Agreement between self-reports and medical records of cardiovascular disease in octogenarians

Teh, Ruth; Doughty, Rob; Connolly, Martin J.; Broad, Joanna; Pillai, Avinesh; Wilkinson, Tim; Edlin, Richard; Jatrana, Santosh; Dyall, Lorna; Kerse, Ngaire

doi:10.1016/j.jclinepi.2013.05.001

Cited by 43 publications

(70 citation statements)

References 22 publications

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“…Similar to medical record review, studies comparing self-report to HF identified from hospital administrative claims returned low agreement (0.19–0.33) and sensitivity (26%), as well as high specificity (99%) [4, 9]. Among ARIC participants with CMS Medicare fee-for-service, sensitivity (28–35%), specificity (96–97%), and agreement (0.32–0.34) were comparable.…”

Section: Discussionmentioning

confidence: 99%

“…HF is difficult to diagnose and identify in population research. Although this difficulty is not limited to estimating the accuracy of self-reported HF, estimates comparing self-reported HF to clinically diagnosed HF [1], medical records [2–8], and health administrative data [4, 9] may be affected. Given the complexity of diagnosing and classifying HF, it may be difficult for health professionals to accurately inform patients of this diagnosis, which may limit the accuracy of self-report of physician-diagnosed HF and thus the practical advantage in using self-report to estimate prevalence of HF.…”

Section: Introductionmentioning

confidence: 99%

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Accuracy of Self-Reported Heart Failure. The Atherosclerosis Risk in Communities (ARIC) Study

Camplain

Kucharska‐Newton

Loehr

et al. 2017

Journal of Cardiac Failure

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Objective To estimate agreement of self-reported heart failure (HF) with physician diagnosed HF and compare the prevalence of HF by method of ascertainment. Study Design and Setting ARIC cohort members (60–83 years of age) were asked annually whether a physician indicated they have HF. For those self-reporting HF, physicians were asked to confirm their patient’s HF status. Physician diagnosed HF included surveillance of hospitalized HF, and hospitalized and outpatient HF identified in administrative claims databases. We estimated sensitivity, specificity, positive predicted value, kappa, prevalence and biased adjusted kappa (PABAK), and prevalence. Results Compared to physician diagnosed HF, sensitivity of self-report was low (28–38%) and specificity was high (96–97%). Agreement was poor (kappa 0.32–0.39) and increased when adjusted for prevalence and bias (PABAK 0.73–0.83). Prevalence of HF measured by self-report (9.0%), ARIC-classified hospitalizations (11.2%), or administrative hospitalization claims (12.7%) were similar. When outpatient HF claims were included, prevalence of HF increased to 18.6%. Conclusions For accurate estimates HF burden, self-reports of HF are best confirmed by appropriate diagnostic tests or medical records. Our results highlight the need for improved awareness and understanding of HF by patients as accurate patient awareness of this diagnosis may enhance management of this common condition.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Accuracy of Self-Reported Heart Failure. The Atherosclerosis Risk in Communities (ARIC) Study

Camplain

Kucharska‐Newton

Loehr

et al. 2017

Journal of Cardiac Failure

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“…Diagnoses of diabetes, asthma, chronic lung disease and cardiovascular disease were established using a combination of a self‐reported list asking whether a doctor had ever told the participant that they had the diagnoses, review of general practitioner records, review of hospital record, an electrocardiogram and blood pressure reading. The algorithm used for ascertaining these conditions has been described 25 . Weight and height measurements were completed by trained research nurses using standardised procedures.…”

Section: Methodsmentioning

confidence: 99%

“…The algorithm used for ascertaining these conditions has been described. 25 Weight and height measurements were completed by trained research nurses using standardised procedures. Weight was ascertained using a Tanita digital measuring scale (BC-541, Tanita Corporation, Japan) and height using a portable stadiometer.…”

Section: Participant Characteristicsmentioning

confidence: 99%

Dietary protein intake may reduce hospitalisation due to infection in Māori of advanced age: LiLACS NZ

Wham

Baggett

Teh

et al. 2015

Australian and New Zealand Journal of Public Health

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Objective: To investigate factors related to hospital admission for infection, specifically examining nutrient intakes of Māori in advanced age (80+ years). Method: Face‐to‐face interviews with 200 Māori (85 men) to obtain demographic, social and health information. Diagnoses were validated against medical records. Detailed nutritional assessment using the 24‐hour multiple‐pass recall method was collected on two separate days. FOODfiles was used to analyse nutrient intake. National Health Index (NHI) numbers were matched to hospitalisations over a two‐year period (12 months prior and 12 months following dietary assessment). Selected International Classification of Disease (ICD) codes were used to identify admissions related to infection. Results: A total of 18% of participants were hospitalised due to infection, most commonly lower respiratory tract infection. Controlling for age, gender, NZ deprivation index, diabetes, CVD and chronic lung disease, a lower energy‐adjusted protein intake was independently associated with hospitalisation due to infection: OR (95%CI) 1.14 (1.00–1.29), p=0.046. Conclusions: Protein intake may have a protective effect on the nutrition‐related morbidity of older Māori. Improving dietary protein intake is a simple strategy for dietary modification aiming to decrease the risk of infections that lead to hospitalisation and other morbidities.

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“…In the 12-month follow-up interview, a detailed dietary intake assessment was completed (2 × 24 h multiple pass recall (MPR)), from the 24-month follow-up onwards, carers were engaged and interviewed in the kaiawhina study and questions about end of life preferences were included. Further information is available including preliminary results (19)(20)(21)(22)(23)(24) some of which will be described in this review.…”

Section: Uk and New Zealand Cohort Studies Of Health And Ageing In Admentioning

confidence: 99%

What do we know about the nutritional status of the very old? Insights from three cohorts of advanced age from the UK and New Zealand

et al. 2016

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Very old people (referred to as those aged 85 years and over) are the fastest growing age segment of many Western societies owing to the steady rise of life expectancy and decrease in later life mortality. In the UK, there are now more than 1·5 million very old people (2·5 % of total population) and the number is projected to rise to 3·3 million or 5 % over the next 20 years. Reduced mobility and independence, financial constraints, higher rates of hospitalisation, chronic diseases and disabilities, changes in body composition, taste perception, digestion and absorption of food all potentially influence either nutrient intake or needs at this stage of life. The nutritional needs of the very old have been identified as a research priority by the British Nutrition Foundation's Task Force report, Healthy Ageing: The Role of Nutrition and Lifestyle. However, very little is known about the dietary habits and nutritional status of the very old. The Newcastle 85+ study, a cohort of more than 1000 85-year olds from the North East of England and the Life and Living in Advanced Age study (New Zealand), a bicultural cohort study of advanced ageing of more than 900 participants from the Bay of Plenty and Rotorua regions of New Zealand are two unique cohort studies of ageing, which aim to assess the spectrum of health in the very old as well as examine the associations of health trajectories and outcomes with biological, clinical and social factors as each cohort ages. The nutrition domain included in both studies will help to fill the evidence gap by identifying eating patterns, and measures of nutritional status associated with better, or worse, health and wellbeing. This review will explore some of this ongoing work. The European Commission's 2015 ageing reports that the percentage of those aged ⩾80 years in the total population in Europe will increase from 5 % in 2013 to 12 % in 2060 (1) . Over the next 20 years, the population of England and Wales will increase by almost 10 %; in comparison, older people in the over 85 years age group will increase by around two-thirds (2) . In addition to the policy priority assigned to improving the healthcare of older

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Agreement between self-reports and medical records of cardiovascular disease in octogenarians

Cited by 43 publications

References 22 publications

Accuracy of Self-Reported Heart Failure. The Atherosclerosis Risk in Communities (ARIC) Study

Accuracy of Self-Reported Heart Failure. The Atherosclerosis Risk in Communities (ARIC) Study

Dietary protein intake may reduce hospitalisation due to infection in Māori of advanced age: LiLACS NZ

What do we know about the nutritional status of the very old? Insights from three cohorts of advanced age from the UK and New Zealand

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