up for myocardial infarction, ischemic stroke resulting in hospitalization, vascular death, and arterial revascularization in primary prevention cardiovascular trials, without the need for verification by clinical adjudication.

Abstract 9330: Machine Learning Can Enable the Automation of Clinical Endpoint Adjudication

Introduction: Clinical Endpoint Adjudication is a critical component of Cardiovascular (CV) clinical outcome trials and relies on manual decision making to adjudicate clinical events, including CV death. This process is resource intensive and subject to human-driven variance. As part of a broader initiative to automate data collection and analysis of clinical endpoints, we evaluated whether machine learning (ML) algorithms could replicate the outcomes of expert adjudication for CV death. Algorithms were trained on data from THEMIS (NCT01991795), a large, randomized trial comparing ticagrelor to placebo in patients with Type 2 Diabetes Mellitus. Methods: We deployed a deep learning, biomedical named entity (NE) extraction model called BERN to extract relevant NE’s from clinical text of THEMIS events. NE’s were transformed into a sparse, numerical matrix and concatenated with event-level structured features to form a data set of 962 events. Expert adjudicator consensus for CV death was used as ground truth. We trained models using grid search and cross validation, experimenting with XGBoost, Random Forest, Logistic Regression, and Naïve Bayes. Performance was assessed on a 25% (240 of 962) validation subset of the data excluded from training. Metrics used to evaluate performance were Precision, Recall, Accuracy and Area Under the Receiver Operating Characteristic Curve (AUC). Results: Best performance was observed on models trained using Naïve Bayes (&gt;97% ROC AUC on validation data), see Table. Top ranked features for classifying CV death included site investigator decision, sex, and NE’s associated with diagnoses or symptoms, such as “edema” and “chest pain.” Conclusion: With high consistency between automated and expert adjudication, our models demonstrate that machine learning may augment or even replace clinician adjudication in CV outcome trials. Subsequent research will focus on pursuing ML approaches to adjudicate other outcome events.

Abstract 13664: Identification of Myocardial Scar Using Deep Residual Network Integration of CMR Images in Ischemic Cardiomyopathy

Introduction: Ischemic scar development is a potential precursor of lethal arrhythmias and heart failure, conditions with exceptionally high mortality rates. Contrast-enhanced cardiac magnetic resonance imaging (CMR) is frequently used in clinical practice to quantify myocardial scar. With the advance of machine learning, increasing amounts of information can be garnered from CMR scans, including information that has both diagnostic and prognostic value for patients with ischemic cardiomyopathy. Hypothesis: We hypothesize that deep residual network integration combined with an augmented CMR scan selection can more accurately differentiate between patients with and without myocardial ischemic scarring. Methods: CMR scans from 170 patients, 138 with ischemic scarring and 32 controls without myocardial scarring, were collected from a tertiary care facility. CMR scans were selected to include those that had a clear visualization of the left ventricle and the surrounding myocardium. This region of interest (ROI) was then cropped. Images from patients with no myocardial scarring were additionally rotated 3 times to improve class balance. The final dataset was composed of 9,840 images from the patients with no myocardial scarring and 10,480 images with ischemic scarring. Results: Applying a ResNet-50-based convolutional neural network machine learning algorithm, we were able to identify patients with ischemic scarring at an accuracy of 75.9%. Sensitivity and specificity were 76.2% and 75.7%, respectively, with an F1 Score of 76.7%. By introducing targeted ROI selection, we were able to further improve accuracy to 81.7% with an F1 score of 82.4%. Sensitivity and specificity were also higher at 83.4% and 79.8%, respectively. The data acceptance rate of the short axis images for this implementation was 22.0%. Conclusion: Application of our residual network integration algorithm- along with targeted ROI selection- can significantly enhance the accuracy of myocardial scar detection in patients with ischemic cardiomyopathy. When tested in larger samples this is expected to aid clinical adjudication and enhance workflow.

Comparing the Diagnostic Accuracy of Clinician Judgment to a Novel Host Response Diagnostic for Acute Respiratory Illness.

Difficulty discriminating bacterial from viral infections drives antibacterial misuse. Host gene expression tests discriminate bacterial and viral etiologies, but their clinical utility has not been evaluated. Host gene expression and procalcitonin levels were measured in 582 emergency department participants with suspected infection. We also recorded clinician diagnosis and clinician-recommended treatment. These 4 diagnostic strategies were compared with clinical adjudication as the reference. To estimate the clinical impact of host gene expression, we calculated the change in overall Net Benefit (∆NB; the difference in Net Benefit comparing 1 diagnostic strategy with a reference) across a range of prevalence estimates while factoring in the clinical significance of false-positive and -negative errors. Gene expression correctly classified bacterial, viral, or noninfectious illness in 74.1% of subjects, similar to the other strategies. Clinical diagnosis and clinician-recommended treatment revealed a bias toward overdiagnosis of bacterial infection resulting in high sensitivity (92.6% and 94.5%, respectively) but poor specificity (67.2% and 58.8%, respectively), resulting in a 33.3% rate of inappropriate antibacterial use. Gene expression offered a more balanced sensitivity (79.0%) and specificity (80.7%), which corresponded to a statistically significant improvement in average weighted accuracy (79.9% vs 71.5% for procalcitonin and 76.3% for clinician-recommended treatment; P<.0001 for both). Consequently, host gene expression had greater Net Benefit in diagnosing bacterial infection than clinician-recommended treatment (∆NB=6.4%) and procalcitonin (∆NB=17.4%). Host gene expression-based tests to distinguish bacterial and viral infection can facilitate appropriate treatment, improving patient outcomes and mitigating the antibacterial resistance crisis.

Hospital management of major stroke types in Chinese adults: a population-based study of 20 000 hospitalised stroke cases

ObjectivesTo compare hospital treatments for major stroke types in Chinese adults by stroke pathological types, sex, age, calendar year, hospital tier, region and other factors.DesignCross-sectional analysis of medical records retrieved...

Breath analysis for detection and trajectory monitoring of acute respiratory distress syndrome in swine.

Despite the enormous impact on human health, acute respiratory distress syndrome (ARDS) is poorly defined, and its timely diagnosis is difficult, as is tracking the course of the syndrome. The objective of this pilot study was to explore the utility of breath collection and analysis methodologies to detect ARDS through changes in the volatile organic compound (VOC) profiles present in breath. Five male Yorkshire mix swine were studied and ARDS was induced using both direct and indirect lung injury. An automated portable gas chromatography device developed in-house was used for point of care breath analysis and to monitor swine breath hourly, starting from initiation of the experiment until the development of ARDS, which was adjudicated based on the Berlin criteria at the breath sampling points and confirmed by lung biopsy at the end of the experiment. A total of 67 breath samples (chromatograms) were collected and analysed. Through machine learning, principal component analysis and linear discrimination analysis, seven VOC biomarkers were identified that distinguished ARDS. These represent seven of the nine biomarkers found in our breath analysis study of human ARDS, corroborating our findings. We also demonstrated that breath analysis detects changes 1–6 h earlier than the clinical adjudication based on the Berlin criteria. The findings provide proof of concept that breath analysis can be used to identify early changes associated with ARDS pathogenesis in swine. Its clinical application could provide intensive care clinicians with a noninvasive diagnostic tool for early detection and continuous monitoring of ARDS.

Risk Factors for Respiratory Syncytial Virus-Associated Community Deaths in Zambian Infants.

BackgroundRespiratory syncytial virus (RSV) is a major cause of infant deaths. Its epidemiology in low- and middle-income countries is poorly understood. Risk factors associated with RSV-associated infant deaths that occur in community settings are incompletely known.MethodsCommunity deaths for infants aged 4 days to 6 months were identified during a 3-year postmortem RSV prevalence study at the main city morgue in Lusaka, Zambia, where 80% of deaths are registered. This analysis focuses on the subset of deaths for which an abbreviated verbal autopsy was available and intended to sort deaths into respiratory or nonrespiratory causes by clinical adjudication. Posterior nasopharyngeal swab samples were collected within 48 hours of death and tested for RSV using quantitative reverse-transcription polymerase chain reaction. Associations between potential risk factors were determined as relative risks with 95% confidence intervals (CIs).ResultsWe prospectively enrolled 798 community infant deaths with verbal autopsies and RSV laboratory results, of which 62 results were positive. The mean age of the infants was 10 weeks, and 41.4% of them were male. Of all deaths, 44% were attributed to respiratory causes. RSV was detected in 7.8% of the community infants and was significantly associated with respiratory deaths (risk ratio, 4.0 [95% CI, 2.2–7.1]). Compared with older infants, those aged 0–8 weeks had a 2.83 (95% CI, 1.30–6.15) increased risk of dying with RSV. The risk of RSV for the 0–8-week age group increased to 5.24 (1.56–33.14) with adjustment for demographics, parental education, and geography. RSV deaths were increased with domiciliary overcrowding and were concentrated in poor and dense neighborhoods in Lusaka (risk ratio, 2.00 [95% CI, 1.22–3.27]).ConclusionRSV is a significant contributor to community respiratory deaths in this population, particularly in the first 3 months of life and in the more poor and dense parts of Lusaka.

The relationship between coronary stent strut thickness and the incidences of clinical outcomes after drug-eluting stent implantation: A systematic review and meta-regression analysis.

Drug-eluting stents (DESs) have been developed with thinner stent struts, and more biocompatible polymers and anti-proliferative drugs to improve the clinical performance. However, it remains unclear whether thinner struts are associated with favorable short- and long-term clinical outcomes such as target lesion revascularization (TLR), periprocedural myocardial infarction (PMI), and stent thrombosis (ST). We searched MEDLINE, Embase and other online sources for randomized controlled trials (RCTs) comparing clinical outcomes between a DES and other stent(s), with independent clinical event adjudication. We investigated stent-related events (TLR, PMI, and ST) in 5 years. Each outcome was analyzed with random-effects meta-regression model against strut thickness, then adjusted for DES generation and patient and lesion characteristics. We identified 49 RCTs enrolling 97,465 patients, of which strut thickness ranged from 60 to 140 μm. Incidences of 1-year TLR, PMI, and early ST were reduced with thinner stent struts, when adjusted for stent generation (adjusted relative risk [RR] per 10μm increase 1.12 [95% CI 1.04-1.21], 1.15 [95% CI 1.05-1.26], and 1.15 [95% CI 1.06-1.25], respectively). Strut thickness was not independently associated with incidences of 5-year TLR, late and very late ST. In addition, early DESs contributed to a higher incidence of very late ST (adjusted RR 2.97 [95% CI 1.36-6.50]). In this meta-regression analysis, a thinner strut thickness was associated with reduced incidences of early stent-related adverse events (1-year TLR, PMI, and early ST), but not with later events (5-year TLR, late ST, and very late ST).

Use of multidimensional item response theory methods for dementia prevalence prediction: an example using the Health and Retirement Survey and the Aging, Demographics, and Memory Study

BackgroundData sparsity is a major limitation to estimating national and global dementia burden. Surveys with full diagnostic evaluations of dementia prevalence are prohibitively resource-intensive in many settings. However, validation samples from nationally representative surveys allow for the development of algorithms for the prediction of dementia prevalence nationally.MethodsUsing cognitive testing data and data on functional limitations from Wave A (2001–2003) of the ADAMS study (n = 744) and the 2000 wave of the HRS study (n = 6358) we estimated a two-dimensional item response theory model to calculate cognition and function scores for all individuals over 70. Based on diagnostic information from the formal clinical adjudication in ADAMS, we fit a logistic regression model for the classification of dementia status using cognition and function scores and applied this algorithm to the full HRS sample to calculate dementia prevalence by age and sex.ResultsOur algorithm had a cross-validated predictive accuracy of 88% (86–90), and an area under the curve of 0.97 (0.97–0.98) in ADAMS. Prevalence was higher in females than males and increased over age, with a prevalence of 4% (3–4) in individuals 70–79, 11% (9–12) in individuals 80–89 years old, and 28% (22–35) in those 90 and older.ConclusionsOur model had similar or better accuracy as compared to previously reviewed algorithms for the prediction of dementia prevalence in HRS, while utilizing more flexible methods. These methods could be more easily generalized and utilized to estimate dementia prevalence in other national surveys.

A 29-mRNA host response test from blood accurately distinguishes bacterial and viral infections among emergency department patients

BackgroundWhether or not to administer antibiotics is a common and challenging clinical decision in patients with suspected infections presenting to the emergency department (ED). We prospectively validate InSep, a 29-mRNA blood-based host response test for the prediction of bacterial and viral infections.MethodsThe PROMPT trial is a prospective, non-interventional, multi-center clinical study that enrolled 397 adult patients presenting to the ED with signs of acute infection and at least one vital sign change. The infection status was adjudicated using chart review (including a syndromic molecular respiratory panel, procalcitonin and C-reactive protein) by three infectious disease physicians blinded to InSep results. InSep (version BVN-2) was performed using PAXgene Blood RNA processed and quantified on NanoString nCounter SPRINT. InSep results (likelihood of bacterial and viral infection) were compared to the adjudicated infection status.ResultsSubject mean age was 64 years, comorbidities were significant for diabetes (17.1%), chronic obstructive pulmonary disease (13.6%), and severe neurological disease (6.8%); 16.9% of subjects were immunocompromised. Infections were adjudicated as bacterial (14.1%), viral (11.3%) and noninfected (0.25%): 74.1% of subjects were adjudicated as indeterminate. InSep distinguished bacterial vs. viral/noninfected patients and viral vs. bacterial/noninfected patients using consensus adjudication with AUROCs of 0.94 (95% CI 0.90–0.99) and 0.90 (95% CI 0.83–0.96), respectively. AUROCs for bacterial vs. viral/noninfected patients were 0.88 (95% CI 0.79–0.96) for PCT, 0.80 (95% CI 0.72–89) for CRP and 0.78 (95% CI 0.69–0.87) for white blood cell counts (of note, the latter biomarkers were provided as part of clinical adjudication). To enable clinical actionability, InSep incorporates score cutoffs to allocate patients into interpretation bands. The Very Likely (rule in) InSep bacterial band showed a specificity of 98% compared to 94% for the corresponding PCT band (> 0.5 µg/L); the Very Unlikely (rule-out) band showed a sensitivity of 95% for InSep compared to 86% for PCT. For the detection of viral infections, InSep demonstrated a specificity of 93% for the Very Likely band (rule in) and a sensitivity of 96% for the Very Unlikely band (rule out).ConclusionsInSep demonstrated high accuracy for predicting the presence of both bacterial and viral infections in ED patients with suspected acute infections or suspected sepsis. When translated into a rapid, point-of-care test, InSep will provide ED physicians with actionable results supporting early informed treatment decisions to improve patient outcomes while upholding antimicrobial stewardship.Registration number at Clinicaltrials.gov NCT 03295825.

A non-contact device for fast screening of wound infections.

Screening for wound infection relies on the expertise of the provider. Clinical diagnosis of infections based on wound swab/biopsy results often takes a few days and may not assess the full wound. There is a need for a non-invasive tool that can quickly and accurately diagnose wound infection. Leukocyte esterase strips are used to identify various infectious diseases. However, it is not clear whether infected wounds also have elevated leukocyte esterase activities as compared with non-infected wounds. To achieve the objective, a device was developed to detect elevated leukocyte esterase activities in wounds by measuring wound exudates adsorbed onto wound dressings in 3minutes. The efficacy of the device in assessing leukocyte esterase activities across various chronic wounds was tested. Such measurements were unaffected by the type of underlying wound dressing. By correlating the device outputs with clinical adjudication of infection, we found that this device had high positive predictive values for diagnosing wound infection in a wide variety of chronic wounds. In addition, a positive device output increases the probability of detecting infected wounds, while the negative device output reduces the probability of detecting infected wounds. This rapid non-contact and disposable diagnostic tool may serve as a rapid and accurate indication of infection in the chronic wound.

Consensus disease definitions for the spectrum of neurologic immune related adverse events.

2647 Background: Expanding FDA-approved indications for immune checkpoint inhibitors in patients with cancer has resulted in both therapeutic success and immune related adverse events (irAEs). Neurologic irAEs (irAE-Ns) have an incidence of 1-12% and a high fatality rate relative to other irAEs. Lack of standardized disease definitions and accurate phenotyping leads to syndrome misclassification and impedes evidence-based treatments and research progress. The objectives of this study were to develop consensus guidance for an approach to irAE-Ns including disease definitions and severity grading. Methods: A working group of 4 neurologists drafted irAE-N consensus guidance and definitions, which were reviewed by the Neuro irAE Disease Definition Panel, consisting of neurologists, oncologists, neuro-oncologists and irAE subspecialists. A modified Delphi consensus process was used, with 2 rounds of anonymous ratings by panelists and 2 virtual meetings to discuss areas of controversy. Panelists rated content for usability, appropriateness and accuracy on 9-point scales in electronic surveys and provided free text comments. The working group aggregated survey responses and incorporated them into revised definitions. Consensus was based on numeric ratings using the RAND/UCLA Appropriateness Method with prespecified definitions. Results: Twenty-seven panelists from 15 academic medical centers voted on a total of 53 rating scales (6 general guidance, 24 central and 18 peripheral nervous system disease definition components, 3 severity criteria and 2 clinical trial adjudication statements); of these, 77% (41/53) received first round consensus. After revisions, all items received second round consensus. Consensus definitions were achieved for 7 core disorders: irMeningitis, irEncephalitis/Encephalomyelitis, irDemyelinating disease, irVasculitis, irNeuropathy, irNeuromuscular junction disorders and irMyopathy. For each disorder, 6 sub-classifications are described: disease subtype, diagnostic certainty, severity, autoantibody association, exacerbation of pre-existing disease or de novo presentation and present or absent concurrent irAE. Conclusions: These disease definitions standardize irAE-N classification. They are being incorporated into a multi-institutional registry that our group has initiated to study irAEs. Given consensus on their accuracy and usability from a representative panel group, we anticipate that they can be used broadly across clinical and research settings.

Accuracy of Cardiovascular Trial Outcome Ascertainment and Treatment Effect Estimates from Routine Health Data: A Systematic Review and Meta-Analysis.

Registry-based randomized controlled trials allow for outcome ascertainment using routine health data (RHD). While this method provides a potential solution to the rising cost and complexity of clinical trials, comparative analyses of outcome ascertainment by clinical end point committee (CEC) adjudication compared with RHD sources are sparse. Among cardiovascular trials, we set out to systematically compare the incidence of cardiovascular events and estimated randomized treatment effects ascertained from RHD versus traditional clinical evaluation and adjudication. We searched MEDLINE (1976 to August 2020) for studies where outcome ascertainment was performed by both RHD and CEC adjudication to compare the incidence of cardiovascular events and treatment effects. We derived ratios of hazard ratios to compare treatment effects from RHD and CEC adjudication. We pooled ratios of hazard ratios using an inverse variance random-effects meta-analysis. Nine studies (1988-2020; 32 156 patients) involving 10 randomized control trials compared outcome ascertainment with RHD and CEC in patients with or at risk of cardiovascular disease. There was a high degree of agreement and interrater reliability between CEC and RHD outcome determination for all-cause mortality (agreement percentage: 98.4%-100% and κ: 0.95-1.0) and cardiovascular mortality (agreement percentage: 97.8%-99.9% and κ: 0.66-0.99). For myocardial infarction, the κ values ranged from 0.67-0.98, and for stroke the values ranged from 0.52-0.89. In contrast, the κ value for peripheral artery disease was low (κ: 0.27). There was little difference in the randomized treatment effect derived from CEC and RHD ascertainment of events based on the ratios of hazard ratio, with pooled ratios of hazard ratios ranging from 0.93 (95% CI, 0.63-1.39) for cardiovascular mortality to 1.27 (95% CI, 0.67-2.41) for stroke. Clinical outcome ascertainment using retrospectively acquired RHD displayed high levels of agreement with CEC adjudication for identifying all-cause mortality and cardiovascular outcomes. Importantly, cardiovascular treatment effects in randomized control trials determined from RHD and CEC resulted in similar point estimates. Overall, our review supports the use of RHD as a potential alternative source for clinical outcome ascertainment in cardiovascular trials. Validation studies with prospectively planned linkage are warranted.

Discriminating Bacterial and Viral Infection Using a Rapid Host Gene Expression Test.

Host gene expression signatures discriminate bacterial and viral infection but have not been translated to a clinical test platform. This study enrolled an independent cohort of patients to describe and validate a first-in-class host response bacterial/viral test. Subjects were recruited from 2006 to 2016. Enrollment blood samples were collected in an RNA preservative and banked for later testing. The reference standard was an expert panel clinical adjudication, which was blinded to gene expression and procalcitonin results. Four U.S. emergency departments. Six-hundred twenty-three subjects with acute respiratory illness or suspected sepsis. Forty-five-transcript signature measured on the BioFire FilmArray System (BioFire Diagnostics, Salt Lake City, UT) in ~45 minutes. Host response bacterial/viral test performance characteristics were evaluated in 623 participants (mean age 46 yr; 45% male) with bacterial infection, viral infection, coinfection, or noninfectious illness. Performance of the host response bacterial/viral test was compared with procalcitonin. The test provided independent probabilities of bacterial and viral infection in ~45 minutes. In the 213-subject training cohort, the host response bacterial/viral test had an area under the curve for bacterial infection of 0.90 (95% CI, 0.84-0.94) and 0.92 (95% CI, 0.87-0.95) for viral infection. Independent validation in 209 subjects revealed similar performance with an area under the curve of 0.85 (95% CI, 0.78-0.90) for bacterial infection and 0.91 (95% CI, 0.85-0.94) for viral infection. The test had 80.1% (95% CI, 73.7-85.4%) average weighted accuracy for bacterial infection and 86.8% (95% CI, 81.8-90.8%) for viral infection in this validation cohort. This was significantly better than 68.7% (95% CI, 62.4-75.4%) observed for procalcitonin (p < 0.001). An additional cohort of 201 subjects with indeterminate phenotypes (coinfection or microbiology-negative infections) revealed similar performance. The host response bacterial/viral measured using the BioFire System rapidly and accurately discriminated bacterial and viral infection better than procalcitonin, which can help support more appropriate antibiotic use.