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Record W2961256776 · doi:10.1111/jpm.12546

Glucose, cholesterol and blood pressure in type II diabetes: A longitudinal observational study comparing patients with and without severe mental illness

2019· article· en· W2961256776 on OpenAlexaff
Robert Smith, Lu Han, Shehzad Ali, Stephanie L. Prady, Joanne E. Taylor, Tom Hughes, Ramzi Ajjan, Najma Siddiqi, Tim Doran

Bibliographic record

VenueJournal of Psychiatric and Mental Health Nursing · 2019
Typearticle
Languageen
FieldMedicine
TopicSchizophrenia research and treatment
Canadian institutionsWestern University
FundersNational Institute for Health Research Collaboration for Leadership in Applied Health Research and Care Yorkshire and HumberNational Institute for Health and Care ResearchNational Institute on Handicapped Research
KeywordsMedicineBlood pressureType 2 diabetesType 2 Diabetes MellitusPopulationInternal medicineDiabetes mellitusMental illnessObservational studyRisk factorLife expectancyAdverse effectDiseasePsychiatryMental healthEndocrinologyEnvironmental health

Abstract

fetched live from OpenAlex

Accessible Summary What is known on the subject? People with severe mental illness (SMI) have a life expectancy of 15–20 years less than the general population, partly due to increased risk of physical disease, including type II diabetes (T2DM) and cardiovascular disease. Little is known about changes in cardiovascular risk factors over time in people with both T2DM and SMI compared to those with T2DM and no SMI. What this paper adds to existing knowledge? We investigated whether levels of cardiovascular risk factors, cholesterol, HbA 1c, systolic and diastolic blood pressure associated with adverse clinical outcomes are different in T2DM patients with and without SMI. We found significant differences in systolic blood pressure and HbA 1c between the two groups. Fifty‐five percent and twenty‐nine percent of T2DM patients with comorbid SMI are at increased risk of adverse clinical outcomes due to sub‐optimal HbA 1c and systolic blood pressure levels, respectively. What are the implications for practice? Many patients with T2DM and SMI have higher levels of cardiovascular risk compared to patients with T2DM only, and good management of risk factors is therefore particularly important in patients with both conditions. Achieving better control of HbA 1c levels is likely to be central to addressing inequalities in outcomes for patients with both SMI and T2DM. Abstract Introduction Patients with both severe mental illness (SMI) and type II diabetes (T2DM) have lower life expectancy than patients with T2DM alone, partly due to poor control of cardiovascular risk factors in comorbid patients. Aim To compare levels of cholesterol, HbA 1c and blood pressure in T2DM patients with and without SMI. Method We analysed longitudinal clinical records of 30,353 people with T2DM (657 with SMI; 29,696 controls without SMI) between 2001 and 2013 using the Clinical Practice Research Datalink (CPRD). We used mixed‐effects regression models to compare cardiovascular risk factors between SMI and controls. Results Patients with SMI had lower mean systolic blood pressure (SBP; β : −2.49; SE = .45 p = <.01) and were more likely to have extreme (high and low) values of HbA 1c and SBP (OR: 1.38, 95% CI: 1.16, 1.64 and 1.76:1.40, 2.21, respectively). Discussion People with T2DM and SMI have similar average values of cardiovascular risk factors to people with T2DM alone but are more likely to have values of HbA 1c and SBP indicating increased risk of adverse clinical outcomes. Implications for Practice Improved management of cardiovascular risk factors in general, glycaemic control in particular, is central to addressing the increased risk of adverse outcomes in people with both SMI and T2DM.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.021
Threshold uncertainty score0.041

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0010.003
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.029
GPT teacher head0.333
Teacher spread0.304 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations20
Published2019
Admission routes1
Has abstractyes

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