scholarly journals Health status in patients at risk of inherited arrhythmias and sudden unexpected death compared to the general population

2010 ◽  
Vol 11 (1) ◽  
Author(s):  
Anniken Hamang ◽  
Geir Egil Eide ◽  
Karin Nordin ◽  
Berit Rokne ◽  
Cathrine Bjorvatn ◽  
...  
Keyword(s):  
At Risk ◽  
Health Status ◽  
General Population ◽  
Sudden Unexpected Death ◽  
Unexpected Death ◽  
Patients At Risk ◽  
Inherited Arrhythmias

Abstract 15714: Prediction of Sudden Cardiac Death With Automated High-Throughput Analysis of T-Wave Heterogeneity in Standard 12-Lead Electrocardiogram

Circulation ◽  
2014 ◽  
Vol 130 (suppl_2) ◽  
Author(s):  
Tuomas Kenttä ◽  
Bruce D Nearing ◽  
Kimmo Porthan ◽  
Jani T Tikkanen ◽  
Matti Viitasalo ◽  
...  
Keyword(s):  
At Risk ◽  
Relative Risk ◽  
Sudden Cardiac Death ◽  
General Population ◽  
Cardiac Death ◽  
Left Ventricular ◽  
Adjusted Relative Risk ◽  
T Wave ◽  
Increased Risk ◽  
Patients At Risk

Introduction: Noninvasive identification of patients at risk for sudden cardiac death (SCD) remains a major clinical challenge. Abnormal ventricular repolarization is associated with increased risk of lethal ventricular arrhythmias and SCD. Hypothesis: We investigated the hypothesis that spatial repolarization heterogeneity can identify patients at risk for SCD in general population. Methods: Spatial R-, J- and T-wave heterogeneities (RWH, JWH and TWH, respectively) were automatically analyzed with second central moment technique from standard digital 12-lead ECGs in 5618 adults (46% men; age 50.9±12.5 yrs.) who took part in Health 2000 Study, an epidemiological survey representative of the entire Finnish adult population. During average follow-up of 7.7±1.4 years, a total of 72 SCDs occurred. Thresholds of RWH, JWH and TWH were based on optimal cutoff points from ROC curves. Results: Increased RWH, JWH and TWH (Fig.1) in left precordial leads (V4-V6) were univariately associated with SCD (P<0.001, each). When adjusted with clinical risk markers (age, gender, BMI, systolic blood pressure, cholesterol, heart rate, left ventricular hypertrophy, QRS duration, arterial hypertension, diabetes, coronary heart disease and previous myocardial infarction) JWH and TWH remained as independent predictors of SCD. Increased TWH (≥102μV) was associated with a 1.9-fold adjusted relative risk (95% confidence interval [CI]: 1.2 - 3.1; P=0.011) and increased JWH (≥123μV) with a 2.0-fold adjusted relative risk for SCD (95% CI: 1.2 - 3.3; P=0.004). When both TWH and JWH were above threshold, the adjusted relative risk for SCD was 3.2-fold (95% CI: 1.7 - 6.2; P<0.001). When all heterogeneity measures (RWH, JWH and TWH) were above threshold, the risk for SCD was 3.7-fold (95% CI: 1.6 - 8.6; P=0.003). Conclusions: Automated measurement of spatial J- and T-wave heterogeneity enables analysis of high patient volumes and is able to stratify SCD risk in general population.

INFANTS AT RISK OF SUDDEN UNEXPECTED DEATH

The Lancet ◽  
1979 ◽  
Vol 314 (8149) ◽  
pp. 954 ◽  
Author(s):  
DenisR. Benjamin
Keyword(s):  
At Risk ◽  
Sudden Unexpected Death ◽  
Unexpected Death

Temporal trends in sudden unexpected death in a general population: The Hisayama Study

2013 ◽  
Vol 165 (6) ◽  
pp. 932-938.e1 ◽  
Author(s):  
Masaharu Nagata ◽  
Toshiharu Ninomiya ◽  
Yasufumi Doi ◽  
Jun Hata ◽  
Fumie Ikeda ◽  
...  
Keyword(s):  
General Population ◽  
Temporal Trends ◽  
Sudden Unexpected Death ◽  
Unexpected Death

A comparison of ovarian cancer treatments: analysis of utility assessments of ovarian cancer patients, at-risk population, general population, and physicians

2004 ◽  
Vol 93 (1) ◽  
pp. 164-169 ◽  
Author(s):  
Elizabeth A Calhoun ◽  
David A Fishman ◽  
John R Lurain ◽  
Emily E Welshman ◽  
Charles L Bennett
Keyword(s):  
Ovarian Cancer ◽  
At Risk ◽  
General Population ◽  
Cancer Patients ◽  
Cancer Treatments ◽  
Risk Population ◽  
Patients At Risk

scholarly journals Interventions to Improve Safer Sleep Practices in Families With Children Considered to Be at Increased Risk for Sudden Unexpected Death in Infancy: A Systematic Review

2022 ◽  
Vol 9 ◽  
Author(s):  
Catherine Ellis ◽  
Anna Pease ◽  
Joanna Garstang ◽  
Debbie Watson ◽  
Peter S. Blair ◽  
...  
Keyword(s):  
Systematic Review ◽  
At Risk ◽  
Health Education ◽  
Mode Of Delivery ◽  
Sudden Unexpected Death ◽  
Quality Data ◽  
Infant Sleep ◽  
Unexpected Death ◽  
Information Giving ◽  
Increased Risk

Background: Advice to families to follow infant care practices known to reduce the risks of Sudden Unexpected Death in Infancy (SUDI) has led to a reduction in deaths across the world. This reduction has slowed in the last decade with most deaths now occurring in families experiencing social and economic deprivation. A systematic review of the literature was commissioned by the National Child Safeguarding Practice Review Panel in England. The review covered three areas: interventions to improve engagement with support services, parental decision-making for the infant sleep environment, and interventions to improve safer sleep practices in families with infants considered to be at risk of SUDI.Aim: To describe the safer sleep interventions tested with families with infants at risk of SUDI and investigate what this literature can tell us about what works to reduce risk and embed safer sleep practices in this group.Methods: Eight online databases were systematically searched in December 2019. Intervention studies that targeted families with infants (0–1 year) at increased risk of SUDI were included. Studies were limited to those from Western Europe, North America or Australasia, published in the last 15 years. The Quality Assessment Tool for Studies with Diverse Designs was applied to assess quality. Data from included studies were extracted for narrative synthesis, including mode of delivery using Michie et al.'s Mode of Delivery Taxonomy.Results: The wider review returned 3,367 papers, with 23 intervention papers. Five types of intervention were identified: (1) infant sleep space and safer sleep education programs, (2) intensive or targeted home visiting services, (3) peer educators/ambassadors, (4) health education/raising awareness interventions, (5) targeted health education messages using digital media.Conclusion: Influencing behavior in families with infants at risk of SUDI has traditionally focused on “getting messages across,” with interventions predominantly using education and awareness raising mechanisms. This review found evidence of interventions moving from “information giving” to “information exchange” models using personalized, longer term relationship-building models. This shift may represent an improvement in how safer sleep advice is implemented in families with infants at risk, but more robust evidence of effectiveness is required.Systematic Review Registration:https://assets.publishing.service.gov.uk/government/uploads/system/uploads/attachment_data/file/901091/DfE_Death_in_infancy_review.pdf, identifier: CRD42020165302.

scholarly journals Artificial Intelligence for COVID-19 Risk Classification in Kidney Disease: Can Technology Unmask an Unseen Disease?

2020 ◽  
Author(s):  
Caitlin Monaghan ◽  
John W. Larkin ◽  
Sheetal Chaudhuri ◽  
Hao Han ◽  
Yue Jiao ◽  
...  
Keyword(s):  
At Risk ◽  
General Population ◽  
Characteristic Curve ◽  
Patient Data ◽  
County Level ◽  
Patient Level ◽  
Testing Dataset ◽  
Select Group ◽  
Patients At Risk ◽  
Level Model

AbstractBackgroundWe developed two unique machine learning (ML) models that predict risk of: 1) a major COVID-19 outbreak in the service county of a local HD population within following week, and 2) a hemodialysis (HD) patient having an undetected SARS-CoV-2 infection that is identified after following 3 or more days.MethodsWe used county-level data from United States population (March 2020) and HD patient data from a network of clinics (February-May 2020) to develop two ML models. First was a county-level model that used data from general and HD populations (21 variables); outcome of a COVID-19 outbreak in a dialysis service area was defined as a clinic being located in one of the national counties with the highest growth in COVID-19 positive cases (number and people per million (ppm)) in general population during 22-28 Mar 2020. Second was a patient-level model that used HD patient data (82 variables) to predict an individual having an undetected SARS-CoV-2 infection that is identified in subsequent ≥3 days.ResultsAmong 1682 counties with dialysis clinics, 82 (4.9%) had a COVID-19 outbreak during 22-28 Mar 2020. Area under the receiver operating characteristic curve (AUROC) for the county-level model was 0.86 in testing dataset. Top predictor of a county experiencing an outbreak was the COVID-19 positive ppm in the general population in the prior week. In a select group (n=11,664) used to build the patient-level model, 28% of patients had COVID-19; prevalence was by design 10% in the testing dataset. AUROC for the patient-level model was 0.71 in the testing dataset. Top predictor of an HD patient having a SARS-CoV-2 infection was mean pre-HD body temperature in the prior week.ConclusionsDeveloped ML models appear suitable for predicting counties at risk of a COVID-19 outbreak and HD patients at risk of having an undetected SARS-CoV-2 infection.

scholarly journals Decision-making for the infant sleep environment among families with children considered to be at risk of sudden unexpected death in infancy: a systematic review and qualitative metasynthesis

2021 ◽  
Vol 5 (1) ◽  
pp. e000983
Author(s):  
Anna Pease ◽  
Joanna J Garstang ◽  
Catherine Ellis ◽  
Debbie Watson ◽  
Jenny Ingram ◽  
...  
Keyword(s):  
Decision Making ◽  
At Risk ◽  
Sudden Unexpected Death ◽  
Infant Sleep ◽  
Unexpected Death ◽  
Parental Decision ◽  
Parental Decision Making ◽  
Increased Risk ◽  
Sleep Environment ◽  
Families With Children

BackgroundAdvice to families to sleep infants on their backs, avoid smoke exposure, reduce excess bedcovering and avoid specific risks associated with cosleeping has greatly reduced sudden unexpected death in infancy (SUDI) rates worldwide. The fall in rates has not been equal across all groups, and this advice has been less effective for more socially deprived families. Understanding decision-making processes of families with infants at risk would support the development of more effective interventions.AimTo synthesise the qualitative evidence on parental decision-making for the infant sleep environment among families with children considered to be at increased risk of SUDI.MethodsThis study was one of three related reviews of the literature for the Child Safeguarding Practice Review Panel’s National Review in England into SUDI in families where the children are considered at risk of harm. A systematic search of eight online databases was carried out in December 2019. Metasynthesis was conducted, with themes extracted from each paper, starting with the earliest publication first.ResultsThe wider review returned 3367 papers, with 16 papers (across 13 studies) specifically referring to parental decision-making. Six overall themes were identified from the synthesis: (1) knowledge as different from action; (2) external advice must be credible; (3) comfort, convenience and disruption to the routine; (4) plausibility and mechanisms of protection; (5) meanings of safety and risk mitigation using alternative strategies; and (6) parents’ own expertise, experience and instincts.ConclusionInterventions that are intended to improve the uptake of safer sleep advice in families with infants at risk of sleep-related SUDI need to be based on credible advice with mechanisms of protection that are understandable, consistent with other sources, widened to all carers of the infant and fit within the complex practice of caring for infants.

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