scholarly journals Analysis of individual patient data to describe the incubation period distribution of Shiga-toxin producingEscherichia coli

2019 ◽  
Vol 147 ◽  
Author(s):  
A. Awofisayo-Okuyelu ◽  
I. Hall ◽  
E. Arnold ◽  
L. Byrne ◽  
N. McCarthy
Keyword(s):  
Incubation Period ◽  
Shiga Toxin ◽  
Individual Patient Data ◽  
Age Groups ◽  
Patient Characteristics ◽  
Patient Data ◽  
Bloody Diarrhoea ◽  
Period Distribution ◽  
Public Health Officials ◽  
The Relationship

AbstractShiga-toxin producingEscherichia coli(STEC) is a pathogen that can cause bloody diarrhoea and severe complications. Cases occur sporadically but outbreaks are also common. Understanding the incubation period distribution and factors influencing it will help in the investigation of exposures and consequent disease control. We extracted individual patient data for STEC cases associated with outbreaks with a known source of exposure in England and Wales. The incubation period was derived and cases were described according to patient and outbreak characteristics. We tested for heterogeneity in reported incubation period between outbreaks and described the pattern of heterogeneity. We employed a multi-level regression model to examine the relationship between patient characteristics such as age, gender and reported symptoms; and outbreak characteristics such as mode of transmission with the incubation period. A total of 205 cases from 41 outbreaks were included in the study, of which 64 cases (31%) were from a single outbreak. The median incubation period was 4 days. Cases reporting bloody diarrhoea reported shorter incubation periods compared with cases without bloody diarrhoea, and likewise, cases aged between 40 and 59 years reported shorter incubation period compared with other age groups. It is recommended that public health officials consider the characteristics of cases involved in an outbreak in order to inform the outbreak investigation and the period of exposure to be investigated.

scholarly journals Delayed antibiotic prescribing for respiratory tract infections: protocol of an individual patient data meta-analysis

BMJ Open ◽  
2019 ◽  
Vol 9 (1) ◽  
pp. e026925 ◽  
Author(s):  
Beth Stuart ◽  
Hilda Hounkpatin ◽  
Taeko Becque ◽  
Guiqing Yao ◽  
Shihua Zhu ◽  
...  
Keyword(s):  
Individual Patient Data ◽  
Meta Analysis ◽  
Patient Characteristics ◽  
Patient Data ◽  
Published Data ◽  
Controlled Trials ◽  
Antibiotic Prescribing ◽  
Cochrane Central Register ◽  
Life Years ◽  
Tract Infections

IntroductionDelayed prescribing can be a useful strategy to reduce antibiotic prescribing, but it is not clear for whom delayed prescribing might be effective. This protocol outlines an individual patient data (IPD) meta-analysis of randomised controlled trials (RCTs) and observational cohort studies to explore the overall effect of delayed prescribing and identify key patient characteristics that are associated with efficacy of delayed prescribing.Methods and analysisA systematic search of the databases Cochrane Central Register of Controlled Trials, Ovid MEDLINE, Ovid Embase, EBSCO CINAHL Plus and Web of Science was conducted to identify relevant studies from inception to October 2017. Outcomes of interest include duration of illness, severity of illness, complication, reconsultation and patient satisfaction. Study authors of eligible papers will be contacted and invited to contribute raw IPD data. IPD data will be checked against published data, harmonised and aggregated to create one large IPD database. Multilevel regression will be performed to explore interaction effects between treatment allocation and patient characteristics. The economic evaluation will be conducted based on IPD from the combined trial and observational studies to estimate the differences in costs and effectiveness for delayed prescribing compared with normal practice. A decision model will be developed to assess potential savings and cost-effectiveness in terms of reduced antibiotic usage of delayed prescribing and quality-adjusted life years.Ethics and disseminationEthical approval was obtained from the University of Southampton Faculty of Medicine Research Ethics Committee (Reference number: 30068). Findings of this study will be published in peer-reviewed academic journals as well as General Practice trade journals and will be presented at national and international conferences. The results will have important public health implications, shaping the way in which antibiotics are prescribed in the future and to whom delayed prescriptions are issued.PROSPERO registration numberCRD42018079400.

scholarly journals Characteristics of telehealth users in NYC for COVID-related care during the coronavirus pandemic

2020 ◽  
Vol 27 (12) ◽  
pp. 1949-1954
Author(s):  
Ellerie Weber ◽  
Sarah J Miller ◽  
Varuna Astha ◽  
Teresa Janevic ◽  
Emma Benn
Keyword(s):  
Multinomial Logistic Regression ◽  
Age Groups ◽  
Office Visit ◽  
Patient Characteristics ◽  
Parameter Estimates ◽  
Office Visits ◽  
Older Americans ◽  
The Us ◽  
The Relationship ◽  
Racial Ethnic

Abstract Objective To explore whether racial/ethnic differences in telehealth use existed during the peak pandemic period among NYC patients seeking care for COVID-19 related symptoms. Materials and Methods This study used data from a large health system in NYC – the epicenter of the US crisis – to describe characteristics of patients seeking COVID-related care via telehealth, ER, or office encounters during the peak pandemic period. Using multinomial logistic regression, we estimated the magnitude of the relationship between patient characteristics and the odds of having a first encounter via telehealth versus ER or office visit, and then used regression parameter estimates to predict patients’ probabilities of using different encounter types given their characteristics. Results Demographic factors, including race/ethnicity and age, were significantly predictive of telehealth use. As compared to Whites, Blacks had higher adjusted odds of using both the ER versus telehealth (OR: 4.3, 95% CI: 4.0-4.6) and office visits versus telehealth (OR: 1.4, 95% CI: 1.3-1.5). For Hispanics versus Whites, the analogous ORs were 2.5 (95% CI: 2.3-2.7) and 1.2 (95% CI: 1.1-1.3). Compared to any age groups, patients 65+ had significantly higher odds of using either ER or office visits versus telehealth. Conclusions The response to COVID-19 has involved an unprecedented expansion in telehealth. While older Americans and minority populations among others are known to be disadvantaged by the digital divide, few studies have examined disparities in telehealth specifically, and none during COVID-19. Additional research into sociodemographic heterogeneity in telehealth use is needed to prevent potentially further exacerbating health disparities overall.

scholarly journals Ganglioneuromas across age groups: Systematic review of individual patient data

2020 ◽  
Vol 94 (1) ◽  
pp. 12-23
Author(s):  
Stephanie M. J. Fliedner ◽  
Philipp E. R. Winkelmann ◽  
Robert Wesley ◽  
Reinhard Vonthein ◽  
Hendrik Lehnert
Keyword(s):  
Systematic Review ◽  
Individual Patient Data ◽  
Age Groups ◽  
Patient Data

Geosocial Factors Associated With Adherence to Statin Medications

2020 ◽  
Vol 54 (12) ◽  
pp. 1194-1202 ◽  
Author(s):  
Steven R. Erickson ◽  
Mercedes Bravo ◽  
Joshua Tootoo
Keyword(s):  
Age Groups ◽  
Patient Characteristics ◽  
Racial Isolation ◽  
Geographic Accessibility ◽  
Public Health Initiative ◽  
Pharmacy Claims ◽  
The Social ◽  
Proportion Of Days Covered ◽  
Statin Adherence ◽  
The Relationship

Background: Individual patient characteristics, social determinants, and geographic access may be associated with patients engaging in appropriate health behaviors. Objective: To assess the relationship between statin adherence, geographic accessibility to pharmacies, and neighborhood sociodemographic characteristics in Michigan. Methods: The proportion of days covered (PDC) was calculated from pharmacy claims of a large insurer of adults who had prescriptions for statins between July 2009 and June 2010. A PDC ≥0.80 was defined as adherent. The predictor of interest was a ZIP code tabulation area (ZCTA)-level measure of geographic accessibility to pharmacies, measured using a method that integrates availability and access into a single index. We fit unadjusted models as well as adjusted models controlling for age, sex, and ZCTA-level measures of socioeconomic status (SES), racial isolation (RI) of non-Hispanic blacks, and urbanicity. Results: More than 174 000 patients’ claims data were analyzed. In adjusted models, pharmacy access was not associated with adherence (0.99; 95% CI: 0.96, 1.03). Greater RI (0.87; 95% CI: 0.85, 0.88) and urban status (0.93; 95% CI: 0.89, 0.96) were associated with lower odds of adherence. Individuals in ZCTAs with higher SES had higher odds of adherence, as were men and older age groups. Conclusion and Relevance: Adherence to statin prescriptions was lower for patients living in areas characterized as being racially segregated or lower income. Initiating interventions to enhance adherence, informed by understanding the social and systematic barriers patients face when refilling medication, is an important public health initiative that pharmacists practicing in these areas may undertake.

scholarly journals Predicting outcomes following holistic breathlessness services: A pooled analysis of individual patient data

2019 ◽  
Vol 33 (4) ◽  
pp. 462-466 ◽  
Author(s):  
Lisa Jane Brighton ◽  
Wei Gao ◽  
Morag Farquhar ◽  
Sara Booth ◽  
Sabrina Bajwah ◽  
...  
Keyword(s):  
Clinical Trials ◽  
Health Status ◽  
Lung Function ◽  
Confidence Intervals ◽  
Odds Ratio ◽  
Individual Patient Data ◽  
Secondary Analysis ◽  
Patient Characteristics ◽  
Patient Data ◽  
Stepwise Logistic Regression

Background: Holistic breathlessness services have been developed for people with advanced disease and chronic breathlessness, leading to improved psychological aspects of breathlessness and health. The extent to which patient characteristics influence outcomes is unclear. Aim: To identify patient characteristics predicting outcomes of mastery and distress due to breathlessness following holistic breathlessness services. Design: Secondary analysis of pooled individual patient data from three clinical trials. Our primary analysis assessed predictors of clinically important improvements in Chronic Respiratory Questionnaire mastery scores (+0.5 point), and our secondary analysis predictors of improvements in Numerical Rating Scale distress due to breathlessness (−1 point). Variables significantly related to improvement in univariate models were considered in separate backwards stepwise logistic regression models. Participants: The dataset comprised 259 participants (118 female; mean (standard deviation) age 69.2 (10.6) years) with primary diagnoses of chronic obstructive pulmonary disease (49.8%), cancer (34.7%) and interstitial lung disease (10.4%). Results: Controlling for age, sex and trial, baseline mastery remained the only significant independent predictor of improvement in mastery (odds ratio 0.57, 95% confidence intervals 0.43–0.74; p < 0.001), and baseline distress remained the only significant predictor of improvement in distress (odds ratio 1.64; 95% confidence intervals 1.35–2.03; p < 0.001). Baseline lung function, breathlessness severity, health status, mild anxiety and depression, and diagnosis did not predict outcomes. Conclusions: Outcomes of mastery and distress following holistic breathlessness services are influenced by baseline scores for these variables, and not by diagnosis, lung function or health status. Stratifying patients by levels of mastery and/or distress due to breathlessness appears appropriate for clinical trials and services.

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