Evidence map›Paper›PMID 29950478›Full record

ArticleBMJ open2018

Factors influencing early and late readmissions in Australian hospitalised patients and investigating role of admission nutrition status as a predictor of hospital readmissions: a cohort study.

Yogesh Sharma, Michelle Miller, Billingsley Kaambwa, Rashmi Shahi, Paul Hakendorf, Chris Horwood, Campbell Thompson

Open access · goldAbstract readMulticenter Study
In one paragraph

Article in BMJ open, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
26citing papers in PubMed, 2 pooled it
1.9field-weighted citation impact, top 14% of its field
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

26 citing papers in PubMed, 2 syntheses or guidelines pooled it, 41 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
  3. Addressing Malnutrition in Australian Hospitals: A Scoping Review to Inform Systems Thinking.Journal of human nutrition and dietetics : the official journal of the British Dietetic Association · 2026
    Article
  4. Article
  5. Article
  6. Review
  7. Observational
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Article
  19. Article
  20. Article
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

7 authors at 3 institutions in 1 country.

Yogesh SharmaDepartment of General Medicine, Flinders Medical Centre, Bedford Park, South Australia, Australia.ORCID 0000-0002-7716-2599
Michelle MillerDepartment of Nutrition and Dietetics, Flinders University Faculty of Medicine Nursing and Health Sciences, Adelaide, South Australia, Australia.
Billingsley KaambwaHealth Economics Unit, Flinders University, Adelaide, South Australia, Australia.
Rashmi ShahiFaculty of Health Sciences, Flinders University, Adelaide, South Australia, Australia.
Paul HakendorfDepartment of Clinical Epidemiology, Flinders Medical Centre, Bedford Park, South Australia, Australia.
Chris HorwoodDepartment of Clinical Epidemiology, Flinders Medical Centre, Bedford Park, South Australia, Australia.
Campbell ThompsonDiscipline of Medicine, University of Adelaide, Adelaide, South Australia, Australia.
Flinders University · AUFlinders Medical Centre · AUThe University of Adelaide · AU

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesLimited studies have identified predictors of early and late hospital readmissions in Australian healthcare settings. Some of these predictors may be modifiable through targeted interventions. A recent study has identified malnutrition as a predictor of readmissions in older patients but this has not been verified in a larger population. This study investigated what predictors are associated with early and late readmissions and determined whether nutrition status during index hospitalisation can be used as a modifiable predictor of unplanned hospital readmissions.

designA retrospective cohort study.

settingTwo tertiary-level hospitals in Australia.

participantsAll medical admissions ≥18 years over a period of 1 year. OUTCOMES: Primary objective was to determine predictors of early (0-7 days) and late (8-180 days) readmissions. Secondary objective was to determine whether nutrition status as determined by malnutrition universal screening tool (MUST) can be used to predict readmissions.

resultsThere were 11 750 (44.8%) readmissions within 6 months, with 2897 (11%) early and 8853 (33.8%) late readmissions. MUST was completed in 16.2% patients and prevalence of malnutrition during index admission was 31%. Malnourished patients had a higher risk of both early (OR 1.39, 95% CI 1.12 to 1.73) and late readmissions (OR 1.23, 95% CI 1.06 to 128). Weekend discharges were less likely to be associated with both early (OR 0.81, 95% CI 0.74 to 0.91) and late readmissions (OR 0.91, 95% CI 0.84 to 0.97). Indigenous Australians had a higher risk of early readmissions while those living alone had a higher risk of late readmissions. Patients ≥80 years had a lower risk of early readmissions while admission to intensive care unit was associated with a lower risk of late readmissions.

conclusionsMalnutrition is a strong predictor of unplanned readmissions while weekend discharges are less likely to be associated with readmissions. Targeted nutrition intervention may prevent unplanned hospital readmissions.

trial registrationANZCTRN 12617001362381; Results.

Indexed as

Nutritional StatusAdultAgedAged, 80 and overAustraliaFemaleHumansLength of StayLogistic ModelsMaleMalnutritionMiddle AgedNutrition AssessmentPatient ReadmissionPredictive Value of TestsRetrospective Studiesepidemiologyinternal medicinequality in health care

Identifiers

PMID29950478
PMCPMC6020977
OpenAlexW2810591358

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

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.