Patient Care

This page includes news coverage of various aspects of patient healthcare, including new technology innovations, what is working, what is not, personalized medicine and remote and telemedicine delivery. Find specific news in the areas of Care DeliveryDigital TransformationPrecision MedicineRemote Monitoring and Telehealth.

On review, popular imaging decision aid earns 1 thumbs-up—with caveats

With 91% sensitivity but only 25% specificity, the tool is worthwhile for clinicians who remain wary of frequent false positives that would send patients with no fractures for unneeded imaging.

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Experts concerned with radiation doses in young women call for stricter ordering criteria for CT exams

Experts found that compared to the average effective doses of organs, breast doses were higher, representing increased risks of breast cancer for women. 

Could a repurposed drug break a centurylong stalemate in the war on cancer?

A pharmaceutical compound approved 21 years ago to treat breast cancer in postmenopausal women is showing fresh promise as a therapy for glioblastomas. 

Newborn brains invigorated by mother’s active lifestyle during pregnancy

The boon comes in the form of greater brain cortical thickness observable on neonatal MRI two weeks after the baby enters the world.

4D ultrasound shows preborn humans ‘laughing’ over carrots, ‘crying’ over kale

Researchers in the U.K. have documented fetuses smiling when exposed to sweet flavors and frowning over bitter tastes.

Written PDAs a quick, easy way to ‘enhance IR patients’ sense of empowerment’

Interventional radiology patients who receive this type of patient decision aid for consent purposes tend to feel more heard and better informed.

Intravascular lithotripsy (IVL) Shockwave Medical PCI PAD CAD Disrupt PAD Disrupt CAD SCAI 2022

Is IVL equally effective in male and female patients? Shockwave Medical aims to find out with a historic new study

Shockwave announced at TCT 2022 that it hopes to enroll up to 400 patients for a new all-female clinical trial.

Self-supervised AI ‘reads’ radiology reports to speed algorithm development

A machine learning system has come along that needs no human labeling of data for training yet matches radiologists at classifying diseases on chest X-rays—including some that the model was not specifically taught to detect.