Testing ChatGPT ability to answer laypeople questions about cardiac arrest and cardiopulmonary resuscitation.

INTRODUCTION: Cardiac arrest leaves witnesses, survivors, and their relatives with a multitude of questions. When a young or a public figure is affected, interest around cardiac arrest and cardiopulmonary resuscitation (CPR) increases. ChatGPT allows everyone to obtain human-like responses on any topic. Due to the risks of accessing incorrect information, we assessed ChatGPT accuracy in answering laypeople questions about cardiac arrest and CPR. METHODS: We co-produced a list of 40 questions with members of Sudden Cardiac Arrest UK covering all aspects of cardiac arrest and CPR. Answers provided by ChatGPT to each question were evaluated by professionals for their accuracy, by professionals and laypeople for their relevance, clarity, comprehensiveness, and overall value on a scale from 1 (poor) to 5 (excellent), and for readability. RESULTS: ChatGPT answers received an overall positive evaluation (4.3 ± 0.7) by 14 professionals and 16 laypeople. Also, clarity (4.4 ± 0.6), relevance (4.3 ± 0.6), accuracy (4.0 ± 0.6), and comprehensiveness (4.2 ± 0.7) of answers was rated high. Professionals, however, rated overall value (4.0 ± 0.5 vs 4.6 ± 0.7; p = 0.02) and comprehensiveness (3.9 ± 0.6 vs 4.5 ± 0.7; p = 0.02) lower compared to laypeople. CPR-related answers consistently received a lower score across all parameters by professionals and laypeople. Readability was 'difficult' (median Flesch reading ease score of 34 [IQR 26-42]). CONCLUSIONS: ChatGPT provided largely accurate, relevant, and comprehensive answers to questions about cardiac arrest commonly asked by survivors, their relatives, and lay rescuers, except CPR-related answers that received the lowest scores. Large language model will play a significant role in the future and healthcare-related content generated should be monitored.

Artificial intelligence and "the Art of Kintsugi" in Anesthesiology: ten influential papers for clinical users.

Artificial intelligence refers to the simulation of human intelligence in machines that are programmed to think like humans and mimic their actions. In the present review we chose ten influential papers from the last five years and through Kintsugi, shed the light on recent evolution of artificial intelligence in anesthesiology. A comprehensive search in in Medline, Embase, Web of Science and Scopus databases was conducted. Each author searched the databases independently and created a list of six articles that influenced their clinical practice during this period, with a focus on their area of competence. During a subsequent step, each researcher presented his own list and most cited papers were selected to create the final collection of ten articles. In recent years purely methodological works with a cryptic technology (black-box) represented by the intact and static vessel, translated to a "modern artificial intelligence" in clinical practice and comprehensibility (glass-box). The purposes of this review are to explore the ten most cited papers about artificial intelligence in anesthesiology and to understand how and when it should be integrated in clinical practice.

Understanding left ventricular diastolic dysfunction in anesthesia and intensive care patients: a glass with progressive shape change.

Left ventricular (LV) diastolic dysfunction is a commonly encountered condition and its impact on the anesthesia and the intensive care population is often underestimated. The study of the diastole is known as "diastology" and comprises four phases: isovolumetric relaxation, early filling phase, diastasis, and late filling phase. Diastolic function needs at least the same attention as systolic function, since its alteration has been associated with worse prognosis. Notwithstanding, many physicians consider the assessment of diastolic function too much complex. In this context, the latest 2016 guideline have simplified the assessment of diastolic function. In this educational review, we approach diastolic dysfunction with didactic purposes. First, we use a metaphor to consider the LV as a glass that progressively changes its shape and height along the disease course, resembling variable end-diastolic pressures and volumes at different stages while progressing with diastolic dysfunction. We guide readers in the process of diagnosis and grading of LV diastolic dysfunction, with description of pathophysiological changes in LV relaxation and consequently in the pressure gradient between the left-sided heart chambers. In the second part, starting from physiology we move towards suggestions for the clinical management of anesthesia and intensive care patients with diastolic dysfunction under different scenarios (hypo- and hypervolemia, weaning, sepsis, tachycardia and arrhythmias, right ventricular dysfunction).

The effects of exposure to severe hyperoxemia on neurological outcome and mortality after cardiac arrest.

INTRODUCTION: Hyperoxemia during cardiac arrest (CA) may increase chances of successful resuscitation. However, episodes of severe hyperoxemia after intensive care unit admission occurs frequently (up to 60%), and these have been associated with higher mortality in CA patients. The impact of severe hyperoxemia on neurological outcome is more unclear. EVIDENCE ACQUISITION: We conducted a systematic review and meta-analysis on Pubmed and EMBASE to evaluate the effects of severe hyperoxemia according to arterial blood gas analysis on neurological outcome and mortality in patients resuscitated from CA and admitted to intensive care unit. EVIDENCE SYNTHESIS: Thirteen observational studies were included, eight of them reporting data on neurological outcome and ten on mortality. Most studies reported odds ratio adjusted for confounders. Severe hyperoxemia was associated with worse neurological outcome (OR 1.37 [95%CI 1.01,1.86], P=0.04) and higher mortality at longest follow-up (OR 1.32 [95%CI 1.11,1.57], P=0.002). Subgroup analyses according to timing of hyperoxemia showed that any hyperoxemia during the first 36 hours was associated with worse neurological outcome (OR 1.52 [95%CI 1.12,2.08], P=0.008) and higher mortality (OR 1.40 [95%CI 1.18,1.66], P=0.0001), whilst early hyperoxemia was not (neurological: P=0.29; mortality: P=0.19). Sensitivity analyses mostly confirmed the results of the primary analyses. CONCLUSIONS: Severe hyperoxemia is associated with worse neurological outcome and lower survival in CA survivors admitted to intensive care unit. Clinical efforts should be made to avoid severe hyperoxemia during at least the first 36 hours after cardiac arrest.

24-Month Effectiveness of Periduoscopic Adhesiolysis in Reducing the Use of Spinal Cord Stimulation in Patient With Chronic Lumbar Pain: A Possible Therapeutic Regimen?

Objectives Epiduroscopy is a minimally invasive procedure that is used in pain therapy to treat lumbar and root pain that is resistant to medical and infiltrative therapies. The indications for periduroscopy are partly shared with those of spinal cord stimulation (SCS): failed back surgery syndrome (FBSS) and stenosis of the vertebral canal in particular. The costs and risks of periduroscopy are considerably lower than those of SCS. The purpose of this study is to evaluate the clinical and economic advantages of integrating periduroscopy as a step prior to SCS for patients with severe lumbar or radicular pain that is unresponsive to pharmacological and infiltrative treatments. Materials and Methods Patients were enrolled if they had FBSS and spinal stenosis with indications for SCS and accepted periduroscopy treatment before the possible SCS trial. Patients were followed up for 24 months with evaluations of clinical data on the day after the procedure and at one and 24 months. The pain trend, satisfaction with the periduroscopy procedure, and the incidence of SCS implants in the study period were analyzed. Results A total of 106 patients were enrolled. Immediately after the procedure and in the first month, the reduction of pain and the level of patient satisfaction were high, but they were drastically reduced at 24 months with a progressive reappearance of symptoms that substantially overlapped with the pre-surgery levels. At 24 months, 48% of the patients underwent a neurostimulation trial, and a significant percentage of them were able to avoid the implantation of an SCS. Conclusions Periduroscopy appears to be rational as a step prior to SCS in terms of the improvement of pain symptoms in the short term, the definitive results in a significant percentage of patients, and the significant economic savings for the health system.

A case of thrombotic thrombocytopenic purpura associated with COVID-19.

Acquired thrombotic thrombocytopenic purpura (TTP) is an autoimmune disease that can be triggered by different events, including viral infections. It presents as thrombotic microangiopathy and can lead to severe complications that often require management in the intensive care unit (ICU). We report a patient who presented with acquired TTP following COVID-19 infection. A 44-year-old woman presented to the emergency department with severe anemia, acute kidney injury and respiratory failure due to COVID-19. Clinical and laboratory findings were suggestive for thrombotic microangiopathy. On day 8 laboratory tests confirmed the diagnosis of acquired TTP. The patient needed 14 plasma exchanges, treatment with steroids, rituximab and caplacizumab and 18 days of mechanical ventilation. She completely recovered and was discharged home on day 51. Acquired TTP can be triggered by different events leading to immune stimulation. COVID-19 has been associated with different inflammatory and auto-immune diseases. Considering the temporal sequence and the lack of other possible causes, we suggest that COVID-19 infection could have been the triggering factor in the development of TTP. Since other similar cases have already been described, possible association between COVID and TTP deserves further investigation.

The role of artificial intelligence in surgical patient perioperative management.

Perioperative medicine is a patient-centered, multidisciplinary and integrated clinical practice that starts from the moment of contemplation of surgery until full recovery. Every perioperative phase (preoperative, intraoperative and postoperative) must be studied and planned in order to optimize the entire patient management. Perioperative optimization does not only concern a short-term outcome improvement, but it has also a strong impact on long term survival. Clinical cases variability leads to the collection and analysis of a huge amount of different data, coming from multiple sources, making perioperative management standardization very difficult. Artificial Intelligence (AI) can play a primary role in this challenge, helping human mind in perioperative practice planning and decision-making process. AI refers to the ability of a computer system to perform functions and reasoning typical of the human mind; Machine Learning (ML) could play a fundamental role in presurgical planning, during intraoperative phase and postoperative management. Perioperative medicine is the cornerstone of surgical patient management and the tools deriving from the application of AI seem very promising as a support in optimizing the management of each individual patient. Despite the increasing help that will derive from the use of AI tools, the uniqueness of the patient and the particularity of each individual clinical case will always keep the role of the human mind central in clinical and perioperative management. The role of the physician, who must analyze the outputs provided by AI by following his own experience and knowledge, remains and will always be essential.