Light curves and colours of the ejecta from Dimorphos after the DART impact.

On 26 September 2022, the Double Asteroid Redirection Test (DART) spacecraft struck Dimorphos, a satellite of the asteroid 65803 Didymos1. Because it is a binary system, it is possible to determine how much the orbit of the satellite changed, as part of a test of what is necessary to deflect an asteroid that might threaten Earth with an impact. In nominal cases, pre-impact predictions of the orbital period reduction ranged from roughly 8.8 to 17 min (refs. 2,3). Here we report optical observations of Dimorphos before, during and after the impact, from a network of citizen scientists' telescopes across the world. We find a maximum brightening of 2.29 ± 0.14 mag on impact. Didymos fades back to its pre-impact brightness over the course of 23.7 ± 0.7 days. We estimate lower limits on the mass contained in the ejecta, which was 0.3-0.5% Dimorphos's mass depending on the dust size. We also observe a reddening of the ejecta on impact.

Determination of Clinically Acceptable Analytical Variation of Cardiac Troponin at Decision Thresholds.

BACKGROUND: Clinical decision-making for risk stratification for possible myocardial infarction (MI) uses high-sensitivity cardiac troponin (hs-cTn) thresholds that range from the limit of detection to several-fold higher than the upper reference limit (URL). To establish a minimum analytical variation standard, we can quantify the effect of variation on the population clinical measures of safety (sensitivity) and effectiveness [proportion below threshold, or positive predictive value (PPV)]. METHODS: From large datasets of patients investigated for possible MI with the Abbott hs-cTnI and Roche hs-cTnT assays, we synthesized datasets of 1 000 000 simulated patients. Troponin concentrations were randomly varied several times based on absolute deviations of 0.5 to 3 ng/L and relative changes of 2% to 20% around the low-risk threshold (5 ng/L) and URLs, respectively. RESULTS: For both assays at the low-risk thresholds, there were negligible differences in sensitivity (<0.3%) with increasing analytical variation. The proportion of patients characterized as low risk reduced by 30% to 29% (Roche) and 53% to 44% (Abbott). At the URL, increasing analytical variation also did not change sensitivity; the PPV fell by less than 3%. For risk stratification, increased delta thresholds (change between serial troponin concentrations) increased sensitivity at the cost of a decreased percentage of patients below the delta threshold, with the largest changes at the greatest analytical variation. CONCLUSIONS: At the low-risk threshold, analytical variation up to 3 ng/L minimally impacted the safety metric (sensitivity) but marginally reduced effectiveness. Similarly, at the URL even relative variation up to 25% minimally impacted safety metrics and effectiveness. Analytical variation for delta thresholds did not negatively impact sensitivity but decreased effectiveness.

Analytical verification of the Atellica VTLi point of care high sensitivity troponin I assay.

OBJECTIVES: The Siemens Point-of-Care Testing (POC) Atellica® VTLi high-sensitivity troponin I (hsTnI) device has been previously validated. Verification independently provides evidence that an analytical procedure fulfils concordance with laboratory assays, imprecision, and hemolysis interference requirements. METHODS: Five whole blood samples spanning the measuring interval were analysed 20 times in succession. Hemolysis interference was assessed at three troponin concentrations by spiking five hemolysate concentrations to plasma to achieve free hemoglobin concentrations 35-1,000 mg/dL. Concordance between whole blood (VTLi) and plasma on laboratory analysers (Beckman, Roche, Siemens) was assessed by Pearson correlation and kappa statistics at the (LOQ) and upper reference limit (URL). This was repeated for frozen plasma samples. RESULTS: Coefficients of variation for whole blood were <10 % for whole blood troponin concentrations of 9.2 and 15.9 ng/L, thus below the URL. Hemolysis positively interfered; at 250 mg/dL affecting the low troponin sample (+3 ng/L; +60 %) and high troponin sample (+37 ng/L; +24 %). Correlation coefficients were 0.98, 0.90 and 0.97 between VTLi and Beckman, Roche and Siemens assays respectively. Corresponding kappa statistics were 0.80, 0.73 and 0.84 at the LOQ and 0.70, 0.44 and 0.67 at the URL. CONCLUSIONS: Concordances between VTLi and laboratory assays were at least non-inferior to those between laboratory assays. Imprecision met manufacturer claims and was consistent with a high sensitivity assay. There is potential for hemolysis interference, highlighting the need for quality samples. The results support performance characteristics previously reported in validation studies, and the device offers acceptable performance for use within intended medical settings.

Chronic health conditions and mortality among older adults with complex care needs in Aotearoa New Zealand.

BACKGROUND: Older people have more comorbidities than younger groups and multimorbidity will increase. Often chronic conditions affect quality of life, functional ability and social participation. Our study aim was to quantify the prevalence of chronic conditions over a three-year period and their association with mortality after accounting for demographics. METHODS: We conducted a retrospective cohort study using routinely collected health data including community-dwelling older adults in New Zealand who had an interRAI Home Care assessment between 1 January 2017 and 31 December 2017. Descriptive statistics and differences between variables of interest among ethnic groups were reported. Cumulative density plots of mortality were developed. Logistic regression models adjusted for age and sex to estimate mortality were created independently for each combination of ethnicity and disease diagnosis. RESULTS: The study cohort consisted of 31,704 people with a mean (SD) age of 82.3 years (8.0), and of whom 18,997 (59.9%) were female. Participants were followed for a median 1.1 (range 0 to 3) years. By the end of the follow-up period 15,678 (49.5%) people had died. Nearly 62% of Maori and Pacific older adults and 57% of other ethnicities had cognitive impairment. Diabetes the next most prevalent amongst Maori and Pacific peoples, and coronary heart disease amongst Non-Maori/Non-Pacific individuals. Of the 5,184 (16.3%) who had congestive heart failure (CHF), 3,450 (66.6%) died. This was the highest mortality rate of any of the diseases. There was a decrease in mortality rate with age for both sexes and all ethnicities for those with cancer. CONCLUSIONS: Cognitive impairment was the most common condition in community dwelling older adults who had an interRAI assessment. Cardiovascular disease (CVD) has the highest mortality risk for all ethnic groups, and in non-Maori/non-Pacific group of advanced age, risk of mortality with cognitive impairment is as high as CVD risk. We observed an inverse for cancer mortality risk with age. Important differences between ethnic groups are reported.

Performance of the European Society of Cardiology 0/1-Hour, 0/2-Hour, and 0/3-Hour Algorithms for Rapid Triage of Acute Myocardial Infarction : An International Collaborative Meta-analysis.

BACKGROUND: The 2020 European Society of Cardiology (ESC) guidelines recommend using the 0/1-hour and 0/2-hour algorithms over the 0/3-hour algorithm as the first and second choices of high-sensitivity cardiac troponin (hs-cTn)-based strategies for triage of patients with suspected acute myocardial infarction (AMI). PURPOSE: To evaluate the diagnostic accuracies of the ESC 0/1-hour, 0/2-hour, and 0/3-hour algorithms. DATA SOURCES: PubMed, Embase, Cochrane Central Register of Controlled Trials, Web of Science, and Scopus from 1 January 2011 to 31 December 2020. (PROSPERO: CRD42020216479). STUDY SELECTION: Prospective studies that evaluated the ESC 0/1-hour, 0/2-hour, or 0/3-hour algorithms in adult patients presenting with suspected AMI. DATA EXTRACTION: The primary outcome was index AMI. Twenty unique cohorts were identified. Primary data were obtained from investigators of 16 cohorts and aggregate data were extracted from 4 cohorts. Two independent authors assessed each study for methodological quality. DATA SYNTHESIS: A total of 32 studies (20 cohorts) with 30 066 patients were analyzed. The 0/1-hour algorithm had a pooled sensitivity of 99.1% (95% CI, 98.5% to 99.5%) and negative predictive value (NPV) of 99.8% (CI, 99.6% to 99.9%) for ruling out AMI. The 0/2-hour algorithm had a pooled sensitivity of 98.6% (CI, 97.2% to 99.3%) and NPV of 99.6% (CI, 99.4% to 99.8%). The 0/3-hour algorithm had a pooled sensitivity of 93.7% (CI, 87.4% to 97.0%) and NPV of 98.7% (CI, 97.7% to 99.3%). Sensitivity of the 0/3-hour algorithm was attenuated in studies that did not use clinical criteria (GRACE score <140 and pain-free) compared with studies that used clinical criteria (90.2% [CI, 82.9 to 94.6] vs. 98.4% [CI, 88.6 to 99.8]). All 3 algorithms had similar specificities and positive predictive values for ruling in AMI, but heterogeneity across studies was substantial. Diagnostic performance was similar across the hs-cTnT (Elecsys; Roche), hs-cTnI (Architect; Abbott), and hs-cTnI (Centaur/Atellica; Siemens) assays. LIMITATION: Diagnostic accuracy, inclusion and exclusion criteria, and cardiac troponin sampling time varied among studies. CONCLUSION: The ESC 0/1-hour and 0/2-hour algorithms have higher sensitivities and NPVs than the 0/3-hour algorithm for index AMI. PRIMARY FUNDING SOURCE: National Taiwan University Hospital.

Leukocyte surface biomarkers implicate deficits of innate immunity in sporadic Alzheimer's disease.

INTRODUCTION: Blood-based diagnostics and prognostics in sporadic Alzheimer's disease (AD) are important for identifying at-risk individuals for therapeutic interventions. METHODS: In three stages, a total of 34 leukocyte antigens were examined by flow cytometry immunophenotyping. Data were analyzed by logistic regression and receiver operating characteristic (ROC) analyses. RESULTS: We identified leukocyte markers differentially expressed in the patients with AD. Pathway analysis revealed a complex network involving upregulation of complement inhibition and downregulation of cargo receptor activity and Aß clearance. A proposed panel including four leukocyte markers - CD11c, CD59, CD91, and CD163 - predicts patients' PET Aß status with an area under the curve (AUC) of 0.93 (0.88 to 0.97). CD163 was the top performer in preclinical models. These findings have been validated in two independent cohorts. CONCLUSION: Our finding of changes on peripheral leukocyte surface antigens in AD implicates the deficit in innate immunity. Leukocyte-based biomarkers prove to be both sensitive and practical for AD screening and diagnosis.

Comparison of SPEED, S-Trap, and In-Solution-Based Sample Preparation Methods for Mass Spectrometry in Kidney Tissue and Plasma.

Mass spectrometry is a powerful technique for investigating renal pathologies and identifying biomarkers, and efficient protein extraction from kidney tissue is essential for bottom-up proteomic analyses. Detergent-based strategies aid cell lysis and protein solubilization but are poorly compatible with downstream protein digestion and liquid chromatography-coupled mass spectrometry, requiring additional purification and buffer-exchange steps. This study compares two well-established detergent-based methods for protein extraction (in-solution sodium deoxycholate (SDC); suspension trapping (S-Trap)) with the recently developed sample preparation by easy extraction and digestion (SPEED) method, which uses strong acid for denaturation. We compared the quantitative performance of each method using label-free mass spectrometry in both sheep kidney cortical tissue and plasma. In kidney tissue, SPEED quantified the most unique proteins (SPEED 1250; S-Trap 1202; SDC 1197). In plasma, S-Trap produced the most unique protein quantifications (S-Trap 150; SDC 148; SPEED 137). Protein quantifications were reproducible across biological replicates in both tissue (R2 = 0.85-0.90) and plasma (SPEED R2 = 0.84; SDC R2 = 0.76, S-Trap R2 = 0.65). Our data suggest SPEED as the optimal method for proteomic preparation in kidney tissue and S-Trap or SPEED as the optimal method for plasma, depending on whether a higher number of protein quantifications or greater reproducibility is desired.

Application of High-Sensitivity Troponin in Suspected Myocardial Infarction.

BACKGROUND: Data regarding high-sensitivity troponin concentrations in patients presenting to the emergency department with symptoms suggestive of myocardial infarction may be useful in determining the probability of myocardial infarction and subsequent 30-day outcomes. METHODS: In 15 international cohorts of patients presenting to the emergency department with symptoms suggestive of myocardial infarction, we determined the concentrations of high-sensitivity troponin I or high-sensitivity troponin T at presentation and after early or late serial sampling. The diagnostic and prognostic performance of multiple high-sensitivity troponin cutoff combinations was assessed with the use of a derivation-validation design. A risk-assessment tool that was based on these data was developed to estimate the risk of index myocardial infarction and of subsequent myocardial infarction or death at 30 days. RESULTS: Among 22,651 patients (9604 in the derivation data set and 13,047 in the validation data set), the prevalence of myocardial infarction was 15.3%. Lower high-sensitivity troponin concentrations at presentation and smaller absolute changes during serial sampling were associated with a lower likelihood of myocardial infarction and a lower short-term risk of cardiovascular events. For example, high-sensitivity troponin I concentrations of less than 6 ng per liter and an absolute change of less than 4 ng per liter after 45 to 120 minutes (early serial sampling) resulted in a negative predictive value of 99.5% for myocardial infarction, with an associated 30-day risk of subsequent myocardial infarction or death of 0.2%; a total of 56.5% of the patients would be classified as being at low risk. These findings were confirmed in an external validation data set. CONCLUSIONS: A risk-assessment tool, which we developed to integrate the high-sensitivity troponin I or troponin T concentration at emergency department presentation, its dynamic change during serial sampling, and the time between the obtaining of samples, was used to estimate the probability of myocardial infarction on emergency department presentation and 30-day outcomes. (Funded by the German Center for Cardiovascular Research [DZHK]; ClinicalTrials.gov numbers, NCT00470587, NCT02355457, NCT01852123, NCT01994577, and NCT03227159; and Australian New Zealand Clinical Trials Registry numbers, ACTRN12611001069943, ACTRN12610000766011, ACTRN12613000745741, and ACTRN12611000206921.).

Development and validation of a frailty index compatible with three interRAI assessment instruments.

BACKGROUND: a Frailty Index (FI) calculated by the accumulation of deficits is often used to quantify the extent of frailty in individuals in specific settings. This study aimed to derive a FI that can be applied across three standardised international Residential Assessment Instrument assessments (interRAI), used at different stages of ageing and the corresponding increase in support needs. METHODS: deficit items common to the interRAI Contact Assessment (CA), Home Care (HC) or Long-Term Care Facilities assessment (LTCF) were identified and recoded to form a cumulative deficit FI. The index was validated using a large dataset of needs assessments of older people in New Zealand against mortality prediction using Kaplan Meier curves and logistic regression models. The index was further validated by comparing its performance with a previously validated index in the HC cohort. RESULTS: the index comprised 15 questions across seven domains. The assessment cohort and their mean frailty (SD) were: 89,506 CA with 0.26 (0.15), 151,270 HC with 0.36 (0.15) and 83,473 LTCF with 0.41 (0.17). The index predicted 1-year mortality for each of the CA, HC and LTCF, cohorts with area under the receiver operating characteristic curves (AUCs) of 0.741 (95% confidence interval, CI: 0.718-0.762), 0.687 (95%CI: 0.684-0.690) and 0.674 (95%CI: 0.670-0.678), respectively. CONCLUSIONS: the results for this multi-instrument FI are congruent with the differences in frailty expected for people in the target settings for these instruments and appropriately associated with mortality at each stage of the journey of progressive ageing.

Sensitivity of modern multislice CT for subarachnoid haemorrhage at incremental timepoints after headache onset: a 10-year analysis.

BACKGROUND: CT performed within 6 hours of headache onset is highly sensitive for the detection of subarachnoid haemorrhage (SAH). Beyond this time frame, if the CT is negative for blood, a lumbar puncture is often performed. Technology improvements in image noise reduction, resolution and motion artefact have enhanced the performance of multislice CT (MSCT) and may have further improved sensitivity. We aimed to describe how the sensitivity to SAH of modern MSCT changes with time from headache onset. METHODS: This was a retrospective analysis of electronic data collected as part of routine care among all patients presenting to Christchurch Hospital diagnosed with a SAH between 1 January 2008 and 31 December 2017. Patients were imaged with MSCT. The primary outcome was the proportion of patients with spontaneous aneurysmal SAH (identified via coding and confirmed by clinical and radiological records) that had a positive MSCT. The secondary outcome was the proportion of patients with any type of spontaneous SAH that had a positive MSCT. RESULTS: There were 347 patients with an SAH of whom 260 were aneurysmal SAH. MSCT identified 253 (97.3%) of all aneurysmal SAH and 332 (95.7%) of all SAH. The sensitivity of MSCT was 99.6% (95% CI 97.6 to 100) for aneurysmal SAH and 99.0% (95% CI 97.1 to 99.8) for all SAH at 48 hours after headache onset. At 24 hours after headache onset, the sensitivity for aneurysmal SAH was 100% (95% CI 98.3 to 100). CONCLUSION: These data suggest that it may be possible to extend the timeframe from headache onset within which modern MSCT can be used to rule out aneurysmal SAH.

Identifying Candidate Protein Markers of Acute Kidney Injury in Acute Decompensated Heart Failure.

One-quarter of patients with acute decompensated heart failure (ADHF) experience acute kidney injury (AKI)-an abrupt reduction or loss of kidney function associated with increased long-term mortality. There is a critical need to identify early and real-time markers of AKI in ADHF; however, to date, no protein biomarkers have exhibited sufficient diagnostic or prognostic performance for widespread clinical uptake. We aimed to identify novel protein biomarkers of AKI associated with ADHF by quantifying changes in protein abundance in the kidneys that occur during ADHF development and recovery in an ovine model. Relative quantitative protein profiling was performed using sequential window acquisition of all theoretical fragment ion spectra-mass spectrometry (SWATH-MS) in kidney cortices from control sheep (n = 5), sheep with established rapid-pacing-induced ADHF (n = 8), and sheep after ~4 weeks recovery from ADHF (n = 7). Of the 790 proteins quantified, we identified 17 candidate kidney injury markers in ADHF, 1 potential kidney marker of ADHF recovery, and 2 potential markers of long-term renal impairment (differential abundance between groups of 1.2-2.6-fold, adjusted p < 0.05). Among these 20 candidate protein markers of kidney injury were 6 candidates supported by existing evidence and 14 novel candidates not previously implicated in AKI. Proteins of differential abundance were enriched in pro-inflammatory signalling pathways: glycoprotein VI (activated during ADHF development; adjusted p < 0.01) and acute phase response (repressed during recovery from ADHF; adjusted p < 0.01). New biomarkers for the early detection of AKI in ADHF may help us to evaluate effective treatment strategies to prevent mortality and improve outcomes for patients.

Prioritizing Candidates of Post-Myocardial Infarction Heart Failure Using Plasma Proteomics and Single-Cell Transcriptomics.

BACKGROUND: Heart failure (HF) is the most common long-term complication of acute myocardial infarction (MI). Understanding plasma proteins associated with post-MI HF and their gene expression may identify new candidates for biomarker and drug target discovery. METHODS: We used aptamer-based affinity-capture plasma proteomics to measure 1305 plasma proteins at 1 month post-MI in a New Zealand cohort (CDCS [Coronary Disease Cohort Study]) including 181 patients post-MI who were subsequently hospitalized for HF in comparison with 250 patients post-MI who remained event free over a median follow-up of 4.9 years. We then correlated plasma proteins with left ventricular ejection fraction measured at 4 months post-MI and identified proteins potentially coregulated in post-MI HF using weighted gene co-expression network analysis. A Singapore cohort (IMMACULATE [Improving Outcomes in Myocardial Infarction through Reversal of Cardiac Remodelling]) of 223 patients post-MI, of which 33 patients were hospitalized for HF (median follow-up, 2.0 years), was used for further candidate enrichment of plasma proteins by using Fisher meta-analysis, resampling-based statistical testing, and machine learning. We then cross-referenced differentially expressed proteins with their differentially expressed genes from single-cell transcriptomes of nonmyocyte cardiac cells isolated from a murine MI model, and single-cell and single-nucleus transcriptomes of cardiac myocytes from murine HF models and human patients with HF. RESULTS: In the CDCS cohort, 212 differentially expressed plasma proteins were significantly associated with subsequent HF events. Of these, 96 correlated with left ventricular ejection fraction measured at 4 months post-MI. Weighted gene co-expression network analysis prioritized 63 of the 212 proteins that demonstrated significantly higher correlations among patients who developed post-MI HF in comparison with event-free controls (data set 1). Cross-cohort meta-analysis of the IMMACULATE cohort identified 36 plasma proteins associated with post-MI HF (data set 2), whereas single-cell transcriptomes identified 15 gene-protein candidates (data set 3). The majority of prioritized proteins were of matricellular origin. The 6 most highly enriched proteins that were common to all 3 data sets included well-established biomarkers of post-MI HF: N-terminal B-type natriuretic peptide and troponin T, and newly emergent biomarkers, angiopoietin-2, thrombospondin-2, latent transforming growth factor-ß binding protein-4, and follistatin-related protein-3, as well. CONCLUSIONS: Large-scale human plasma proteomics, cross-referenced to unbiased cardiac transcriptomics at single-cell resolution, prioritized protein candidates associated with post-MI HF for further mechanistic and clinical validation.

Emerging microRNA biomarkers for acute kidney injury in acute decompensated heart failure.

Acute decompensated heart failure (ADHF) is associated with a high incidence of acute kidney injury (AKI), an abrupt loss of kidney function associated with a near doubling of mortality at 1 year. In addition to the direct threat acute HF itself poses to kidney function, the beneficial effects of commonly prescribed HF treatments must be weighed against their potentially adverse effects on glomerular perfusion. Consequently, there is an urgent need to identify early markers for AKI in ADHF to facilitate timely implementation of supportive measures to minimize kidney damage and improve outcomes. The recent recognition of the diagnostic potential of circulating microRNAs presents the potential to address this gap if microRNAs specific for AKI can be identified in serial plasma, serum and/or urine samples from well-phenotyped cohorts of ADHF patients, including a proportion with AKI. This review summarizes emerging circulating diagnostic and prognostic microRNA biomarkers (serum, plasma or urine) in HF and AKI.

Long-term outcomes in patients with pulmonary embolism: results from a longitudinal cohort study.

BACKGROUND: Patients with pulmonary embolism (PE) have increased mortality in short-term; however, long-term prognosis is not well defined. AIM: In this long-term cohort study, we aimed to determine if PE was associated with increased risk of mortality or serious clinical events (SCE). Secondary aims were to ascertain predictors of mortality and SCE. METHODS: Patients admitted with clinical suspicion of PE were prospectively recruited from July 2002 to May 2003 and followed up until March 2015. Clinical outcomes in patients with PE were compared to those without PE. SCE was defined as composite of mortality, malignancy, cardiovascular events, recurrent venous thromboembolism and chronic thromboembolic pulmonary hypertension. RESULTS: A total of 501 patients with median follow up of 11.9 years (interquartile range 3.91-12.28) was included. PE was diagnosed in 104 (20.7%) patients. Overall, 45.9% died and 57.1% developed SCE during follow up, with no significant difference in PE and no-PE groups (both P > 0.5). Major determinants of mortality were age (hazard ratio (HR) 1.06 per year, 95% confidence interval (CI) 1.05-1.08), malignancy (HR 2.19, 95% CI 1.64-2.91) and congestive heart failure (HR 1.72, 95% CI 1.23-2.42). Factors associated with increased risk of SCE were age (HR 1.05 per year, 95% CI 1.04-1.06), malignancy (HR 1.93, 95% CI 1.48-2.52) and congestive heart failure (HR 1.77, 95% CI 1.29-2.43). In patients without PE, elevated D-dimer concentration was not found to be associated with diagnosis of malignancy during follow up (HR 1.31, 95% CI 0.55-3.12). CONCLUSIONS: In this prospective study, we did not find association between PE and risk of all-cause mortality or SCE. Major determinants of poor clinical outcomes were advancing age and underlying comorbidities.

Machine Learning to Predict the Likelihood of Acute Myocardial Infarction.

BACKGROUND: Variations in cardiac troponin concentrations by age, sex, and time between samples in patients with suspected myocardial infarction are not currently accounted for in diagnostic approaches. We aimed to combine these variables through machine learning to improve the assessment of risk for individual patients. METHODS: A machine learning algorithm (myocardial-ischemic-injury-index [MI3]) incorporating age, sex, and paired high-sensitivity cardiac troponin I concentrations, was trained on 3013 patients and tested on 7998 patients with suspected myocardial infarction. MI3 uses gradient boosting to compute a value (0-100) reflecting an individual's likelihood of a diagnosis of type 1 myocardial infarction and estimates the sensitivity, negative predictive value, specificity and positive predictive value for that individual. Assessment was by calibration and area under the receiver operating characteristic curve. Secondary analysis evaluated example MI3 thresholds from the training set that identified patients as low risk (99% sensitivity) and high risk (75% positive predictive value), and performance at these thresholds was compared in the test set to the 99th percentile and European Society of Cardiology rule-out pathways. RESULTS: Myocardial infarction occurred in 404 (13.4%) patients in the training set and 849 (10.6%) patients in the test set. MI3 was well calibrated with a very high area under the receiver operating characteristic curve of 0.963 [0.956-0.971] in the test set and similar performance in early and late presenters. Example MI3 thresholds identifying low- and high-risk patients in the training set were 1.6 and 49.7, respectively. In the test set, MI3 values were <1.6 in 69.5% with a negative predictive value of 99.7% (99.5-99.8%) and sensitivity of 97.8% (96.7-98.7%), and were ≥49.7 in 10.6% with a positive predictive value of 71.8% (68.9-75.0%) and specificity of 96.7% (96.3-97.1%). Using these thresholds, MI3 performed better than the European Society of Cardiology 0/3-hour pathway (sensitivity, 82.5% [74.5-88.8%]; specificity, 92.2% [90.7-93.5%]) and the 99th percentile at any time point (sensitivity, 89.6% [87.4-91.6%]); specificity, 89.3% [88.6-90.0%]). CONCLUSIONS: Using machine learning, MI3 provides an individualized and objective assessment of the likelihood of myocardial infarction, which can be used to identify low- and high-risk patients who may benefit from earlier clinical decisions. CLINICAL TRIAL REGISTRATION: URL: https://www.anzctr.org.au. Unique identifier: ACTRN12616001441404.

Early acetaminophen-protein adducts predict hepatotoxicity following overdose (ATOM-5).

BACKGROUND & AIMS: Acetaminophen-protein adducts are specific biomarkers of toxic acetaminophen (paracetamol) metabolite exposure. In patients with hepatotoxicity (alanine aminotransferase [ALT] >1,000 U/L), an adduct concentration ≥1.0 nmol/ml is sensitive and specific for identifying cases secondary to acetaminophen. Our aim was to characterise acetaminophen-protein adduct concentrations in patients following acetaminophen overdose and determine if they predict toxicity. METHODS: We performed a multicentre prospective observational study, recruiting patients 14 years of age or older with acetaminophen overdose regardless of intent or formulation. Three serum samples were obtained within the first 24 h of presentation and analysed for acetaminophen-protein adducts. Acetaminophen-protein adduct concentrations were compared to ALT and other indicators of toxicity. RESULTS: Of the 240 patients who participated, 204 (85%) presented following acute ingestions, with a median ingested dose of 20 g (IQR 10-40), and 228 (95%) were treated with intravenous acetylcysteine at a median time of 6 h (IQR 3.5-10.5) post-ingestion. Thirty-six (15%) patients developed hepatotoxicity, of whom 22 had an ALT ≤1,000 U/L at the time of initial acetaminophen-protein adduct measurement. Those who developed hepatotoxicity had a higher initial acetaminophen-protein adduct concentration compared to those who did not, 1.63 nmol/ml (IQR 0.76-2.02, n = 22) vs. 0.26 nmol/ml (IQR 0.15-0.41; n = 204; p <0.0001), respectively. The AUROC for hepatotoxicity was 0.98 (95% CI 0.96-1.00; n = 226; p <0.0001) with acetaminophen-protein adduct concentration and 0.89 (95% CI 0.82-0.96; n = 219; p <0.0001) with ALT. An acetaminophen-protein adduct concentration of 0.58 nmol/ml was 100% sensitive and 91% specific for identifying patients with an initial ALT ≤1,000 U/L who would develop hepatotoxicity. Adding acetaminophen-protein adduct concentrations to risk prediction models improved prediction of hepatotoxicity to a level similar to that obtained by more complex models. CONCLUSION: Acetaminophen-protein adduct concentration on presentation predicted which patients with acetaminophen overdose subsequently developed hepatotoxicity, regardless of time of ingestion. An adduct threshold of 0.58 nmol/L was required for optimal prediction. LAY SUMMARY: Acetaminophen poisoning is one of the most common causes of liver injury. This study examined a new biomarker of acetaminophen toxicity, which measures the amount of toxic metabolite exposure called acetaminophen-protein adduct. We found that those who developed liver injury had a higher initial level of acetaminophen-protein adducts than those who did not. CLINICAL TRIAL REGISTRATION: Australian Toxicology Monitoring (ATOM) Study-Australian Paracetamol Project: ACTRN12612001240831 (ANZCTR) Date of registration: 23/11/2012.

Neutrophil Gelatinase-Associated Lipocalin Measured on Clinical Laboratory Platforms for the Prediction of Acute Kidney Injury and the Associated Need for Dialysis Therapy: A Systematic Review and Meta-analysis.

RATIONALE & OBJECTIVE: The usefulness of measures of neutrophil gelatinase-associated lipocalin (NGAL) in urine or plasma obtained on clinical laboratory platforms for predicting acute kidney injury (AKI) and AKI requiring dialysis (AKI-D) has not been fully evaluated. We sought to quantitatively summarize published data to evaluate the value of urinary and plasma NGAL for kidney risk prediction. STUDY DESIGN: Literature-based meta-analysis and individual-study-data meta-analysis of diagnostic studies following PRISMA-IPD guidelines. SETTING & STUDY POPULATIONS: Studies of adults investigating AKI, severe AKI, and AKI-D in the setting of cardiac surgery, intensive care, or emergency department care using either urinary or plasma NGAL measured on clinical laboratory platforms. SELECTION CRITERIA FOR STUDIES: PubMed, Web of Science, Cochrane Library, Scopus, and congress abstracts ever published through February 2020 reporting diagnostic test studies of NGAL measured on clinical laboratory platforms to predict AKI. DATA EXTRACTION: Individual-study-data meta-analysis was accomplished by giving authors data specifications tailored to their studies and requesting standardized patient-level data analysis. ANALYTICAL APPROACH: Individual-study-data meta-analysis used a bivariate time-to-event model for interval-censored data from which discriminative ability (AUC) was characterized. NGAL cutoff concentrations at 95% sensitivity, 95% specificity, and optimal sensitivity and specificity were also estimated. Models incorporated as confounders the clinical setting and use versus nonuse of urine output as a criterion for AKI. A literature-based meta-analysis was also performed for all published studies including those for which the authors were unable to provide individual-study data analyses. RESULTS: We included 52 observational studies involving 13,040 patients. We analyzed 30 data sets for the individual-study-data meta-analysis. For AKI, severe AKI, and AKI-D, numbers of events were 837, 304, and 103 for analyses of urinary NGAL, respectively; these values were 705, 271, and 178 for analyses of plasma NGAL. Discriminative performance was similar in both meta-analyses. Individual-study-data meta-analysis AUCs for urinary NGAL were 0.75 (95% CI, 0.73-0.76) and 0.80 (95% CI, 0.79-0.81) for severe AKI and AKI-D, respectively; for plasma NGAL, the corresponding AUCs were 0.80 (95% CI, 0.79-0.81) and 0.86 (95% CI, 0.84-0.86). Cutoff concentrations at 95% specificity for urinary NGAL were>580ng/mL with 27% sensitivity for severe AKI and>589ng/mL with 24% sensitivity for AKI-D. Corresponding cutoffs for plasma NGAL were>364ng/mL with 44% sensitivity and>546ng/mL with 26% sensitivity, respectively. LIMITATIONS: Practice variability in initiation of dialysis. Imperfect harmonization of data across studies. CONCLUSIONS: Urinary and plasma NGAL concentrations may identify patients at high risk for AKI in clinical research and practice. The cutoff concentrations reported in this study require prospective evaluation.

Factors influencing physician risk estimates for acute cardiac events in emergency patients with suspected acute coronary syndrome.

BACKGROUND: Emergency physicians frequently assess risk of acute cardiac events (ACEs) in patients with undifferentiated chest pain. Such estimates have been shown to have moderate to high sensitivity for ACE but are conservative. Little is known about the factors implicitly used by physicians to determine the pretest probability of risk. This study sought to identify the accuracy of physician risk estimates for ACE in patients presenting to the ED with chest pain and to identify the demographic and clinical information emergency physicians use in their determination of patient risk. METHODS: This study used data from two prospective studies of consenting adult patients presenting to the ED with symptoms of possible acute coronary syndrome. ED physicians estimated the pretest probability of ACE. Multiple linear regression analysis was used to identify predictors of physician risk estimates. Logistic regression was used to determine whether there was a correlation between physicians' estimated risk and ACE. RESULTS: Increasing age, male sex, abnormal ECG features, heavy/crushing chest pain and risk factors were correlated with physician risk estimates. Physician risk estimates were consistently found to be higher than the expected proportion of ACE from the sampled population. CONCLUSION: Physicians systematically overestimate ACE risk. A range of factors are associated with physician risk estimates. These include factors strongly predictive of ACE, such as age and ECG characteristics. They also include other factors that have been shown to be unreliable predictors of ACE in an ED setting, such as typicality of pain and risk factors.

Combining High-Sensitivity Cardiac Troponin I and Cardiac Troponin T in the Early Diagnosis of Acute Myocardial Infarction.

BACKGROUND: Combining 2 signals of cardiomyocyte injury, cardiac troponin I (cTnI) and T (cTnT), might overcome some individual pathophysiological and analytical limitations and thereby increase diagnostic accuracy for acute myocardial infarction with a single blood draw. We aimed to evaluate the diagnostic performance of combinations of high-sensitivity (hs) cTnI and hs-cTnT for the early diagnosis of acute myocardial infarction. METHODS: The diagnostic performance of combining hs-cTnI (Architect, Abbott) and hs-cTnT (Elecsys, Roche) concentrations (sum, product, ratio, and a combination algorithm) obtained at the time of presentation was evaluated in a large multicenter diagnostic study of patients with suspected acute myocardial infarction. The optimal rule-out and rule-in thresholds were externally validated in a second large multicenter diagnostic study. The proportion of patients eligible for early rule-out was compared with the European Society of Cardiology 0/1 and 0/3 hour algorithms. RESULTS: Combining hs-cTnI and hs-cTnT concentrations did not consistently increase overall diagnostic accuracy as compared with the individual isoforms. However, the combination improved the proportion of patients meeting criteria for very early rule-out. With the European Society of Cardiology 2015 guideline recommended algorithms and cut-offs, the proportion meeting rule-out criteria after the baseline blood sampling was limited (6% to 24%) and assay dependent. Application of optimized cut-off values using the sum (9 ng/L) and product (18 ng2/L2) of hs-cTnI and hs-cTnT concentrations led to an increase in the proportion ruled-out after a single blood draw to 34% to 41% in the original (sum: negative predictive value [NPV] 100% [95% confidence interval (CI), 99.5% to 100%]; product: NPV 100% [95% CI, 99.5% to 100%]) and in the validation cohort (sum: NPV 99.6% [95% CI, 99.0-99.9%]; product: NPV 99.4% [95% CI, 98.8-99.8%]). The use of a combination algorithm (hs-cTnI <4 ng/L and hs-cTnT <9 ng/L) showed comparable results for rule-out (40% to 43% ruled out; NPV original cohort 99.9% [95% CI, 99.2-100%]; NPV validation cohort 99.5% [95% CI, 98.9-99.8%]) and rule-in (positive predictive value [PPV] original cohort 74.4% [95% Cl, 69.6-78.8%]; PPV validation cohort 84.0% [95% Cl, 79.7-87.6%]). CONCLUSIONS: New strategies combining hs-cTnI and hs-cTnT concentrations may significantly increase the number of patients eligible for very early and safe rule-out, but do not seem helpful for the rule-in of acute myocardial infarction. CLINICAL TRIAL REGISTRATION: URL (APACE): https://www.clinicaltrial.gov . Unique identifier: NCT00470587. URL (ADAPT): www.anzctr.org.au . Unique identifier: ACTRN12611001069943.

ICare-ACS (Improving Care Processes for Patients With Suspected Acute Coronary Syndrome): A Study of Cross-System Implementation of a National Clinical Pathway.

BACKGROUND: Efforts to safely reduce length of stay for emergency department patients with symptoms suggestive of acute coronary syndrome (ACS) have had mixed success. Few system-wide efforts affecting multiple hospital emergency departments have ever been evaluated. We evaluated the effectiveness of a nationwide implementation of clinical pathways for potential ACS in disparate hospitals. METHODS: This was a multicenter pragmatic stepped-wedge before-and-after trial in 7 New Zealand acute care hospitals with 31 332 patients investigated for suspected ACS with serial troponin measurements. The implementation was a clinical pathway for the assessment of patients with suspected ACS that included a clinical pathway document in paper or electronic format, structured risk stratification, specified time points for electrocardiographic and serial troponin testing within 3 hours of arrival, and directions for combining risk stratification and electrocardiographic and troponin testing in an accelerated diagnostic protocol. Implementation was monitored for >4 months and compared with usual care over the preceding 6 months. The main outcome measure was the odds of discharge within 6 hours of presentation RESULTS: There were 11 529 participants in the preimplementation phase (range, 284-3465) and 19 803 in the postimplementation phase (range, 395-5039). Overall, the mean 6-hour discharge rate increased from 8.3% (range, 2.7%-37.7%) to 18.4% (6.8%-43.8%). The odds of being discharged within 6 hours increased after clinical pathway implementation. The odds ratio was 2.4 (95% confidence interval, 2.3-2.6). In patients without ACS, the median length of hospital stays decreased by 2.9 hours (95% confidence interval, 2.4-3.4). For patients discharged within 6 hours, there was no change in 30-day major adverse cardiac event rates (0.52% versus 0.44%; P=0.96). In these patients, no adverse event occurred when clinical pathways were correctly followed. CONCLUSIONS: Implementation of clinical pathways for suspected ACS reduced the length of stay and increased the proportions of patients safely discharged within 6 hours. CLINICAL TRIAL REGISTRATION: URL: https://www.anzctr.org.au/ (Australian and New Zealand Clinical Trials Registry). Unique identifier: ACTRN12617000381381.