Abstract TP25: Model-Free Dynamic Contrast-Enhanced MRI in Cerebral Small Vessel Disease: Test-Retest Reliability and Association With WMH Lesion Burden

Stroke, Volume 55, Issue Suppl_1, Page ATP25-ATP25, February 1, 2024. Introduction:Dynamic contrast enhanced (DCE)-MRI has been used to study blood-brain barrier (BBB) disruption in cerebral small vessel disease (CSVD), but complex kinetic modeling of DCE MRI is sensitive to noise and is not robust in detecting subtle BBB impairments. In contrast, model-free DCE is simple and does not require arterial input function and complex computation. In this study, we aimed to evaluate the test-retest repeatability of model-free DCE and its association with white matter hyperintensity (WMH) burden.Methods:Patients with CSVD were recruited. DCE-MRI, FLAIR, and T1 MPRage scans were acquired. A subgroup of patients had two repeated DCE MRI scans with an average interval of 41 days. WMH segmentation was performed to obtain the relative volume of WMH (rVwmh). Ten subjects had DCE-MRI data in two sessions for test-retest repeatability analysis. DCE-MRI were acquired using a Siemens volumetric interpolated breath-hold examination (VIBE) gradient echo sequence with a temporal resolution of 49 seconds and an acquisition time of ~20 minutes. The wash-out slope (WOS), which indicates the rate of contrast agent leaving the tissue, was computed.Results:64 patients (mean (SD) age = 68.6 (8.51), 37 females) with CSVD were studied. WOS demonstrated good test-retest repeatability for WM and GM with an intra-class correlation coefficient (ICC) of 0.626 and 0.671 in cerebrum WM and GM, respectively. WMH WOS has a significant negative correlation with rVwmh (r=-0.31; p

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Febbraio 2024

Effect of an algorithm for automatic placing of standardised test order sets on low-value appointments and attendance rates at four Spanish teaching hospitals: an interrupted time series analysis

Objective
Reducing backlogs for elective care is a priority for healthcare systems. We conducted an interrupted time series analysis demonstrating the effect of an algorithm for placing automatic test order sets prior to first specialist appointment on avoidable follow-up appointments and attendance rates.

Design
Interrupted time series analysis.

Setting
4 academic hospitals from Madrid, Spain.

Participants
Patients referred from primary care attending 10 033 470 outpatient appointments from 16 clinical specialties during a 6-year period (1 January 2018 to 30 June 2023).

Intervention
An algorithm using natural language processing was launched in May 2021. Test order sets developed for 257 presenting complaints from 16 clinical specialties were placed automatically before first specialist appointments to increase rates of diagnosis and initiation of treatment with discharge back to primary care.

Primary and secondary outcome measures
Primary outcomes included rate of diagnosis and discharge to primary care and follow-up to first appointment index. The secondary outcome was trend in ‘did not attend’ rates.

Results
Since May 2021, a total of 1 175 814 automatic test orders have been placed. Significant changes in trend of diagnosis and discharge to primary care at first appointment (p=0.005, 95% CI 0.5 to 2.9) and ‘did not attend’ rates (p=0.006, 95% CI –0.1 to –0.8) and an estimated attributable reduction of 11 306 avoidable follow-up appointments per month were observed.

Conclusion
An algorithm for placing automatic standardised test order sets can reduce low-value follow-up appointments by allowing specialists to confirm diagnoses and initiate treatment at first appointment, also leading to early discharge to primary care and a reduction in ‘did not attend’ rates. This initiative points to an improved process for outpatient diagnosis and treatment, delivering healthcare more effectively and efficiently.

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Gennaio 2024

Risk factors for SARS-CoV-2 infection: a test-negative case-control study with additional population controls in Norway

Objectives
This study aims to assess risk factors for SARS-CoV-2 infection by combined design; first comparing positive cases to negative controls as determined by PCR testing and then comparing these two groups to an additional prepandemic population control group.

Design and setting
Test-negative design (TND), multicentre case–control study with additional population controls in South-Eastern Norway.

Participants
Adults who underwent SARS-CoV-2 PCR testing between February and December 2020. PCR-positive cases, PCR-negative controls and additional age-matched population controls.

Primary outcome measures
The associations between various risk factors based on self- reported questionnaire and SARS-CoV-2 infection comparing PCR-positive cases and PCR-negative controls. Using subgroup analysis, the risk factors for both PCR-positive and PCR-negative participants were compared with a population control group.

Results
In total, 400 PCR-positive cases, 719 PCR-negative controls and 14 509 population controls were included. Male sex was associated with the risk of SARS-CoV-2 infection only in the TND study (OR 1.9, 95% CI 1.4 to 2.6), but not when PCR-positive cases were compared with population controls (OR 1.2, 95% CI 0.9. to 1.5). Some factors were positively (asthma, wood heating) or negatively (hypertension) associated with SARS-CoV-2 infection when PCR-positive cases were compared with population controls, but lacked convincing association in the TND study. Smoking was negatively associated with the risk of SARS-CoV-2 infection in both analyses (OR 0.5, 95% CI 0.3 to 0.8 and OR 0.6, 95% CI 0.4 to 0.8).

Conclusions
Male sex was a possible risk factor for SARS-CoV-2 infection only in the TND study, whereas smoking was negatively associated with SARS-CoV-2 infection in both the TND study and when using population controls. Several factors were associated with SARS-CoV-2 infection when PCR-positive cases were compared with population controls, but not in the TND study, highlighting the strength of combining case–control study designs during the pandemic.

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Gennaio 2024