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Chest pain with long COVID common but undertreated
And chronic chest discomfort may persist in some individuals for years after COVID, warranting future studies of reliable treatments and pain management in this population, a new study shows.
“Recent studies have shown that chest pain occurs in as many as 89% of patients who qualify as having long COVID,” said Ansley Poole, an undergraduate student at the University of South Florida, Tampa, who conducted the research under the supervision of Christine Hunt, DO, and her colleagues at Mayo Clinic, Jacksonville, Fla.
The findings, though preliminary, shed light on the prevalence, current treatments, and ongoing challenges in managing symptoms of long COVID, said Ms. Poole, who presented the research at the annual Pain Medicine Meeting sponsored by the American Society of Regional Anesthesia and Pain Medicine.
Long COVID, which affects an estimated 18 million Americans, manifests approximately 12 weeks after the initial infection and can persist for 2 months or more. Ms. Poole and her team set out to identify risk factors, treatment options, and outcomes for patients dealing with post-COVID chest discomfort.
The study involved a retrospective chart review of 520 patients from the Mayo Clinic network, narrowed down to a final sample of 104. To be included, patients had to report chest discomfort 3-6 months post COVID that continued for 3-6 months after presentation, with no history of chronic chest pain before the infection.
The researchers identified no standardized method for the treatment or management of chest pain linked to long COVID. “Patients were prescribed multiple different treatments, including opioids, post-COVID treatment programs, anticoagulants, steroids, and even psychological programs,” Ms. Poole said.
The median age of the patients was around 50 years; more than 65% were female and over 90% identified as White. More than half (55%) had received one or more vaccine doses at the time of infection. The majority were classified as overweight or obese at the time of their SARS-CoV-2 infection.
Of the 104 patients analyzed, 30 were referred to one or more subspecialties within the pain medicine department, 23 were hospitalized, and 9 were admitted to the intensive care unit or critical care.
“Fifty-three of our patients visited the ER one or more times after COVID because of chest discomfort; however, only six were admitted for over 24 hours, indicating possible overuse of emergency services,” Ms. Poole noted.
Overall, chest pain was described as intermittent instead of constant, which may have been a barrier to providing adequate and timely treatment. The inconsistent presence of pain contributed to the prolonged suffering some patients experienced, Ms. Poole noted.
The study identified several comorbidities, potentially complicating the treatment and etiology of chest pain. These comorbidities – when combined with COVID-related chest pain – contributed to the wide array of prescribed treatments, including steroids, anticoagulants, beta blockers, and physical therapy. Chest pain also seldom stood alone; it was often accompanied by other long COVID–related symptoms, such as shortness of breath.
“Our current analysis indicates that chest pain continues on for years in many individuals, suggesting that COVID-related chest pain may be resistant to treatment,” Ms. Poole reported.
The observed heterogeneity in treatments and outcomes in patients experiencing long-term chest discomfort after COVID infection underscores the need for future studies to establish reliable treatment and management protocols for this population, said Dalia Elmofty, MD, an associate professor of anesthesia and critical care at the University of Chicago, who was not involved in the study. “There are things about COVID that we don’t fully understand. As we’re seeing its consequences and trying to understand its etiology, we recognize the need for further research,” Dr. Elmofty said.
“So many different disease pathologies came out of COVID, whether it’s organ pathology, myofascial pathology, or autoimmune pathology, and all of that is obviously linked to pain,” Dr. Elmofty told this news organization. “It’s an area of research that we are going to have to devote a lot of time to in order to understand, but I think we’re still in the very early phases, trying to fit the pieces of the puzzle together.”
Ms. Poole and Dr. Elmofty report no relevant financial relationships.
A version of this article appeared on Medscape.com.
And chronic chest discomfort may persist in some individuals for years after COVID, warranting future studies of reliable treatments and pain management in this population, a new study shows.
“Recent studies have shown that chest pain occurs in as many as 89% of patients who qualify as having long COVID,” said Ansley Poole, an undergraduate student at the University of South Florida, Tampa, who conducted the research under the supervision of Christine Hunt, DO, and her colleagues at Mayo Clinic, Jacksonville, Fla.
The findings, though preliminary, shed light on the prevalence, current treatments, and ongoing challenges in managing symptoms of long COVID, said Ms. Poole, who presented the research at the annual Pain Medicine Meeting sponsored by the American Society of Regional Anesthesia and Pain Medicine.
Long COVID, which affects an estimated 18 million Americans, manifests approximately 12 weeks after the initial infection and can persist for 2 months or more. Ms. Poole and her team set out to identify risk factors, treatment options, and outcomes for patients dealing with post-COVID chest discomfort.
The study involved a retrospective chart review of 520 patients from the Mayo Clinic network, narrowed down to a final sample of 104. To be included, patients had to report chest discomfort 3-6 months post COVID that continued for 3-6 months after presentation, with no history of chronic chest pain before the infection.
The researchers identified no standardized method for the treatment or management of chest pain linked to long COVID. “Patients were prescribed multiple different treatments, including opioids, post-COVID treatment programs, anticoagulants, steroids, and even psychological programs,” Ms. Poole said.
The median age of the patients was around 50 years; more than 65% were female and over 90% identified as White. More than half (55%) had received one or more vaccine doses at the time of infection. The majority were classified as overweight or obese at the time of their SARS-CoV-2 infection.
Of the 104 patients analyzed, 30 were referred to one or more subspecialties within the pain medicine department, 23 were hospitalized, and 9 were admitted to the intensive care unit or critical care.
“Fifty-three of our patients visited the ER one or more times after COVID because of chest discomfort; however, only six were admitted for over 24 hours, indicating possible overuse of emergency services,” Ms. Poole noted.
Overall, chest pain was described as intermittent instead of constant, which may have been a barrier to providing adequate and timely treatment. The inconsistent presence of pain contributed to the prolonged suffering some patients experienced, Ms. Poole noted.
The study identified several comorbidities, potentially complicating the treatment and etiology of chest pain. These comorbidities – when combined with COVID-related chest pain – contributed to the wide array of prescribed treatments, including steroids, anticoagulants, beta blockers, and physical therapy. Chest pain also seldom stood alone; it was often accompanied by other long COVID–related symptoms, such as shortness of breath.
“Our current analysis indicates that chest pain continues on for years in many individuals, suggesting that COVID-related chest pain may be resistant to treatment,” Ms. Poole reported.
The observed heterogeneity in treatments and outcomes in patients experiencing long-term chest discomfort after COVID infection underscores the need for future studies to establish reliable treatment and management protocols for this population, said Dalia Elmofty, MD, an associate professor of anesthesia and critical care at the University of Chicago, who was not involved in the study. “There are things about COVID that we don’t fully understand. As we’re seeing its consequences and trying to understand its etiology, we recognize the need for further research,” Dr. Elmofty said.
“So many different disease pathologies came out of COVID, whether it’s organ pathology, myofascial pathology, or autoimmune pathology, and all of that is obviously linked to pain,” Dr. Elmofty told this news organization. “It’s an area of research that we are going to have to devote a lot of time to in order to understand, but I think we’re still in the very early phases, trying to fit the pieces of the puzzle together.”
Ms. Poole and Dr. Elmofty report no relevant financial relationships.
A version of this article appeared on Medscape.com.
And chronic chest discomfort may persist in some individuals for years after COVID, warranting future studies of reliable treatments and pain management in this population, a new study shows.
“Recent studies have shown that chest pain occurs in as many as 89% of patients who qualify as having long COVID,” said Ansley Poole, an undergraduate student at the University of South Florida, Tampa, who conducted the research under the supervision of Christine Hunt, DO, and her colleagues at Mayo Clinic, Jacksonville, Fla.
The findings, though preliminary, shed light on the prevalence, current treatments, and ongoing challenges in managing symptoms of long COVID, said Ms. Poole, who presented the research at the annual Pain Medicine Meeting sponsored by the American Society of Regional Anesthesia and Pain Medicine.
Long COVID, which affects an estimated 18 million Americans, manifests approximately 12 weeks after the initial infection and can persist for 2 months or more. Ms. Poole and her team set out to identify risk factors, treatment options, and outcomes for patients dealing with post-COVID chest discomfort.
The study involved a retrospective chart review of 520 patients from the Mayo Clinic network, narrowed down to a final sample of 104. To be included, patients had to report chest discomfort 3-6 months post COVID that continued for 3-6 months after presentation, with no history of chronic chest pain before the infection.
The researchers identified no standardized method for the treatment or management of chest pain linked to long COVID. “Patients were prescribed multiple different treatments, including opioids, post-COVID treatment programs, anticoagulants, steroids, and even psychological programs,” Ms. Poole said.
The median age of the patients was around 50 years; more than 65% were female and over 90% identified as White. More than half (55%) had received one or more vaccine doses at the time of infection. The majority were classified as overweight or obese at the time of their SARS-CoV-2 infection.
Of the 104 patients analyzed, 30 were referred to one or more subspecialties within the pain medicine department, 23 were hospitalized, and 9 were admitted to the intensive care unit or critical care.
“Fifty-three of our patients visited the ER one or more times after COVID because of chest discomfort; however, only six were admitted for over 24 hours, indicating possible overuse of emergency services,” Ms. Poole noted.
Overall, chest pain was described as intermittent instead of constant, which may have been a barrier to providing adequate and timely treatment. The inconsistent presence of pain contributed to the prolonged suffering some patients experienced, Ms. Poole noted.
The study identified several comorbidities, potentially complicating the treatment and etiology of chest pain. These comorbidities – when combined with COVID-related chest pain – contributed to the wide array of prescribed treatments, including steroids, anticoagulants, beta blockers, and physical therapy. Chest pain also seldom stood alone; it was often accompanied by other long COVID–related symptoms, such as shortness of breath.
“Our current analysis indicates that chest pain continues on for years in many individuals, suggesting that COVID-related chest pain may be resistant to treatment,” Ms. Poole reported.
The observed heterogeneity in treatments and outcomes in patients experiencing long-term chest discomfort after COVID infection underscores the need for future studies to establish reliable treatment and management protocols for this population, said Dalia Elmofty, MD, an associate professor of anesthesia and critical care at the University of Chicago, who was not involved in the study. “There are things about COVID that we don’t fully understand. As we’re seeing its consequences and trying to understand its etiology, we recognize the need for further research,” Dr. Elmofty said.
“So many different disease pathologies came out of COVID, whether it’s organ pathology, myofascial pathology, or autoimmune pathology, and all of that is obviously linked to pain,” Dr. Elmofty told this news organization. “It’s an area of research that we are going to have to devote a lot of time to in order to understand, but I think we’re still in the very early phases, trying to fit the pieces of the puzzle together.”
Ms. Poole and Dr. Elmofty report no relevant financial relationships.
A version of this article appeared on Medscape.com.
AI algorithm aids egg retrieval date during fertility treatment cycles
According to the researchers, such an algorithm is needed due to the increased demand for fertility treatments, as well as the high day-to-day variability in lab workload.
According to the study investigators, predicting retrieval dates in advance for ongoing cycles is of major importance for both patients and clinicians.
“The population requiring fertility treatments, including genetic testing and fertility preservation, has massively increased, and this causes many more cycles and a high day-to-day variability in IVF activity, especially in the lab workload,” said Rohi Hourvitz, MBA, from FertilAI, an Israeli health care company focused on developing technologies that improve fertility treatments.
“We also need to accommodate and reschedule for non-working days, which causes a big issue with managing the workload in many clinics around the world,” added Mr. Hourvitz, who presented the research highlighting AI’s growing role in reproductive medicine.
In addition, AI has recently emerged as an effective tool for assisting in clinical decision-making in assisted reproductive technology, prompting further research in this space, he said.
The new study used a dataset of 9,550 predictable antagonist cycles (defined as having all necessary data) gathered from one lab with over 50 physicians between August 2018 and October 2022. The data were split into two subsets: one for training the AI model and the other for prospective testing.
To train and test the AI model, data from nearly 6,000 predictable antagonist cycles were used. Key factors used for each cycle included estrogen levels, mean follicle size, primary follicle size, and various patient demographics. Other features were considered, but Mr. Hourvitz noted that primary follicle size influenced the algorithm most, “because that is what most of us use when we want to trigger.”
Mr. Hourvitz explained that these patient data were run through an algorithm that produced a graph predicting the most probable date for a cycle retrieval.
“We could accurately predict when those ‘peak days’ were going to be happening in the clinic, and we could also give a pretty good estimate on how many cycles you’re going to have every day,” Mr. Hourvitz said, explaining that this information could help clinics more efficiently allocate resources and manage patients.
According to Mr. Hourvitz, the predictions derived from this study could improve various aspects of fertility treatments and related procedures, including better staff planning and caseload management in IVF labs, as well as higher-quality eggs at retrieval. Patients would have a clearer timeline for their treatment cycles.
Nikica Zaninovic, PhD, MS, director of the embryology lab at Weill Cornell Medical College, New York City, cautioned that the new findings are not yet ready for clinical application but emphasized the importance of more AI research focusing on the quality of oocytes, not only embryos.
“We’re so focused on the end of the process: the embryo,” Dr. Zaninovic, who was not involved in the research, said in an interview. “I think the focus should be on the beginning – the quality of eggs and sperm, not just the quantity – because that’s what the embryos will depend on.”
He noted the increasing numbers of young women in the United States undergoing egg freezing.
“Cornell is the largest academic IVF center in the United States; 20%-30% of all of the patients that we treat are actually freezing their eggs,” he said. “It’s a huge population.”
“When they come to us, they ask how many eggs they’ll need to guarantee one or two children in the future,” Dr. Zaninovic continued. “We don’t have that answer, so we always tell them [we’ll retrieve] as many as we can. That’s not the answer; we need to be more precise. We’re still lacking these tools, and I think that’s where the research will go.”
The study was funded by FertilAI. Mr. Hourvitz is a shareholder and CEO of FertilAI. Dr. Zaninovic is president of the AI Fertility Society.
A version of this article appeared on Medscape.com.
According to the researchers, such an algorithm is needed due to the increased demand for fertility treatments, as well as the high day-to-day variability in lab workload.
According to the study investigators, predicting retrieval dates in advance for ongoing cycles is of major importance for both patients and clinicians.
“The population requiring fertility treatments, including genetic testing and fertility preservation, has massively increased, and this causes many more cycles and a high day-to-day variability in IVF activity, especially in the lab workload,” said Rohi Hourvitz, MBA, from FertilAI, an Israeli health care company focused on developing technologies that improve fertility treatments.
“We also need to accommodate and reschedule for non-working days, which causes a big issue with managing the workload in many clinics around the world,” added Mr. Hourvitz, who presented the research highlighting AI’s growing role in reproductive medicine.
In addition, AI has recently emerged as an effective tool for assisting in clinical decision-making in assisted reproductive technology, prompting further research in this space, he said.
The new study used a dataset of 9,550 predictable antagonist cycles (defined as having all necessary data) gathered from one lab with over 50 physicians between August 2018 and October 2022. The data were split into two subsets: one for training the AI model and the other for prospective testing.
To train and test the AI model, data from nearly 6,000 predictable antagonist cycles were used. Key factors used for each cycle included estrogen levels, mean follicle size, primary follicle size, and various patient demographics. Other features were considered, but Mr. Hourvitz noted that primary follicle size influenced the algorithm most, “because that is what most of us use when we want to trigger.”
Mr. Hourvitz explained that these patient data were run through an algorithm that produced a graph predicting the most probable date for a cycle retrieval.
“We could accurately predict when those ‘peak days’ were going to be happening in the clinic, and we could also give a pretty good estimate on how many cycles you’re going to have every day,” Mr. Hourvitz said, explaining that this information could help clinics more efficiently allocate resources and manage patients.
According to Mr. Hourvitz, the predictions derived from this study could improve various aspects of fertility treatments and related procedures, including better staff planning and caseload management in IVF labs, as well as higher-quality eggs at retrieval. Patients would have a clearer timeline for their treatment cycles.
Nikica Zaninovic, PhD, MS, director of the embryology lab at Weill Cornell Medical College, New York City, cautioned that the new findings are not yet ready for clinical application but emphasized the importance of more AI research focusing on the quality of oocytes, not only embryos.
“We’re so focused on the end of the process: the embryo,” Dr. Zaninovic, who was not involved in the research, said in an interview. “I think the focus should be on the beginning – the quality of eggs and sperm, not just the quantity – because that’s what the embryos will depend on.”
He noted the increasing numbers of young women in the United States undergoing egg freezing.
“Cornell is the largest academic IVF center in the United States; 20%-30% of all of the patients that we treat are actually freezing their eggs,” he said. “It’s a huge population.”
“When they come to us, they ask how many eggs they’ll need to guarantee one or two children in the future,” Dr. Zaninovic continued. “We don’t have that answer, so we always tell them [we’ll retrieve] as many as we can. That’s not the answer; we need to be more precise. We’re still lacking these tools, and I think that’s where the research will go.”
The study was funded by FertilAI. Mr. Hourvitz is a shareholder and CEO of FertilAI. Dr. Zaninovic is president of the AI Fertility Society.
A version of this article appeared on Medscape.com.
According to the researchers, such an algorithm is needed due to the increased demand for fertility treatments, as well as the high day-to-day variability in lab workload.
According to the study investigators, predicting retrieval dates in advance for ongoing cycles is of major importance for both patients and clinicians.
“The population requiring fertility treatments, including genetic testing and fertility preservation, has massively increased, and this causes many more cycles and a high day-to-day variability in IVF activity, especially in the lab workload,” said Rohi Hourvitz, MBA, from FertilAI, an Israeli health care company focused on developing technologies that improve fertility treatments.
“We also need to accommodate and reschedule for non-working days, which causes a big issue with managing the workload in many clinics around the world,” added Mr. Hourvitz, who presented the research highlighting AI’s growing role in reproductive medicine.
In addition, AI has recently emerged as an effective tool for assisting in clinical decision-making in assisted reproductive technology, prompting further research in this space, he said.
The new study used a dataset of 9,550 predictable antagonist cycles (defined as having all necessary data) gathered from one lab with over 50 physicians between August 2018 and October 2022. The data were split into two subsets: one for training the AI model and the other for prospective testing.
To train and test the AI model, data from nearly 6,000 predictable antagonist cycles were used. Key factors used for each cycle included estrogen levels, mean follicle size, primary follicle size, and various patient demographics. Other features were considered, but Mr. Hourvitz noted that primary follicle size influenced the algorithm most, “because that is what most of us use when we want to trigger.”
Mr. Hourvitz explained that these patient data were run through an algorithm that produced a graph predicting the most probable date for a cycle retrieval.
“We could accurately predict when those ‘peak days’ were going to be happening in the clinic, and we could also give a pretty good estimate on how many cycles you’re going to have every day,” Mr. Hourvitz said, explaining that this information could help clinics more efficiently allocate resources and manage patients.
According to Mr. Hourvitz, the predictions derived from this study could improve various aspects of fertility treatments and related procedures, including better staff planning and caseload management in IVF labs, as well as higher-quality eggs at retrieval. Patients would have a clearer timeline for their treatment cycles.
Nikica Zaninovic, PhD, MS, director of the embryology lab at Weill Cornell Medical College, New York City, cautioned that the new findings are not yet ready for clinical application but emphasized the importance of more AI research focusing on the quality of oocytes, not only embryos.
“We’re so focused on the end of the process: the embryo,” Dr. Zaninovic, who was not involved in the research, said in an interview. “I think the focus should be on the beginning – the quality of eggs and sperm, not just the quantity – because that’s what the embryos will depend on.”
He noted the increasing numbers of young women in the United States undergoing egg freezing.
“Cornell is the largest academic IVF center in the United States; 20%-30% of all of the patients that we treat are actually freezing their eggs,” he said. “It’s a huge population.”
“When they come to us, they ask how many eggs they’ll need to guarantee one or two children in the future,” Dr. Zaninovic continued. “We don’t have that answer, so we always tell them [we’ll retrieve] as many as we can. That’s not the answer; we need to be more precise. We’re still lacking these tools, and I think that’s where the research will go.”
The study was funded by FertilAI. Mr. Hourvitz is a shareholder and CEO of FertilAI. Dr. Zaninovic is president of the AI Fertility Society.
A version of this article appeared on Medscape.com.
FROM ASRM 2023