This Special Music Helped Preemie Babies’ Brains Develop
Move over, Baby Einstein: New research from Switzerland shows that listening to soothing music in the first weeks of life helps encourage brain development in preterm babies.
For the study, the scientists recruited a harpist and a new-age musician to compose three pieces of music.
The Lowdown
Children who are born prematurely, between 24 and 32 weeks of pregnancy, are far more likely to survive today than they used to be—but because their brains are less developed at birth, they're still at high risk for learning difficulties and emotional disorders later in life.
Researchers in Geneva thought that the unfamiliar and stressful noises in neonatal intensive care units might be partially responsible. After all, a hospital ward filled with alarms, other infants crying, and adults bustling in and out is far more disruptive than the quiet in-utero environment the babies are used to. They decided to test whether listening to pleasant music could have a positive, counterbalancing effect on the babies' brain development.
Led by Dr. Petra Hüppi at the University of Geneva, the scientists recruited Swiss harpist and new-age musician Andreas Vollenweider (who has collaborated with the likes of Carly Simon, Bryan Adams, and Bobby McFerrin). Vollenweider developed three pieces of music specifically for the NICU babies, which were played for them five times per week. Each track was used for specific purposes: To help the baby wake up; to stimulate a baby who was already awake; and to help the baby fall back asleep.
When they reached an age equivalent to a full-term baby, the infants underwent an MRI. The researchers focused on connections within the salience network, which determines how relevant information is, and then processes and acts on it—crucial components of healthy social behavior and emotional regulation. The neural networks of preemies who had listened to Vollenweider's pieces were stronger than preterm babies who had not received the intervention, and were instead much more similar to full-term babies.
Next Up
The first infants in the study are now 6 years old—the age when cognitive problems usually become diagnosable. Researchers plan to follow up with more cognitive and socio-emotional assessments, to determine whether the effects of the music intervention have lasted.
The first infants in the study are now 6 years old—the age when cognitive problems usually become diagnosable.
The scientists note in their paper that, while they saw strong results in the babies' primary auditory cortex and thalamus connections—suggesting that they had developed an ability to recognize and respond to familiar music—there was less reaction in the regions responsible for socioemotional processing. They hypothesize that more time spent listening to music during a NICU stay could improve those connections as well; but another study would be needed to know for sure.
Open Questions
Because this initial study had a fairly small sample size (only 20 preterm infants underwent the musical intervention, with another 19 studied as a control group), and they all listened to the same music for the same amount of time, it's still undetermined whether variations in the type and frequency of music would make a difference. Are Vollenweider's harps, bells, and punji the runaway favorite, or would other styles of music help, too? (Would "Baby Shark" help … or hurt?) There's also a chance that other types of repetitive sounds, like parents speaking or singing to their children, might have similar effects.
But the biggest question is still the one that the scientists plan to tackle next: Whether the intervention lasts as the children grow up. If it does, that's great news for any family with a preemie — and for the baby-sized headphone industry.
There's a quiet revolution going on in medicine. It's driven by artificial intelligence, but paradoxically, new technology may put a more human face on healthcare.
AI's usefulness in healthcare ranges far and wide.
Artificial intelligence is software that can process massive amounts of information and learn over time, arriving at decisions with striking accuracy and efficiency. It offers greater accuracy in diagnosis, exponentially faster genome sequencing, the mining of medical literature and patient records at breathtaking speed, a dramatic reduction in administrative bureaucracy, personalized medicine, and even the democratization of healthcare.
The algorithms that bring these advantages won't replace doctors; rather, by offloading some of the most time-consuming tasks in healthcare, providers will be able to focus on personal interactions with patients—listening, empathizing, educating and generally putting the care back in healthcare. The relationship can focus on the alleviation of suffering, both the physical and emotional kind.
Challenges of Getting AI Up and Running
The AI revolution, still in its early phase in medicine, is already spurring some amazing advances, despite the fact that some experts say it has been overhyped. IBM's Watson Health program is a case in point. IBM capitalized on Watson's ability to process natural language by designing algorithms that devour data like medical articles and analyze images like MRIs and medical slides. The algorithms help diagnose diseases and recommend treatment strategies.
But Technology Review reported that a heavily hyped partnership with the MD Anderson Cancer Center in Houston fell apart in 2017 because of a lack of data in the proper format. The data existed, just not in a way that the voraciously data-hungry AI could use to train itself.
The hiccup certainly hasn't dampened the enthusiasm for medical AI among other tech giants, including Google and Apple, both of which have invested billions in their own healthcare projects. At this point, the main challenge is the need for algorithms to interpret a huge diversity of data mined from medical records. This can include everything from CT scans, MRIs, electrocardiograms, x-rays, and medical slides, to millions of pages of medical literature, physician's notes, and patient histories. It can even include data from implantables and wearables such as the Apple Watch and blood sugar monitors.
None of this information is in anything resembling a standard format across and even within hospitals, clinics, and diagnostic centers. Once the algorithms are trained, however, they can crunch massive amounts of data at blinding speed, with an accuracy that matches and sometimes even exceeds that of highly experienced doctors.
Genome sequencing, for example, took years to accomplish as recently as the early 2000s. The Human Genome Project, the first sequencing of the human genome, was an international effort that took 13 years to complete. In April of this year, Rady Children's Institute for Genomic Medicine in San Diego used an AI-powered genome sequencing algorithm to diagnose rare genetic diseases in infants in about 20 hours, according to ScienceDaily.
"Patient care will always begin and end with the doctor."
Dr. Stephen Kingsmore, the lead author of an article published in Science Translational Medicine, emphasized that even though the algorithm helped guide the treatment strategies of neonatal intensive care physicians, the doctor was still an indispensable link in the chain. "Some people call this artificial intelligence, we call it augmented intelligence," he says. "Patient care will always begin and end with the doctor."
One existing trend is helping to supply a great amount of valuable data to algorithms—the electronic health record. Initially blamed for exacerbating the already crushing workload of many physicians, the EHR is emerging as a boon for algorithms because it consolidates all of a patient's data in one record.
Examples of AI in Action Around the Globe
If you're a parent who has ever taken a child to the doctor with flulike symptoms, you know the anxiety of wondering if the symptoms signal something serious. Kang Zhang, M.D., Ph.D., the founding director of the Institute for Genomic Medicine at the University of California at San Diego, and colleagues developed an AI natural language processing model that used deep learning to analyze the EHRs of 1.3 million pediatric visits to a clinic in Guanzhou, China.
The AI identified common childhood diseases with about the same accuracy as human doctors, and it was even able to split the diagnoses into two categories—common conditions such as flu, and serious, life-threatening conditions like meningitis. Zhang has emphasized that the algorithm didn't replace the human doctor, but it did streamline the diagnostic process and could be used in a triage capacity when emergency room personnel need to prioritize the seriously ill over those suffering from common, less dangerous ailments.
AI's usefulness in healthcare ranges far and wide. In Uganda and several other African nations, AI is bringing modern diagnostics to remote villages that have no access to traditional technologies such as x-rays. The New York Times recently reported that there, doctors are using a pocket-sized, hand-held ultrasound machine that works in concert with a cell phone to image and diagnose everything from pneumonia (a common killer of children) to cancerous tumors.
The beauty of the highly portable, battery-powered device is that ultrasound images can be uploaded on computers so that physicians anywhere in the world can review them and weigh in with their advice. And the images are instantly incorporated into the patient's EHR.
Jonathan Rothberg, the founder of Butterfly Network, the Connecticut company that makes the device, told The New York Times that "Two thirds of the world's population gets no imaging at all. When you put something on a chip, the price goes down and you democratize it." The Butterfly ultrasound machine, which sells for $2,000, promises to be a game-changer in remote areas of Africa, South America, and Asia, as well as at the bedsides of patients in developed countries.
AI algorithms are rapidly emerging in healthcare across the U.S. and the world. China has become a major international player, set to surpass the U.S. this year in AI capital investment, the translation of AI research into marketable products, and even the number of often-cited research papers on AI. So far the U.S. is still the leader, but some experts describe the relationship between the U.S. and China as an AI cold war.
"The future of machine learning isn't sentient killer robots. It's longer human lives."
The U.S. Food and Drug Administration expanded its approval of medical algorithms from two in all of 2017 to about two per month throughout 2018. One of the first fields to be impacted is ophthalmology.
One algorithm, developed by the British AI company DeepMind (owned by Alphabet, the parent company of Google), instantly scans patients' retinas and is able to diagnose diabetic retinopathy without needing an ophthalmologist to interpret the scans. This means diabetics can get the test every year from their family physician without having to see a specialist. The Financial Times reported in March that the technology is now being used in clinics throughout Europe.
In Copenhagen, emergency service dispatchers are using a new voice-processing AI called Corti to analyze the conversations in emergency phone calls. The algorithm analyzes the verbal cues of callers, searches its huge database of medical information, and provides dispatchers with onscreen diagnostic information. Freddy Lippert, the CEO of EMS Copenhagen, notes that the algorithm has already saved lives by expediting accurate diagnoses in high-pressure situations where time is of the essence.
Researchers at the University of Nottingham in the UK have even developed a deep learning algorithm that predicts death more accurately than human clinicians. The algorithm incorporates data from a huge range of factors in a chronically ill population, including how many fruits and vegetables a patient eats on a daily basis. Dr. Stephen Weng, lead author of the study, published in PLOS ONE, said in a press release, "We found machine learning algorithms were significantly more accurate in predicting death than the standard prediction models developed by a human expert."
New digital technologies are allowing patients to participate in their healthcare as never before. A feature of the new Apple Watch is an app that detects cardiac arrhythmias and even produces an electrocardiogram if an abnormality is detected. The technology, approved by the FDA, is helping cardiologists monitor heart patients and design interventions for those who may be at higher risk of a cardiac event like a stroke.
If having an algorithm predict your death sends a shiver down your spine, consider that algorithms may keep you alive longer. In 2018, technology reporter Tristan Greene wrote for Medium that "…despite the unending deluge of panic-ridden articles declaring AI the path to apocalypse, we're now living in a world where algorithms save lives every day. The future of machine learning isn't sentient killer robots. It's longer human lives."
The Risks of AI Compiling Your Data
To be sure, the advent of AI-infused medical technology is not without its risks. One risk is that the use of AI wearables constantly monitoring our vital signs could turn us into a nation of hypochondriacs, racing to our doctors every time there's a blip in some vital sign. Such a development could stress an already overburdened system that suffers from, among other things, a shortage of doctors and nurses. Another risk has to do with the privacy protections on the massive repository of intimately personal information that AI will have on us.
In an article recently published in the Journal of the American Medical Association, Australian researcher Kit Huckvale and colleagues examined the handling of data by 36 smartphone apps that assisted people with either depression or smoking cessation, two areas that could lend themselves to stigmatization if they fell into the wrong hands.
Out of the 36 apps, 33 shared their data with third parties, despite the fact that just 25 of those apps had a privacy policy at all and out of those, only 23 stated that data would be shared with third parties. The recipients of all that data? It went almost exclusively to Facebook and Google, to be used for advertising and marketing purposes. But there's nothing to stop it from ending up in the hands of insurers, background databases, or any other entity.
Even when data isn't voluntarily shared, any digital information can be hacked. EHRs and even wearable devices share the same vulnerability as any other digital record or device. Still, the promise of AI to radically improve efficiency and accuracy in healthcare is hard to ignore.
AI Can Help Restore Humanity to Medicine
Eric Topol, director of the Scripps Research Translational Institute and author of the new book Deep Medicine, says that AI gives doctors and nurses the most precious gift of all: time.
Topol welcomes his patients' use of the Apple Watch cardiac feature and is optimistic about the ways that AI is revolutionizing medicine. He says that the watch helps doctors monitor how well medications are working and has already helped to prevent strokes. But in addition to that, AI will help bring the humanity back to a profession that has become as cold and hard as a stainless steel dissection table.
"When I graduated from medical school in the 1970s," he says, "you had a really intimate relationship with your doctor." Over the decades, he has seen that relationship steadily erode as medical organizations demanded that doctors see more and more patients within ever-shrinking time windows.
"Doctors have no time to think, to communicate. We need to restore the mission in medicine."
In addition to that, EHRs have meant that doctors and nurses are getting buried in paperwork and administrative tasks. This is no doubt one reason why a recent study by the World Health Organization showed that worldwide, about 50 percent of doctors suffer from burnout. People who are utterly exhausted make more mistakes, and medical clinicians are no different from the rest of us. Only medical mistakes have unacceptably high stakes. According to its website, Johns Hopkins University recently announced that in the U.S. alone, 250,000 people die from medical mistakes each year.
"Doctors have no time to think, to communicate," says Topol. "We need to restore the mission in medicine." AI is giving doctors more time to devote to the thing that attracted them to medicine in the first place—connecting deeply with patients.
There is a real danger at this juncture, though, that administrators aware of the time-saving aspects of AI will simply push doctors to see more patients, read more tests, and embrace an even more crushing workload.
"We can't leave it to the administrators to just make things worse," says Topol. "Now is the time for doctors to advocate for a restoration of the human touch. We need to stand up for patients and for the patient-doctor relationship."
AI could indeed be a game changer, he says, but rather than squander the huge benefits of more time, "We need a new equation going forward."
Couples Facing Fertility Treatments Should Beware of This
When Jane Stein and her husband used in-vitro fertilization in 2001 to become pregnant with twins, her fertility clinic recommended using a supplemental procedure called intracytoplasmic sperm injection (ICSI), known in fertility lingo as "ix-see."
'Add-on' fertility procedures are increasingly coming under scrutiny for having a high cost and low efficacy rate.
During IVF, an egg and sperm are placed in a petri dish together with the hope that a sperm will seek out and fertilize the egg. With ICSI, doctors inject sperm directly into the egg.
Stein, whose name has been changed to protect her privacy, agreed to try it. Her twins are now 16, but while 17 years have gone by since that procedure, the efficacy of ICSI is still unclear. In other words, while Stein succeeded in having children, it may not have been because of ICSI. It may simply have been because she did IVF.
The American Society for Reproductive Medicine has concluded, "There are no data to support the routine use of ICSI for non-male factor infertility." That is, ICSI can help couples have a baby when the issue is male infertility. But when it's not, the evidence of its effectiveness is lacking. And yet the procedure is being used more and more, even when male infertility is not the issue. Some 40 percent of fertility treatments in Europe, Asia and the Middle East now use ICSI, according to a world report released in 2016 by the International Committee for Monitoring Assisted Reproductive Technologies. In the Middle East, the figure is actually 100 percent, the report said.
ICSI is just one of many supplemental procedures, or 'add-ons,' increasingly coming under scrutiny for having a high cost and low efficacy rate. They cost anywhere from a couple of hundred dollars to several thousand – ICSI costs $2,000 to $3,000 -- hiking up the price of what is already a very costly endeavor. And many don't even work. Worse, some actually cause harm.
It's no surprise couples use them. They promise to increase the chance of conceiving. For patients who desperately want a child, money is no object. The Human Fertilization and Embryology Authority (HFEA) in the U.K. found that some 74 percent of patients who received fertility treatments over the last two years were given at least one type of add-on. Now, fertility associations in the U.S. and abroad have begun issuing guidance about which add-ons are worth the extra cost and which are not.
"Many IVF add-ons have little in the way of conclusive evidence supporting their role in successful IVF treatment," said Professor Geeta Nargund, medical director of CREATE Fertility and Lead Consultant for reproductive medicine at St George's Hospital, London.
The HFEA has actually rated these add-ons, indicating which procedures are effective and safe. Some treatments were rated 'red' because they were considered to have insufficient evidence to justify their use. These include assisted hatching, which uses acid or lasers to make a hole in the surrounding layer of proteins to help the embryo hatch; intrauterine culture, where a device is inserted into the womb to collect and incubate the embryo; and reproductive immunology, which suppresses the body's natural immunity so that it accepts the embryo.
"Fertility care is a highly competitive market. In a private system, offering add-ons may discern you from your neighboring clinic."
For some treatments, the HFEA found there is evidence that they don't just fail to work, but can even be harmful. These procedures include ICSI used when male infertility is not at issue, as well as a procedure called endometrial scratching, where the uterus is scratched, not unlike what would happen with a biopsy, to stimulate the local uterine immune system.
And then for some treatments, there is conflicting evidence, warranting further research. These include artificial egg activation by calcium ionophore, elective freezing in all cycles, embryo glue, time-lapse imaging and pre-implantation genetic testing for abnormal chromosomes on day 5.
"Currently, there is very little evidence to suggest that many of the add-ons could increase success rates," Nargund said. "Indeed, the HFEA's assessment of add-on treatments concluded that none of the add-ons could be given a 'green' rating, due to a lack of conclusive supporting research."
So why do fertility clinics offer them?
"Fertility care is a highly competitive market," said Professor Hans Evers, editor-in-chief of the journal Human Reproduction. "In a private system, offering add-ons may discern you from your neighboring clinic. The more competition, the more add-ons. Hopefully the more reputable institutions will only offer add-ons (for free) in the context of a randomized clinical trial."
The only way for infertile couples to know which work and which don't is the guidance released by professional organizations like the ASRM, and through government regulation in countries that have a public health care system.
The problem is, infertile couples will sometimes do anything to achieve a pregnancy.
"They will stand on their heads if this is advocated as helpful. Someone has to protect them," Evers said.
In the Netherlands, where Evers is based, the national health care system tries to make the best use of the limited resources it has, so it makes sure the procedures it's funding actually work, Evers said.
"We have calculated that to serve a population of 17 million, we need 13 IVF clinics, and we have 13," he said. "We as professionals discuss and try to agree on the value of newly proposed add-ons, and we will implement only those that are proven effective and safe."
Likewise, in the U.K., there's been a lot of squawking about speculative add-ons because the government, or National Health Service, pays for them. In the U.S., it's private insurers or patients' own cash.
"The [U.K.] government takes a very close look at what therapies they are offering and what the evidence is around offering the therapy," said Alan Penzias, who chairs the Practice Committee of the ASRM. It wants to make sure the treatments it is funding are at least worth the money.
ICSI is a case in point. Originally intended for male infertility, it's now being applied across the board because fertility clinics didn't want couples to pay $10,000 to $15,000 and wind up with no embryos.
"It is so disastrous to have no fertilization whatsoever, clinics started to make this bargain with their patients, saying, 'Well, listen, even though it's not indicated, what we would like to do is to take half of your eggs and do the ICSI procedure, and half we'll do conventional insemination just to make sure,'" he said. "It's a disaster if you have no embryos, and now you're out 10 to 12 thousand dollars, so for a small added fee, we can do the injection just to guard against that."
In the Netherlands, the national health care system tries to make the best use of its limited resources, so it makes sure the procedures it's funding actually work.
Clinics offer it where they see lower rates of fertilization, such as with older women or in cases where induced ovulation results in just two or three eggs instead of, say, 13. Unfortunately, ICSI may result in a higher fertilization rate, but it doesn't result in a higher live birth rate, according to a study last year in Human Reproduction, so couples wind up paying for a procedure that doesn't even result in a child.
Private insurers in the U.S. are keen to it. Penzia, who is also an associate professor of obstetrics, gynecology and reproductive biology at Harvard Medical School and works as a reproductive endocrinology and infertility specialist at Boston IVF, said Massachusetts requires that insurers cover infertility treatments. But when he submits claims for ICSI, for instance, insurers now want to see two sperm counts and proof that the man has seen a urologist.
"They want to make sure we're doing it for male factor (infertility)," he said. "That's not unreasonable, because the insurance company is taking the burden of this."