Evidence map›Paper›PMID 23800985›Full record

ArticleCirculation. Cardiovascular quality and outcomes2013

Optimal in-hospital and discharge medical therapy in acute coronary syndromes in Kerala: results from the Kerala acute coronary syndrome registry.

Mark D Huffman, Dorairaj Prabhakaran, Adangapuram Kurien Abraham, Mangalath Narayanan Krishnan, Asokan Cheviri Nambiar, Padinhare Purayil Mohanan, Kerala Acute Coronary Syndrome Registry Investigators

Open access · bronzeAbstract readMulticenter Study
In one paragraph

Article in Circulation. Cardiovascular quality and outcomes, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
25citing papers in PubMed, 1 pooled it
3.6field-weighted citation impact, top 6% 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

25 citing papers in PubMed, 1 synthesis or guideline pooled it, 43 citations in OpenAlex.

  1. Pooled it
  2. Trial
  3. Trial
  4. Trial
  5. Article
  6. Review
  7. Observational
  8. [The Value of Using SCAI Cardiogenic Shock Stages in Predicting Mortality in CICU Patients].Sichuan da xue xue bao. Yi xue ban = Journal of Sichuan University. Medical science edition · 2021
    Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Review
  15. Review
  16. Article
  17. Article
  18. Review
  19. Observational
  20. Observational
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 2 countries.

Mark D HuffmanDepartment of Preventive Medicine, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA. m-huffman@northwestern.edu
Dorairaj Prabhakaran
Adangapuram Kurien Abraham
Mangalath Narayanan Krishnan
Asokan Cheviri Nambiar
Padinhare Purayil Mohanan
Kerala Acute Coronary Syndrome Registry Investigators
Baby Memorial Hospital · INCentre for Chronic Disease Control · INNorthwestern University · US

Funding

Interdisciplinary research training: NCD epidemiology and prevention in IndiaD43HD065249 · NICHD · CENTRE FOR CHRONIC DISEASE CONTROL · PI NARAYAN, KABAYAM M VENKAT, TANDON, NIKHIL · 2009 to 2013
$1.2M
Acute Coronary Syndrome Quality Improvement in Kerala (ACS QUIK)K99HL107749 · NHLBI · NORTHWESTERN UNIVERSITY AT CHICAGO · PI HUFFMAN, MARK D · 2012 to 2013
$171k
NHLBI NIH HHS 1 K99 HL107749-01A1NHLBI NIH HHS HHSN268200900026CNHLBI NIH HHS K99 HL107749NICHD NIH HHS 1D43HD065249NICHD NIH HHS D43 HD065249PHS HHS HHS N268200900026C
6 · The paper itself

Abstract

backgroundIn-hospital and postdischarge treatment rates for acute coronary syndrome (ACS) remain low in India. However, little is known about the prevalence and associations of the package of optimal ACS medical care in India. Our objective was to define the prevalence, associations, and impact of optimal in-hospital and discharge medical therapy in the Kerala ACS Registry of 25,718 admissions. METHODS AND

resultsWe defined optimal in-hospital ACS medical therapy as receiving the following 5 medications: aspirin, clopidogrel, heparin, β-blocker, and statin. We defined optimal discharge ACS medical therapy as receiving all of the above therapies except heparin. Comparisons by optimal versus nonoptimal ACS care were made via Student t test for continuous variables and χ(2) test for categorical variables. We created random effects logistic regression models to evaluate the association between Global Registry of Acute Coronary Events risk score variables and optimal in-hospital or discharge medical therapy. Optimal in-hospital and discharge medical care were delivered in 40% and 46% of admissions, respectively. Wide variability in both in-hospital and discharge medical care was present, with few hospitals reaching consistently high (>90%) levels. Patients receiving optimal in-hospital medical therapy had an adjusted odds ratio (95% confidence interval)=0.93 (0.71, 1.22) for in-hospital death and an adjusted odds ratio (95% confidence interval)=0.79 (0.63, 0.99) for major adverse cardiovascular event rates. Patients who received optimal in-hospital medical care were far more likely to receive optimal discharge care (adjusted odds ratio [95% confidence interval] = 10.48 [9.37, 11.72]).

conclusionsStrategies to improve in-hospital and discharge medical therapy are needed to improve local process-of-care measures and ACS outcomes in Kerala.

Indexed as

Acute Coronary SyndromeAgedCardiology Service, HospitalCardiovascular AgentsChi-Square DistributionContinuity of Patient CareFemaleGuideline AdherenceHospital MortalityHumansIndiaLogistic ModelsMaleMiddle AgedOdds RatioPatient AdmissionCardiovascular Agentsacute coronary syndromehealth policy and outcome researchregistries

Identifiers

PMID23800985
PMCPMC3830530
OpenAlexW2548217250

What OpenQuestion holds

Textmetadata
LicenceTDM
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.