Mastodawn

Daniel Dvorkin Nov 4, 2025

#Covid causes what we in the biz call "#cardiovascular events," among its other nasty effects. #Heart attack, #stroke, pulmonary #embolism, deep vein #thrombosis. All things you should try to avoid.

https://www.nature.com/articles/s41467-024-49634-x

The covid #vaccine—any of the currently approved vaccines—helps protect against such events. A #mechanism isn't yet clear: the obvious hypothesis is that it works by reducing the incidence and sincerity of covid, and therefore reduces the effects of the disease. Say it with me now: further research is needed. Send me a pile of cash and I'll be happy to get on that, BTW.

(It also helps protect against #cancer, by an entirely different mechanism. I can natter about that if anyone wants.)

But the effect itself is clear. Has been from the start of the #mRNA vaccine era, really. Now a very large-scale study has confirmed it. There will be more studies, as there should be. They will show the same result. I'd bet my fortune on that, if I had a fortune, because then I'd have an even bigger fortune. Have I mentioned lately that #scientists need to eat?

As it is, all I have to pledge is my life and my sacred honor. I take both of those pretty seriously.

Of course this runs directly counter to the #antivax narrative. Based on a transitory and maybe illusory increase in clotting risk from an early vaccine that's no longer on the market (Johnson & Johnson) they've built an entire mythology about "the #clot shot." Lately they've added "#turbo cancer," which is not a thing that exists, to the canon.

So when dedicated antivaxers see any of the large and ever-growing number of studies showing protective effects against more than the #infection itself, especially against the exact same problems they claim the vaccine causes, they react with mockery and/or rage. It's all they know how to do.

Years of bitter experience have taught me there's no point in trying to reason with them. I still hold out hope that at least some antivax sentiment isn't that dedicated, that a lot of people are scared of getting vaccinated out of the general unease brought on by ignorance.

Oh yeah: the Methods section in the linked article provides details on data collection and analysis. It looks good to me, and I have a whole lot of experience in study design. Note that no vaccine manufacturers provided #funding. For a full list of funding sources, see the Acknowledgements.

I don't suppose I have many if any antivaxers left in my audience. If I do, well, I guess there's a reason you're still here. And if you like me or trust me or respect me at all, please pay attention to my words.

For everyone else, if what I've written here is useful, please do with it what you can.

Cohort study of cardiovascular safety of different COVID-19 vaccination doses among 46 million adults in England - Nature Communications

COVID-19 vaccines have been associated with rare cardiovascular and thrombotic complications. Here, the authors use population-based longitudinal electronic health record data from ~46 million adults in England to quantify these outcomes following different vaccine doses and schedules.

Nature

All Scientifical Feb 2, 2025

Arteriography - visualization of the arteries
A radiopaque contrast agent is injected into the arteries that need to be analyzed.
This test is done on an empty stomach.
Arteriography can detect arterial cholesterol deposits, as well as atherosclerosis or pulmonary embolism.

#arteries #Atherosclerosis #Embolism #Arteriography

Mike Smale Aug 16, 2024

"Embolism"

A heavily altered photograph that resembles a medical scan of an embolism. Inspired by my own pulmonary embolism in March of 2021.

Link: https://mike-smale.pixels.com/featured/embolism-mike-smale.html

#Abstract #AbstractPhotography #Embolism #Medical #BloodClot #Clot #PulmonaryEmbolism #Photography #Art #Artwork #AbstractArt #Weird

Embolism by Mike Smale

Mike Smale - Artist Website

Mike Smale Jan 31, 2024

Embolism by Mike Smale

Mike Smale - Artist Website

European Radiology Sep 11, 2023

Study compares incremental value of #AI to diagnostic accuracy of radiologists in the detection of incidental acute #pulmonary #embolism. (Eline Langius-Wiffen et al.)

#EuropeanRadiology

🔗 https://link.springer.com/article/10.1007/s00330-023-10029-z

Added value of an artificial intelligence algorithm in reducing the number of missed incidental acute pulmonary embolism in routine portal venous phase chest CT - European Radiology

Objectives The purpose of this study was to evaluate the incremental value of artificial intelligence (AI) compared to the diagnostic accuracy of radiologists alone in detecting incidental acute pulmonary embolism (PE) on routine portal venous contrast-enhanced chest computed tomography (CT). Methods CTs of 3089 consecutive patients referred to the radiology department for a routine contrast-enhanced chest CT between 27–5-2020 and 31–12-2020, were retrospectively analysed by a CE-certified and FDA-approved AI algorithm. The diagnostic performance of the AI was compared to the initial report. To determine the reference standard, discordant findings were independently evaluated by two readers. In case of disagreement, another experienced cardiothoracic radiologist with knowledge of the initial report and the AI output adjudicated. Results The prevalence of acute incidental PE in the reference standard was 2.2% (67 of 3089 patients). In 25 cases, AI detected initially unreported PE. This included three cases concerning central/lobar PE. Sensitivity of the AI algorithm was significantly higher than the outcome of the initial report (respectively 95.5% vs. 62.7%, p < 0.001), whereas specificity was very high for both (respectively 99.6% vs 99.9%, p = 0.012). The AI algorithm only showed a slightly higher amount of false-positive findings (11 vs. 2), resulting in a significantly lower PPV (85.3% vs. 95.5%, p = 0.047). Conclusion The AI algorithm showed high diagnostic accuracy in diagnosing incidental PE, detecting an additional 25 cases of initially unreported PE, accounting for 37.3% of all positive cases. Clinical relevance statement Radiologist support from AI algorithms in daily practice can prevent missed incidental acute PE on routine chest CT, without a high burden of false-positive cases. Key Points • Incidental pulmonary embolism is often missed by radiologists in non-diagnostic scans with suboptimal contrast opacification within the pulmonary trunk. • An artificial intelligence algorithm showed higher sensitivity detecting incidental pulmonary embolism on routine portal venous chest CT compared to the initial report. • Implementation of artificial intelligence support in routine daily practice will reduce the number of missed incidental pulmonary embolism.

SpringerLink

European Radiology Jul 7, 2023

A novel convolutional #NeuralNetwork (CNN) model with high accuracy was developed to identify and differentiate chronic #pulmonary #embolism (CPE) from CT pulmonary angiograms (CTPA). (Tuomas Vainio et al.)

#EuropeanRadiologyExperimental

🔗 https://eurradiolexp.springeropen.com/articles/10.1186/s41747-023-00346-9

Leveraging open dataset and transfer learning for accurate recognition of chronic pulmonary embolism from CT angiogram maximum intensity projection images - European Radiology Experimental

Background Early diagnosis of the potentially fatal but curable chronic pulmonary embolism (CPE) is challenging. We have developed and investigated a novel convolutional neural network (CNN) model to recognise CPE from CT pulmonary angiograms (CTPA) based on the general vascular morphology in two-dimensional (2D) maximum intensity projection images. Methods A CNN model was trained on a curated subset of a public pulmonary embolism CT dataset (RSPECT) with 755 CTPA studies, including patient-level labels of CPE, acute pulmonary embolism (APE), or no pulmonary embolism. CPE patients with right-to-left-ventricular ratio (RV/LV) < 1 and APE patients with RV/LV ≥ 1 were excluded from the training. Additional CNN model selection and testing were done on local data with 78 patients without the RV/LV-based exclusion. We calculated area under the receiver operating characteristic curves (AUC) and balanced accuracies to evaluate the CNN performance. Results We achieved a very high CPE versus no-CPE classification AUC 0.94 and balanced accuracy 0.89 on the local dataset using an ensemble model and considering CPE to be present in either one or both lungs. Conclusions We propose a novel CNN model with excellent predictive accuracy to differentiate chronic pulmonary embolism with RV/LV ≥ 1 from acute pulmonary embolism and non-embolic cases from 2D maximum intensity projection reconstructions of CTPA. Relevance statement A DL CNN model identifies chronic pulmonary embolism from CTA with an excellent predictive accuracy. Key points • Automatic recognition of CPE from computed tomography pulmonary angiography was developed. • Deep learning was applied on two-dimensional maximum intensity projection images. • A large public dataset was used for training the deep learning model. • The proposed model showed an excellent predictive accuracy. Graphical Abstract

SpringerOpen

Ms. Opossum (now @ratnegative)Mar 10, 2023

DeVries et al, 2023: In a mostly un-hospitalized sample, people who've had #COVID19 in the last year had higher #mortality (2.8% vs. 1.2%) & more healthcare use for cardiac #arrhythmia (2.35x), pulmonary #embolism (3.64x), ischemic #stroke (2.17x), etc.
https://www.reddit.com/r/COVIDZero/comments/11nfn5x/devries_et_al_2023_even_in_a_mostly/

isAAAc 🏴🏴‍☠️ ⏚ 🇺🇦 🇵🇸Jan 8, 2023

#SundayMusic #BloodyFist 10 #embolism

Patrick Ching Nov 30, 2022

Pts w presumed #COPD exacerbation that are unresponsive to conventional tx (steroids, abx, bronchodilators) should be evaluated for #pulmonary #embolism #PE #medicine #MedMastodon #IMPearls #Pulm #PulmCC