Evidence map›Paper›PMID 26048212›Full record

ArticleBMJ open2015

A comparison of the recording of comorbidity in primary and secondary care by using the Charlson Index to predict short-term and long-term survival in a routine linked data cohort.

C J Crooks, J West, T R Card

Abstract readComparative Study
In one paragraph

Article in BMJ open, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 49 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
49citing papers in PubMed, 2 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

49 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Guideline
  2. Pooled it
  3. Relative effectiveness of high-dose versus standard-dose influenza vaccine against hospitalizations and mortality according to Charlson Comorbidity Index: A post-hoc analysis of the DANFLU-1 randomized trial.European journal of clinical microbiology & infectious diseases : official publication of the European Society of Clinical Microbiology · 2026
    Trial
  4. Article
  5. Article
  6. Article
  7. Article
  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

3 authors.

C J CrooksDivision of Epidemiology and Public Health, Nottingham City Hospital, University of Nottingham, Nottingham, Nottinghamshire, UK.
J WestDivision of Epidemiology and Public Health, Nottingham City Hospital, University of Nottingham, Nottingham, Nottinghamshire, UK.ORCID http://orcid.org/0000-0002-1135-9356
T R CardDivision of Epidemiology and Public Health, Nottingham City Hospital, University of Nottingham, Nottingham, Nottinghamshire, UK.

Funding

Medical Research Council G0802427
6 · The paper itself

Abstract

objectiveHospital admission records provide snapshots of clinical histories for a subset of the population admitted to hospital. In contrast, primary care records provide continuous clinical histories for complete populations, but might lack detail about inpatient stays. Therefore, combining primary and secondary care records should improve the ability of comorbidity scores to predict survival in population-based studies, and provide better adjustment for case-mix differences when assessing mortality outcomes.

designCohort study.

settingEnglish primary and secondary care 1 January 2005 to 1 January 2010.

participantsAll patients 20 years and older registered to a primary care practice contributing to the linked Clinical Practice Research Datalink from England. OUTCOME: The performance of the Charlson index with mortality was compared when derived from either primary or secondary care data or both. This was assessed in relation to short-term and long-term survival, age, consultation rate, and specific acute and chronic diseases.

results657,264 people were followed up from 1 January 2005. Although primary care recorded more comorbidity than secondary care, the resulting C statistics for the Charlson index remained similar: 0.86 and 0.87, respectively. Higher consultation rates and restricted age bands reduced the performance of the Charlson index, but the index's excellent performance persisted over longer follow-up; the C statistic was 0.87 over 1 year, and 0.85 over all 5 years of follow-up. The Charlson index derived from secondary care comorbidity had a greater effect than primary care comorbidity in reducing the association of upper gastrointestinal bleeding with mortality. However, they had a similar effect in reducing the association of diabetes with mortality.

conclusionsThese findings support the use of the Charlson index from linked data and show that secondary care comorbidity coding performed at least as well as that derived from primary care in predicting survival.

Indexed as

ComorbidityHospital MortalityAdultAgedAged, 80 and overCohort StudiesDatabases, FactualDeath CertificatesEnglandFemaleHumansMaleMiddle AgedPredictive Value of TestsEPIDEMIOLOGYGASTROENTEROLOGYGENERAL MEDICINE (see Internal Medicine)PRIMARY CARESTATISTICS & RESEARCH METHODS

Identifiers

PMID26048212
PMCPMC4458584

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.