Evidence map›Paper›PMID 33632124›Full record

ArticleBMC geriatrics2021

A practical laboratory index to predict institutionalization and mortality - an 18-year population-based follow-up study.

Elisa Heikkilä, Marika Salminen, Anna Viljanen, Taina Katajamäki, Marja-Kaisa Koivula, Kari Pulkki, Raimo Isoaho, Sirkka-Liisa Kivelä, Matti Viitanen, Minna Löppönen and 3 more

Abstract read
In one paragraph

Article in BMC geriatrics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed, 1 pooled it
–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

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

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

6 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Observational
  3. Article
  4. Article
  5. Article
  6. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

13 authors.

Elisa HeikkiläDepartment of Clinical Medicine, Faculty of Medicine, Unit of Clinical Chemistry, Turku University, 20521, Turku, Finland. etmhei@utu.fi.
Marika SalminenDepartment of Clinical Medicine, Faculty of Medicine, Unit of Family Medicine, University of Turku and Turku University Hospital, 20014, Turku, Finland.
Anna ViljanenMunicipality of Lieto, Health Care Center, 21420, Lieto, Finland.
Taina KatajamäkiDepartment of Clinical Medicine, Faculty of Medicine, Unit of Clinical Chemistry, Turku University, 20521, Turku, Finland.
Marja-Kaisa KoivulaDepartment of Clinical Medicine, Faculty of Medicine, Unit of Clinical Chemistry, Turku University, 20521, Turku, Finland.
Kari PulkkiDiagnostic Center, Clinical Chemistry and Hematology, Helsinki University Hospital and University of Helsinki, 00029, Helsinki, Finland.
Raimo IsoahoDepartment of Clinical Medicine, Faculty of Medicine, Unit of Family Medicine, University of Turku and Turku University Hospital, 20014, Turku, Finland.
Sirkka-Liisa KiveläDepartment of Clinical Medicine, Faculty of Medicine, Unit of Family Medicine, University of Turku and Turku University Hospital, 20014, Turku, Finland.
Matti ViitanenFaculty of Medicine, Department of Clinical Medicine, Unit of Geriatrics, Turku City Hospital, University of Turku, 20700, Turku, Finland.
Minna LöppönenCity of Raisio, Social and Health Care for Elderly, 21200, Raisio, Finland.
Tero VahlbergDepartment of Clinical Medicine, Faculty of Medicine, Unit of Biostatistics, University of Turku, Turku, Finland.
Laura ViikariCity of Turku, Welfare Division, 20101, Turku, Finland.
Kerttu IrjalaDepartment of Clinical Medicine, Faculty of Medicine, Unit of Clinical Chemistry, Turku University, 20521, Turku, Finland.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundPreviously, several indexes based on a large number of clinical and laboratory tests to predict mortality and frailty have been produced. However, there is still a need for an easily applicable screening tool for every-day clinical practice.

methodsA prospective study with 10- and 18-year follow-ups. Fourteen common laboratory tests were combined to an index. Cox regression model was used to analyse the association of the laboratory index with institutionalization and mortality.

resultsThe mean age of the participants (n = 1153) was 73.6 (SD 6.8, range 64.0-100.0) years. Altogether, 151 (14.8%) and 305 (29.9%) subjects were institutionalized and 422 (36.6%) and 806 (69.9%) subjects deceased during the 10- and 18-year follow-ups, respectively. Higher LI (laboratory index) scores predicted increased mortality. Mortality rates increased as LI scores increased both in unadjusted and in age- and gender-adjusted models during both follow-ups. The LI did not significantly predict institutionalization either during the 10- or 18-year follow-ups.

conclusionsA practical index based on routine laboratory tests can be used to predict mortality among older people. An LI could be automatically counted from routine laboratory results and thus an easily applicable screening instrument in clinical settings.

Indexed as

Frail ElderlyLaboratoriesAgedAged, 80 and overFollow-Up StudiesGeriatric AssessmentHumansInstitutionalizationProspective StudiesAgedInstitutionalizationLaboratory indexMortality

Identifiers

PMID33632124
PMCPMC7905906

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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.