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Steinberg A. Emergent Management of Hypoxic-Ischemic Brain Injury. Continuum (Minneap Minn) 2024; 30:588-610. [PMID: 38830064 DOI: 10.1212/con.0000000000001426] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/05/2024]
Abstract
OBJECTIVE This article outlines interventions used to improve outcomes for patients with hypoxic-ischemic brain injury after cardiac arrest. LATEST DEVELOPMENTS Emergent management of patients after cardiac arrest requires prevention and treatment of primary and secondary brain injury. Primary brain injury is minimized by excellent initial resuscitative efforts. Secondary brain injury prevention requires the detection and correction of many pathophysiologic processes that may develop in the hours to days after the initial arrest. Key physiologic parameters important to secondary brain injury prevention include optimization of mean arterial pressure, cerebral perfusion, oxygenation and ventilation, intracranial pressure, temperature, and cortical hyperexcitability. This article outlines recent data regarding the treatment and prevention of secondary brain injury. Different patients likely benefit from different treatment strategies, so an individualized approach to treatment and prevention of secondary brain injury is advisable. Clinicians must use multimodal sources of data to prognosticate outcomes after cardiac arrest while recognizing that all prognostic tools have shortcomings. ESSENTIAL POINTS Neurologists should be involved in the postarrest care of patients with hypoxic-ischemic brain injury to improve their outcomes. Postarrest care requires nuanced and patient-centered approaches to the prevention and treatment of primary and secondary brain injury and neuroprognostication.
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Steinberg A, Yang Y, Fischhoff B, Callaway CW, Coppler P, Geocadin R, Silbergleit R, Meurer WJ, Ramakrishnan R, Yeatts SD, Elmer J. Clinicians' approach to predicting post-cardiac arrest outcomes for patients enrolled in a United States clinical trial. Resuscitation 2024; 199:110226. [PMID: 38685376 DOI: 10.1016/j.resuscitation.2024.110226] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2024] [Revised: 04/16/2024] [Accepted: 04/20/2024] [Indexed: 05/02/2024]
Abstract
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.
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Affiliation(s)
- Alexis Steinberg
- Department of Neurology, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA; Department of Critical Care Medicine, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA; Department of Emergency Medicine, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA.
| | - Yanran Yang
- Department of Engineering and Public Policy, Carnegie Mellon University, Pittsburgh, PA; Global Health Research Center, Duke Kunshan University, Suzhou, China
| | - Baruch Fischhoff
- Department of Engineering and Public Policy, Carnegie Mellon University, Pittsburgh, PA; Institute for Politics and Strategy, Carnegie Mellon University, Pittsburgh, PA, USA
| | - Clifton W Callaway
- Department of Emergency Medicine, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | - Patrick Coppler
- Department of Emergency Medicine, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | - Romergryko Geocadin
- Department of Neurology, Neurosurgery, Anesthesiology-Critical Care Medicine, Johns Hopkins University, Baltimore, MD. USA
| | - Robert Silbergleit
- Department of Emergency Medicine, University of Michigan, Ann Arbor, MI. USA
| | - William J Meurer
- Department of Emergency Medicine, University of Michigan, Ann Arbor, MI. USA; Department of Neurology, University of Michigan, Ann Arbor, MI. USA
| | - Ramesh Ramakrishnan
- Department of Public Health Sciences, Medical University of South Carolina, Charleston, SC. USA
| | - Sharon D Yeatts
- Department of Public Health Sciences, Medical University of South Carolina, Charleston, SC. USA
| | - Jonathan Elmer
- Department of Neurology, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA; Department of Critical Care Medicine, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA; Department of Emergency Medicine, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
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Sultanian P, Lundgren P, Louca A, Andersson E, Djärv T, Hessulf F, Henningsson A, Martinsson A, Nordberg P, Piasecki A, Gupta V, Mandalenakis Z, Taha A, Redfors B, Herlitz J, Rawshani A. Prediction of survival in out-of-hospital cardiac arrest: the updated Swedish cardiac arrest risk score (SCARS) model. EUROPEAN HEART JOURNAL. DIGITAL HEALTH 2024; 5:270-277. [PMID: 38774371 PMCID: PMC11104459 DOI: 10.1093/ehjdh/ztae016] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 12/28/2023] [Revised: 01/28/2024] [Accepted: 02/08/2024] [Indexed: 05/24/2024]
Abstract
Aims Out-of-hospital cardiac arrest (OHCA) is a major health concern worldwide. Although one-third of all patients achieve a return of spontaneous circulation and may undergo a difficult period in the intensive care unit, only 1 in 10 survive. This study aims to improve our previously developed machine learning model for early prognostication of survival in OHCA. Methods and results We studied all cases registered in the Swedish Cardiopulmonary Resuscitation Registry during 2010 and 2020 (n = 55 615). We compared the predictive performance of extreme gradient boosting (XGB), light gradient boosting machine (LightGBM), logistic regression, CatBoost, random forest, and TabNet. For each framework, we developed models that optimized (i) a weighted F1 score to penalize models that yielded more false negatives and (ii) a precision-recall area under the curve (PR AUC). LightGBM assigned higher importance values to a larger set of variables, while XGB made predictions using fewer predictors. The area under the curve receiver operating characteristic (AUC ROC) scores for LightGBM were 0.958 (optimized for weighted F1) and 0.961 (optimized for a PR AUC), while for XGB, the scores were 0.958 and 0.960, respectively. The calibration plots showed a subtle underestimation of survival for LightGBM, contrasting with a mild overestimation for XGB models. In the crucial range of 0-10% likelihood of survival, the XGB model, optimized with the PR AUC, emerged as a clinically safe model. Conclusion We improved our previous prediction model by creating a parsimonious model with an AUC ROC at 0.96, with excellent calibration and no apparent risk of underestimating survival in the critical probability range (0-10%). The model is available at www.gocares.se.
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Affiliation(s)
- Pedram Sultanian
- Department of Molecular and Clinical Medicine, Institute of Medicine, University of Gothenburg, Wallenberg Laboratory, Blå stråket 5, staircase H, Sahlgrenska University Hospital, 413 45 Gothenburg, Sweden
| | - Peter Lundgren
- Department of Molecular and Clinical Medicine, Institute of Medicine, University of Gothenburg, Wallenberg Laboratory, Blå stråket 5, staircase H, Sahlgrenska University Hospital, 413 45 Gothenburg, Sweden
- Department of Cardiology, Sahlgrenska University Hospital, Blå stråket 5, Västra Götalands län, 413 45 Gothenburg, Sweden
| | - Antros Louca
- Department of Molecular and Clinical Medicine, Institute of Medicine, University of Gothenburg, Wallenberg Laboratory, Blå stråket 5, staircase H, Sahlgrenska University Hospital, 413 45 Gothenburg, Sweden
| | - Erik Andersson
- Department of Molecular and Clinical Medicine, Institute of Medicine, University of Gothenburg, Wallenberg Laboratory, Blå stråket 5, staircase H, Sahlgrenska University Hospital, 413 45 Gothenburg, Sweden
| | - Therese Djärv
- Department of Clinical Medicine, Medicine Solna, Karolinska Institutet, Framstegsgatan, 171 64 Solna, Sweden
| | - Fredrik Hessulf
- Department of Anesthesiology and Intensive Care, Sahlgrenska University Hospital, Blå stråket 5, 413 45 Gothenburg, Sweden
- Department of Anaesthesiology and Intensive Care, Institute of Clinical Sciences, Sahlgrenska Academy, University of Gothenburg, Blå stråket 5, 413 45 Gothenburg, Sweden
| | - Anna Henningsson
- Department of Anesthesiology and Intensive Care, Sahlgrenska University Hospital, Blå stråket 5, 413 45 Gothenburg, Sweden
- Department of Anaesthesiology and Intensive Care, Institute of Clinical Sciences, Sahlgrenska Academy, University of Gothenburg, Blå stråket 5, 413 45 Gothenburg, Sweden
| | - Andreas Martinsson
- Department of Molecular and Clinical Medicine, Institute of Medicine, University of Gothenburg, Wallenberg Laboratory, Blå stråket 5, staircase H, Sahlgrenska University Hospital, 413 45 Gothenburg, Sweden
- Department of Cardiology, Sahlgrenska University Hospital, Blå stråket 5, Västra Götalands län, 413 45 Gothenburg, Sweden
| | - Per Nordberg
- Center for Resuscitation Science, Department of Clinical Science and Education, Karolinska Institutets, Södersjukhuset, Jägargatan 20, staircase 1, 171 77 Stockholm, Sweden
- Function Perioperative Medicine and Intensive Care, Karolinska University Hospital, Tomtebodavägen 18, 171 76 Stockholm, Sweden
| | - Adam Piasecki
- Department of Anesthesiology and Intensive Care, Sahlgrenska University Hospital, Blå stråket 5, 413 45 Gothenburg, Sweden
- Department of Anaesthesiology and Intensive Care, Institute of Clinical Sciences, Sahlgrenska Academy, University of Gothenburg, Blå stråket 5, 413 45 Gothenburg, Sweden
| | - Vibha Gupta
- Department of Molecular and Clinical Medicine, Institute of Medicine, University of Gothenburg, Wallenberg Laboratory, Blå stråket 5, staircase H, Sahlgrenska University Hospital, 413 45 Gothenburg, Sweden
| | - Zacharias Mandalenakis
- Department of Molecular and Clinical Medicine, Institute of Medicine, University of Gothenburg, Wallenberg Laboratory, Blå stråket 5, staircase H, Sahlgrenska University Hospital, 413 45 Gothenburg, Sweden
- Department of Cardiology, Sahlgrenska University Hospital, Blå stråket 5, Västra Götalands län, 413 45 Gothenburg, Sweden
| | - Amar Taha
- Department of Molecular and Clinical Medicine, Institute of Medicine, University of Gothenburg, Wallenberg Laboratory, Blå stråket 5, staircase H, Sahlgrenska University Hospital, 413 45 Gothenburg, Sweden
- Department of Cardiology, Sahlgrenska University Hospital, Blå stråket 5, Västra Götalands län, 413 45 Gothenburg, Sweden
| | - Bengt Redfors
- Department of Molecular and Clinical Medicine, Institute of Medicine, University of Gothenburg, Wallenberg Laboratory, Blå stråket 5, staircase H, Sahlgrenska University Hospital, 413 45 Gothenburg, Sweden
| | - Johan Herlitz
- Department of Molecular and Clinical Medicine, Institute of Medicine, University of Gothenburg, Wallenberg Laboratory, Blå stråket 5, staircase H, Sahlgrenska University Hospital, 413 45 Gothenburg, Sweden
- The Swedish Registry for Cardiopulmonary Resuscitation, Medicinaregatan 18G, 413 90 Gothenburg, Sweden
| | - Araz Rawshani
- Department of Molecular and Clinical Medicine, Institute of Medicine, University of Gothenburg, Wallenberg Laboratory, Blå stråket 5, staircase H, Sahlgrenska University Hospital, 413 45 Gothenburg, Sweden
- Department of Cardiology, Sahlgrenska University Hospital, Blå stråket 5, Västra Götalands län, 413 45 Gothenburg, Sweden
- The Swedish Registry for Cardiopulmonary Resuscitation, Medicinaregatan 18G, 413 90 Gothenburg, Sweden
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Steinberg A, Fischhoff B. Cognitive Biases and Shared Decision Making in Acute Brain Injury. Semin Neurol 2023; 43:735-743. [PMID: 37793424 DOI: 10.1055/s-0043-1775596] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/06/2023]
Abstract
Many patients hospitalized after severe acute brain injury are comatose and require life-sustaining therapies. Some of these patients make favorable recoveries with continued intensive care, while others do not. In addition to providing medical care, clinicians must guide surrogate decision makers through high-stakes, emotionally charged decisions about whether to continue life-sustaining therapies. These consultations require clinicians first to assess a patient's likelihood of recovery given continued life-sustaining therapies (i.e., prognosticate), then to communicate that prediction to surrogates, and, finally, to elicit and interpret the patient's preferences. At each step, both clinicians and surrogates are vulnerable to flawed decision making. Clinicians can be imprecise, biased, and overconfident when prognosticating after brain injury. Surrogates can misperceive the choice and misunderstand or misrepresent a patient's wishes, which may never have been communicated clearly. These biases can undermine the ability to reach choices congruent with patients' preferences through shared decision making (SDM). Decision science has extensively studied these biases. In this article, we apply that research to improving SDM for patients who are comatose after acute brain injury. After introducing SDM and the medical context, we describe principal decision science results as they relate to neurologic prognostication and end-of-life decisions, by both clinicians and surrogates. Based on research regarding general processes that can produce imprecise, biased, and overconfident prognoses, we propose interventions that could improve SDM, supporting clinicians and surrogates in making these challenging decisions.
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Affiliation(s)
- Alexis Steinberg
- Department of Critical Care Medicine, Neurology, and Emergency Medicine, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania
| | - Baruch Fischhoff
- Department of Engineering and Public Policy, Institute for Politics and Strategy, Carnegie Mellon University, Pittsburgh, Pennsylvania
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Elmer J, Steinberg A, Callaway CW. Paucity of neuroprognostic testing after cardiac arrest in the United States. Resuscitation 2023; 188:109762. [PMID: 36924822 PMCID: PMC10293050 DOI: 10.1016/j.resuscitation.2023.109762] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2022] [Revised: 03/04/2023] [Accepted: 03/08/2023] [Indexed: 03/17/2023]
Abstract
BACKGROUND Withdrawal of life-sustaining therapies for perceived poor neurological prognosis is the most common cause of death for patients hospitalized after resuscitation from cardiac arrest. Accurate neuroprognostication is challenging and high stakes, so guidelines recommend multimodality testing. We quantified the frequency and timing with which guideline recommended diagnostics were acquired prior to in-hospital death after cardiac arrest. METHODS We performed a retrospective cohort study using the Optum® deidentified Electronic Health Record dataset for 2010 to 2021. We included in-hospital decedents admitted after resuscitation from non-traumatic cardiac arrest. We quantified the number of decedents who underwent head computed tomographic imaging, electroencephalography, somatosensory evoked potentials, brain magnetic resonance imaging, or evaluation by a neurologist, as well as the timing of these tests. RESULTS Of 34,585 included patients, median age was 66 [interquartile range 53 - 79] years and 13,609 (39%) were female. Median hospital length of stay was 0 days [0-1] days, and only 16% of deaths occurred on or after day three. Only 3,245 patients (9%) had at least one neurodiagnostic test acquired and only 1,708 (5%) were evaluated by a neurologist. The most common neurological diagnostic test to be obtained was CT imaging, acquired in 3,004 (9%) of the overall cohort. Only 852 patients (2%) of patients had at least two diagnostic modalities obtained. DISCUSSION In this retrospective cohort, we found few patients hospitalized after out-of-hospital cardiac arrest underwent guideline-recommended prognostic testing. If validated in prospective cohorts with more granular clinical information, better guideline adherence and more frequent use of multimodality neuroprognostication offer an opportunity to improve quality of post-arrest care.
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Affiliation(s)
- Jonathan Elmer
- Department of Emergency Medicine, University of Pittsburgh, Pittsburgh, PA, USA; Department of Critical Care Medicine, University of Pittsburgh, Pittsburgh, PA, USA; Department of Neurology, University of Pittsburgh, Pittsburgh, PA, USA.
| | - Alexis Steinberg
- Department of Emergency Medicine, University of Pittsburgh, Pittsburgh, PA, USA; Department of Critical Care Medicine, University of Pittsburgh, Pittsburgh, PA, USA; Department of Neurology, University of Pittsburgh, Pittsburgh, PA, USA
| | - Clifton W Callaway
- Department of Emergency Medicine, University of Pittsburgh, Pittsburgh, PA, USA
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Rajajee V, Muehlschlegel S, Wartenberg KE, Alexander SA, Busl KM, Chou SHY, Creutzfeldt CJ, Fontaine GV, Fried H, Hocker SE, Hwang DY, Kim KS, Madzar D, Mahanes D, Mainali S, Meixensberger J, Montellano F, Sakowitz OW, Weimar C, Westermaier T, Varelas PN. Guidelines for Neuroprognostication in Comatose Adult Survivors of Cardiac Arrest. Neurocrit Care 2023; 38:533-563. [PMID: 36949360 PMCID: PMC10241762 DOI: 10.1007/s12028-023-01688-3] [Citation(s) in RCA: 32] [Impact Index Per Article: 32.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/19/2023] [Accepted: 01/30/2023] [Indexed: 03/24/2023]
Abstract
BACKGROUND Among cardiac arrest survivors, about half remain comatose 72 h following return of spontaneous circulation (ROSC). Prognostication of poor neurological outcome in this population may result in withdrawal of life-sustaining therapy and death. The objective of this article is to provide recommendations on the reliability of select clinical predictors that serve as the basis of neuroprognostication and provide guidance to clinicians counseling surrogates of comatose cardiac arrest survivors. METHODS A narrative systematic review was completed using Grading of Recommendations Assessment, Development and Evaluation (GRADE) methodology. Candidate predictors, which included clinical variables and prediction models, were selected based on clinical relevance and the presence of an appropriate body of evidence. The Population, Intervention, Comparator, Outcome, Timing, Setting (PICOTS) question was framed as follows: "When counseling surrogates of comatose adult survivors of cardiac arrest, should [predictor, with time of assessment if appropriate] be considered a reliable predictor of poor functional outcome assessed at 3 months or later?" Additional full-text screening criteria were used to exclude small and lower-quality studies. Following construction of the evidence profile and summary of findings, recommendations were based on four GRADE criteria: quality of evidence, balance of desirable and undesirable consequences, values and preferences, and resource use. In addition, good practice recommendations addressed essential principles of neuroprognostication that could not be framed in PICOTS format. RESULTS Eleven candidate clinical variables and three prediction models were selected based on clinical relevance and the presence of an appropriate body of literature. A total of 72 articles met our eligibility criteria to guide recommendations. Good practice recommendations include waiting 72 h following ROSC/rewarming prior to neuroprognostication, avoiding sedation or other confounders, the use of multimodal assessment, and an extended period of observation for awakening in patients with an indeterminate prognosis, if consistent with goals of care. The bilateral absence of pupillary light response > 72 h from ROSC and the bilateral absence of N20 response on somatosensory evoked potential testing were identified as reliable predictors. Computed tomography or magnetic resonance imaging of the brain > 48 h from ROSC and electroencephalography > 72 h from ROSC were identified as moderately reliable predictors. CONCLUSIONS These guidelines provide recommendations on the reliability of predictors of poor outcome in the context of counseling surrogates of comatose survivors of cardiac arrest and suggest broad principles of neuroprognostication. Few predictors were considered reliable or moderately reliable based on the available body of evidence.
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Affiliation(s)
- Venkatakrishna Rajajee
- Departments of Neurology and Neurosurgery, 3552 Taubman Health Care Center, SPC 5338, University of Michigan, 1500 E. Medical Center Drive, Ann Arbor, MI, 48109-5338, USA.
| | - Susanne Muehlschlegel
- Departments of Neurology, Anesthesiology, and Surgery, University of Massachusetts Chan Medical School, Worcester, MA, USA
| | | | | | - Katharina M Busl
- Departments of Neurology and Neurosurgery, College of Medicine, University of Florida, Gainesville, FL, USA
| | - Sherry H Y Chou
- Department of Neurology, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
| | | | - Gabriel V Fontaine
- Departments of Pharmacy and Neurosciences, Intermountain Healthcare, Salt Lake City, UT, USA
| | - Herbert Fried
- Department of Neurosurgery, Denver Health Medical Center, Denver, CO, USA
| | - Sara E Hocker
- Department of Neurology, Mayo Clinic, Rochester, MN, USA
| | - David Y Hwang
- Department of Neurology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Keri S Kim
- Pharmacy Practice, University of Illinois, Chicago, IL, USA
| | - Dominik Madzar
- Department of Neurology, University of Erlangen, Erlangen, Germany
| | - Dea Mahanes
- Departments of Neurology and Neurosurgery, University of Virginia Health, Charlottesville, VA, USA
| | - Shraddha Mainali
- Department of Neurology, Virginia Commonwealth University, Richmond, VA, USA
| | | | | | - Oliver W Sakowitz
- Department of Neurosurgery, Neurosurgery Center Ludwigsburg-Heilbronn, Ludwigsburg, Germany
| | - Christian Weimar
- Institute of Medical Informatics, Biometry, and Epidemiology, University Hospital Essen, Essen, Germany
- BDH-Clinic Elzach, Elzach, Germany
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Rousoulioti T, Tsagari D, Giannikas CN. Parents’ New Role and Needs During the COVID-19 Educational Emergency. INTERCHANGE 2022; 53:429-455. [PMID: 35669247 PMCID: PMC9156614 DOI: 10.1007/s10780-022-09464-6] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/15/2022] [Accepted: 05/05/2022] [Indexed: 11/27/2022]
Abstract
This article contributes to the on-going discussion of parental involvement in the education of children, with emphasis on new and unfamiliar roles of parents during the COVID-19 pandemic. The case study undertaken focuses on parents of first graders who belong to non-vulnerable and vulnerable social groups, and the first-grade teachers of a public primary school in the north of Greece. Research questions address the experience of ‘parents–teachers’, the need for technological tools and the required digital literacy, as well as the impact of homeschooling on the wellbeing of the family unit. Data were collected using semi-structured individual interviews. The data analysis shows that parents of both social groups took on the role of the teacher to accommodate the learning challenges of first graders. Mothers from vulnerable groups, in particular, encountered various challenges when attempting to support their children mainly in language lessons. Regarding the use of new technologies, the pandemic found parents of both groups unprepared and unfamiliar with the process of distance education. Stress and worry were the dominant emotions from the very start of homeschooling during the early stages of the pandemic while towards the end of the first lockdown, exhaustion overwhelmed parents and pupils. The article concludes with emphasizing the importance of active parental involvement and coaching that enables parents to contribute substantially to their children’s education in emergency situations.
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Steinberg A, Hudoba C, Hwang DY, Kramer NM, Mehta AK, Muehlschlegel S, Jones CA, Besbris J. Top Ten Tips Palliative Care Clinicians Should Know About Disorders of Consciousness: A Focus on Traumatic and Anoxic Brain Injury. J Palliat Med 2022; 25:1571-1578. [PMID: 35639356 DOI: 10.1089/jpm.2022.0202] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Abstract
Palliative care (PC) teams commonly encounter patients with disorders of consciousness (DOC) following anoxic or traumatic brain injury (TBI). Primary teams may consult PC to help surrogates in making treatment choices for these patients. PC clinicians must understand the complexity of predicting neurologic outcomes, address clinical nihilism, and appropriately guide surrogates in making decisions that are concordant with patients' goals. The purpose of this article was to provide PC providers with a better understanding of caring for patients with DOC, specifically following anoxic or TBI. Many of the tips acknowledge the uncertainty of DOC and provide strategies to help tackle this dilemma.
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Affiliation(s)
- Alexis Steinberg
- Department of Critical Care Medicine, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania, USA.,Department of Neurology, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania, USA.,Department of Emergency Medicine, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania, USA
| | - Christine Hudoba
- Department of Internal Medicine, Rush University Medical Center, Chicago, Illinois, USA
| | - David Y Hwang
- Division of Neurocritical Care and Emergency Neurology, Yale School of Medicine, New Haven, Connecticut, USA
| | - Neha M Kramer
- Department of Internal Medicine, Rush University Medical Center, Chicago, Illinois, USA.,Department of Neurological Sciences, Rush University Medical Center, Chicago, Illinois, USA
| | - Ambereen K Mehta
- Palliative Care Program, Department of Medicine, Johns Hopkins Bayview Medical Center, Baltimore, Maryland, USA.,Department of Neurology, Johns Hopkins Hospital, Baltimore, Maryland, USA
| | - Susanne Muehlschlegel
- Department of Neurology, University of Massachusetts Chan Medical School, Worcester, Massachusetts, USA.,Department of Anesthesia/Critical Care, University of Massachusetts Chan Medical School, Worcester, Massachusetts, USA.,Department of Surgery, University of Massachusetts Chan Medical School, Worcester, Massachusetts, USA
| | - Christopher A Jones
- Department of Medicine and Palliative Care Program, Duke University Hospital, Durham, North Carolina, USA
| | - Jessica Besbris
- Department of Internal Medicine and Neurology, Cedars-Sinai Medical Center, Los Angeles, California, USA
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Steinberg A, Grayek E, Arnold RM, Callaway C, Fischhoff B, Krishnamurti T, Mohan D, White DB, Elmer J. Physicians' cognitive approach to prognostication after cardiac arrest. Resuscitation 2022; 173:112-121. [PMID: 35017011 PMCID: PMC8983442 DOI: 10.1016/j.resuscitation.2022.01.001] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2021] [Revised: 12/02/2021] [Accepted: 01/03/2022] [Indexed: 12/19/2022]
Abstract
OBJECTIVE Elucidate how physicians formulate a neurological prognosis after cardiac arrest and compare differences between experts and general providers. METHODS We performed semi-structured interviews with experts in post-arrest care and general physicians. We created an initial model and interview guide based on professional society guidelines. Two authors independently coded interviews based on this initial model, then identified new topics not included in it. To describe individual physicians' cognitive approach to prognostication, we created a graphical representation. We summarized these individual "mental models" into a single overall model, as well as two models stratified by expertise. RESULTS We performed 36 interviews (17 experts and 19 generalists), most of whom practice in Europe (23) or North America (12). Participants described their approach to prognosis formulation as complex and iterative, with sequential and repeated data acquisition, interpretation, and prognosis formulation. Eventually, this cycle results in a final prognosis and treatment recommendation. Commonly mentioned factors were diagnostic test performance, time from arrest, patient characteristics. Participants also discussed factors rarely discussed in prognostication research including physician and hospital characteristics. We found no substantial differences between experts and general physicians. CONCLUSION Physicians' cognitive approach to neurologic prognostication is complex and influenced by many factors, including some rarely considered in current research. Understanding these processes better could inform interventions designed to aid physicians in prognostication.
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Affiliation(s)
- Alexis Steinberg
- Department of Critical Care Medicine, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA; Department of Neurology, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA; Department of Emergency Medicine, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA.
| | - Emily Grayek
- Department of Engineering and Public Policy, Carnegie Mellon University, Pittsburgh, PA, USA
| | - Robert M Arnold
- Section of Palliative Care and Medical Ethics, Department of Medicine, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | - Clifton Callaway
- Department of Emergency Medicine, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | - Baruch Fischhoff
- Department of Engineering and Public Policy, Carnegie Mellon University, Pittsburgh, PA, USA; Institute for Politics and Strategy, Carnegie Mellon University, Pittsburgh, PA, USA
| | - Tamar Krishnamurti
- Department of General Internal Medicine, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | - Deepika Mohan
- Department of Critical Care Medicine, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA; Department of Surgery, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | - Douglas B White
- Program on Ethics and Decision Making in Critical Illness, Department of Critical Care Medicine, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | - Jonathan Elmer
- Department of Critical Care Medicine, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA; Department of Neurology, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA; Department of Emergency Medicine, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
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10
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Steinberg A, Elmer J. Public perceptions on post-cardiac arrest care and outcomes. Resuscitation 2021; 170:373-374. [PMID: 34822937 DOI: 10.1016/j.resuscitation.2021.11.011] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/05/2021] [Accepted: 11/13/2021] [Indexed: 11/26/2022]
Affiliation(s)
- Alexis Steinberg
- Department of Critical Care Medicine, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA; Department of Neurology, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA; Department of Emergency Medicine, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA.
| | - Jonathan Elmer
- Department of Critical Care Medicine, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA; Department of Neurology, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA; Department of Emergency Medicine, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA.
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Prognostication of patients in coma after cardiac arrest: Public perspectives. Resuscitation 2021; 169:4-10. [PMID: 34634358 DOI: 10.1016/j.resuscitation.2021.10.002] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2021] [Revised: 09/30/2021] [Accepted: 10/01/2021] [Indexed: 11/24/2022]
Abstract
AIM To elicit preferences for prognostic information, attitudes towards withdrawal of life-sustaining treatment (WLST) and perspectives on acceptable quality of life after post-anoxic coma within the adult general population of Germany, Italy, the Netherlands and the United States of America. METHODS A web-based survey, consisting of questions on respondent characteristics, perspectives on quality of life, communication of prognostic information, and withdrawal of life-sustaining treatment, was taken by adult respondents recruited from four countries. Statistical analysis included descriptive analysis and chi2-tests for differences between countries. RESULTS In total, 2012 respondents completed the survey. In each country, at least 84% indicated they would prefer to receive early prognostic information. If a poor outcome was predicted with some uncertainty, 37-54% of the respondents indicated that WLST was not to be allowed. A conscious state with severe physical and cognitive impairments was perceived as acceptable quality of life by 17-44% of the respondents. Clear differences between countries exist, including respondents from the U.S. being more likely to allow WLST than respondents from Germany (OR = 1.99, p < 0.001) or the Netherlands (OR = 1.74, p < 0.001) and preferring to stay alive in a conscious state with severe physical and cognitive impairments more than respondents from Italy (OR = 3.76, p < 0.001), Germany (OR = 2.21, p < 0.001), or the Netherlands (OR = 2.39, p < 0.001). CONCLUSIONS Over one-third of the respondents considered WLST unacceptable when there is any remaining prognostic uncertainty. Respondents had a more positive perspective on acceptable quality of life after coma than what is currently considered acceptable in medical literature. This indicates a need for a closer look at the practice of WLST based on prognostic information, to ensure responsible use of novel prognostic tests.
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Frequency of Withdrawal of Life-Sustaining Therapy for Perceived Poor Neurologic Prognosis. Crit Care Explor 2021; 3:e0487. [PMID: 34278317 PMCID: PMC8280080 DOI: 10.1097/cce.0000000000000487] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/28/2022] Open
Abstract
Supplemental Digital Content is available in the text. OBJECTIVES: To measure the frequency of withdrawal of life-sustaining therapy for perceived poor neurologic prognosis among decedents in hospitals of different sizes and teaching statuses. DESIGN: We performed a multicenter, retrospective cohort study. SETTING: Four large teaching hospitals, four affiliated small teaching hospitals, and nine affiliated nonteaching hospitals in the United States. PATIENTS: We included a sample of all adult inpatient decedents between August 2017 and August 2019. MEASUREMENTS AND MAIN RESULTS: We reviewed inpatient notes and categorized the immediately preceding circumstances as withdrawal of life-sustaining therapy for perceived poor neurologic prognosis, withdrawal of life-sustaining therapy for nonneurologic reasons, limitations or withholding of life support or resuscitation, cardiac death despite full treatment, or brain death. Of 2,100 patients, median age was 71 years (interquartile range, 60–81 yr), median hospital length of stay was 5 days (interquartile range, 2–11 d), and 1,326 (63%) were treated at four large teaching hospitals. Withdrawal of life-sustaining therapy for perceived poor neurologic prognosis occurred in 516 patients (25%) and was the sole contributing factor to death in 331 (15%). Withdrawal of life-sustaining therapy for perceived poor neurologic prognosis was common in all hospitals: 30% of deaths at large teaching hospitals, 19% of deaths in small teaching hospitals, and 15% of deaths at nonteaching hospitals. Withdrawal of life-sustaining therapy for perceived poor neurologic prognosis happened frequently across all hospital units. Withdrawal of life-sustaining therapy for perceived poor neurologic prognosis contributed to one in 12 deaths in patients without a primary neurologic diagnosis. After accounting for patient and hospital characteristics, significant between-hospital variability in the odds of withdrawal of life-sustaining therapy for perceived poor neurologic prognosis persisted. CONCLUSIONS: A quarter of inpatient deaths in this cohort occurred after withdrawal of life-sustaining therapy for perceived poor neurologic prognosis. The rate of withdrawal of life-sustaining therapy for perceived poor neurologic prognosis occurred commonly in all type of hospital settings. We observed significant unexplained variation in the odds of withdrawal of life-sustaining therapy for perceived poor neurologic prognosis across participating hospitals.
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Steinberg A, Elmer J. Thinking beyond our biases after in-hospital cardiac arrest patient. Resuscitation 2021; 162:420-422. [PMID: 33705804 DOI: 10.1016/j.resuscitation.2021.02.042] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/24/2021] [Accepted: 02/26/2021] [Indexed: 11/29/2022]
Affiliation(s)
- Alexis Steinberg
- Department of Neurology, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA; Department of Critical Care Medicine, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | - Jonathan Elmer
- Department of Neurology, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA; Department of Critical Care Medicine, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA; Department of Emergency Medicine, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA.
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