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All Outputs (13)

Evaluating a clinical tool (FAMCAT) for identifying familial hypercholesterolaemia in primary care: a retrospective cohort study (2020)
Journal Article
Akyea, R. K., Qureshi, N., Kai, J., de Lusignan, S., Sherlock, J., McGee, C., & Weng, S. (2020). Evaluating a clinical tool (FAMCAT) for identifying familial hypercholesterolaemia in primary care: a retrospective cohort study. BJGP Open, 4(5), 1-10. https://doi.org/10.3399/bjgpopen20X101114

Background: Familial hypercholesterolaemia (FH) is an inherited lipid disorder causing premature heart disease, which is severely underdiagnosed. Improving the identification of people with FH in primary care settings would help to reduce avoidable h... Read More about Evaluating a clinical tool (FAMCAT) for identifying familial hypercholesterolaemia in primary care: a retrospective cohort study.

Performance and clinical utility of supervised machine-learning approaches in detecting familial hypercholesterolaemia in primary care (2020)
Journal Article
Akyea, R. K., Qureshi, N., Kai, J., & Weng, S. F. (2020). Performance and clinical utility of supervised machine-learning approaches in detecting familial hypercholesterolaemia in primary care. npj Digital Medicine, 3(1), Article 142. https://doi.org/10.1038/s41746-020-00349-5

Familial hypercholesterolaemia (FH) is a common inherited disorder, causing lifelong elevated low-density lipoprotein cholesterol (LDL-C). Most individuals with FH remain undiagnosed, precluding opportunities to prevent premature heart disease and de... Read More about Performance and clinical utility of supervised machine-learning approaches in detecting familial hypercholesterolaemia in primary care.

Predicting major adverse cardiovascular events for secondary prevention: protocol for a systematic review and meta-analysis of risk prediction models (2020)
Journal Article
Akyea, R. K., Leonardi-Bee, J., Asselbergs, F. W., Patel, R. S., Durrington, P., Wierzbicki, A. S., …Weng, S. F. (2020). Predicting major adverse cardiovascular events for secondary prevention: protocol for a systematic review and meta-analysis of risk prediction models. BMJ Open, 10(7), Article e034564. https://doi.org/10.1136/bmjopen-2019-034564

Introduction: Cardiovascular disease (CVD) is the leading cause of morbidity and mortality globally. With advances in early diagnosis and treatment of CVD and increasing life expectancy, more people are surviving initial CVD events. However, models t... Read More about Predicting major adverse cardiovascular events for secondary prevention: protocol for a systematic review and meta-analysis of risk prediction models.

Improving primary care identification of familial breast cancer risk using proactive invitation and decision support (2020)
Journal Article
Qureshi, N., Dutton, B., Weng, S., Sheehan, C., Chorley, W., Robertson, J. F., …Kai, J. (2021). Improving primary care identification of familial breast cancer risk using proactive invitation and decision support. Familial Cancer, 20(1), 13-21. https://doi.org/10.1007/s10689-020-00188-z

Family history of breast cancer is a key risk factor, accounting for up to 10% of cancers. We evaluated the proactive assessment of familial breast cancer (FBC) risk in primary care. Eligible women (30 to 60 years) were recruited from eight English g... Read More about Improving primary care identification of familial breast cancer risk using proactive invitation and decision support.

Development and validation of the DIabetes Severity SCOre (DISSCO) in 139 626 individuals with type 2 diabetes: a retrospective cohort study (2020)
Journal Article
Zghebi, S. S., Mamas, M. A., Ashcroft, D. M., Salisbury, C., Mallen, C. D., Chew-Graham, C. A., …Kontopantelis, E. (2020). Development and validation of the DIabetes Severity SCOre (DISSCO) in 139 626 individuals with type 2 diabetes: a retrospective cohort study. BMJ Open Diabetes Research and Care, 8(1), Article e000962. https://doi.org/10.1136/bmjdrc-2019-000962

Objective: Clinically-applicable diabetes severity measures are lacking, with no previous studies compared their predictive value to HbA1c. We developed and validated a type 2 diabetes severity score (DISSCO) and evaluated its association with risks... Read More about Development and validation of the DIabetes Severity SCOre (DISSCO) in 139 626 individuals with type 2 diabetes: a retrospective cohort study.

Risk of cardiovascular disease outcomes in primary care subjects with familial hypercholesterolaemia: A cohort study (2019)
Journal Article
Iyen, B., Qureshi, N., Leonardi-Bee, J., Kai, J., Akyea, R. K., Roderick, P., …Weng, S. (2019). Risk of cardiovascular disease outcomes in primary care subjects with familial hypercholesterolaemia: A cohort study. Atherosclerosis, 287, 8-15. https://doi.org/10.1016/j.atherosclerosis.2019.05.017

Background and aims: Familial hypercholesterolaemia (FH) is a known major cause of premature heart disease. However, the risks of atherosclerotic disease in other vascular regions are less known. We determined the risk of major cardiovascular disease... Read More about Risk of cardiovascular disease outcomes in primary care subjects with familial hypercholesterolaemia: A cohort study.

Effectiveness of interventions to identify and manage patients with familial cancer risk in primary care: a systematic review (2019)
Journal Article
Ing Lee, S., Patel, M., Dutton, B., Weng, S., Luveta, J., & Qureshi, N. (2019). Effectiveness of interventions to identify and manage patients with familial cancer risk in primary care: a systematic review. Journal of Community Genetics, https://doi.org/10.1007/s12687-019-00419-6

This systematic review evaluated the effectiveness of strategies to identify and manage patients with familial risk of breast, ovarian, colorectal and prostate cancer in primary careto improve clinical outcomes. MEDLINE, EMBASE, CINAHL and Cochrane l... Read More about Effectiveness of interventions to identify and manage patients with familial cancer risk in primary care: a systematic review.

Detection of familial hypercholesterolaemia: external validation of the FAMCAT clinical case-finding algorithm to identify patients in primary care (2019)
Journal Article
Weng, S., Kai, J., Akyea, R., & Qureshi, N. (2019). Detection of familial hypercholesterolaemia: external validation of the FAMCAT clinical case-finding algorithm to identify patients in primary care. Lancet Public Health, 4(5), e256-e264. https://doi.org/10.1016/S2468-2667%2819%2930061-1

Background: The vast majority of individuals with familial hypercholesterolaemia (FH) in the general population remain unidentified worldwide. Recognising patients most at risk of having the condition, to enable targeted specialist assessment and tre... Read More about Detection of familial hypercholesterolaemia: external validation of the FAMCAT clinical case-finding algorithm to identify patients in primary care.

Sub-optimal cholesterol response to initiation of statins and future risk of cardiovascular disease (2019)
Journal Article
Akyea, R., Kai, J., Qureshi, N., Iyen, B., & Weng, S. (2019). Sub-optimal cholesterol response to initiation of statins and future risk of cardiovascular disease. Heart, 105(13), 975-981. https://doi.org/10.1136/heartjnl-2018-314253

Objective: To assess low-density lipoprotein cholesterol (LDL-C) response in patients after initiation of statins, and future risk of CVD. Method: Prospective cohort study of 165,411 primary care patients, from the UK Clinical Practice Research... Read More about Sub-optimal cholesterol response to initiation of statins and future risk of cardiovascular disease.

Prediction of premature all-cause mortality: a prospective general population cohort study comparing machine-learning and standard epidemiological approaches (2019)
Journal Article
Weng, S. F., Vaz, L., Qureshi, N., & Kai, J. (2019). Prediction of premature all-cause mortality: a prospective general population cohort study comparing machine-learning and standard epidemiological approaches. PLoS ONE, 14(3), 1-22. https://doi.org/10.1371/journal.pone.0214365

Background: Prognostic modelling using standard methods is well-established, particularly for predicting risk of single diseases. Machine-learning may offer potential to explore outcomes of even greater complexity, such as premature death. This stud... Read More about Prediction of premature all-cause mortality: a prospective general population cohort study comparing machine-learning and standard epidemiological approaches.

Proactive assessment of obesity risk during infancy (ProAsk): a qualitative study of parents’ and professionals’ perspectives on an mHealth intervention. (2019)
Journal Article
Rose, J., Glazebrook, C., Wharrad, H., Siriwardena, A. N., Swift, J. A., Nathan, D., …Redsell, S. (2019). Proactive assessment of obesity risk during infancy (ProAsk): a qualitative study of parents’ and professionals’ perspectives on an mHealth intervention. BMC Public Health, 19, Article 294. https://doi.org/10.1186/s12889-019-6616-5

Background: Prevention of childhood obesity is a public health priority. Interventions that establish healthy growth trajectories early in life promise lifelong benefits to health and wellbeing. Proactive Assessment of Obesity Risk during Infancy... Read More about Proactive assessment of obesity risk during infancy (ProAsk): a qualitative study of parents’ and professionals’ perspectives on an mHealth intervention..