CLOT and the BSH 2020

CLOT are again pleased to be organising a session at the BSH at their annual scientific meeting in Birmingham from the 27th to the 29th April 2020. This is their 60th birthday and they are very keen for nurses and AHP to join them for this meeting. Further to this funding is available for nurses to attend details here. Why not submit an abstract for poster or presentation for the nursing session which is on the Tuesday which is a day aimed specifically at nurses. More details about the conference available here


CLOT Website

After nearly 10 years the CLOT website is in need of some updating and modernising. We are in the process of working with our website hosts to develop a new website and if there is anything you would like to see or any changers please contact us as this is our opportunity to make this better for all

CLOT Conference 2020 Save the Date

Following another successful conference we are always looking ahead and next year the conference will again be at the Crowne Plaza in Manchester on Friday 2nd October 2020 more details in due course. Also if any members have any work to present CLOT would love to welcome any talks and you would even attend for free if you speak please contact us if you have any ideas or for more information.

Thrombosis UK Masterclass Bath Wednesday 30th October 2019

Thrombosis UK are holding a masterclass in Bath at the Apex City of Bath hotel, BA1 2DA, on Wednesday the 30th October 2019. Topics covered include NICE guidance one year on from Prof Beverley Hunt, Thrombolysis for VTE in pregnancy by Dr Amanda Clarke, lower limb immobilisation and thromboprophylaxis by Mr Nural Ahad and supporting the psychological impact of VTE by Prof Paul Bennett. More details at and registration at



Artificial Intelligence may help to spot heart problems

An article published in the Lancet looked at diagnosing AF which is is frequently asymptomatic and thus underdetected but is associated with stroke, heart failure, and death.  Existing screening methods require prolonged monitoring and are limited by cost and low yield. They looked at whether a rapid, inexpensive, point-of-care means of identifying these patients with atrial fibrillation using machine learning could be developed. 

Researchers said it was still early days, but believe the system could lead to earlier and easier detection of the problem and, therefore, ensure patients get the right treatment, saving lives. The abstract is available at and was featured on the bbc website at