Evidence map›Paper›PMID 33687979›Full record

ArticleJournal of the American Society of Nephrology : JASN2021

The Preventable Productivity Burden of Kidney Disease in Australia.

Feby Savira, Zanfina Ademi, Bing H Wang, Andrew R Kompa, Alice J Owen, Danny Liew, Ella Zomer

Abstract read
In one paragraph

Article in Journal of the American Society of Nephrology : JASN, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

12 citing papers in PubMed.

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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

7 authors.

Feby SaviraSchool of Public Health and Preventive Medicine, Monash University, Melbourne, Australia.
Zanfina AdemiSchool of Public Health and Preventive Medicine, Monash University, Melbourne, Australia.
Bing H WangSchool of Public Health and Preventive Medicine, Monash University, Melbourne, Australia.
Andrew R KompaDepartment of Medicine, University of Melbourne, St Vincent's Hospital, Fitzroy, Australia.
Alice J OwenSchool of Public Health and Preventive Medicine, Monash University, Melbourne, Australia.
Danny LiewSchool of Public Health and Preventive Medicine, Monash University, Melbourne, Australia.
Ella ZomerSchool of Public Health and Preventive Medicine, Monash University, Melbourne, Australia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundKidney disease is associated with impaired work productivity. However, the collective effect of missed work days, reduced output at work, and early withdrawal from the workforce is rarely considered in health-economic evaluations.

methodsTo determine the effect on work productivity of preventing incident cases of kidney disease, using the novel measure "productivity-adjusted life year" (PALY), we constructed a dynamic life table model for the Australian working-age population (aged 15-69 years) over 10 years (2020-2029), stratified by kidney-disease status. Input data, including productivity estimates, were sourced from the literature. We ascribed a financial value to the PALY metric in terms of gross domestic product (GDP) per equivalent full-time worker and assessed the total number of years lived, total PALYs, and broader economic costs (GDP per PALY). We repeated the model simulation, assuming a reduced kidney-disease incidence; the differences reflected the effects of preventing new kidney-disease cases. Outcomes were discounted by 5% annually.

resultsOur projections indicate that, from 2020 to 2029, the estimated number of new kidney-disease cases will exceed 161,000. Preventing 10% of new cases of kidney disease during this period would result in >300 premature deaths averted and approximately 550 years of life and 7600 PALYs saved-equivalent to a savings of US$1.1 billion in GDP or US$67,000 per new case avoided.

conclusionsPursuing a relatively modest target for preventing kidney disease in Australia may prolong years of life lived and increase productive life years, resulting in substantial economic benefit. Our findings highlight the need for investment in preventive measures to reduce future cases of kidney disease.

Indexed as

burdenchronic kidney diseasedynamic life table modelend stage kidney diseaseincidenceproductivity

Identifiers

PMID33687979
PMCPMC8017534

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.