Evidence map›Paper›PMID 27091655›Full record

ArticleSchizophrenia research2016

Predictors of long-term (≥6months) antipsychotic polypharmacy prescribing in secondary mental healthcare.

Giouliana Kadra, Robert Stewart, Hitesh Shetty, Johnny Downs, James H MacCabe, David Taylor, Richard D Hayes

Abstract read
In one paragraph

Article in Schizophrenia research, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
12citing 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

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

  1. Pooled it
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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

7 authors.

Giouliana KadraKing's College London, Institute of Psychiatry, Psychology and Neuroscience, London, UK. Electronic address: Giouliana.kadra@kcl.ac.uk.
Robert StewartKing's College London, Institute of Psychiatry, Psychology and Neuroscience, London, UK.
Hitesh ShettySouth London and Maudsley NHS Foundation Trust, London, UK.
Johnny DownsKing's College London, Institute of Psychiatry, Psychology and Neuroscience, London, UK.
James H MacCabeKing's College London, Institute of Psychiatry, Psychology and Neuroscience, London, UK.
David TaylorSouth London and Maudsley NHS Foundation Trust, London, UK.
Richard D HayesKing's College London, Institute of Psychiatry, Psychology and Neuroscience, London, UK.

Funding

Medical Research Council MR/J01219X/1Medical Research Council MR/L011794/1Medical Research Council MR/L017105/1
6 · The paper itself

Abstract

introductionThe predictors of long-term antipsychotic polypharmacy (APP) initiation are poorly understood. Existing research has been hampered by residual confounding, failure to exclude cross-titration, and difficulties in separating the timing of predictors and APP administration. MATERIALS AND

methodsUsing data from the South London and Maudsley (SLaM) case register, we identified all adult patients with serious mental illness (SMI) who were receiving care between 1st July 2011 and 30th June 2012. Exposures measured between 1st July and 31st December 2011 included socio-demographic, socioeconomic, clinical and service use characteristics. We then determined if long-term APP (six or more months) had been initiated between 1st January and 30th June 2012. Multivariable logistic regression models, adjusted for socio-demographic and socioeconomic factors, were built to investigate the associations between the above factors and the initiation of long-term APP.

resultsWe identified 6857 adults with SMI receiving SLaM care, of whom 115 (1.7%) were newly prescribed long-term APP. In the adjusted models, predictors of long-term APP initiation included: symptoms (severity of hallucinations and/or delusions), previous treatments (clozapine and long-acting injectable antipsychotic agents), service use (more contact with outpatient services, community treatment order receipt), social factors (higher area-level deprivation, homelessness) and socio-demographic status (younger age, not in a relationship).

conclusionOur findings highlight that certain patient groups are at an increased risk for long-term APP initiation. Identifying these groups earlier in their treatment could encourage clinicians to employ a broader range of interventions in addition to pharmacotherapy to reduce the risk of APP prescribing.

Indexed as

AdolescentAdultAntipsychotic AgentsBipolar DisorderFemaleFollow-Up StudiesHumansLondonMaleMiddle AgedPolypharmacyPrognosisPsychotic DisordersRegistriesRetrospective StudiesRisk FactorsAntipsychotic AgentsAntipsychotic polypharmacyClinical symptomsPredictorsService useSocio-demographicSocioeconomic

Identifiers

PMID27091655
PMCPMC4922621

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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.