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Archive for month: August, 2020
Organ donation, the opt-in or opt-out debate
The shortage of transplant organs is a pressing issue around the world. In an effort to increase the number of donated organs, various initiatives have been implemented in a number of countries to prompt people to donate their organs in the event of death.
Some of these interventions are referred to as nudges. Nudges are psychological and refer to behavioural change interventions that alter people’s behaviour by modifying the context of their choice in such a way as to make the “better” option the most salient or easiest choice without substantially changing the underlying incentive structure.
Several countries, such as Germany, Denmark, Lithuania and the Netherlands have a default opt-in registry whereby citizens have to actively choose to register as an organ donor. However, some countries, such as Austria, Spain, France, Italy, Belgium, Sweden and Greece have an opt-out system whereby citizens are automatically registered as organ donors and have to actively choose to opt-out if they prefer not to be an organ donor.
However, whether opt-in or opt-out, most organ donation legislative systems include a clause that allows the final decision to donate to be made by family members of the deceased.
In the United kingdom the NHS Blood and Transplant reported in 2016 that more than 500 families vetoed organ donations between 2010 and 2015 despite being informed that their relative was on the opt-in NHS Organ Donation Register. This translated into an estimated 1,200 people missing out on potential life-saving transplants.
This was one of the reasons why England recently announced plans to change their opt-in registry to an opt-out one in 2020.
However, a recent study from Queen Mary University of London argues this move is unlikely to result in any significant increase in donated organs. Although the authors of the study note that several studies have shown that default opt-out systems have substantially increased registered donations and give examples from Belgium where kidney donations increased from 10.9 to 41.3 per million people during a 3-year period, and from Singapore where kidney donations increased from 4.7 to 31.3 per year over a 3-year period.
Nonetheless, in the study, published in May this year, the authors argue that under an opt-out system the family would perceive the donor’s preference as weaker because it involves a passive choice to donate compared to a default opt-in system where an active choice to donate is made.
The study concludes that the opt-out system is unlikely to increase actual rates of organ donation or reduce veto rates, all it will do is increase the number of people on the organ donation register.
The hospital of tomorrow: an ICU perspective
Hospitals have evolved considerably over the years from the early Greek temples of healing, asclepeia, to the large dark, cramped multiple-patient wards of the early Western hospitals, essentially for those who could not afford private care at home, and the brighter, more open smaller ward or single room hospitals of today. These changes have come about as medicine has advanced, technology has progressed and societal and patient conditions and demands have changed. It is difficult to predict how the hospital of tomorrow will look with any precision, but we can make some fairly accurate suggestions based on current trends and developments.
by Prof Jean-Louis Vincent
One key change is that intensive care unit (ICU) patients will represent an increasingly large proportion of hospital patients in the future. There are several reasons for this. First, improved disease prevention and primary care, shorter post-surgery hospital stays and facilitated home care will mean that patients who are hospitalized will be more seriously ill than at present and more likely to need intensive care. Another reason for the increased need for ICU beds is prolonged life expectancy. Improved healthcare means that the average age of the population is increasing worldwide, and older patients are more likely to have multiple comorbidities and to develop complex acute illness. In one report from the US, the number of hospital beds decreased by 2.2% while ICU beds increased by 17.8% over a 10-year period.
As such, the hospital of the future will be composed of a large number of ICU beds with relatively few hospital beds (other than daycare) for other patients (see figure). The ICU may be a physical unit at a strategic place within the hospital, or it may be a more “virtual” ICU with beds dispersed around the hospital. It is possible that in the future all hospital beds will have the potential to be an ICU bed, limiting the need for patient transfers between wards and reducing the time for key ICU interventions to be put into place when a patient is identified as deteriorating. This could also reduce any problems associated with ICU bed shortages. The potential limitations of such an approach include the need for all nursing staff to be trained in intensive care.
So, assuming that the physical ICU structure remains, at least for the near future, what will it look like? With current patient demands for privacy and problems associated with multiresistant pathogens, the ICU will almost certainly consist of multiple single rooms. These rooms will be large and spacious with easy access to the bed from all sides and room for relatives to visit and stay and for the patient to mobilize when possible. The rooms will have large interactive screens with access to patient results and monitored parameters, the ability to call and speak to healthcare staff via telemedicine, and of course standard entertainment channels. Because almost all monitoring, of hemodynamic parameters as well as laboratory values, will be non-invasive and results transmitted to the doctor’s smartphone and to central remote monitoring hubs by wireless technology, there will be much less visible equipment, cables and tubes. What equipment is still necessary will be much smaller, less cumbersome and more user-friendly than at present. Continuous monitoring, multiple feedback systems and computerized interrogation across multiple systems and disciplines will make ICUs much safer with fewer iatrogenic errors.
Visiting hours will be unrestricted throughout the hospital, including in the ICU, and family members, including children, will be welcome. This open access and greater involvement will impact positively on patients and on their families, reducing anxiety and helping to reduce post-ICU stress.
The hospital as a whole will be much more technology oriented than at present and interactive screens will be responsible for much of the routine administration with robots involved in basic services, such as delivery of food and medication, as well as patient mobilization and social stimulation. Care will be more patient-centered and personalized and the flow from home to general ward to ICU will be much more of a continuum. Indeed, some patients may be discharged directly home from the ICU, an option facilitated by continued surveillance using telemedicine. Patients and healthcare staff will have continuous and real-time access to patient medical results and data. Such data will be fed automatically into large international databases to help continuously improve patient management. This process will have become routine and current issues related to data privacy will no longer be a problem.
There will be fewer medical and nursing staff physically present on the wards as telemedicine will be more widely used, enabling remote control of drug infusions and other interventions and e-consultations at the request of the physician or patient. Although healthcare staff may therefore be seen less frequently, they will actually be able to spend more quality time talking to patients and their families.
Technological advances are changing how the world around us operates and the hospital is no exception. Future hospital and ICU design needs to provide flexibility and adaptability to continued technological developments. Healthcare workers and patients will need time to adapt to these changes and to learn how best to use them to improve care and outcomes. We must all be involved in developing the ICU of the future. As Abraham Lincoln said, “The best way to predict the future is to create it”.
Suggested reading:
1. Vincent JL. Critical care–where have we been and where are we going? Crit Care 2013;17 Suppl 1:S2.
2. Halpern NA, Goldman DA, Tan KS et al. Trends in critical care beds and use among population groups and Medicare and Medicaid beneficiaries in the United States: 2000-2010. Crit Care Med 2016;44:1490-1499.
3. Ewbank L, Thompson J, McKenna H: NHS hospital bed numbers: past, present, future. https://www kingsfund org uk/publications/nhs-hospital-bed-numbers#hospital-beds-in-england-and-abroad.
4. Vincent JL, Creteur J. The hospital of tomorrow in 10 points. Crit Care 2017;21:93.
5. Vincent JL, Michard F, Saugel B. Intensive care medicine in 2050: towards critical care without central lines. Intensive Care Med 2018;44:922-924.
6.Denis K, Bidet F, Egault J et al. Utilization of Robo-K for improving walking and balance in patients affected by neurological injuries: A preliminary study. Ann Phys Rehabil Med 2016;59S:e88.
7. Bailly S, Meyfroidt G, Timsit JF. What’s new in ICU in 2050: big data and machine learning. Intensive Care Med 2018; 44:1524-1527.
8.Michard F, Pinsky MR, Vincent JL. Intensive care medicine in 2050: NEWS for hemodynamic monitoring. Intensive Care Med 2017;43:440-442.
The author
Jean-Louis Vincent, MD, PhD
Dept of Intensive Care, Erasme Hospital, Université libre de Bruxelles, Brussels, Belgium
Big data in the ICU – critical care databases and decision support
The deluge of data produced during medical care has typically been under-utilized or simply wasted. In the era of paper, this was explicable. However, in spite of nearly three decades of computerization, medical data remains difficult to access and organize, let alone use. Such a gap is both large and dramatic in the intensive care unit (ICU), where the complexity of illness and new possibilities unveiled by the unremitting march of technology transcend typical cognitive capabilities. In turn, this serves to further highlight the critical role of data support in evidence-based healthcare decision making.
From structured analysis to personalized treatment
Big Data’s case in the ICU, whose environment is both critical and intense by definition, is self-evident. One of the first arguments in its favour is that new ICU patients usually require extremely close monitoring. This is a highly data intensive process. The accumulation of data, in turn, can cause information overload in physicians who are providing the care.
Some experts foresee using Big Data in the ICU for structured analysis of complex decisions and the quantifying of expected benefits versus harms in different treatment options. Although such a tool has not been well received by several clinicians, it has considerable potential in terms of personalizing treatment. Today, ICU patients in particular can be provided with interventions that sustain life in spite of severe organ dysfunction. However, the treatments can also result in prolonged suffering with no guarantee of outcomes in line with patient preferences. Decision analysis based on Big Data might enable such concerns to be addressed.
Reducing uncertainty
There are several other practical drivers for Big Data in the ICU. Very often, ICU decisions have to be made with a high degree of uncertainty, and clinical staff may have minutes or seconds to make those decisions. These could cover issues such as knowing patient sub-populations that experience significant divergences in efficacy or unanticipated delayed adverse effects from drug treatments. At present, ICU practices vary due to either an absence of medical knowledge or conflicting opinions. Given time constraints, therapeutic decisions and choices depend largely on clinician preference and local practice patterns, leading to significant variability in quality of care.
Study shows scale of challenge in ICU interventions
As it stands, however, a large number of ICU interventions are not based on proven cases or standardized guidelines.
In 2008, a team at Erasmus Hospital in Brussels, Belgium, made a systematic review of 72 multi-centre randomized controlled trials evaluating the effect of ICU interventions on mortality and found that just 10 (about one in seven) showed benefit. 55 had no measurable value while as many as 7 (one in ten) were actually harmful.
Organizing critical care
Apologists for the lack of use of Big Data in the ICU point out that medicine can be as much art and science, and standardized protocols and best practices are not always sufficiently flexible. Such flexibility can indeed be imperative in an ICU, where decisions are subject to exceptional complexity and variability in patient status and clinical situation.
Nevertheless, a study on the concept of ‘organized care’ showed that applying W. Edwards Deming’s process management theory to manage variation in providing care can yield huge savings to the healthcare system. The study, titled ‘How Intermountain trimmed healthcare costs through robust quality improvement efforts’, was published in the June 2011 issue of ‘Health Affairs’. Its authors estimated that such efforts could save the US healthcare system about USD 3.5 billion (€3 billion) a year.
As a result, it may well be argued that variability in ICU practices is the result of a failure to research and establish evidence for a particular approach, in spite of the fact that both the data and the technology exist.
Scoring systems
Typical Big Data deployments in the ICU would be focused on the most expensive or high-risk parts of current clinical practice in critical care, and cover predictive alerts and analytics for complex case patients, decompensation and adverse events, intervention optimization for multiple organ involvement as well as triaging and readmissions.
Progress has already been made by using clinical data to infer high-level information in ICU scoring systems. These are largely used to compare ICU performance in terms of outcomes.
APACHE and SAPS
Two of the best known scoring systems are APACHE (Acute Physiology and Chronic Health Evaluation) and SAPS (Simplified Acute Physiology Score).
APACHE was designed to provide morbidity scores for a patient and help decide on a specific therapy. Methods to derive a predicted mortality from this score exist, but they are yet to be sufficiently well defined and precise.
SAPS was originally aimed at predicting mortality, originally for benchmarking. It has since been updated to provide a predicted mortality score for a particular patient or patient group by calibrating against recorded mortalities on an existing set of patients. SAPS can be used to compare the evolution in performance of an ICU over a period of time or compare treatment at different ICUs.
Variety of ICU databases in development
At present, ICU databases are being developed by hospitals/professional societies, academic institutions and medical equipment vendors. They structure and aggregate demographic data (age and sex of patient, condition or disease, co-morbidities, length of stay, date and time of discharge, mortality, readmission etc.) and provide such information on a hospital-specific basis. Rather than decision or standardization of protocols and practice, such databases simply provide monitoring and selective comparisons of ICU patient outcomes and costs – over time, or by region. However, there are new efforts to go further and build decision support tools.
Non-commercial databases
One good example of a non-commercial database is the Adult Patient Database (APD) from the Australia and New Zealand Intensive Care Society (ANZICS). It contains data from over 1.3 million patient episodes and is considered one of the largest single datasets on intensive care in the world. The database collects episodes from over 140 ICUs in Australia and New Zealand on a quarterly basis, and is used to benchmark performance of individual units.
The Danish Intensive Care Database (DID) is another non-commercial database, with data for over 350,000 ICU stays. DID made a big leap in introducing the ICU scoring indicator, SAPS II in 2010, which however remains less than 80% complete. DID quality indicators include readmission to the ICU within 48 hours and standardized mortality ratios for death within 30 days of admission using case-mix adjustment (age, sex, co-morbidity level and SAPS). Process indicators consist of out-of-hour discharge and transfer to other ICUs for capacity reasons.
Commercial databases
ICU databases are also being developed by medical technology vendors for commercial use. Cerner has created APACHE Outcomes, which has gathered physiologic and laboratory measurements from over 1 million patient records across 105 ICUs since 2010. Although large, it still contains incomplete physiologic and laboratory measurements, and does not offer waveform data and provider notes.
Another commercial database known as eICU is provided by Philips. This telemedicine-intensive care support provider archives data from participating ICUs and is available to qualified researchers via the eICU Research Institute. The database size is estimated at over 1.5 million ICU stays, and it is reported to be adding 400,000 patient records per year from about 180 subscribing hospitals. As with APACHE Outcomes, eICU does not archive waveform data. However, provider notes are captured if entered into the software.
MIMIC
In contrast to commercial databases like eICU and APACHE Outcomes, MIMIC (Multiparameter Intelligent Monitoring in Intensive Care) is an open and public database with a host of clinical data from ICUs, vital signs, medications, laboratory measurements, observations and notes, fluid balance, procedure codes, diagnostic codes, imaging reports, hospital length of stay, survival data, and more.
Currently in its third generation, MIMIC provides a unique research resource with data from about 40,000 critical care patients. Hundreds of researchers from over 30 countries are given free access under data use agreements. In addition, several thousands of students, educators and investigators have used MIMIC’s waveform data, which is freely available to all.
History
MIMIC is the fruit of a collaboration since the early 2000s between Beth Israel Deaconess (a unit of Harvard Medical School), the Laboratory of Computational Physiology at the Massachusetts Institute of Technology (MIT), and Philips Healthcare, with support provided by the National Institute of Biomedical Imaging and Bioinformatics.
MIMIC was launched as a research project to establish a critical care alert and display (CCAD) system and assist decision support in the ICU, on the basis of a large temporal ICU patient research database. The system generated abnormal clinical values as clinician alerts via a user interface designed to allow efficient and ergonomic display of data. Within a short time after launch, it was producing over 50 alerts per patient ICU day.
Unique capability has promise for modelling
The MIMIC database is considered unique due to its capability to capture structured and extremely granular data. This includes per minute changes in physiologic signals, as well as time-stamped treatments with dosages, and permits modelling individual response to clinical intervention, which, in turn, allows for improved risk-benefit calculation and prediction of outcomes.
Some of these models might be optimal to develop effective early triage in terms of level of care and monitoring, as well as the allotment of scarce human and technical resources. In turn, such tools could assist emergency departments facing limitations in ICU resources.
Findings
Recent observational studies on the MIMIC ICU database have yielded several findings of interest. These cover areas such as long-term outcomes of minor elevations in troponin, heterogeneity in impact of red blood cell transfusion, the optimization of heparin dosing to minimize chance of under- or over-anticoagulation and the impact of selective serotonin reuptake inhibitors (SSRI) on mortality. Researchers are also studying areas of potentially great impact such as determining the proper duration for a trial of aggressive ICU care among high-risk patients.
International expansion
The MIMIC database is being used to design and develop decision support tools. Outcomes of concern are not limited to mortality or length of stay, but will instead be extended to include factors such as the probability of discharge to a nursing facility and expected duration of stay there, as well as the need for procedures such as hemodialysis or repeat hospitalization.
In spite of its clear utility, MIMIC is currently limited because its data is derived entirely from just one institution, namely Beth Israel Deaconess, and does not therefore account for practice variation across ICUs. There are however plans to expand the project to include data from ICUs in Britain and France.
A helping hand for pediatric intensive care
Doctors working in the eight-bed Pediatric Intensive Care Unit at the Ramón y Cajal University Hospital in Madrid use point-of-care ultrasound extensively to evaluate the condition of critically ill children, and find it essential to their work. Dr José Luis Vázquez Martínez, Head of UCIP at Hospital Ramón y Cajal, with over 25 years’ experience in pediatric intensive care medicine, explained.
Point-of-care ultrasound (POCUS) is used extensively in our unit, allowing comprehensive, head-to-toe assessment of critically ill children, including respiratory, oncology and post-operative cardiac patients, as well as those being treated for sepsis or multiple trauma. The POCUS approach allows not only an initial diagnosis, but also routine monitoring of treatment to see whether or not a patient’s condition changes, enabling alternative strategies to be implemented if there is no improvement.
POCUS helps pediatric doctors in many ways. For example, ultrasound scans enable evaluation of a patient’s hemodynamic state, looking at their heart function and blood volume to see if these factors are contributing to respiratory failure. Conversely, doctors can see if a lung problem, such as pneumonia, is affecting the heart. For a patient in a coma due to multiple trauma, ultrasound is used to look for signs of bleeding – a potential cause of unexplained anemia – and to assess the intracranial pressure. It is also used to monitor kidney function in children with blood pressure problems, and visualize intestinal indications of sepsis. In addition, ultrasound guidance can be used for endotracheal intubation. In short, broader applications that we did not anticipate until very recently.
We have used ultrasound in our PICU for more than a decade, and have always had SonoSite systems, upgrading them as new technology is introduced. In the beginning, when my knowledge was more limited, the aim was to perform clinical echocardiography but, when the SonoSite representative showed me the linear probe and the various techniques available, it was as if I was being shown electricity after using candles! It was amazing, a real turning point in the use of ultrasound, and everyone recognized it as a step forward in the pediatric intensive care world. For the patients, a major benefit of ultrasound is that exposure to radiation can be reduced. Before ultrasound, X-ray examinations were performed two or three times in the first few days after admission to try to establish the cause of the problem, often with limited success. With ultrasound, we can scan the patient as often as necessary, implementing treatment and monitoring its effect without exposing the child to more radiation.
In PICU, we consider an ultrasound system essential – there is nothing else that gives us so much information, so quickly and non-invasively – and today we have a dedicated Edge II ultrasound system with linear, including hockey stick, and adult and pediatric cardiac transducers. It is in constant demand and is a perfect fit for our work, fulfilling all our expectations. All my colleagues use it, and we are very satisfied with it. The system is high quality and ergonomic, and strikes a good balance between image quality and ease of use. It is also quick to boot up, which is crucial for an instrument that is frequently moved between different beds in the unit. Robustness is vital too; if a patient deteriorates, we may have to move any equipment surrounding the bed very quickly to create space to treat them. However careful you are, there is always the risk of unintentional knocks to the system.
A while ago someone said to me that they ‘sell ultrasound machines but don’t offer training’, but this view isn’t enough – it’s very short-sighted – training is very important. Ramón y Cajal pioneered the use of ultrasound in PICUs across Spain, and was the first hospital to offer external training courses for doctors from other facilities, initially focused on clinical echocardiography. Over time, this has expanded to include neuromonitoring, respiratory and abdominal monitoring. I acquired my ultrasound experience through a combination of external training in adult ultrasound and practical, hands-on learning, and am largely self-taught. If courses like these had been available when I started using ultrasound, I would have saved so much time.
FUJIFILM SonoSite is clearly committed to organising and supporting ultrasound training, and this is unquestionably a great benefit to the scientific community – long may it last!
Today, we are seeing a boom in the use of ultrasound in pediatric care, as it non-invasively provides immediate information in situations where time is of the essence. Our advice to people attending our training courses who do not have – or have to share – an ultrasound system is to tell their hospital managers that, just like a ventilator, it is an essential piece of equipment for an intensive care unit.
www.sonosite.comwww.fujifilmholdings.com
Pregnancy and critical care
Though global maternal mortality has declined by 1.3 percent a year since 1990, the rate continues to remain stubbornly high in certain regions. At present, fewer than one of 50 pregnant women require critical care. However, both maternal and fetal mortality can be high when it is required.
In industrialized countries, the rate of obstetric ICU admissions varies from 50 to over 400 per 100,000 deliveries with an overall case-fatality rate of 2%. In developing countries, fatality in obstetric ICU patients can be 3-5 times higher.
Obstetric disorders in the ICU
Obstetric ICU patients include those with obstetric disorders as well as pregnant patients with medical/surgical disorders. The bulk of patients are admitted to the ICU for obstetric disorders. In general, obstetricians are aware of all obstetric patients in hospital, whether they have a medical or obstetric problem.
There are several obstetric conditions which can require ICU admission. The most common are hemorrhage and hypertensive disorders, above all pre-eclampsia toxemia (PET) and eclampsia. In industrialiZed Western countries, these typically account for 30-35% and 20% of admissions to the ICU.
Hemorrhage leading cause of mortality, ICU admission
Obstetric hemorrhage is either antepartum or postpartum, and remains the leading cause of maternal mortality. Antepartum hemorrhage occurs in 5 percent of pregnant women, and in the bulk of cases carries no risk to the mother or fetus. Major causes involve the placenta and uterine rupture.
Postpartum hemorrhage (PPH) is the single most frequent indication for ICU admission, and involves major blood loss, regardless of the mode of birth. Though there is no universally accepted definition, it typically means more than a half litre of blood loss within 24 hours. In about two out of three cases, PPH is due to failure of uterine contraction after delivery, with most of the rest caused by placental retention. Genital trauma, due to laceration of the vagina or cervix because of instrument delivery, is also increasingly implicated in PPH.
Patient management of obstetric hemorrhage depends on identifying the cause and whether or not delivery has occurred. In PPH, management is aggressive, beginning with administration of oxytocin, emptying of the bladder and massage of the uterus. The care team also begins intravenous prostaglandin therapy, coupled with uterine tamponade via balloon compression or packing. If bleeding persists, surgical intervention is indicated: arterial ligation, suture, Cesarean hysterectomy or uterine artery embolization. Should bleeding continue, recombinant factor VIIa is administered and repeated, if there is no response.
Hypertensive disorders
Pre-eclampsia toxemia (PET) occurs in 2 to 3 percent of all pregnancies after 20 weeks of gestation, and is classified as mild, moderate or severe. Its pathogenesis results from abnormal placenta formation, and it is characterized by impaired organ perfusion due to impaired vasodilation and placental ischemia. As pregnancy progresses, the ischemia worsens. This makes the mother hypertensive, with a risk of renal dysfunction.
Severe PET is associated with significant morbidity and mortality, both for the mother and fetus. It requires one or more of the following indicators: hypertension (BP over 160 systolic or 110 diastolic), proteinuria higher than 5 grams per 24 hours or oliguria below 400 ml per 24 hours, along with cerebral irritability, epigastric pain, and pulmonary edema.
PET usually resolves following delivery of the fetus but may manifest postpartum. A variety of antihypertensive agents, including hydralazine, labetalol, sodium nitroprusside, alpha blockers, calcium channel blockers and methyl dopa, have been advocated in PET. Hydralazine and labetalol are the most widely used in the critical care setting. Magnesium is usually co-administered to provide vasodilatation and prevent seizures. Care should be taken with fluid resuscitation because of the risk of pulmonary edema.
Eclampsia is an extreme complication of PET, and is marked by the occurrence of convulsions and seizures, 40% of which occur following delivery. The seizures tend to be self-limiting, with a very rare incidence of status epilepticus. Though the mortality from eclampsia has been high in the past, death is now uncommon. Common causes of mortality are hepatic complications, including hepatic failure, hemorrhage, or infarction.
Other challenges of pregnancy
Peripartum cardiomyopathy is another challenging condition during pregnancy, albeit of unknown cause. It is one of the leading causes of maternal death, with mortality as high as 25-50%. It can occur from the final month of pregnancy up to 5 months after delivery.
Other conditions unique to pregnancy include HELPP syndrome (hemolysis, elevated liver enzymes and low platelets), placental disorders (abruption, previa or retention), amniotic fluid embolism and chorioamnionitis, and acute fatty liver.
Changing epidemiology
The epidemiology of obstetrics in the ICU has changed dramatically since the past decade. Obstetric conditions such as thrombocytopenic purpura of pregnancy, which were rare in the past, are now being diagnosed more frequently. Massive hemorrhage from adherent placenta is increasing due to the growing number of pregnant women bearing scars from previous cesarean sections (CS). Uterine rupture during labour is also sometimes associated with previous CS. Another condition is ovarian hyper-stimulation syndrome, which is not uncommon any more due to the sharp growth in the availability of assisted reproduction techniques.
There are now many older mothers with pre-existing disorders and chronic medical conditions, some of which can be in an advanced stage. Typical co-morbidities today including essential hypertension, Type 2 diabetes and coronary heart disease. Obesity is also a major concern, which poses numerous challenges for managing pregnant patients in the ICU.
Impact on multiple physiological systems
Pregnancy affects several physiological systems – among them, the cardiovascular, respiratory, renal, hematologic and endocrine. These tax a patient’s reserves and often compromise responses needed to combat a disease state during pregnancy and the peripartum period.
Pregnancy’s impact on physiological systems is twofold: first, by worsening pre-existing conditions, and second, by heightening susceptibility.
For example, cardiovascular conditions which can deteriorate significantly in pregnancy include aortal coarctation, primary pulmonary hypertension and valvular disease; congenital heart disease is another such condition. Cardiovascular issues are also important since that shortness of breath is a very common symptom in pregnancy. When this occurs, clinicians must distinguish the dyspnea resulting from underlying medical disorders versus that caused by normal physiologic changes in pregnancy. The latter include anemia, upward displacement of the diaphragm, and respiratory alkalosis.
One of the most confounding cardiovascular challenges is associated with PET. Aside from hypertension, patients also show increased systemic vascular resistance and reduced intravascular volume, which cause a reduction in cardiac output as disease severity progresses. In such cases, left ventricular function can deteriorate leading to a risk of pulmonary edema after fluid resuscitation.
On the other side, pregnant women also face an increase in risk for a gamut of infections ranging from varicella pneumonia and urinary tract infections to malaria and hepatitis.
In the respiratory system, the impact of pregnancy on cystic fibrosis is well known. However, pregnant women also face a concurrent increase in susceptibility to venous embolisms and pulmonary thromboembolism.
This kind of dual impact is also faced by the renal, endocrinal and neurological systems. Pregnancy worsens renal insufficiency and glomerulonephritis and enhances susceptibility to acute renal failure.
In the endocrinal system, it worsens diabetes and prolactinoma and increases susceptibility to gestational diabetes.
The list of neurological conditions which deteriorate during pregnancy is especially large, and includes epilepsy, myasthena gravis and multiple sclerosis, while an increase in susceptibility is seen with intracranial hemorrhage. Another complicating factor is that up to half of obstetric critical care patients have some form of neurological compromise. In most circumstances, this is the result of their admission diagnosis (that is, pre-eclampsia or obstetric hemorrhage), rather than as the precipitant of their ICU admission.
Two patients in one
As a result of the above factors, obstetric critical care represents a major challenge for medical professionals. Obstetricians need to master both maternal and fetal physiology, and avoid any potentially adverse effects on a fetus of diagnostic and therapeutic interventions given as part of care for the mother. Indeed, it is a common statement that obstetricians treat two patients, the mother and the fetus. They must also assess two separate risks – maternal and fetal – from continuing with a pregnancy and decide if termination of the pregnancy improves the outcome for the mother. This is a very charged challenge since a fetus is generally robust despite maternal illness, and it has been demonstrated that pregnancy-induced critical illnesses are resolved by delivery of the fetus.
Mastering general principles
Obstetric ICU practice consists of firstly mastering general principles such as drug safety, ventilation and management of patient airways, monitoring of the fetus, muscle relaxation and sedation, cardiovascular support, thromboprophylaxis, as well as radiology and ethical issues. This is followed by the acquisition of expertise in the management of obstetric and medical conditions.
Critical care interventions for an obstetric patient are similar to those for the non-pregnant patient. However, it is often necessary to adjust physiologic targets for metabolic, pulmonary, and hemodynamic control.
The need for teamwork
Given the complexity and time-sensitiveness of critical care medicine, teamwork skills are essential. Typically, the care team for an obstetric patient at an ICU is multidisciplinary, consisting of the intensivist, obstetrician, anesthesiologist, maternal-fetal medicine specialist, the neonatologist and the ICU nurses. This team needs to operate effectively alongside regular staff.
Although clinicians working in critical care environments are generally highly trained and competent, they have traditionally not learned how to work well as part of a team. Remedying this has become a priority on both sides of the Atlantic.
As part of a paper on standards of care, the European Board and College of Obstetrics and Gynaecology (EBCOG) explicitly recommends “multidisciplinary, high-quality teamwork” as being “essential” in obstetric medical care and urges healthcare providers to ensure that maternity services have adequate facilities, expertise, capacity and back-up for “timely transfer to intensive care.” EBCOG also seeks to give substance to such a mission. It urges a system of “clear referral paths” to enable pregnant women requiring additional care to be managed and treated by the appropriate specialist teams when problems are identified. One of its most interesting recommendations is for development and routine use of an obstetric ‘early warning chart’ to help in the timely recognition, treatment and referral of women developing a critical illness.
Teamwork is also seen as being a priority in the US, where the Joint Commission pointed to failures in teamwork and communication as among the leading causes of adverse obstetric events. Although obstetric clinicians seem aware of deficiencies in teamwork, their perceptions of teamwork differ based upon their role. In a survey by Johns Hopkins University of 44 hospitals across the US, the majority had fewer than half of respondents reporting ‘good teamwork’ in their labour and delivery units.
Inconsistencies with breast density protocols can be solved
While everyone in the healthcare industry agrees that early detection of breast cancer saves lives, much less consensus can be found across the broader conversation of breast cancer screening in general. This inconsistency is especially apparent as it pertains to breast density, an issue that carries significant weight for both clinicians and patients. It is necessary for radiologists to not only acknowledge and understand how breast density impacts screening in general, but also to recognize the discrepancies in today’s breast density protocols, best practices for handling them and how this can affect clinicians and patients.
by Tracy Accardi
To start, consider the way a patient’s breast density is currently assessed. Most commonly, radiologists complete a visual assessment, which involves looking at digital images of the patient’s breasts and determining which of the categories her tissue fits into best according to a classification system known as the Breast Imaging Reporting and Data System (BI-RADS). There are four classifications to establish breast density type, which include – from least to most dense – fatty, scattered fibroglandular, heterogeneously dense, and extremely dense. Although the four categories help establish what radiologists should be looking for visually to determine if a woman has dense breasts, each radiologist’s individual perceptions are open to interpretation, potentially leading to inconsistencies in classification. As a result, some women may be misinformed about what their breast density is, which can be problematic considering breast density has long been recognized as a risk factor for cancer. In fact, women with very dense breasts are four to five times more likely to develop breast cancer than women with less dense breasts [1,2].
Screening protocol for dense breast patients
Once a woman’s breast density is classified, there is a good deal of debate regarding next steps for breast cancer screening. In fact, in a 2017 Kadence study, only 32 percent of the surveyed radiologists in Europe indicated they have a formal screening protocol in place for patients with dense breastS [3]. There are a number of modalities radiologists can choose to utilize when screening women for breast cancer, however, very dense breasts are challenging to read, particularly when using traditional 2D mammography. This is because suspicious calcifications appear white on a mammogram, blending in with dense breast tissue that is similar in colouring that is also known as a “masking effect.” Therefore, the imaging modality used to screen patients, especially those with dense breasts, truly matters. In the U.S., for example, Hologic’s 3D Mammography Exam is the only mammogram that is FDA-approved as superior to standard 2D mammography for routine breast cancer screening of all women, including those with dense breasts [4]. Despite this, there are no official guidelines that radiologists are encouraged to follow when screening their patients with dense breasts. As a result, patients may be missing the opportunity to receive a breast cancer diagnosis earlier on so they can start treatment right away because they weren’t screened with the most appropriate technology.
Clearly, there are many ways that clinicians across the world are currently approaching breast density protocols, especially as they pertain to assessment and screening. These inconsistencies are creating confusion among clinicians and patients alike. Fortunately, there are a number of solutions for this issue. When assessing density, radiologists should consider technology available to them to help remove subjectivity from their evaluations. In fact, clinicians can combine their patient-specific knowledge with artificial intelligence (AI), which—thanks to machine learning-based algorithms—can be used to classify breast tissue within the BI-RADS category, allowing for objective, accurate assessments. As a result, women can and should be better informed about what their breast density truly is, which may help those who didn’t realize they were at risk for cancer to be more compliant with screenings. Additionally, radiologists and their facilities should offer their patients the best possible technology that exists for screening dense breasts, pending they have no extenuating limitations based on their individual patient profiles.
Healthcare professionals owe it to their patients to find solutions that provide the best possible outcomes. By making breast density and the inconsistencies surrounding it a priority for reconciliation, radiologists can best deliver care to their patients.
References
1. Boyd NF, Guo H, Martin LJ, et al. Mammographic density and the risk and detection of breast cancer. N Engl J Med. 356(3):227-36, 2007.
2. Yaghjyan L, Colditz GA, Collins LC, et al. Mammographic breast density and subsequent risk of breast cancer in postmenopausal women according to tumor characteristics. J Natl Cancer Inst. 103(15):1179-89, 2011.
3. Kadence study conducted in partnership with Hologic in 2017. Data on file.
4. FDA submissions P080003, P080003/S001, P080003/S004, P080003/S005.
The author
Tracy Accardi, Global Vice President of Research & Development for Breast & Skeletal Solutions at Hologic, Inc.
Understanding connected memories
It is fascinating following our expanding knowledge of the workings of the brain with the use of functional MRI over the past 10-15 years. fMRI has provided an extraordinary view of brain function and enabled a wide range of remarkable discoveries. As this research proliferates, it promises many more new insights, with a multitude of applications.
Particularly interesting has been the growing understanding of memory formation and retrieval. Expanding on this knowledge and taking it to the next level, a recent study by neuroscientists and artificial intelligence researchers at DeepMind, Otto von Guericke University Magdeburg and the German Centre for Neurodegenerative Diseases shows how the human brain connects individual – or episodic – memories to solve problems and draw new insights.
The researchers proposed a novel brain mechanism that would allow retrieved memories to trigger the retrieval of other, related memories.
There have been many studies of episodic memories which advance the theory that they are stored as separate memory traces in a brain region called the hippocampus. Taking this as standard knowledge, the researchers’ new theory explores an anatomical connection that loops out of the hippocampus to the neighbouring entorhinal cortex but then passes back in to the hippocampus. It is this recurrent connection, the researchers thought, that allows memories retrieved from the hippocampus to trigger the retrieval of further, multiple linked memories.
To test the theory the researchers used a 7 Tesla fMRI to scan brain activation in 26 male and female study participants as they performed a task that required them to draw insights across separate events using a series of paired images. Their results are published in the September 2018 issue of Neuron.
Part of the study involved the development of a technique where they were able to separate out the parts of the entorhinal cortex that provide the input to the hippocampus, which allowed them to precisely measure the patterns of activation in the hippocampus to distinguish input and output separately.
Their resulting data showed that when the hippocampus retrieves a memory, it doesn’t simply pass it to the rest of the brain, but instead recirculates the activation back into the hippocampus, triggering the retrieval of other related memories.
They say their results preserve the best of both worlds – you preserve the ability to remember individual episodic experiences by keeping them separate, while at the same time allowing related memories to be combined on the fly at the point of retrieval.
In addition, they reckon this understanding could be replicated in Artificial Intelligence systems so they will have a greater capacity for rapidly solving novel problems.
What’s next?