New research has estimated that each year five babies in every 1,000 born in England suffer a condition or sign linked to brain injury.
The study, conducted by researchers at the Neonatal Data Analysis Unit at Imperial College London and Chelsea and Westminster Hospital NHS Foundation Trust, analysed data on babies born between 2010 and 2015 to assess the number that may have sustained brain injury at or soon after birth.
The researchers used routinely recorded NHS data and so were able to measure the incidence rate of brain injury in newborns without any additional workload for doctors or nurses. Ultimately, this research could lead to a better understanding of how to prevent brain injury in preterm and full term babies.
Dr Chris Gale, lead author and Clinical Senior Lecturer in Neonatal Medicine at Imperial College London and Consultant Neonatologist at Chelsea and Westminster Hospital NHS Foundation Trust, said: “Brain injury at or soon after birth is a serious problem, as it can lead to long-term conditions later in life such as cerebral palsy, blindness, deafness and learning deficits. A proportion of these cases could be avoided.”
Neena Modi, Professor of Neonatal Medicine at Imperial College London and Head of the Neonatal Data Analysis Unit, said: “Before now UK health services did not have a standard definition of brain injury in babies and there has been no systematic collection of data for this purpose.
Professor Modi added: “With colleagues, and in collaboration with the Department of Health, we have devised a practical way to measure the incidence rate of brain injury in babies.”
Published in the journal Archives of Disease in Childhood, the research estimated that 3,418 babies suffered conditions linked to brain injury at or soon after birth in 2015, which equates to an overall incidence rate of 5.14 per 1,000 live births. For preterm births (babies born at or less than 37 weeks) the rate was 25.88 per 1,000 live births in 2015, more than seven times greater than the rate for full term births, which was 3.47 per 1,000 live births.
It is often not known whether a baby has suffered brain injury until later in life. Therefore, the new standardized definition of brain injuries in newborn babies, developed by a group of experts convened by the Department of Health, consists of a range of conditions and signs that are known to be related to brain injury. These include seizures or fits, bleeding within the brain, stroke just before or at birth, infections like meningitis, and damage caused by oxygen deprivation.
The research, commissioned by the Department of Health, is the first to present estimates for the number of babies with brain injuries based on a definition that includes multiple conditions in one measure.
It is also the first time this estimate has been made using data gathered routinely during day-to-day clinical care on neonatal units. The use of routine data required no additional work for clinical staff and provides a valuable way to measure the effectiveness of interventions to reduce brain injury.
As part of a drive to make England a safer place to give birth, the Department of Health has set a target of reducing the number of babies that incur brain injury during or soon after birth by 20% by 2020 and to halve them by 2030. Using these new estimates this equates to lowering the incidence of babies with brain injury to four per 1,000 live births by 2020 and to 2.5 babies per 1,000 live births by 2030.
Overall, the research found that the most common type of condition that contributed to brain injuries was damage caused by lack of oxygen to the brain, called hypoxic ischemic encephalopathy; this is seen mainly in full term babies. For preterm babies, the largest contributor to brain injuries is from bleeding into and around the ventricles of the brain, a condition called periventricular hemorrhage.
Dr Gale added: “Being able to measure how common brain injuries are allows health professionals and researchers to focus on reducing these devastating conditions. This includes the consistent use of treatments that reduce the risk of brain injuries in preterm infants, such as steroids and magnesium sulphate given to the mother before birth.
“This measure will also help us to evaluate other interventions, for example, making sure that as many preterm babies as possible are born at hospitals with advanced neonatal services on site, which we know reduces the risk of brain injury.
“The next step is to use routine data to understand the long-term effects of these conditions on the children and their families.”

Imperial College Londonhttps://tinyurl.com/ycnbqzlo

Massive banks of genetic information are being harnessed to shed new light on modifiable health risks that underlie common diseases.
University of Queensland researchers have pioneered a method to integrate data from multiple large-scale studies to assess risk factors such as body mass index (BMI) and cholesterol levels, and their association with diseases including type two diabetes and heart disease.
Professor Jian Yang, from UQ’s Institute for Molecular Bioscience and Queensland Brain Institute, said the new method was more powerful than earlier techniques and enabled scientists to identify risk associations that were difficult to detect in smaller samples.
“Identifying new risk factors provides an avenue to look at diseases from a different angle,” Professor Yang said.
“For example, LDL-cholesterol is known to be a risk factor for cardiovascular disease, but we were surprised to see that it actually lowers your risk of type two diabetes.
“Discoveries like this could have significant implications for medical research, the pharmaceutical industry and public health policy.”
The study looked at seven known health risk factors and more than 30 common diseases, in genetic data from more than 400,000 people.
Professor Yang said the method identified 45 potentially causal associations between health risk factors and diseases.
“Some of these associations – such as the link between BMI and type 2 diabetes and cardiovascular disease – have already been confirmed in randomized controlled trials, which validates our methods,” Professor Yang said.
“Others identified in this study provide candidates for prioritization in future trials, and fundamental knowledge to understand the biology of the diseases.
“For example, we identified a highly significant risk effect of HDL-cholesterol on age-related macular degeneration.”
Professor Yang said the method was particularly valuable where clinical trials to investigate associations would be impractical or even unethical.
“Years of education is one trait we looked at in the study, and it had a protective effect against most diseases, particularly for Alzheimer’s and coronary artery disease – but it is something that needs to be carefully investigated in the future,” Professor Yang said.
University of Queenslandhttps://tinyurl.com/y9lfo963

In 2017, an estimated 252,710 new cases of invasive breast cancer were diagnosed in women and 2,470 cases were diagnosed in men. Many of these diagnoses are made using X-ray mammography. Although standard and widely used, X-ray imaging for breast cancer suffers from both low sensitivity (50-75%) and the use of ionizing radiation that cannot be considered completely safe.
While X-ray mammography is widely used and is still the recommended method for routine screenings, its use is limited by the patient’s age, weight or body mass index, the breast tissue itself, whether or not hormone replacement therapy is being used, and other issues. In addition, its accuracy — particularly when used in younger women — has been called into question. Other imaging techniques, such as MRI and ultrasound, are sometimes suggested, but neither is an effective replacement for X-ray mammography.
Optical imaging methods, on the other hand, have attracted increasing interest for breast cancer diagnosis since both visible and infrared light are highly sensitive to tissue composition. Tumours are characterized by a high volume of blood due to the increased vascularization that occurs as tumours grow. OM (Optical Mammography) can be used to measure blood volume, oxygenation, lipid, water and collagen content for a suspicious area identified through standard X-ray imaging. Collagen measurements are particularly important since this species is known to be involved in the onset and progression of breast cancer.
One major disadvantage to OM imaging is the poor spatial resolution that has been achieved to date. Breast cancer tumours larger than 1 centimetre are very dangerous and more likely to lead to death, so a successful screening technique must be able to resolve smaller lesions. This remains a problem with OM imaging as a stand-alone technique, but combining OM with other imaging methods shows some promise.
A possible advantage to OM, however, is that only gentle pressure need be applied to the breast tissue, in stark contrast to the standard technique for X-ray imaging. In fact, breast compression tends to reduce blood volume in the tissue, which would interfere with the OM image, so some three-dimensional OM detectors being developed use no compression at all but, rather, surround the breast tissue with rings of light sources and detectors.
While poor spatial resolution of OM methods remains a challenge, the method does show promise for use in pre-surgical chemotherapy. As Edoardo Ferocino, Politecnico di Milano, Italy, co-author of the work explains, “This technique is able to provide information on the outcome of chemotherapy just weeks after beginning treatment, or possibly even sooner.” Ferocino’s group is planning clinical studies to explore the use of OM to monitor and predict the outcome of chemotherapy.
The investigators in Milan are working with a larger consortium on a project known as SOLUS, “Smart Optical and Ultrasound Diagnostics of Breast Cancer.” This project is funded by the European Union through the Horizon 2020 Research and Innovation Program and aims to combine optical imaging methods with ultrasound to improve specificity in the diagnosis of breast cancer.
The Optical Societywww.osa.org/en-us/about_osa/newsroom/news_releases/2018/diagnosing_breast_cancer_using_red_light/

The composite stroke decision tool studied by researchers from the Intermountain Medical Center Heart Institute in Salt Lake City combines the widely used CHA₂DS₂-VASc with the Intermountain Risk Scores (IMRS) to derive and validate new stroke prediction scores.
The study shows the new model, IMRS-VASc, was significantly more effective in predicting stroke risk and will give clinicians a more effective and accurate tool to assess patients with cardiovascular disease.
Atrial fibrillation, the most common heart arrhythmia in the world, affects more than 2.7 million American adults. The abnormal heart rhythm causes blood to pool and clot in the heart, and when those blood clots break free, they can cause a stroke.
Researchers found that the new IMRS-VASc risk score model nearly doubles their ability to appropriately predict stroke risk compared to the traditional CHA₂DS₂-VASc risk tool. The development of the IMRS-VASc risk score model is the first step in a research pathway for other conditions that will ultimately result in time and cost savings for both patient and physician.
This improved effectiveness of the new risk score model results from better assignment of low-risk and high-risk people to the appropriate stroke prognosis category, said Benjamin Horne, PhD, lead author of the study and director of cardiovascular and genetic epidemiology of the Intermountain Medical Center Heart Institute.
He notes that the CHA₂DS₂-VASc score places about 80% of women and 50% of men with atrial fibrillation in a group of people at high risk of stroke. In contrast, IMRS-VASc places one third of all people each in a low, moderate, and high-risk category.
Additionally, the study found that IMRS-VASc more appropriately assigns people to the risk group that relates to their actual prognosis, with a lower rate of stroke in the low-risk group (about 1% having a stroke over a two-year period for women and men), and a higher rate in the high-risk category (two-year stroke rates of 6% in women, 5% in men).
This improved effectiveness may help to limit the near-term use of treatments for atrial fibrillation among people who do not yet need the therapies and reinforce and encourage the use of treatments among those whose short-term risk actually is high, Dr, Horne said.
“We provide information to clinicians so they can make better decisions about who should have oral anticoagulants and who should have other types of medications and diagnostics tests, and which patients need to have more frequent clinic visits,” said Dr. Horne. “The result will be care that can be more precisely targeted to each patient’s risks and more likely to prevent a stroke.”
Dr. Horne said the integrated IMRS-VASc model combines tried-and-true attributes of the CHA₂DS₂-VASc and the IMRS.
“While the CHA2DS2-VASc is easy to use, it does not reliably predict what will happen in the future. The Intermountain Risk Score incorporates data available to clinicians in the electronic health record to calculate a score that predicts what’s going to happen in the future and the two combined result in IMRS-VASc Models,” he notes.
The CHA₂DS₂-VASc score is a mnemonic that’s easy and convenient for clinicians to use. Each of the letters and the numbers reflect a characteristic that’s used in the score.

• The C is for CHF, or congestive heart failure.
• The H is for hypertension.
• The A is for age.
• D is for diabetes.
• S is for history of stroke.
• V is for vascular disease.
• The second A is for threshold for age.
• The final S is for sex.
• The A and S have a 2 by them. Each of these components gets one additional point for each additional risk factor. If you have congestive heart failure you get one point. If you have hypertension you get one. If you’re above age 75 you get 2 points, and the S2 means if you have a history of stroke you get 2 points, and subsequently, all the others get 1 point.
• The second A is for age between 65 to 74, which adds one point.

For the observational study, researchers collected existing data from patients who visited an Intermountain Healthcare clinic from 1990 to 2013. There were 56,000 individuals evaluated in the study to create the score.
Another set of 24,000 patients were then tested after the new combined risk score was created to validate that it worked in a separate set of individuals who hadn’t been involved in the creation of the risk score.

The Intermountain Medical Centerintermountainhealthcare.org/news/2018/05/new-risk-score-predicts-stroke-risk-afib-patients/