Richard Grieve

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Professor

London School of Hygiene & Tropical Medicine

United Kingdom

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About

Richard Grieve is a Professor at the London School of Hygiene and Tropical Medicine in the United Kingdom. His research interests include the comparative effectiveness of glucose-lowering therapies for type 2 diabetes, treatment outcomes for early-stage cancer, and the management of acute myocardial infarction. He focuses on integrating clinical judgment with machine learning to enhance medical decision-making and emphasizes the importance of data and team science in public health policy.

Recent Grants

Grant: Close

HOD2: Instrumental Variable approaches for estimating heterogeneity of treatment effects to inform personalisation using electronic health records

Open Date: 2021-04-30

Close Date: 2024-04-29

Grant: Close

Prioritising patients for emergency surgery or not: the impact of COVID-19 (ESORT-C19)

Open Date: 2021-03-15

Close Date: 2022-04-15

Grant: Close

PERsonalised Medicine for Intensification of Treatment (PERMIT): the case of type 2 Diabetes Mellitus

Open Date: 2020-01-01

Close Date: 2022-09-30

Grant: Close

Emergency Surgery Or noT (ESORT)

Open Date: 2019-10-01

Close Date: 2021-09-30

Grant: Close

Development of a fully Bayesian framework for the identification and estimation of subgroup effects in Randomised Controlled Trials

Open Date: 2017-03-31

Close Date: 2021-03-30

Articles (17)

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2025

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2022

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2022

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2022

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2022

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2022

Collaborators (15)

Andrew Hutchings

Assistant Professor

London School of Hygiene & Tropical Medicine

UNITED KINGDOM

Richard Grieve

Research Interests

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About

Recent Grants

Articles (17)

Comparative effectiveness of alternative second-line oral glucose-lowering therapies for type 2 diabetes: a precision medicine approach applied to routine data

Long‐term outcomes following alternative second‐line oral glucose‐lowering treatments: Results from the real‐world progression in type 2 diabetes mellitus United Kingdom (RAPIDS‐UK) model

Surgery or radiotherapy for early-stage cancer study (SORT) target trial protocol: stereotactic ablative radiotherapy (SABR) with curative intent versus surgical resection for early-stage non-small cell lung cancer (NSCLC)

Variation in acute myocardial infarction management by kidney function across hospitals in England: a cross-sectional study using the Myocardial Ischaemia National Audit Project (MINAP)

Going beyond randomised controlled trials to assess treatment effect heterogeneity across target populations

An Approach for Combining Clinical Judgment with Machine Learning to Inform Medical Decision Making: Analysis of Nonemergency Surgery Strategies for Acute Appendicitis in Patients with Multiple Long-Term Conditions

How does a local instrumental variable method perform across settings with instruments of differing strengths? A simulation study and an evaluation of emergency surgery

Adapting Patient and Public Involvement processes in response to the Covid‐19 pandemic

A Comparison of Ordered Categorical versus Discrete Choices within a Stated Preference Survey of Whole-Blood Donors

Clinical effectiveness and cost-effectiveness of emergency surgery for adult emergency hospital admissions with common acute gastrointestinal conditions: the ESORT study

The importance of investing in data, models, experiments, team science, and public trust to help policymakers prepare for the next pandemic

Local Instrumental Variable Methods to Address Confounding and Heterogeneity when Using Electronic Health Records: An Application to Emergency Surgery

A Machine-Learning Approach for Estimating Subgroup- and Individual-Level Treatment Effects: An Illustration Using the 65 Trial

Effect of High-Flow Nasal Cannula Therapy vs Continuous Positive Airway Pressure Therapy on Liberation From Respiratory Support in Acutely Ill Children Admitted to Pediatric Critical Care Units: A Randomized Clinical Trial.

Impact of the first wave of COVID-19 on outcomes following emergency admissions for common acute surgical conditions: analysis of a national database in England.

Application of quantitative bias analysis for unmeasured confounding in cost-effectiveness modelling.

Unmeasured confounding in nonrandomized studies: quantitative bias analysis in health technology assessment.

Collaborators (15)

Andrew Hutchings

Woojoo Lee

Karla DiazOrdaz

Amanda Adler

Padmanabhan Ramnarayan

Anirban Basu

Kamlesh Khunti

Zia Sadique

Luke Keele

Claire Snowdon

Nazima Pathan

Richard Silverwood

Mark Peters

David Cromwell

R. J. Hinchliffe

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