We aim to identify and critically appraise clinical prediction models of mortality and function following ischaemic stroke.
Electronic databases, reference lists, citations were searched from ...inception to September 2015. Studies were selected for inclusion, according to pre-specified criteria and critically appraised by independent, blinded reviewers. The discrimination of the prediction models was measured by the area under the curve receiver operating characteristic curve or c-statistic in random effects meta-analysis. Heterogeneity was measured using I2. Appropriate appraisal tools and reporting guidelines were used in this review.
31395 references were screened, of which 109 articles were included in the review. These articles described 66 different predictive risk models. Appraisal identified poor methodological quality and a high risk of bias for most models. However, all models precede the development of reporting guidelines for prediction modelling studies. Generalisability of models could be improved, less than half of the included models have been externally validated(n = 27/66). 152 predictors of mortality and 192 predictors and functional outcome were identified. No studies assessing ability to improve patient outcome (model impact studies) were identified.
Further external validation and model impact studies to confirm the utility of existing models in supporting decision-making is required. Existing models have much potential. Those wishing to predict stroke outcome are advised to build on previous work, to update and adapt validated models to their specific contexts opposed to designing new ones.
Acute Coronavirus Disease 2019 (COVID-19) has been associated with new-onset cardiovascular disease (CVD) and diabetes mellitus (DM), but it is not known whether COVID-19 has long-term impacts on ...cardiometabolic outcomes. This study aimed to determine whether the incidence of new DM and CVDs are increased over 12 months after COVID-19 compared with matched controls.
We conducted a cohort study from 2020 to 2021 analysing electronic records for 1,356 United Kingdom family practices with a population of 13.4 million. Participants were 428,650 COVID-19 patients without DM or CVD who were individually matched with 428,650 control patients on age, sex, and family practice and followed up to January 2022. Outcomes were incidence of DM and CVD. A difference-in-difference analysis estimated the net effect of COVID-19 allowing for baseline differences, age, ethnicity, smoking, body mass index (BMI), systolic blood pressure, Charlson score, index month, and matched set. Follow-up time was divided into 4 weeks from index date ("acute COVID-19"), 5 to 12 weeks from index date ("post-acute COVID-19"), and 13 to 52 weeks from index date ("long COVID-19"). Net incidence of DM increased in the first 4 weeks after COVID-19 (adjusted rate ratio, RR 1.81, 95% confidence interval (CI) 1.51 to 2.19) and remained elevated from 5 to 12 weeks (RR 1.27, 1.11 to 1.46) but not from 13 to 52 weeks overall (1.07, 0.99 to 1.16). Acute COVID-19 was associated with net increased CVD incidence (5.82, 4.82 to 7.03) including pulmonary embolism (RR 11.51, 7.07 to 18.73), atrial arrythmias (6.44, 4.17 to 9.96), and venous thromboses (5.43, 3.27 to 9.01). CVD incidence declined from 5 to 12 weeks (RR 1.49, 1.28 to 1.73) and showed a net decrease from 13 to 52 weeks (0.80, 0.73 to 0.88). The analyses were based on health records data and participants' exposure and outcome status might have been misclassified.
In this study, we found that CVD was increased early after COVID-19 mainly from pulmonary embolism, atrial arrhythmias, and venous thromboses. DM incidence remained elevated for at least 12 weeks following COVID-19 before declining. People without preexisting CVD or DM who suffer from COVID-19 do not appear to have a long-term increase in incidence of these conditions.
Background The management of peanut allergy relies on allergen avoidance and epinephrine autoinjector for rescue treatment in patients at risk of anaphylaxis. Biomarkers of severity and threshold of ...allergic reactions to peanut could significantly improve the care for patients with peanut allergy. Objective We sought to assess the utility of the basophil activation test (BAT) to predict the severity and threshold of reactivity to peanut during oral food challenges (OFCs). Methods The severity of the allergic reaction and the threshold dose during OFCs to peanut were determined. Skin prick tests, measurements of specific IgE to peanut and its components, and BATs to peanut were performed on the day of the challenge. Results Of the 124 children submitted to OFCs to peanut, 52 (median age, 5 years) reacted with clinical symptoms that ranged from mild oral symptoms to anaphylaxis. Severe reactions occurred in 41% of cases, and 57% reacted to 0.1 g or less of peanut protein. The ratio of the percentage of CD63+ basophils after stimulation with peanut and after stimulation with anti-IgE (CD63 peanut/anti-IgE) was independently associated with severity ( P = .001), whereas the basophil allergen threshold sensitivity CD-sens (1/EC50 × 100, where EC50 is half maximal effective concentration) value was independently associated with the threshold ( P = .020) of allergic reactions to peanut during OFCs. Patients with CD63 peanut/anti-IgE levels of 1.3 or greater had an increased risk of severe reactions (relative risk, 3.4; 95% CI, 1.8-6.2). Patients with a CD-sens value of 84 or greater had an increased risk of reacting to 0.1 g or less of peanut protein (relative risk, 1.9; 95% CI, 1.3-2.8). Conclusions Basophil reactivity is associated with severity and basophil sensitivity is associated with the threshold of allergic reactions to peanut. CD63 peanut/anti-IgE and CD-sens values can be used to estimate the severity and threshold of allergic reactions during OFCs.
Benralizumab is an IL5-receptor monoclonal antibody licensed for the treatment of severe eosinophilic asthma (SEA). It has demonstrated efficacy in clinical trials in reducing asthma exacerbation ...rates and maintenance oral corticosteroids (mOCSs).
What is the real-world effectiveness of benralizumab and what baseline characteristics are associated with response to therapy?
We assessed outcomes in all SEA patients who began benralizumab treatment at our specialist center. At each dosing visit, exacerbation history, mOCS dose, spirometry, and Asthma Control Questionnaire (ACQ6) and Mini-Asthma Quality of Life Questionnaire (mAQLQ) scores were recorded. Response to treatment was defined as a reduction of ≥ 50% in annualized exacerbation rate (AER) or in mOCS dose after 48 weeks of treatment. Super response was defined as zero exacerbations and no mOCSs for asthma.
One hundred thirty patients were included in the analysis. At 48 weeks, a 72.8% reduction in AER was noted, from 4.92 ± 3.35 per year in the year preceding biologic treatment to 1.34 ± 1.71 per year (P < .001), including 57 patients (43.8%) who were exacerbation-free with benralizumab. In those receiving mOCSs (n = 74 56.9%), the median daily prednisolone dose fell from 10 mg (interquartile range, 5-20 mg) to 0 mg (interquartile range, 0-5 mg; P < .001), and 38 of 74 patients (51.4%) were able to discontinue mOCS therapy. Clinically and statistically significant improvements were found in ACQ6 scores, mAQLQ scores, and FEV1. Overall, 51 patients (39%) met the super responder definition and 112 patients (86%) met the responder definition. The optimal regression model of super responders vs other responders included baseline characteristics associated with a strongly eosinophilic phenotype and less severe disease. Eighteen patients (13.8%) were nonresponders to benralizumab. Evidence of chronic airway infection was observed in 6 of 18 patients, and an increase in the blood eosinophil count consistent with the development of anti-drug antibodies was observed in 5 of 18 patients.
In a large real-world SEA cohort, benralizumab led to significant improvements in all clinical outcome measures. A lack of response was seen in a minority of patients and should be a focus for future investigation.
Background History and severity of atopic dermatitis (AD) are risk factors for peanut allergy. Recent evidence suggests that children can become sensitized to food allergens through an impaired skin ...barrier. Household peanut consumption, which correlates strongly with peanut protein levels in household dust, is a risk factor for peanut allergy. Objective We sought to assess whether environmental peanut exposure (EPE) is a risk for peanut sensitization and allergy and whether markers of an impaired skin barrier modify this risk. Methods Peanut protein in household dust (in micrograms per gram) was assessed in highly atopic children (age, 3-15 months) recruited to the Consortium of Food Allergy Research Observational Study. History and severity of AD, peanut sensitization, and likely allergy (peanut-specific IgE, ≥5 kUA /mL) were assessed at recruitment into the Consortium of Food Allergy Research study. Results There was an exposure-response relationship between peanut protein levels in household dust and peanut skin prick test (SPT) sensitization and likely allergy. In the final multivariate model an increase in 4 log2 EPE units increased the odds of peanut SPT sensitization (1.71-fold; 95% CI, 1.13- to 2.59-fold; P = .01) and likely peanut allergy (PA; 2.10-fold; 95% CI, 1.20- to 3.67-fold; P < .01). The effect of EPE on peanut SPT sensitization was augmented in children with a history of AD (OR, 1.97; 95% CI, 1.26-3.09; P < .01) and augmented even further in children with a history of severe AD (OR, 2.41; 95% CI, 1.30-4.47; P < .01); the effect of EPE on PA was also augmented in children with a history of AD (OR, 2.34; 95% CI, 1.31-4.18; P < .01). Conclusion Exposure to peanut antigen in dust through an impaired skin barrier in atopically inflamed skin is a plausible route for peanut SPT sensitization and PA.
Background Most of the peanut-sensitized children do not have clinical peanut allergy. In equivocal cases, oral food challenges (OFCs) are required. However, OFCs are laborious and not without risk; ...thus, a test that could accurately diagnose peanut allergy and reduce the need for OFCs is desirable. Objective To assess the performance of basophil activation test (BAT) as a diagnostic marker for peanut allergy. Methods Peanut-allergic (n = 43), peanut-sensitized but tolerant (n = 36) and non–peanut-sensitized nonallergic (n = 25) children underwent skin prick test (SPT) and specific IgE (sIgE) to peanut and its components. BAT was performed using flow cytometry, and its diagnostic performance was evaluated in relation to allergy versus tolerance to peanut and validated in an independent population (n = 65). Results BAT in peanut-allergic children showed a peanut dose-dependent upregulation of CD63 and CD203c while there was no significant response to peanut in peanut-sensitized but tolerant ( P < .001) and non–peanut-sensitized nonallergic children ( P < .001). BAT optimal diagnostic cutoffs showed 97% accuracy, 95% positive predictive value, and 98% negative predictive value. BAT allowed reducing the number of required OFCs by two-thirds. BAT proved particularly useful in cases in which specialists could not accurately diagnose peanut allergy with SPT and sIgE to peanut and to Arah2. Using a 2-step diagnostic approach in which BAT was performed only after equivocal SPT or Arah2-sIgE, BAT had a major effect (97% reduction) on the number of OFCs required. Conclusions BAT proved to be superior to other diagnostic tests in discriminating between peanut allergy and tolerance, particularly in difficult cases, and reduced the need for OFCs.
Abstract Background Throughout the Covid-19 pandemic, researchers have made use of electronic health records to research this disease in a rapidly evolving environment of questions and discoveries. ...These studies are prone to collider bias as they restrict the population of Covid-19 patients to only those with severe disease. Inverse probability weighting is typically used to correct for this bias but requires information from the unrestricted population. Using electronic health records from a South London NHS trust, this work demonstrates a method to correct for collider bias using externally sourced data while examining the relationship between minority ethnicities and poor Covid-19 outcomes. Methods The probability of inclusion within the observed hospitalised cohort was modelled based on estimates from published national data. The model described the relationship between patient ethnicity, hospitalisation, and death due to Covid-19 – a relationship suggested to be susceptible to collider bias. The obtained probabilities (as applied to the observed patient cohort) were used as inverse probability weights in survival analysis examining ethnicity (and covariates) as a risk factor for death due to Covid-19. Results Within the observed cohort, unweighted analysis of survival suggested a reduced risk of death in those of Black ethnicity – differing from the published literature. Applying inverse probability weights to this analysis amended this aberrant result to one more compatible with the literature. This effect was consistent when the analysis was applied to patients within only the first wave of Covid-19 and across two waves of Covid-19 and was robust against adjustments to the modelled relationship between hospitalisation, patient ethnicity, and death due to Covid-19 made as part of a sensitivity analysis. Conclusions In conclusion, this analysis demonstrates the feasibility of using external publications to correct for collider bias (or other forms of selection bias) induced by the restriction of a population to a hospitalised cohort using an example from the recent Covid-19 pandemic.
Machine learning (ML) has attracted much attention with the hope that it could make use of large, routinely collected datasets and deliver accurate personalised prognosis. The aim of this systematic ...review is to identify and critically appraise the reporting and developing of ML models for predicting outcomes after stroke. We searched PubMed and Web of Science from 1990 to March 2019, using previously published search filters for stroke, ML, and prediction models. We focused on structured clinical data, excluding image and text analysis. This review was registered with PROSPERO (CRD42019127154). Eighteen studies were eligible for inclusion. Most studies reported less than half of the terms in the reporting quality checklist. The most frequently predicted stroke outcomes were mortality (7 studies) and functional outcome (5 studies). The most commonly used ML methods were random forests (9 studies), support vector machines (8 studies), decision trees (6 studies), and neural networks (6 studies). The median sample size was 475 (range 70-3184), with a median of 22 predictors (range 4-152) considered. All studies evaluated discrimination with thirteen using area under the ROC curve whilst calibration was assessed in three. Two studies performed external validation. None described the final model sufficiently well to reproduce it. The use of ML for predicting stroke outcomes is increasing. However, few met basic reporting standards for clinical prediction tools and none made their models available in a way which could be used or evaluated. Major improvements in ML study conduct and reporting are needed before it can meaningfully be considered for practice.
The aim of this study was to define the incidence of left ventricular thrombus (LVT) and its predictors in the contemporary era of primary percutaneous intervention (pPCI) and contrast ...echocardiography. We retrospectively analyzed 1,059 patients presenting with ST-elevation myocardial infarction (STEMI) to our tertiary cardiac center and treated with pPCI. Preprocedural pharmacology and procedural technique (including access route, the use of drug-eluting stents, and thrombectomy) were at the operators' discretion. Transthoracic echocardiography was performed before discharge; echo contrast agent was used when appropriate. LVT was detected in 42 subjects (4%). There were no significant differences in baseline demographics or pre-PCI clinical features between the 2 groups. Post-treatment, mean ejection fraction (EF) in patients with LVT was 35 ± 8.4% and in those without LVT was 47 ± 10%, p <0.001. Thirty-seven patients (88%) in the LVT group presented with an anterior STEMI versus 471 patients (42%) in the without LVT group (p <0.001). Apical akinesis was noted in all patients with LVT irrespective of the principal location of the MI. Multivariate analysis predictors of LVT were reduced EF, anterior site of MI, and the use of platelet glycoprotein IIb/IIIa inhibitors. After diagnosis of LVT, patients were treated with warfarin for 3 to 6 months. No significant difference in mortality was detectable at discharge between the 2 groups. In conclusion, in the contemporary era of pPCI, the incidence of LVT in patients with STEMI is significantly lower than that of the previous (thrombolysis) literature. The early presence of LVT is more likely in patients with anterior STEMI (involving the apex) and reduced EF.
OBJECTIVES:To establish the effect of continuous renal replacement therapy on outcome in pediatric acute liver failure.
DESIGN:Retrospective cohort study.
SETTING:Sixteen-bed PICU in a ...university-affiliated tertiary care hospital and specialist liver centre.
PATIENTS:All children (0–18 yr) admitted to PICU with pediatric acute liver failure between January 2003 and December 2013.
INTERVENTIONS:Children with pediatric acute liver failure were managed according to a set protocol. The guidelines for continuous renal replacement therapy in pediatric acute liver failure were changed in 2011 following preliminary results to indicate the earlier use of continuous renal replacement therapy for both renal dysfunction and detoxification.
MEASUREMENTS AND MAIN RESULTS:Of 165 children admitted with pediatric acute liver failure, 136 met the inclusion criteria and 45 of these received continuous renal replacement therapy prior to transplantation or recovery. Of the children managed with continuous renal replacement therapy, 26 (58%) survived19 were successfully bridged to liver transplantation and 7 spontaneously recovered. Cox proportional hazards regression model clearly showed reducing hyperammonemia by 48 hours after initiating continuous renal replacement therapy significantly improved survival (HR, 1.04; 95% CI, 1.013–1.073; p = 0.004). On average, for every 10% decrease in ammonia from baseline at 48 hours, the likelihood of survival increased by 50%. Time to initiate continuous renal replacement therapy from PICU admission was lower in survivors compared to nonsurvivors (HR, 0.96; 95% CI, 0.916–1.007; p = 0.095). Change in practice to initiate early and high-dose continuous renal replacement therapy led to increased survival with maximum effect being visible in the first 14 days (HR, 3; 95% CI, 1.0–10.3; p = 0.063). Among children with pediatric acute liver failure who did not receive a liver transplant, use of continuous renal replacement therapy significantly improved survival (HR, 4; 95% CI, 1.5–11.6; p = 0.006).
CONCLUSION:Continuous renal replacement therapy can be used successfully in critically ill children with pediatric acute liver failure to provide stability and bridge to transplantation. Inability to reduce ammonia by 48 hours confers poor prognosis. Continuous renal replacement therapy should be considered at an early stage to help prevent further deterioration and buy time for potential spontaneous recovery or bridge to liver transplantation.
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