The Discover In-Hospital Cardiac Arrest (Discover IHCA) Study: An Investigation of Hospital Practices After In-Hospital Cardiac Arrest.

IMPORTANCE: In-hospital cardiac arrest (IHCA) is a significant public health burden. Rates of return of spontaneous circulation (ROSC) have been improving, but the best way to care for patients after the initial resuscitation remains poorly understood, and improvements in survival to discharge are stagnant. Existing North American cardiac arrest databases lack comprehensive data on the post-resuscitation period, and we do not know current post-IHCA practice patterns. To address this gap, we developed the Discover In-Hospital Cardiac Arrest (Discover IHCA) study, which will thoroughly evaluate current post-IHCA care practices across a diverse cohort. OBJECTIVES: Our study collects granular data on post-IHCA treatment practices, focusing on temperature control and prognostication, with the objective of describing variation in current post-IHCA practice. DESIGN, SETTING, AND PARTICIPANTS: This is a multicenter, prospectively collected, observational cohort study of patients who have suffered IHCA and have been successfully resuscitated (achieved ROSC). There are 24 enrolling hospital systems (23 in the United States) with 69 individual enrolling hospitals (39 in the United States). We developed a standardized data dictionary, and data collection began in October 2023, with a projected 1000 total enrollments. Discover IHCA is endorsed by the Society of Critical Care Medicine. INTERVENTIONS, OUTCOMES, AND ANALYSIS: The study collects data on patient characteristics including pre-arrest frailty, arrest characteristics, and detailed information on post-arrest practices and outcomes. Data collection on post-IHCA practice was structured around current American Heart Association and European Resuscitation Council guidelines. Among other data elements, the study captures post-arrest temperature control interventions and post-arrest prognostication methods. Analysis will evaluate variations in practice and their association with mortality and neurologic function. CONCLUSIONS: We expect this study, Discover IHCA, to identify variability in practice and outcomes following IHCA, and be a vital resource for future investigations into best-practice for managing patients after IHCA.

Management of Patients With Cardiac Arrest Requiring Interfacility Transport: A Scientific Statement From the American Heart Association.

People who experience out-of-hospital cardiac arrest often require care at a regional center for continued treatment after resuscitation, but many do not initially present to the hospital where they will be admitted. For patients who require interfacility transport after cardiac arrest, the decision to transfer between centers is complex and often based on individual clinical characteristics, resources at the presenting hospital, and available transport resources. Once the decision has been made to transfer a patient after cardiac arrest, there is little direct guidance on how best to provide interfacility transport. Accepting centers depend on transferring emergency departments and emergency medical services professionals to make important and nuanced decisions about postresuscitation care that may determine the efficacy of future treatments. The consequences of early care are greater when transport delays occur, which is common in rural areas or due to inclement weather. Challenges of providing interfacility transfer services for patients who have experienced cardiac arrest include varying expertise of clinicians, differing resources available to them, and nonstandardized communication between transferring and receiving centers. Although many aspects of care are insufficiently studied to determine implications for specific out-of-hospital treatment on outcomes, a general approach of maintaining otherwise recommended postresuscitation care during interfacility transfer is reasonable. This includes close attention to airway, vascular access, ventilator management, sedation, cardiopulmonary monitoring, antiarrhythmic treatments, blood pressure control, temperature control, and metabolic management. Patient stability for transfer, equity and inclusion, and communication also must be considered. Many of these aspects can be delivered by protocol-driven care.

Inside the Black Box of Deliberate Practice: How do Coaches Coach to Improve Trauma Triage.

INTRODUCTION: Deliberate practice, goal-oriented training with feedback from a coach, is a common tool for improving physicians' performance. However, little is known about how coaches foster performance improvement. METHODS: A content analysis of video-recorded training sessions was performed to analyze the coaches' behaviors during a pilot randomized trial of deliberate practice in trauma triage. The intervention consisted of three video-conference sessions during which trial physicians, under the supervision of a coach, played a customized video game designed to review trauma triage principles. A multidisciplinary team specified tasks (e.g., create collaborative learning environment) that coaches should complete, and suggested 19 coaching strategies (e.g., encourage culture of error) to allow execution of these tasks. Two independent raters translated those strategies into a coding framework and applied it deductively to the recorded sessions. The frequencies of the coaching strategies were summarized, and tested for variation across coaches and time. RESULTS: Thirty physicians received the intervention across two 1-mo blocks. Most (28 [93%]) completed three sessions, each covering two (interquartile range 1-2) triage principles. Coaches used coaching strategies 18 (interquartile range 14.5-22) times per triage principle, using some often (2-3 times/principle) and others infrequently (<1 time/principle). The three coaches used similar numbers (20 versus 16 versus 18.5, P = 0.07) and types of strategies. However, use increased over time (16.8 [Block 1] versus 20 [Block 2] P = 0.018). CONCLUSIONS: Coaches used 19 coaching strategies to deliver this deliberate practice intervention, with behavior that evolved over time. Future trials should isolate the most potent strategies and should assess the best method of standardizing coaching.

Clinical Factors Associated With Mode of Death Following Cardiac Arrest.

BACKGROUND: Death after resuscitation from cardiac arrest is common. Although associated factors have been identified, knowledge about their relationship with specific modes of death is limited. OBJECTIVE: To identify clinical factors associated with specific modes of death following cardiac arrest. METHODS: This study involved a retrospective medical record review of patients admitted to a single health care center from January 2015 to March 2020 after resuscitation from cardiac arrest who died during their index hospitalization. Mode of death was categorized as either brain death, withdrawal of life-sustaining therapies due to neurologic causes, death due to medical causes, or withdrawal of life-sustaining therapies due to patient preference. Clinical characteristics across modes of death were compared. RESULTS: The analysis included 731 patients. Death due to medical causes was the most common mode of death. Compared with the other groups of patients, those with brain death were younger, had fewer comorbidities, were more likely to have experienced unwitnessed and longer cardiac arrest, and had more severe acidosis and hyperglycemia on presentation. Patients who died owing to medical causes or withdrawal of life-sustaining therapies due to patient preference were older and had more comorbidities, fewer unfavorable cardiac arrest characteristics, and fewer days between cardiac arrest and death. CONCLUSIONS: Significant associations were found between several clinical characteristics and specific mode of death following cardiac arrest. Decision-making regarding withdrawal of care after resuscitation from cardiac arrest should be based on a multimodal approach that takes account of a variety of personal and clinical factors.

Clinicians' approach to predicting post-cardiac arrest outcomes for patients enrolled in a United States clinical trial.

PURPOSE: Perceived poor prognosis can lead to withdrawal of life-sustaining therapies (WLST) in patients who might otherwise recover. We characterized clinicians' approach to post-arrest prognostication in a multicenter clinical trial. METHODS: Semi-structured interviews were conducted with clinicians who treated a comatose post-cardiac arrest patient enrolled in the Influence of Cooling Duration on Efficacy in Cardiac Arrest Patients (ICECAP) trial (NCT04217551). Two authors independently analyzed each interview using inductive and deductive coding. The clinician reported how they arrived at a prognosis for the specific patient. We summarized the frequency with which clinicians reported using objective diagnostics to formulate their prognosis, and compared the reported approaches to established guidelines. Each respondent provided demographic information and described local neuroprognostication practices. RESULTS: We interviewed 30 clinicians at 19 US hospitals. Most claimed adherence to local hospital neuroprognostication protocols (n = 19). Prognostication led to WLST for perceived poor neurological prognosis in 15/30 patients, of whom most showed inconsistencies with guidelines or trial recommendations, respectively. In 10/15 WLST cases, clinicians reported relying on multimodal testing. A prevalent theme was the use of "clinical gestalt," defined as prognosticating based on a patient's overall appearance or a subjective impression in the absence of objective data. Many clinicians (21/30) reported using clinical gestalt for initial prognostication, with 9/21 expressing high confidence initially. CONCLUSION: Clinicians in our study state they follow neuroprognostication guidelines in general but often do not do so in actual practice. They reported clinical gestalt frequently informed early, highly confident prognostic judgments, and few objective tests changed initial impressions. Subjective prognostication may undermine well-designed trials.

Early Seizure Prophylaxis in Mild and Moderate Traumatic Brain Injury: A Systematic Review and Meta-Analysis.

Importance: Guidelines recommend seizure prophylaxis for early posttraumatic seizures (PTS) after severe traumatic brain injury (TBI). Use of antiseizure medications for early seizure prophylaxis after mild or moderate TBI remains controversial. Objective: To determine the association between seizure prophylaxis and risk reduction for early PTS in mild and moderate TBI. Data Sources: PubMed, Google Scholar, and Web of Science (January 1, 1991, to April 18, 2023) were systematically searched. Study Selection: Observational studies of adult patients presenting to trauma centers in high-income countries with mild (Glasgow Coma Scale [GCS], 13-15) and moderate (GCS, 9-12) TBI comparing rates of early PTS among patients with seizure prophylaxis with those without seizure prophylaxis. Data Extraction and Synthesis: The Preferred Reporting Items for Systematic Reviews and Meta-analysis (PRISMA) reporting guidelines were used. Two authors independently reviewed all titles and abstracts, and 3 authors reviewed final studies for inclusion. A meta-analysis was performed using a random-effects model with absolute risk reduction. Main Outcome Measures: The main outcome was absolute risk reduction of early PTS, defined as seizures within 7 days of initial injury, in patients with mild or moderate TBI receiving seizure prophylaxis in the first week after injury. A secondary analysis was performed in patients with only mild TBI. Results: A total of 64 full articles were reviewed after screening; 8 studies (including 5637 patients) were included for the mild and moderate TBI analysis, and 5 studies (including 3803 patients) were included for the mild TBI analysis. The absolute risk reduction of seizure prophylaxis for early PTS in mild to moderate TBI (GCS, 9-15) was 0.6% (95% CI, 0.1%-1.2%; P = .02). The absolute risk reduction for mild TBI alone was similar 0.6% (95% CI, 0.01%-1.2%; P = .04). The number needed to treat to prevent 1 seizure was 167 patients. Conclusion and Relevance: Seizure prophylaxis after mild and moderate TBI was associated with a small but statistically significant reduced risk of early posttraumatic seizures after mild and moderate TBI. The small absolute risk reduction and low prevalence of early seizures should be weighed against potential acute risks of antiseizure medications as well as the risk of inappropriate continuation beyond 7 days.

Emotional distress, social support, and functional dependence predict readiness for hospital discharge in a prospective sample of cognitively intact cardiac arrest survivors.

AIM: To inform screening, referral and treatment initiatives, we tested the hypothesis that emotional distress, social support, functional dependence, and cognitive impairment within 72 hours prior to discharge predict readiness for discharge in awake and alert cardiac arrest (CA) survivors. METHODS: This was a secondary analysis of a prospective single-center cohort of CA survivors enrolled between 4/2021 and 9/2022. We quantified emotional distress using the Posttraumatic Stress Disorder Checklist-5 and PROMIS Emotional Distress - Anxiety and Depression Short Forms 4a; perceived social support using the ENRICHD Social Support Inventory; functional dependence using the modified Rankin Scale; and cognitive impairment using the Telephone Interview for Cognitive Status. Our primary outcome was readiness for discharge, measured using the Readiness for Hospital Discharge Scale. We used multivariable linear regression to test the independent association of each survivorship factor and readiness for discharge. RESULTS: We included 110 patients (64% male, 88% white, mean age 59 [standard deviation ± 13.1 years]). Emotional distress, functional dependence, and social support were independently associated with readiness for discharge (adjusted ß's [absolute value]: 0.25-0.30, all p < 0.05). CONCLUSIONS: Hospital systems should consider implementing routine in-hospital screening for emotional distress, social support, and functional dependence for CA survivors who are awake, alert and approaching hospital discharge, and prioritize brief in hospital treatment or post-discharge referrals.

Brain computed tomography after resuscitation from in-hospital cardiac arrest.

BACKGROUND: Few data characterize the role of brain computed tomography (CT) after resuscitation from in-hospital cardiac arrest (IHCA). We hypothesized that identifying a neurological etiology of arrest or cerebral edema on brain CT are less common after IHCA than after resuscitation from out-of-hospital cardiac arrest (OHCA). METHODS: We included all patients comatose after resuscitation from IHCA or OHCA in this retrospective cohort analysis. We abstracted patient and arrest clinical characteristics, as well as pH and lactate, to estimate systemic illness severity. Brain CT characteristics included quantitative measurement of the grey-to-white ratio (GWR) at the level of the basal ganglia and qualitative assessment of sulcal and cisternal effacement. We compared GWR distribution by stratum (no edema ≥1.30, mild-to-moderate <1.30 and >1.20, severe ≤1.20) and newly identified neurological arrest etiology between IHCA and OHCA groups. RESULTS: We included 2,306 subjects, of whom 420 (18.2%) suffered IHCA. Fewer IHCA subjects underwent post-arrest brain CT versus OHCA subjects (149 (35.5%) vs 1,555 (82.4%), p < 0.001). Cerebral edema for IHCA versus OHCA was more often absent (60.1% vs. 47.5%) or mild-to-moderate (34.3% vs. 27.9%) and less often severe (5.6% vs. 24.6%). A neurological etiology of arrest was identified on brain CT in 0.5% of IHCA versus 3.2% of OHCA. CONCLUSIONS: Although severe edema was less frequent in IHCA relative to OHCA, mild-to-moderate or severe edema occurred in one in three patients after IHCA. Unsuspected neurological etiologies of arrest were rarely discovered by CT scan in IHCA patients.

Recent Advances in Group-Based Trajectory Modeling for Clinical Research.

Group-based trajectory modeling (GBTM) identifies groups of individuals following similar trajectories of one or more repeated measures. The categorical nature of GBTM is particularly well suited to clinical psychology and medicine, where patients are often classified into discrete diagnostic categories. This review highlights recent advances in GBTM and key capabilities that remain underappreciated in clinical research. These include accounting for nonrandom subject attrition, joint trajectory and multitrajectory modeling, the addition of the beta distribution to modeling options, associating trajectories with future outcomes, and estimating the probability of future outcomes. Also discussed is an approach to selecting the number of trajectory groups.

Using a theory-based, customized video game as an educational tool to improve physicians' trauma triage decisions: study protocol for a randomized cluster trial.

BACKGROUND: Transfer of severely injured patients to trauma centers, either directly from the field or after evaluation at non-trauma centers, reduces preventable morbidity and mortality. Failure to transfer these patients appropriately (i.e., under-triage) remains common, and occurs in part because physicians at non-trauma centers make diagnostic errors when evaluating the severity of patients' injuries. We developed Night Shift, a theory-based adventure video game, to recalibrate physician heuristics (intuitive judgments) in trauma triage and established its efficacy in the laboratory. We plan a type 1 hybrid effectiveness-implementation trial to determine whether the game changes physician triage decisions in real-life and hypothesize that it will reduce the proportion of patients under-triaged. METHODS: We will recruit 800 physicians who work in the emergency departments (EDs) of non-trauma centers in the US and will randomize them to the game (intervention) or to usual education and training (control). We will ask those in the intervention group to play Night Shift for 2 h within 2 weeks of enrollment and again for 20 min at quarterly intervals. Those in the control group will receive only usual education (i.e., nothing supplemental). We will then assess physicians' triage practices for older, severely injured adults in the 1-year following enrollment, using Medicare claims, and will compare under-triage (primary outcome), 30-day mortality and re-admissions, functional independence, and over-triage between the two groups. We will evaluate contextual factors influencing reach, adoption, implementation, and maintenance with interviews of a subset of trial participants (n = 20) and of other key decision makers (e.g., patients, first responders, administrators [n = 100]). DISCUSSION: The results of the trial will inform future efforts to improve the implementation of clinical practice guidelines in trauma triage and will provide deeper understanding of effective strategies to reduce diagnostic errors during time-sensitive decision making. TRIAL REGISTRATION: ClinicalTrials.gov; NCT06063434 . Registered 26 September 2023.

A multicenter, randomized, doubleblind, placebo-controlled trial of amantadine to stimulate awakening in comatose patients resuscitated from cardiac arrest.

OBJECTIVE: We hypothesized that the administration of amantadine would increase awakening of comatose patients resuscitated from cardiac arrest. METHODS: We performed a prospective, randomized, controlled pilot trial, randomizing subjects to amantadine 100 mg twice daily or placebo for up to 7 days. The study drug was administered between 72 and 120 hours after resuscitation and patients with absent N20 cortical responses, early cerebral edema, or ongoing malignant electroencephalography patterns were excluded. Our primary outcome was awakening, defined as following two-step commands, within 28 days of cardiac arrest. Secondary outcomes included length of stay, awakening, time to awakening, and neurologic outcome measured by Cerebral Performance Category at hospital discharge. We compared the proportion of subjects awakening and hospital survival using Fisher exact tests and time to awakening and hospital length of stay using Wilcoxon rank sum tests. RESULTS: After 2 years, we stopped the study due to slow enrollment and lapse of funding. We enrolled 14 subjects (12% of goal enrollment), seven in the amantadine group and seven in the placebo group. The proportion of patients who awakened within 28 days after cardiac arrest did not differ between amantadine (n=2, 28.6%) and placebo groups (n=3, 42.9%; P>0.99). There were no differences in secondary outcomes. Study medication was stopped in three subjects (21.4%). Adverse events included a recurrence of seizures (n=2; 14.3%), both of which occurred in the placebo group. CONCLUSION: We could not determine the effect of amantadine on awakening in comatose survivors of cardiac arrest due to small sample size.

The impact of COVID-19 pandemic on out-of-hospital cardiac arrest: An individual patient data meta-analysis.

AIM: Prior studies have reported increased out-of-hospital cardiac arrests (OHCA) incidence and lower survival during the COVID-19 pandemic. We evaluated how the COVID-19 pandemic affected OHCA incidence, bystander CPR rate and patients' outcomes, accounting for regional COVID-19 incidence and OHCA characteristics. METHODS: Individual patient data meta-analysis of studies which provided a comparison of OHCA incidence during the first pandemic wave (COVID-period) with a reference period of the previous year(s) (pre-COVID period). We computed COVID-19 incidence per 100,000 inhabitants in each of 97 regions per each week and divided it into its quartiles. RESULTS: We considered a total of 49,882 patients in 10 studies. OHCA incidence increased significantly compared to previous years in regions where weekly COVID-19 incidence was in the fourth quartile (>136/100,000/week), and patients in these regions had a lower odds of bystander CPR (OR 0.49, 95%CI 0.29-0.81, p = 0.005). Overall, the COVID-period was associated with an increase in medical etiology (89.2% vs 87.5%, p < 0.001) and OHCAs at home (74.7% vs 67.4%, p < 0.001), and a decrease in shockable initial rhythm (16.5% vs 20.3%, p < 0.001). The COVID-period was independently associated with pre-hospital death (OR 1.73, 95%CI 1.55-1.93, p < 0.001) and negatively associated with survival to hospital admission (OR 0.68, 95%CI 0.64-0.72, p < 0.001) and survival to discharge (OR 0.50, 95%CI 0.46-0.54, p < 0.001). CONCLUSIONS: During the first COVID-19 pandemic wave, there was higher OHCA incidence and lower bystander CPR rate in regions with a high-burden of COVID-19. COVID-19 was also associated with a change in patient characteristics and lower survival independently of COVID-19 incidence in the region where OHCA occurred.

Common Data Elements for Disorders of Consciousness: Recommendations from the Working Group on Biospecimens and Biomarkers.

BACKGROUND: In patients with disorders of consciousness (DoC), laboratory and molecular biomarkers may help define endotypes, identify therapeutic targets, prognosticate outcomes, and guide patient selection in clinical trials. We performed a systematic review to identify common data elements (CDEs) and key design elements (KDEs) for future coma and DoC research. METHODS: The Curing Coma Campaign Biospecimens and Biomarkers work group, composed of seven invited members, reviewed existing biomarker and biospecimens CDEs and conducted a systematic literature review for laboratory and molecular biomarkers using predetermined search words and standardized methodology. Identified CDEs and KDEs were adjudicated into core, basic, supplemental, or experimental CDEs per National Institutes of Health classification based on level of evidence, reproducibility, and generalizability across different diseases through a consensus process. RESULTS: Among existing National Institutes of Health CDEs, those developed for ischemic stroke, traumatic brain injury, and subarachnoid hemorrhage were most relevant to DoC and included. KDEs were common to all disease states and included biospecimen collection time points, baseline indicator, biological source, anatomical location of collection, collection method, and processing and storage methodology. Additionally, two disease core, nine basic, 24 supplemental, and 59 exploratory biomarker CDEs were identified. Results were summarized and generated into a Laboratory Data and Biospecimens Case Report Form (CRF) and underwent public review. A final CRF version 1.0 is reported here. CONCLUSIONS: Exponential growth in biomarkers development has generated a growing number of potential experimental biomarkers associated with DoC, but few meet the quality, reproducibility, and generalizability criteria to be classified as core and basic biomarker and biospecimen CDEs. Identification and adaptation of KDEs, however, contribute to standardizing methodology to promote harmonization of future biomarker and biospecimens studies in DoC. Development of this CRF serves as a basic building block for future DoC studies.

Simple approach to quantify hypoxic-ischemic brain injury severity from computed tomography imaging files after cardiac arrest.

BACKGROUND: Grey-white ratio (GWR) can estimate severity of cytotoxic cerebral edema secondary to hypoxic-ischemic brain injury after cardiac arrest and predict progression to death by neurologic criteria (DNC). Current approaches to calculating GWR are not standardized and have variable interrater reliability. We tested if measures of variance of brain density on early computed tomographic (CT) imaging after cardiac arrest could predict DNC. METHODS: We performed a retrospective cohort study, identifying post-arrest patients treated between 2011 and 2020 at our single center. We extracted demographic data from our registry and Digital Imaging and Communication in Medicine (DICOM) files for each patient's first brain CT. We analyzed slices 15-20 of each DICOM, corresponding to the level of the basal ganglia while accommodating differences in patient anatomy. We extracted pixel arrays and converted the radiodensities to Hounsfield units (HU). To focus on brain tissue densities, we excluded HU > 60 and < 10. We calculated the variance of each patient's HU distribution and the difference between the means of a two-group Gaussian finite mixture model. We compared these novel metrics to existing measures of cerebral edema, then randomly divided our data into 80% training and 20% test sets and used logistic regression to predict DNC. RESULTS: Of 1,133 included subjects, 457 (40%) were female, mean (standard deviation) age was 58 (16) years, and 115 (10%) progressed to DNC. CTs were obtained a median [interquartile range] of 4.2 [2.8-5.7] hours post-arrest. Our novel measures correlated weakly with GWR. HU variance, but not difference between mixture model means, differed significantly between subjects with and without sulcal or cistern effacement. GWR outperformed our novel measures in predicting progression to DNC with an area under the receiver operating characteristic curve (AUC) of 0.82, compared to HU variance (AUC = 0.73) and the difference between mixture model means (AUC = 0.56). CONCLUSION: There are differences in the distribution of HU on post-arrest CT in patients with qualitative measures of cerebral edema. Current methods to quantify cerebral edema outperform simple measures of attenuation variance on early brain CT. Further analyses could investigate if these measures of variance, or other distributional characteristics of brain density, have improved predictive performance on brain CTs obtained later in the clinical course or derived from discrete regions of anatomical interest.

Metabolic Manipulation and Therapeutic Hypothermia.

Hypothermia has multiple physiological effects, including decreasing metabolic rate and oxygen consumption (VO2). There are few human data about the magnitude of change in VO2 with decreases in core temperature. We aimed to quantify to magnitude of reduction in resting VO2 as we reduced core temperature in lightly sedated healthy individuals. After informed consent and physical screening, we cooled participants by rapidly infusing 20 mL/kg of cold (4°C) saline intravenously and placing surface cooling pads on the torso. We attempted to suppress shivering using a 1 mcg/kg intravenous bolus of dexmedetomidine followed by titrated infusion at 1.0 to 1.5 µg/(kg·h). We measured resting metabolic rate VO2 through indirect calorimetry at baseline (37°C) and at 36°C, 35°C, 34°C, and 33°C. Nine participants had mean age 30 (standard deviation 10) years and 7 (78%) were male. Baseline VO2 was 3.36 mL/(kg·min) (interquartile range 2.98-3.76) mL/(kg·min). VO2 was associated with core temperature and declined with each degree decrease in core temperature, unless shivering occurred. Over the entire range from 37°C to 33°C, median VO2 declined 0.7 mL/(kg·min) (20.8%) in the absence of shivering. The largest average decrease in VO2 per degree Celsius was by 0.46 mL/(kg·min) (13.7%) and occurred between 37°C and 36°C in the absence of shivering. After a participant developed shivering, core body temperature did not decrease further, and VO2 increased. In lightly sedated humans, metabolic rate decreases around 5.2% for each 1°C decrease in core temperature from 37°C to 33°C. Because the largest decrease in metabolic rate occurs between 37°C and 36°C, subclinical shivering or other homeostatic reflexes may be present at lower temperatures.