Infection-related mortality in children with acute lymphoblastic leukemia: an analysis of infectious deaths on UKALL2003.

Although infection is the major cause of treatment-related mortality (TRM) in childhood acute lymphoblastic leukemia, factors associated with infection-related mortality (IRM) are poorly understood. To address this, we report an analysis of all 75 cases of IRM in the United Kingdom Childhood Acute Lymphoblastic Leukaemia Randomised Trial 2003 (UKALL 2003). The 5-year cumulative incidence of IRM was 2.4% (95% confidence interval [CI], 1.9%-3.0%), accounting for 75 (30%) of 249 trial deaths and 75 (64%) of 117 TRM deaths. Risk for IRM as a proportion of TRM was greater in induction than other phases (77% vs 56%; P = .02). Sixty-eight percent of cases were associated with bacterial infection (64% Gram-negative) and 20% with fungal infection. Down syndrome was the most significant risk factor for IRM (odds ratio [OR], 12.08; 95% CI, 6.54-22.32; P < .0001). In addition, there was a trend toward increased IRM in girls (OR, 1.63; 95% CI, 1.02-2.61; P = .04), as well as increasing treatment intensity (regimen B vs A: OR, 2.11 [95% CI, 1.24-3.60]; regimen C vs A: OR, 1.41 [95% CI, 0.76-2.62]; P = .02). Importantly, patients with Down syndrome were at significantly higher risk for IRM during maintenance (P = .048). Our results confirm Down syndrome as a major risk factor for IRM. Enhanced supportive care and prophylactic antibiotics should be considered in high-risk patient groups and during periods of increased risk. This study was registered at http://www.controlled-trials.com/ as #ISRCTN07355119.

Long-Term Cochlear Implant Sound Processor Usage in Children with Single-Sided Deafness.

OBJECTIVE: To assess cochlear implant (CI) sound processor usage over time in children with single-sided deafness (SSD) and identify factors influencing device use. STUDY DESIGN: Retrospective, chart review study. SETTING: Pediatric tertiary referral center. PATIENTS: Children with SSD who received CI between 2014 and 2020. OUTCOME MEASURE: Primary outcome was average daily CI sound processor usage over follow-up. RESULTS: Fifteen children with SSD who underwent CI surgery were categorized based on age of diagnosis and surgery timing. Over an average of 4.3-year follow-up, patients averaged 4.6 hours/day of CI usage. Declining usage trends were noted over time, with the first 2 years postactivation showing higher rates. No significant usage differences emerged based on age, surgery timing, or hearing loss etiology. CONCLUSIONS: Long-term usage decline necessitates further research into barriers and enablers for continued CI use in pediatric SSD cases.

Detection rates of asymptomatic carotid artery stenosis and atrial fibrillation by selective screening of patients without cardiovascular disease.

BACKGROUND: Individuals with significant asymptomatic carotid artery stenosis (ACAS) and atrial fibrillation (AF) could benefit from specific interventions to prevent heart attack and stroke, but are often clinically 'silent'. We aimed to determine detection rate of ACAS and AF by screening, targeting a population at increased cardiovascular risk. METHODS: Data on adults who attended voluntary and self-funded commercial screening clinics in the United States or the United Kingdom between 2008 and 2013 were used. The Atherosclerotic Cardiovascular Disease (ASCVD) risk equation was applied to each participants and detection rates of targeted screening for ≥50% ACAS and AF to those at highest risk of CVD was assessed. RESULTS: Among 0.4 million individuals between 40 and 80 years, without CVD, 6191 (1.6%) had ACAS and 1026 (0.3%) had AF. Selective screening of participants with a predicted 10-year CVD risk of ≥20% identified 40% of ACAS cases, a prevalence of 3.7%, leading to a number needed to screen (NNS) of 27, as well as 39% of AF cases, a prevalence of 0.6%, with a NNS of 170. Selective screening of those with a predicted 10-year CVD risk of ≥15% identified 54% of ACAS cases, a prevalence of 3.3%, and an NNS of 31, as well as 51% of AF cases, a prevalence of 0.5%, with an NNS of 195. CONCLUSIONS: Selective screening for ACAS and AF implemented in ASCVD risk assessment greatly reduces the NNS when compared with population-level screening with detection rates of ACAS and AF substantially greater in people at higher predicted CVD risk.

Utility of risk prediction models to detect atrial fibrillation in screened participants.

AIMS: Atrial fibrillation (AF) is associated with higher risk of stroke. While the prevalence of AF is low in the general population, risk prediction models might identify individuals for selective screening of AF. We aimed to systematically identify and compare the utility of established models to predict prevalent AF. METHODS AND RESULTS: Systematic search of PubMed and EMBASE for risk prediction models for AF. We adapted established risk prediction models and assessed their predictive performance using data from 2.5M individuals who attended vascular screening clinics in the USA and the UK and in the subset of 1.2M individuals with CHA2DS2-VASc ≥2. We assessed discrimination using area under the receiver operating characteristic (AUROC) curves and agreement between observed and predicted cases using calibration plots. After screening 6959 studies, 14 risk prediction models were identified. In our cohort, 10 464 (0.41%) participants had AF. For discrimination, six prediction model had AUROC curves of 0.70 or above in all individuals and those with CHA2DS2-VASc ≥2. In these models, calibration plots showed very good concordance between predicted and observed risks of AF. The two models with the highest observed prevalence in the highest decile of predicted risk, CHARGE-AF and MHS, showed an observed prevalence of AF of 1.6% with a number needed to screen of 63. Selective screening of the 10% highest risk identified 39% of cases with AF. CONCLUSION: Prediction models can reliably identify individuals at high risk of AF. The best performing models showed an almost fourfold higher prevalence of AF by selective screening of individuals in the highest decile of risk compared with systematic screening of all cases. REGISTRATION: This systematic review was registered (PROSPERO CRD42019123847).

Sex-Specific Associations of Vascular Risk Factors With Abdominal Aortic Aneurysm: Findings From 1.5 Million Women and 0.8 Million Men in the United States and United Kingdom.

Background Large studies are required for reliable estimates of important risk factors for abdominal aortic aneurysm (AAA). This could guide targeted AAA screening programs, particularly in subgroups like women who are currently excluded from such programs. Method and Results In a cross-sectional study, 1.5 million women and 0.8 million men without known vascular disease attended commercial screening clinics in the United Kingdom or United States from 2008 to 2013. Measurements of vascular risk factors were related to AAA using logistic regression with correction for regression dilution bias. Screening detected 12 729 new AAA cases (0.6%). Compared with never smoking, current smoking was associated with 15 times the risk of AAA among women (risk ratio 15.0, 95% CI 13.2-17.0) and 7 times among men (7.3, 6.4-8.2). In women aged <75 years, the risk of AAA was nearly 30 times greater in current smokers (26.4, 20.3-34.2). In every age group, the prevalence of AAA in female smokers was greater than in male never-smokers. Positive log-linear associations with AAA for women and men were also observed for usual body mass index, usual systolic blood pressure, height, usual low-density lipoprotein cholesterol, and usual triglycerides. Conclusions Log-linear increases in the risks of AAA with traditional vascular risk factors should be considered when evaluating populations that may be at-risk for the development of AAA, and when considering potential treatments. However, at any given age, female smokers are at higher risk of AAA than male never-smokers, and a policy of screening male never-smokers but not higher-risk female smokers is questionable.

Validation of Risk Prediction Models to Detect Asymptomatic Carotid Stenosis.

Background Significant asymptomatic carotid stenosis (ACS) is associated with higher risk of strokes. While the prevalence of moderate and severe ACS is low in the general population, prediction models may allow identification of individuals at increased risk, thereby enabling targeted screening. We identified established prediction models for ACS and externally validated them in a large screening population. Methods and Results Prediction models for prevalent cases with ≥50% ACS were identified in a systematic review (975 studies reviewed and 6 prediction models identified [3 for moderate and 3 for severe ACS]) and then validated using data from 596 469 individuals who attended commercial vascular screening clinics in the United States and United Kingdom. We assessed discrimination and calibration. In the validation cohort, 11 178 (1.87%) participants had ≥50% ACS and 2033 (0.34%) had ≥70% ACS. The best model included age, sex, smoking, hypertension, hypercholesterolemia, diabetes mellitus, vascular and cerebrovascular disease, measured blood pressure, and blood lipids. The area under the receiver operating characteristic curve for this model was 0.75 (95% CI, 0.74-0.75) for ≥50% ACS and 0.78 (95% CI, 0.77-0.79) for ≥70% ACS. The prevalence of ≥50% ACS in the highest decile of risk was 6.51%, and 1.42% for ≥70% ACS. Targeted screening of the 10% highest risk identified 35% of cases with ≥50% ACS and 42% of cases with ≥70% ACS. Conclusions Individuals at high risk of significant ACS can be selected reliably using a prediction model. The best-performing prediction models identified over one third of all cases by targeted screening of individuals in the highest decile of risk only.