When doctors couldn’t stop her daughter’s seizures, this mom earned a PhD and found a treatment herself.
Twenty-eight years ago, Tracy Dixon-Salazaar woke to the sound of her daughter, two-year-old Savannah, in the midst of a medical emergency.
“I entered [Savannah’s room] to see her tiny little body jerking about violently in her bed,” Tracy said in an interview. “I thought she was choking.” When she and her husband frantically called 911, the paramedic told them it was likely that Savannah had had a seizure—a term neither Tracy nor her husband had ever heard before.
Over the next several years, Savannah’s seizures continued and worsened. By age five Savannah was having seizures dozens of times each day, and her parents noticed significant developmental delays. Savannah was unable to use the restroom and functioned more like a toddler than a five-year-old.
Doctors were mystified: Tracy and her husband had no family history of seizures, and there was no event—such as an injury or infection—that could have caused them. Doctors were also confused as to why Savannah’s seizures were happening so frequently despite trying different seizure medications.
Doctors eventually diagnosed Savannah with Lennox-Gaustaut Syndrome, or LGS, an epilepsy disorder with no cure and a poor prognosis. People with LGS are often resistant to several kinds of anti-seizure medications, and often suffer from developmental delays and behavioral problems. People with LGS also have a higher chance of injury as well as a higher chance of sudden unexpected death (SUDEP) due to the frequent seizures. In about 70 percent of cases, LGS has an identifiable cause such as a brain injury or genetic syndrome. In about 30 percent of cases, however, the cause is unknown.
Watching her daughter struggle through repeated seizures was devastating to Tracy and the rest of the family.
“This disease, it comes into your life. It’s uninvited. It’s unannounced and it takes over every aspect of your daily life,” said Tracy in an interview with Today.com. “Plus it’s attacking the thing that is most precious to you—your kid.”
Desperate to find some answers, Tracy began combing the medical literature for information about epilepsy and LGS. She enrolled in college courses to better understand the papers she was reading.
“Ironically, I thought I needed to go to college to take English classes to understand these papers—but soon learned it wasn’t English classes I needed, It was science,” Tracy said. When she took her first college science course, Tracy says, she “fell in love with the subject.”
Tracy was now a caregiver to Savannah, who continued to have hundreds of seizures a month, as well as a full-time student, studying late into the night and while her kids were at school, using classwork as “an outlet for the pain.”
“I couldn’t help my daughter,” Tracy said. “Studying was something I could do.”
Twelve years later, Tracy had earned a PhD in neurobiology.
After her post-doctoral training, Tracy started working at a lab that explored the genetics of epilepsy. Savannah’s doctors hadn’t found a genetic cause for her seizures, so Tracy decided to sequence her genome again to check for other abnormalities—and what she found was life-changing.
Tracy discovered that Savannah had a calcium channel mutation, meaning that too much calcium was passing through Savannah’s neural pathways, leading to seizures. The information made sense to Tracy: Anti-seizure medications often leech calcium from a person’s bones. When doctors had prescribed Savannah calcium supplements in the past to counteract these effects, her seizures had gotten worse every time she took the medication. Tracy took her discovery to Savannah’s doctor, who agreed to prescribe her a calcium blocker.
The change in Savannah was almost immediate.
Within two weeks, Savannah’s seizures had decreased by 95 percent. Once on a daily seven-drug regimen, she was soon weaned to just four, and then three. Amazingly, Tracy started to notice changes in Savannah’s personality and development, too.
“She just exploded in her personality and her talking and her walking and her potty training and oh my gosh she is just so sassy,” Tracy said in an interview.
Since starting the calcium blocker eleven years ago, Savannah has continued to make enormous strides. Though still unable to read or write, Savannah enjoys puzzles and social media. She’s “obsessed” with boys, says Tracy. And while Tracy suspects she’ll never be able to live independently, she and her daughter can now share more “normal” moments—something she never anticipated at the start of Savannah’s journey with LGS. While preparing for an event, Savannah helped Tracy get ready.
“We picked out a dress and it was the first time in our lives that we did something normal as a mother and a daughter,” she said. “It was pretty cool.”
Ethan Lindenberger, the Ohio teenager who sought out vaccinations after he was denied them as a child, recently testified before Congress about why his parents became anti-vaxxers. The trouble, he believes, stems from the pervasiveness of misinformation online.
There is evidence that 'educating' people with facts about the benefits of vaccination may not be effective.
"For my mother, her love and affection and care as a parent was used to push an agenda to create a false distress," he told the Senate Committee. His mother read posts on social media saying vaccines are dangerous, and that was enough to persuade her against them.
His story is an example of how widespread and harmful the current discourse on vaccinations is—and more importantly—how traditional strategies to convince people about the merits of vaccination have largely failed.
As responsible members of society, all of us have implicitly signed on to what ethicists call the "Social Contract" -- we agree to abide by certain moral and political rules of behavior. This is what our societal values, norms, and often governments are based upon. However, with the unprecedented rise of social media, alternative facts, and fake news, it is evident that our understanding—and application—of the social contract must also evolve.
Nowhere is this breakdown of societal norms more visible than in the failure to contain the spread of vaccine-preventable diseases like measles. What started off as unexplained episodes in New York City last October, mostly in communities that are under-vaccinated, has exploded into a national epidemic: 880 cases of measles across 24 states in 2019, according to the CDC (as of May 17, 2019). In fact, the Unites States is only eight months away from losing its "measles free" status, joining Venezuela as the second country out of North and South America with that status.
The U.S. is not the only country facing this growing problem. Such constant and perilous reemergence of measles and other vaccine-preventable diseases in various parts of the world raises doubts about the efficacy of current vaccination policies. In addition to the loss of valuable life, these outbreaks lead to loss of millions of dollars in unnecessary expenditure of scarce healthcare resources. While we may be living through an age of information, we are also navigating an era whose hallmark is a massive onslaught on truth.
There is ample evidence on how these outbreaks start: low-vaccination rates. At the same time, there is evidence that 'educating' people with facts about the benefits of vaccination may not be effective. Indeed, human reasoning has a limit, and facts alone rarely change a person's opinion. In a fascinating report by researchers from the University of Pennsylvania, a small experiment revealed how "behavioral nudges" could inform policy decisions around vaccination.
In the reported experiment, the vaccination rate for employees of a company increased by 1.5 percent when they were prompted to name the date when they planned to get their flu shot. In the same experiment, when employees were prompted to name both a date and a time for their planned flu shot, vaccination rate increased by 4 percent.
A randomized trial revealed the subtle power of "announcements" – direct, brief, assertive statements by physicians that assumed parents were ready to vaccinate their children.
This experiment is a part of an emerging field of behavioral economics—a scientific undertaking that uses insights from psychology to understand human decision-making. The field was born from a humbling realization that humans probably do not possess an unlimited capacity for processing information. Work in this field could inform how we can formulate vaccination policy that is effective, conserves healthcare resources, and is applicable to current societal norms.
Take, for instance, the case of Human Papilloma Virus (HPV) that can cause several types of cancers in both men and women. Research into the quality of physician communication has repeatedly revealed how lukewarm recommendations for HPV vaccination by primary care physicians likely contributes to under-immunization of eligible adolescents and can cause confusion for parents.
A randomized trial revealed the subtle power of "announcements" – direct, brief, assertive statements by physicians that assumed parents were ready to vaccinate their children. These announcements increased vaccination rates by 5.4 percent. Lengthy, open-ended dialogues demonstrated no benefit in vaccination rates. It seems that uncertainty from the physician translates to unwillingness from a parent.
Choice architecture is another compelling concept. The premise is simple: We hardly make any of our decisions in vacuum; the environment in which these decisions are made has an influence. If health systems were designed with these insights in mind, people would be more likely to make better choices—without being forced.
This theory, proposed by Richard Thaler, who won the 2017 Nobel Prize in Economics, was put to the test by physicians at the University of Pennsylvania. In their study, flu vaccination rates at primary care practices increased by 9.5 percent all because the staff implemented "active choice intervention" in their electronic health records—a prompt that nudged doctors and nurses to ask patients if they'd gotten the vaccine yet. This study illustrated how an intervention as simple as a reminder can save lives.
To be sure, some bioethicists do worry about implementing these policies. Are behavioral nudges akin to increased scrutiny or a burden for the disadvantaged? For example, would incentives to quit smoking unfairly target the poor, who are more likely to receive criticism for bad choices?
The measles outbreak is a sober reminder of how devastating it can be when the social contract breaks down.
While this is a valid concern, behavioral economics offers one of the only ethical solutions to increasing vaccination rates by addressing the most critical—and often legal—challenge to universal vaccinations: mandates. Choice architecture and other interventions encourage and inform a choice, allowing an individual to retain his or her right to refuse unwanted treatment. This distinction is especially important, as evidence suggests that people who refuse vaccinations often do so as a result of cognitive biases – systematic errors in thinking resulting from emotional attachment or a lack of information.
For instance, people are prone to "confirmation bias," or a tendency to selectively believe in information that confirms their preexisting theories, rather than the available evidence. At the same time, people do not like mandates. In such situations, choice architecture provides a useful option: people are nudged to make the right choice via the design of health delivery systems, without needing policies that rely on force.
The measles outbreak is a sober reminder of how devastating it can be when the social contract breaks down and people fall prey to misinformation. But all is not lost. As we fight a larger societal battle against alternative facts, we now have another option in the trenches to subtly encourage people to make better choices.
Using insights from research in decision-making, we can all contribute meaningfully in controversial conversations with family, friends, neighbors, colleagues, and our representatives — and push for policies that protect those we care about. A little more than a hundred years ago, thousands of lives were routinely lost to preventive illnesses. We've come too far to let ignorance destroy us now.
New Tech Can Predict Breast Cancer Years in Advance
Every two minutes, a woman is diagnosed with breast cancer. The question is, can those at high risk be identified early enough to survive?
New AI software has predicted risk equally well in both white and black women for the first time.
The current standard practice in medicine is not exactly precise. It relies on age, family history of cancer, and breast density, among other factors, to determine risk. But these factors do not always tell the whole story, leaving many women to slip through the cracks. In addition, a racial gap persists in breast cancer treatment and survival. African-American women are 42 percent more likely to die from the disease despite relatively equal rates of diagnosis.
But now those grim statistics could be changing. A team of researchers from MIT's Computer Science and Artificial Intelligence Laboratory have developed a deep learning model that can more accurately predict a patient's breast cancer risk compared to established clinical guidelines – and it has predicted risk equally well in both white and black women for the first time.
The Lowdown
Study results published in Radiology described how the AI software read mammogram images from more than 60,000 patients at Massachusetts General Hospital to identify subtle differences in breast tissue that pointed to potential risk factors, even in their earliest stages. The team accessed the patients' actual diagnoses and determined that the AI model was able to correctly place 31 percent of all cancer patients in the highest-risk category of developing breast cancer within five years of the examination, compared to just 18 percent for existing models.
"Each image has hundreds of thousands of pixels identifying something that may not necessarily be detected by the human eye," said MIT professor Regina Barzilay, one of the study's lead authors. "We all have limited visual capacities so it seems some machines trained on hundreds of thousands of images with a known outcome can capture correlations the human eye might not notice."
Barzilay, a breast cancer survivor herself, had abnormal tissue patterns on mammograms in 2012 and 2013, but wasn't diagnosed until after a 2014 image reading, illustrating the limitations of human processing alone.
MIT professor Regina Barzilay, a lead author on the new study and a breast cancer survivor herself.
(Courtesy MIT)
Next up: The MIT team is looking at training the model to detect other cancers and health risks. Barzilay recalls how a cardiologist told her during a conference that women with heart diseases had a different pattern of calcification on their mammograms, demonstrating how already existing images can be used to extract other pieces of information about a person's health status.
Integration of the AI model in standard care could help doctors better tailor screening and prevention programs based on actual instead of perceived risk. Patients who might register as higher risk by current guidelines could be identified as lower risk, helping resolve conflicting opinions about how early and how often women should receive mammograms.
Open Questions: While the results were promising, it's unknown how well the model will work on a larger scale, as the study looked at data from just one institution and used mammograms supplied by just one hospital. Some risk factor information was also unavailable for certain patients during the study, leaving researchers unable to fully compare the AI model's performance to that of the traditional standard.
One incentive to wider implementation and study, however, is the bonus that no new hardware is required to use the AI model. With other institutions now showing interest, this software could lead to earlier routine detection and treatment of breast cancer — resulting in more lives saved.