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Predictors of treatment resistance in patients with schizophrenia: a population-based cohort study

Overview of attention for article published in "The Lancet Psychiatry", February 2016
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43

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  • In the top 5% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (95th percentile)
  • Good Attention Score compared to outputs of the same age and source (70th percentile)

Mentioned by

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1 news outlet
twitter
55 tweeters
facebook
1 Facebook page

Citations

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42 Dimensions

Readers on

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137 Mendeley
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Title
Predictors of treatment resistance in patients with schizophrenia: a population-based cohort study
Published in
"The Lancet Psychiatry", February 2016
DOI 10.1016/s2215-0366(15)00575-1
Pubmed ID
Authors

Theresa Wimberley, Henrik Støvring, Holger J Sørensen, Henriette T Horsdal, James H MacCabe, Christiane Gasse, Wimberley, Theresa, Støvring, Henrik, Sørensen, Holger J, Horsdal, Henriette T, MacCabe, James H, Gasse, Christiane

Abstract

Identification of patients at high risk of treatment-resistant schizophrenia at the time of schizophrenia diagnosis would be of great clinical benefit in minimising the delay to clozapine treatment in patients unlikely to respond to non-clozapine antipsychotics. However, little is known about predictors of treatment resistance in this patient population. We used a treatment-based proxy for treatment-resistant schizophrenia to identify candidate predictors of treatment resistance at first hospital contact with a schizophrenia diagnosis. In this population-based cohort study, we obtained Danish national registry data for all adult patients (≥18 years) with incident schizophrenia diagnosed between Jan 1, 1996, and Dec 31, 2006, and followed up until Dec 31, 2010. Our main proxy definition of treatment-resistant schizophrenia was the earliest instance of either clozapine initiation or hospital admission for schizophrenia after having had two periods of different antipsychotic monotherapy. We did multivariable Cox proportional hazards regression analysis to estimate the association between baseline candidate predictors and treatment resistance. 8624 patients fulfilled the criteria for inclusion. In multivariable complete-case analyses, 1703 (21%) of 8044 patients fulfilled the main proxy definition of treatment-resistant schizophrenia during a median follow-up of 9·1 years (IQR 6·3-11·9). Younger age (hazard ratio 0·96 [95% CI 0·95-0·97]), living in a less urban area (provincial 1·38 [1·23-1·56], rural 1·44 [1·25-1·65]), primary education level (0·88 [0·79-0·98]), more than 30 bed-days in psychiatric hospital in the year before first schizophrenia diagnosis (1·54 [1·35-1·75]), inpatient at first schizophrenia diagnosis (2·07 [1·87-2·29]), paranoid subtype (1·24 [1·13-1·37]), comorbid personality disorder (1·24 [1·11-1·39]), psychotropic drug use (antipsychotics 1·51 [1·35-1·69], antidepressants 1·15 [1·03-1·29], and benzodiazepines 1·22 [1·10-1·37]), and previous suicide attempt (1·21 [1·07-1·39]) were all significantly associated with treatment-resistant schizophrenia. Our study identifies several candidate predictors that could potentially be included in future prediction models for treatment-resistant schizophrenia. Notably, established risk factors for schizophrenia did not predict treatment resistance, suggesting that treatment-resistant disease might be a distinct subtype of schizophrenia and not merely a more severe form. European Community's Seventh Framework Programme.

Twitter Demographics

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Mendeley readers

The data shown below were compiled from readership statistics for 137 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
France 1 <1%
Canada 1 <1%
Unknown 135 99%

Demographic breakdown

Readers by professional status Count As %
Student > Master 27 20%
Researcher 21 15%
Student > Ph. D. Student 21 15%
Unspecified 17 12%
Student > Bachelor 13 9%
Other 38 28%
Readers by discipline Count As %
Medicine and Dentistry 52 38%
Unspecified 30 22%
Psychology 24 18%
Neuroscience 7 5%
Nursing and Health Professions 6 4%
Other 18 13%

Attention Score in Context

This research output has an Altmetric Attention Score of 43. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 14 April 2016.
All research outputs
#416,627
of 13,756,520 outputs
Outputs from "The Lancet Psychiatry"
#454
of 1,519 outputs
Outputs of similar age
#12,832
of 266,642 outputs
Outputs of similar age from "The Lancet Psychiatry"
#19
of 64 outputs
Altmetric has tracked 13,756,520 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 96th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,519 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 74.3. This one has gotten more attention than average, scoring higher than 70% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 266,642 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 95% of its contemporaries.
We're also able to compare this research output to 64 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 70% of its contemporaries.