Evidence map›Paper›PMID 21966317›Full record

ArticleDeutsches Arzteblatt international2011

Predictors of dependency on nursing care after stroke: results from the Dortmund and Münster stroke registry.

Claudia Diederichs, Kristin Mühlenbruch, Hans-Otto Lincke, Peter U Heuschmann, Martin A Ritter, Klaus Berger

Abstract read
In one paragraph

Article in Deutsches Arzteblatt international, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing 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

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

8 citing papers in PubMed.

  1. Article
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  3. Review
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  5. Article
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  7. Observational
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Claudia DiederichsInstitut für Epidemiologie und Sozialmedizin, Westfälische Wilhelms-Universität Münster. cdiederi@uni-muenster.de
Kristin Mühlenbruch
Hans-Otto Lincke
Peter U Heuschmann
Martin A Ritter
Klaus Berger

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe long-term effects of stroke have been inadequately studied. We identified social and clinical factors that were associated with application for insurance payments for long-term care within 3.6 years after stroke.

methodsIn a quality-assurance project called "Stroke Northwest Germany," information was obtained from 2286 stroke patients on their socio-demographic background, type of stroke, comorbidities, and degree of physical impairment during their hospital stay, as measured on the Rankin Scale, the Barthel Index, and the Neurological Symptom Scale. We used logistic regression models to identify possible associations between these factors and application for insurance payments for long-term care within 3.6 years after stroke. We developed an appropriate prognostic model by means of backward selection.

results734 (32.1%) of the patients participated in follow-up and reported whether they had applied for insurance payments for long-term care. 22.5% had submitted an application. The rate of application was positively correlated with age, female sex, the number of comorbidities and complications during hospitalization, and the degree of physical impairment.

conclusionStroke has major long-term effects. The probability that a stroke patient will apply for insurance payments for long-term care is a function of the patient's age, sex, previous stroke history, and physical impairment as measured on the Rankin Scale and the Barthel Index.

Indexed as

Disability EvaluationInsurance, Long-Term CareAgedAged, 80 and overAge FactorsCause of DeathComorbidityEligibility DeterminationFemaleFollow-Up StudiesGermanyHumansMaleMiddle AgedNational Health ProgramsNeeds Assessment

Identifiers

PMID21966317
PMCPMC3183302

What OpenQuestion holds

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Registered trials

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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.