“Coming Back from the Dead” Is No Longer Science Fiction
Last year, there were widespread reports of a 53-year-old Frenchman who had suffered a cardiac arrest and "died," but was then resuscitated back to life 18 hours after his heart had stopped.
The once black-and-white line between life and death is now blurrier than ever.
This was thought to have been possible in part because his body had progressively cooled down naturally after his heart had stopped, through exposure to the outside cold. The medical team who revived him were reported as being "stupefied" that they had been able to bring him back to life, in particular since he had not even suffered brain damage.
Interestingly, this man represents one of a growing number of extraordinary cases in which people who would otherwise be declared dead have now been revived. It is a testament to the incredible impact of resuscitation science -- a science that is providing opportunities to literally reverse death, and in doing so, shedding light on the age-old question of what happens when we die.
Death: Past and Present
Throughout history, the boundary between life and death was marked by the moment a person's heart stopped, breathing ceased, and brain function shut down. A person became motionless, lifeless, and was deemed irreversibly dead. This is because once the heart stops beating, blood flow stops and oxygen is cut off from all the body's organs, including the brain. Consequently, within seconds, breathing stops and brain activity comes to a halt. Since the cessation of the heart literally occurs in a "moment," the philosophical notion of a specific point in time of "irreversible" death still pervades society today. The law, for example, relies on "time of death," which corresponds to when the heart stops beating.
The advent of cardiopulmonary resuscitation (CPR) in the 1960s was revolutionary, demonstrating that the heart could potentially be restarted after it had stopped, and what had been a clear black-and-white line was shown to be potentially reversible in some people. What was once called death—the ultimate end point— was now widely called cardiac arrest, and became a starting point.
From then on, it was only if somebody had requested not to be resuscitated or when CPR was deemed to have failed that people would be declared dead by "cardiopulmonary criteria." Biologically, cardiac arrest and death by cardiopulmonary criteria are the same process, albeit marked at different points in time depending on when a declaration of death is made.
The apparent irreversibility of death as we know it may not necessarily reflect true irretrievable cellular damage inside the body.
Clearly, contrary to many people's perceptions, cardiac arrest is not a heart attack; it is the final step in death irrespective of cause, whether it be a stroke, a heart attack, a car accident, an overwhelming infection or cancer. This is how roughly 95 percent of the population are declared dead.
The only exception is the small proportion of people who may have suffered catastrophic brain injuries, but whose hearts can be artificially kept beating for a period of time on life-support machines. These people can be legally declared dead based on brain death criteria before their hearts have stopped. This is because the brain can die either from oxygen starvation after cardiac arrest or from massive trauma and internal bleeding. Either way, the brain dies hours or possibly longer after these injuries have taken place and not just minutes.
A Profound Realization
What has become increasingly clear is that the apparent irreversibility of death as we know it may not necessarily reflect true irretrievable cellular damage inside the body. This is consistent with a mounting understanding: it is only after a person actually dies that the cells in the body start to undergo their own process of death. Intriguingly, this process is something that can now be manipulated through medical intervention. Being cold is one of the factors that slows down the rate of cellular decay. The 53-year-old Frenchman's case and the other recent cases of resuscitation after prolonged periods of time illustrate this new understanding.
Last week's earth-shattering announcement by neuroscientist Dr. Nenad Sestan and his team out of Yale, published in the prestigious scientific journal Nature, provides further evidence that a time gap exists between actual death and cellular death in cadavers. In this seminal study, these researchers were able to restore partial function in pig brains four hours after their heads were severed from their bodies. These results follow from the pioneering work in 2001 of geneticist Fred Gage and colleagues from the Salk Institute, also published in Nature, which demonstrated the possibility of growing human brain cells in the laboratory by taking brain biopsies from cadavers in the mortuary up to 21 hours post-mortem.
The once black-and-white line between life and death is now blurrier than ever. Some people may argue this means these humans and pigs weren't truly "dead." However, that is like saying the people who were guillotined during the French Revolution were also not dead. Clearly, that is not the case. They were all dead. The problem is not death; it's our reliance on an outdated philosophical, rather than biological, notion of death.
Death can no longer be considered an absolute moment but rather a process that can be reversed even many hours after it has taken place.
But the distinction between irreversibility from a medical perspective and biological irreversibility may not matter much from a pragmatic perspective today. If medical interventions do not exist at any given time or place, then of course death cannot be reversed.
However, it is crucial to distinguish between biologically and medically: When "irreversible" loss of function arises due to inadequate treatment, then a person could be potentially brought back in the future when an alternative therapy becomes available, or even today if he or she dies in a location where novel treatments can slow down the rate of cell death. However, when true irreversible loss of function arises from a biological perspective, then no treatment will ever be able to reverse the process, whether today, tomorrow, or in a hundred years.
Probing the "Grey Zone"
Today, thanks to modern resuscitation science, death can no longer be considered an absolute moment but rather a process that can be reversed even many hours after it has taken place. How many hours? We don't really know.
One of the wider implications of our medical advances is that we can now study what happens to the human mind and consciousness after people enter the "grey zone," which marks the time after the heart stops, but before irreversible and irretrievable cell damage occurs, and people are then brought back to life. Millions have been successfully revived and many have reported experiencing a unique, universal, and transformative mental state.
Were they "dead"? Yes, according to all the criteria we have ever used. But they were able to be brought back before their "dead" bodies had reached the point of permanent, irreversible cellular damage. This reflects the period of death for all of us. So rather than a "near-death experience," I prefer a new terminology to describe these cases -- "an actual-death experience." These survivors' unique experiences are providing eyewitness testimonies of what we will all be likely to experience when we die.
Such an experience reportedly includes seeing a warm light, the presence of a compassionate perfect individual, deceased relatives, a review of their lives, a judgment of their actions and intentions as they pertain to their humanity, and in some cases a sensation of seeing doctors and nurses working to resuscitate them.
Are these experiences compatible with hallucinations or illusions? No -- in part, because these people have described real, verifiable events, which, by definition are not hallucinations, and in part, because their experiences are not compatible with confused and delirious memories that characterize oxygen deprivation.
The challenge for us scientifically is understanding how this is possible at a time when all our science tells us the brain shuts down.
For instance, it is hard to classify a structured meaningful review of one's life and one's humanity as hallucinatory or illusory. Instead, these experiences represent a new understanding of the overall human experience of death. As an intensive care unit physician for more than 10 years, I have seen numerous cases where these reports have been corroborated by my colleagues. In short, these survivors have been known to come back with reports of full consciousness, with lucid, well-structured thought processes and memory formation.
The challenge for us scientifically is understanding how this is possible at a time when all our science tells us the brain shuts down. The fact that these experiences occur is a paradox and suggests the undiscovered entity we call the "self," "consciousness," or "psyche" – the thing that makes us who we are - may not become annihilated at the point of so-called death.
At New York University, the State University of New York, and across 20 hospitals in the U.S. and Europe, we have brought together a new multi-disciplinary team of experts across many specialties, including neurology, cardiology, and intensive care. Together, we hope to improve cardiac arrest prevention and treatment, as well as to address the impact of new scientific discoveries on our understanding of what happens at death.
One of our first studies, Awareness during Resuscitation (AWARE), published in the medical journal Resuscitation in 2014, confirmed that some cardiac arrest patients report a perception of awareness without recall; others report detailed memories and experiences; and a few report full auditory and visual awareness and consciousness of their experience, from a time when brain function would be expected to have ceased.
While you probably have some opinion or belief about this based upon your own philosophical, religious, or cultural background, you may not realize that exploring what happens when we die is now a subject that science is beginning to investigate.
There is no question more intriguing to humankind. And for the first time in our history, we may finally uncover some real answers.
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."
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.