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Cardiopulmonary Arrest

Cardiopulmonary Arrest: A sudden cessation of cardiac pumping function and breathing, often leading to loss of consciousness.
It is critical to restore blood flow and oxygenation quickly to prevent irreversible brain damage or death.
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Most cited protocols related to «Cardiopulmonary Arrest»

1
ICU Mechanical Ventilation Recovery

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Publication 2009
Adult Cardiopulmonary Arrest Ethics Committees, Research Mechanical Ventilation Neuromuscular Diseases Patients
2
Validating Sudden Cardiac Events
Medical records were reviewed independently by a doctorally trained clinical pharmacist (C.E.L.) and by a specially trained public health researcher (C.P.F.), both of whom had prior experience examining the validity of this outcome.11 (link),20 (link) Reviewers used a structured electronic abstraction form to record: (a) clinical documentation of SD, cardiac arrest, or cardio-respiratory arrest; (b) clinical documentation of VA; (c) documentation of the event on electrocardiogram (ECG) reports or mention of ECG evidence; (d) evidence of an outpatient witnessed sudden collapse or person found dead in the field; (e) initial presentation with signs or symptoms suggestive of VA (e.g., near-syncope, palpitations, dizziness, sweating); (f) inpatient telemetry readings and electrophysiology study (EPS) reports; (g) the location of the event's onset (i.e., inpatient vs. ED vs. prior to ED); and (h) documentation of non-physiologic, extrinsic causes precipitating the event (e.g., motor vehicle accident, blunt trauma).
The validation criterion, adapted from one used by Ray et al.,13 (link) was a clinician-diagnosed SD, cardiac arrest, cardiorespiratory arrest, or VA as evidenced by a verbatim statement within the medical record, excluding the coder's face sheet. In addition, documentation of an outpatient witnessed sudden collapse, or a person found dead or unconscious in the field with evidence that the individual had been alive in the prior 24 hours, met the validation criterion. Events identified by clinicians after admission did not meet the criterion unless the person presented to the hospital with signs or symptoms suggestive of VA (e.g., near-syncope, palpitations, dizziness, sweating), plus either (1) ventricular fibrillation or sustained ventricular tachycardia was evidenced on telemetry or (2) an EPS was reported as either positive or demonstrating a sustained or sustainable ventricular tachycardia or fibrillation. Events precipitated by a non-physiologic, extrinsic cause (e.g., blunt trauma) did not meet the outcome criterion regardless of elements met above.
Initial inter-rater agreement was assessed by the per cent initial agreement and Cohen's κ regarding whether the record met the validation criterion. When reviewers disagreed initially, they then attempted to resolve disagreements by consensus. When consensus could not be reached, the record was referred to a third reviewer (S.H.), a doctorally trained clinical pharmacist, to break the tie.
Hennessy S., Leonard C.E., Freeman C.P., Deo R., Newcomb C., Kimmel S.E., Strom B.L, & Bilker W.B. (2010). Validation of diagnostic codes for outpatient-originating sudden cardiac death and ventricular arrhythmia in Medicaid and Medicare claims data. Pharmacoepidemiology and drug safety, 19(6), 555-562.
Publication 2010
Cardiac Arrest Cardiopulmonary Arrest Clinical Pharmacists Electrocardiogram Electrophysiologic Study, Cardiac Face Inpatient Nonpenetrating Wounds Outpatients physiology Presyncope Shock Tachycardia, Ventricular Telemetry Traffic Accidents Ventricular Fibrillation
3
Evaluating Mobility Outcomes in ICU Patients
We collected detailed information at initial hospitalization and ICU discharge. We also collected data regarding independent gait ability upon hospital discharge. All data were obtained as a usual clinical practice.
Information at admission included age, sex, body weight, body mass index (BMI), main cause of ICU admission, Charlson’s Comorbidity Index (CCI) [20 (link)], Acute Physiology and Chronic Health Evaluation (APACHE) II score [21 (link)], and the Sequential Organ Failure Assessment (SOFA) score [22 (link)]. Data during ICU stay included the time to first rehabilitation assessment, duration of mechanical ventilation, time to first out-of-bed mobilization, and highest score achieved on the ICU-mobility scale (IMS) [23 (link)]. We also investigated the incidence of adverse events during rehabilitation, such as cardiopulmonary arrest, fall to knees or the ground, inadvertent removal of medical devices, desaturation (< 90%) or more than 10% decrease from the baseline, bradypnea (< 5 breaths/min), tachypnea (> 40 breaths/min), bradycardia (< 40 beats/min), tachycardia (> 130 beats/min), hypotension (systolic blood pressure [SBP] < 80 mmHg), hypertension (SBP > 200 mmHg), and newly occurring arrhythmia. At ICU discharge, we collected incidence of ICU-acquired weakness (ICU-AW) and delirium, respectively. As mentioned above, early mobilization was performed according to the previous protocol [19 (link)] consisted with five session levels (see Appendix 1). We investigated the number of times levels 3, 4, and 5 were achieved, and total number of times levels higher than level 2 were achieved. We calculated ICU length of stay at ICU discharge, and hospital length of stay and ratio of home discharge at hospital discharge.
The IMS provides a quick and simple bedside method of measuring the mobility of a critically ill patient. As functional endpoints in studies of rehabilitation in the ICU, the IMS provides a sensitive 11-point ordinal scale, ranging from nothing (lying/passive exercises in bed, score of 0) to independent ambulation (score of 10). ICU-AW was evaluated using Medical Research Council (MRC) sum-score by the responsible physical therapist, and a value of less than 48 was defined as having developed an ICU-AW [24 (link), 25 (link)]. The cooperation-level assessment was carried out, and muscle strength tests were only performed when the subject correctly answered the five questions [26 (link)]. For the assessment of delirium, either the delirium screening tool of the Confusion Assessment Method for the Intensive Care Unit (CAM-ICU) [27 (link)] or the Intensive Care Delirium Screening Checklist (ICDSC) [28 (link)] was used according to the usual practice of each participating hospital. Outcomes other than home discharge included transfers to rehabilitation hospitals and to nursing homes.
Patients who could walk 45 m or more with or without braces were determined as gait independent. We also used mobility scale of the Barthel Index (BI) to quantitatively assess gait independence [18 (link), 29 (link)]. BI is the most widely used ADL scale, and its reliability and relevance have been recognized [30 (link)]. Because we previously determined BI was an effective mobility parameter to assess the achievement of gait independence [31 ], we used this parameter in the current study. BI was measured at ICU and hospital discharge.
Watanabe S., Kotani T., Taito S., Ota K., Ishii K., Ono M., Katsukawa H., Kozu R., Morita Y., Arakawa R, & Suzuki S. (2019). Determinants of gait independence after mechanical ventilation in the intensive care unit: a Japanese multicenter retrospective exploratory cohort study. Journal of Intensive Care, 7, 53.
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Publication 2019
Asthenia Body Weight Braces Cardiac Arrhythmia Cardiopulmonary Arrest Critical Illness Delirium Device Removal Early Mobilization High Blood Pressures Hospitalization Index, Body Mass Intensive Care Knee Mechanical Ventilation Muscle Strength Patient Discharge Patients Physical Therapist physiology Range of Motion, Articular Rehabilitation Systolic Pressure
4
Bedside PEWS Score for Predicting Deterioration
Clinical data were grouped into 1-hour blocks for 24 hours ending at the event for case patients or at the end of 12 hours of data collection for control patients. Where there were missing data, the most recent recorded data were used, consistent with the approach used for other scores in critically ill children [21 (link)]. The greatest subscore for each item within each hour was identified and used to calculate the Bedside PEWS score for that hour. We then calculated the maximum PEWS score for the 12 hours ending 1 hour before the clinical deterioration event and in the six 4-hour blocks preceding ICU admission in patients urgently admitted to the ICU.
The primary analysis evaluated the hypothesis that the Bedside PEWS score can identify children at risk for cardiopulmonary arrest with at least one hour's notice. Logistic regression was used to compare the maximum Bedside PEWS score of case and control patients using all 12 hours of data in control patients and the 12 hours of data ending 1 hour before either urgent ICU admission or a code blue event in the case patients. The AUCROC curve was determined from the c-statistic calculated by logistic regression, and the 95% confidence interval (95% CI) was calculated using an accepted algorithm [22 ]. The ROC curve was represented graphically, and the sensitivity and specificity of the score at thresholds of 7 and 8 were calculated based on our previous work [6 (link)].
Repeated measures linear regression was used to evaluate the temporal evolution of scores preceding urgent ICU admission and code blue events in case patients. The dependent variable was the maximum Bedside PEWS score for each of the six 4-hour time periods preceding the clinical deterioration event. The independent variable was the midpoint of the time interval expressed in hours from the time of ICU admission. Linear regression was used to evaluate the relationships between the maximum Bedside PEWS score and the number of risk factors for cardiac arrest. Separate analyses were performed for case and control patients.
The association between the retrospective rating of nurses and the case or control status of patients was evaluated using logistic regression. We used clinical data from the 12 hours ending 1 hour before the clinical deterioration event and for 12 hours in control patients to calculate the maximum Bedside PEWS score. These data were paired with corresponding survey data from frontline nurses. When more than one nurse was surveyed in this time period, we used the data from the nurse who had last cared for the patient. The responses of the frontline nurses were represented on a numerical scale from 1 to 5. We tabulated the maximum Bedside PEWS score for each level of nurse rating in case and control patients. Logistic regression was used to evaluate the performance of nurse rating, the Bedside PEWS score, and the nurse rating with the Bedside PEWS score. We used the c-statistic as a measure of the AUCROC curve and calculated the 95% CI. Comparison of the AUCROC curve for the nurse rating and the maximum Bedside PEWS score was carried out as described by DeLong et al. [23 (link)].
Subgroup analyses described score performance in the following patient categories: urgent ICU patients, code blue patients, those who fell within any of the five age categories of the Bedside PEWS score, across institutions, patients with chronic conditions (bone marrow or organ transplantation, cardiac disease, severe cerebral palsy), patients with medical devices that might have place them at increased risk (tracheostomy, enterostomy feeding device, home oxygen), patients with acute illness (diabetic ketoacidosis, seizures), patients whose conditions had increased complexity (> 3 services involved in care, > 10 medications), patients with an administrative risk (recent transfer of primary service, ICU transfer, postoperative, off-service patient), and patients who had cardiopulmonary arrest. Power calculations based on our previous work suggested that differences between means could be shown with 30 patients per group. Given that our objectives were to evaluate score performance within specified subgroups and at each hospital, we sought to maximise the numbers of cases and controls from participating hospitals. Numbers were thus determined by the duration of the study at each hospital. The protocol was reviewed and approved by the research ethics boards at participating hospitals. All research ethics boards required consent for staff participation in the surveys and waived the need for patient consent.
Parshuram C.S., Duncan H.P., Joffe A.R., Farrell C.A., Lacroix J.R., Middaugh K.L., Hutchison J.S., Wensley D., Blanchard N., Beyene J, & Parkin P.C. (2011). Multicentre validation of the bedside paediatric early warning system score: a severity of illness score to detect evolving critical illness in hospitalised children. Critical Care, 15(4), R184.
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Publication 2011
Biological Evolution Bone Marrow Cardiac Arrest Cardiopulmonary Arrest Cerebral Palsy Child Chronic Condition Clinical Deterioration Code Blue Critical Illness Diabetic Ketoacidosis Enterostomy Heart Diseases Medical Devices Nurses Organ Transplantation Oxygen Patient Admission Patients Pharmaceutical Preparations Seizures Tracheostomy
5
Racial Disparities in Cardiac Arrest Outcomes
The primary independent variable was patient race. Patient factors collected other than race included demographics (age and sex), initial cardiac rhythm, and comorbidities or medical conditions present prior to cardiac arrest (congestive heart failure, myocardial infarction, or diabetes mellitus; renal, hepatic, or respiratory insufficiency; baseline evidence of motor, cognitive, or functional deficits [central nervous system depression]; acute stroke; pneumonia; hypotension; sepsis; major trauma; and requirement for hemodialysis).
Hospital factors collected included the hospital’s geographic region, licensed bed volume (<250, 250–499, ≥500 inpatient beds), and academic training program status (no training program, residency program only, residency and fellowship programs). Hospital process variables included the use of a hospitalwide cardiopulmonary arrest alert, use of an organized hospital code team, defibrillation time, time of cardiac arrest (work hours: 8 am to 5 pm; after hours: 5 pm to 8 am or weekend), and cardiac arrest location (not monitored, telemetry, or intensive care unit [ICU]). Time to defibrillation was evaluated as both a continuous and categorical variable (delayed, >2 minutes vs not delayed, ≤2 minutes) based on current guidelines.10 (link),11 (link)
Chan P.S., Nichol G., Krumholz H.M., Spertus J.A., Jones P.G., Peterson E.D., Rathore S.S, & Nallamothu B.K. (2009). Racial Differences in Survival After In-Hospital Cardiac Arrest. JAMA : the journal of the American Medical Association, 302(11), 1195-1201.
Publication 2009
Academic Training Acute Cerebrovascular Accidents Cardiac Arrest Cardiopulmonary Arrest Central Nervous System Code Team Cognition Congestive Heart Failure Diabetes Mellitus Electric Countershock Fellowships Heart Hemodialysis Inpatient Kidney Myocardial Infarction Patients Pneumonia Residency Respiratory Failure Septicemia Telemetry Training Programs Wounds and Injuries

Most recents protocols related to «Cardiopulmonary Arrest»

1
Prone Positioning in COVID-19 ARDS
The following data were collected: demographic information, comorbidities, complications, D-dimer level, Simplified Acute Physiology Score (SAPS III), Sequential Organ Failure Assessment (SOFA) score, PaO2/FiO2 ratio, Body Mass Index (BMI), comorbidities, and use of anticoagulants and vasopressors. SAPS III and SOFA scores considered for analysis were calculated at the Intensive Care Unit (ICU) admission. D-dimer levels were evaluated using the HemosIL HS-500 automated immunoassay (HemosIL® D-dimer HS 500, Instrumentation Laboratory, 80003610270, Instrumental Laboratory Company, Bedford, MA, USA).
Comorbidities were assessed, including immunosuppression, arterial hypertension, diabetes, obesity, smoking, alcohol consumption, and neurological, hematological, respiratory, and cardiovascular diseases. Furthermore, immunosuppression was defined as a history of organ transplantation, chronic kidney disease, HIV infection, AIDS, and cancer treatment.
Clinical data included arterial blood gas analysis before and after the first prone session. In addition, the time until the first prone positioning, duration of the first prone session (in hours), number of prone sessions, and complications related to prone positioning were also collected. The time between the first intubation and the prone session was considered the first prone position. Unfortunately, due to hospital bed overload, it was impossible to collect data for blood gas analysis from the health staff on time. Therefore, the data considered for the analysis were obtained closest to the beginning and end of the first prone session.
Ventilator settings and respiratory mechanics calculations, such as Driving Pressure (DP), Plateau Pressure (Pplat), and respiratory system static Compliance (Cst), were collected before and after the first prone session. The total duration of the first prone session and a number of prone cycles were recorded. Furthermore, adverse effects, such as decreased oxygenation level, accidental extubation, central venous or arterial line removal, hemodynamic instability, acute arrhythmia, cardiopulmonary arrest, and vomiting, were recorded. Patient outcomes, including duration of invasive mechanical ventilation, length of hospital and ICU stay, reintubation, and survival, were also recorded.
Cunha M.C., Schardong J., Righi N.C., Lunardi A.C., Sant'Anna G.N., Isensee L.P., Xavier R.F., Pompeu J.E., Weigert R.M., Matte D.L., Cardoso R.A., Abras A.C., Silva A.M., Dorneles C.C., Werle R.W., Starke A.C., Ferreira J.C., Plentz R.D, & Carvalho C.R. (2023). Aging-related predictive factors for oxygenation improvement and mortality in COVID-19 and acute respiratory distress syndrome (ARDS) patients exposed to prone position: A multicenter cohort study. Clinics, 78, 100180.
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Publication 2023
Accidents Acquired Immunodeficiency Syndrome Anticoagulants Arterial Lines Arteries BLOOD Blood Gas Analysis Cardiac Arrhythmia Cardiopulmonary Arrest Cardiovascular Diseases Chronic Kidney Diseases Diabetes Mellitus fibrin fragment D Hemodynamics High Blood Pressures HIV Infections Immunoassay Immunosuppression Index, Body Mass Intubation Malignant Neoplasms Mechanical Ventilation Obesity Organ Transplantation Patients Pressure Respiratory Depression Respiratory Mechanics Respiratory Rate Respiratory System Tracheal Extubation Vasoconstrictor Agents Veins
2
Assessing Hepatorenal Syndrome in Cirrhosis
Approval for this study was obtained from the University of Southern California Institutional Review Board (HS-12-00383). Procedures were followed in accordance with the ethical standards of the University of Southern California Institutional Review Board and with the Declaration of Helsinki of 1975, as revised in 2000. Written informed consent was not required for the ultrasound procedure since this was performed for clinical purposes, as was subsequent volume management, and data collection was retrospective.
Adult patients hospitalized between 1 August 2012 and 28 February 2020, with AKI, cirrhosis and ascites, who had an IVC US performed, were evaluated for HRS-AKI defined by current criteria [1 ]. Eighty-three patients were retrieved from the daily renal consult rounding lists of the primary investigator (Figure 1). Initial exclusion criteria adapted from the Practice Guidelines by the American Association for the Study of Liver Diseases [1 ] included documentation of potential causes of AKI other than HRS-AKI such as: (1) recent cardiopulmonary arrest, hypotension with vasopressor support, (2) current or recent use of nephrotoxic agents, (3) evidence of glomerulonephritis or interstitial nephritis, and/or (4) urinary tract obstruction. Other exclusion criteria included: (5) IVC thrombosis, (6) CKD stage 4 or 5 or maintenance dialysis therapy prior to or at the time of IVC US, (7) preexisting acute decompensated heart failure or severe cardiac valvular disease, which may alter IVC US findings [10 (link)] and also impair renal function, and/or (8) patients who had not received the standardized albumin administration and diuretic withdrawal prior to the IVC US. Thirty one patients were excluded based on these criteria.
The remaining 52 patients without exclusion criteria clearly documented on the rounding lists were further evaluated by detailed chart review for the presence of any of the above listed plus additional exclusion criteria (Figure 1). Thirty-two more patients were excluded due to these exclusion criteria: (1) follow-up for <3 days after the IVC US since they may not have had time to receive or respond to the volume management recommendations, (2) had recently received hemodialysis therapy, (3) did not have a documented baseline serum creatinine value, (4) had urinary retention documented by bladder catheterization, and/or (5) had tense ascites and IAH with bladder pressures >12 mmHg [6 (link)].
The remaining 20 patients also had to have a persistent increase in serum creatinine of ≥ 0.3 mg/dL within 2 days of onset of AKI or alternately an increase in serum creatinine of ≥50% from a baseline value documented within the prior 90 days, and failure of serum creatinine to persistently decrease ≥0.3 mg/dL after at least 2 days of diuretic withdrawal and a trial of volume expansion with albumin (1 g/kg of body weight per day to a maximum of 100 g/day) [1 ]. These 20 patients, who met the above criteria for HRS-AKI (Figure 1) and had received volume expansion and diuretic withdrawal prior to the IVC US examination, had been presumed to be intravascularly replete by the primary team.
Kaptein E.M., Oo Z, & Kaptein M.J. (2023). Hepatorenal syndrome misdiagnosis may be reduced using inferior vena cava ultrasound to assess intravascular volume and guide management. Renal Failure, 45(1), 2185468.
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Publication 2023
Adult Albumins Ascites Body Weight Cardiopulmonary Arrest Creatinine Dialysis Diuretics Ethics Committees, Research Glomerulonephritis Heart Failure Hemodialysis Kidney Liver Cirrhosis Liver Diseases Nephritis, Interstitial Patients Serum Therapeutics Thrombosis Ultrasonography Urinary Bladder Urinary Catheterization Urinary Tract Valve Disease, Heart Vasoconstrictor Agents
3
Emergency Medical Care Availability in Japan
The Emergency Medicine System (EMS) in Japan is run by local governments and available to everyone who needs emergency transport to a hospital without any direct payment. After an ambulance is called to pick up a patient, the EMS needs to find an accepting hospital that can provide optimal care in the area. With the exception of a few areas, such as Tokyo, there are no systematic regulations that prevent ambulance diversion and each hospital can decide to accept the patient based on capacity and capability. Sometimes multiple phone calls are required to find an accepting hospital.
Currently, there are 265 level-three emergency care centres (EC3s) (designated critical care hospitals) in Japan to accept severely ill or injured patients due to stroke, acute myocardial infarction, cardiopulmonary arrest, trauma, etc. A hospital must meet certain criteria to be appointed as an EC3. The availability of on-call psychiatrists is one of the evaluation items for the EC3 assessed by Ministry of Health, Labour, and Welfare. However, it is not a mandatory requirement and a lack of psychiatric service does not automatically indicate the loss of credentials for EC3. In this study, we defined high-level emergency care centres as EC3.
MSPHs have medical and surgical specialists for physical diseases as well as psychiatrists for psychiatric issues. However, medical resources at these facilities may be limited compared with EC3s.
Chiba T., Takaku R., Ito E., Tamune H., Rivera M., Ikeda S, & Shiga T. (2023). Are hospitals with both medical/surgical and psychiatric services associated with decreased difficulty in ambulance transfer for patients with self-harm behaviour? A nationwide retrospective observational study using ambulance transfer data in Japan. BMJ Open, 13(2), e065466.
Publication 2023
Ambulance Diversion Ambulances Cardiopulmonary Arrest Cerebrovascular Accident Critical Care Emergencies Myocardial Infarction Operative Surgical Procedures Patients Physical Examination Psychiatrist Service, Emergency Medical Specialists Wounds and Injuries
4
Acute Respiratory Failure in AIDS Patients
Consecutive AIDS patients with ARF admitted to the ICU or the Center for Infectious Diseases, Beijing Ditan Hospital, from April 2019 to March 2022, were screened daily. All enrolled patients in this study were inpatients infected with HIV and were considered to have AIDS as defined by the Centers for Disease Control and Prevention classification system for HIV infection [19 (link)]. A newly diagnosed HIV infection was diagnosed within two months before ICU admission and had not received HAART. If patients at the Center for Infectious Diseases met the inclusion criteria, they would transfer to the ICU. ARF was defined as the onset of respiratory symptoms within 72 h before enrollment, a ratio of the partial pressure of arterial oxygen to the fraction of inspired oxygen (PaO2/ FiO2) ≤ 300 mmHg or PaO2 ≤ 60 mmHg with partial pressure on air with arterial carbon dioxide (PaCO2) ≤ 50 mmHg and symptoms of respiratory distress (tachypnea > 25/min, labored breathing, and dyspnea at rest). In addition to ARF, the inclusion criteria were being between 18 to 70 and being willing to accept endotracheal intubation if needed.
Exclusion criteria were impending cardiopulmonary arrest, a disorder of consciousness, absence of airway protective gag reflex, upper airway obstruction, pregnancy or breastfeeding, other organ failures apart from ARF, consent withdrawal, used immunosuppressant, and enrolment in other research protocols. ARF caused by pneumothorax or massive pleural effusion, acute exacerbation of chronic lung disease, cardiogenic pulmonary edema, and central nervous system lesions were also excluded.
Hao J., Liu J., Pu L., Li C., Zhang M., Tan J., Wang H., Yin N., Sun Y., Liu Y., Guo H, & Li A. (2023). High-Flow Nasal Cannula Oxygen Therapy versus Non-Invasive Ventilation in AIDS Patients with Acute Respiratory Failure: A Randomized Controlled Trial. Journal of Clinical Medicine, 12(4), 1679.
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Publication 2023
Acquired Immunodeficiency Syndrome Acute Disease Airway Obstruction Antiretroviral Therapy, Highly Active Arteries Carbon dioxide Cardiopulmonary Arrest Central Nervous System Communicable Diseases Consciousness Disorders HIV Infections Immunosuppressive Agents Inpatient Intubation, Intratracheal Lung Oxygen Partial Pressure Patients Pleural Effusion Pneumothorax Pregnancy Pulmonary Edema Signs and Symptoms, Respiratory
5
Prehospital Evaluation of ACVD Patients
Recruitment was carried out back-to-back, considering adult patients (>18 years old) with a prehospital diagnosis of ACVD who were transferred to an ED by ambulance. Without exception, all patients included in this study were evaluated on-scene by an ALS and, following evaluation, the ALS physician either decided on no transfer (discharge on site), or alternatively that the case required emergency transfer to an ED, either by a BLS or an ALS. Minors, end-stage patients (documented by a specialist report), non-recovered cardiorespiratory arrest, pregnant women (at any period of gestation), cases where it was not possible to obtain prehospital analysis and patients without informed consent were excluded.
Castro Portillo E., López-Izquierdo R., Castro Villamor M.A., Sanz-García A., Martín-Conty J.L., Polonio-López B., Sánchez-Soberón I., del Pozo Vegas C., Durantez-Fernández C., Conty-Serrano R, & Martín-Rodríguez F. (2023). Modified Sequential Organ Failure Assessment Score vs. Early Warning Scores in Prehospital Care to Predict Major Adverse Cardiac Events in Acute Cardiovascular Disease. Journal of Cardiovascular Development and Disease, 10(2), 88.
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Publication 2023
Adult Ambulances Cardiopulmonary Arrest Diagnosis Emergencies Patient Discharge Patients Physicians Pregnancy Pregnant Women

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More about "Cardiopulmonary Arrest"

Cardiopulmonary arrest, also known as sudden cardiac arrest or sudden cardiac death, is a life-threatening condition characterized by the abrupt loss of heart function and breathing.
It occurs when the heart suddenly stops pumping blood effectively, leading to a lack of oxygen supply to the brain and vital organs.
This critical situation requires immediate intervention to restore blood flow and oxygenation and prevent irreversible brain damage or death.
Accurate research protocols are crucial for improving outcomes in cardiopulmonary arrest.
Leveraging the power of AI, platforms like PubCompare.ai can help researchers locate the best evidence-based approaches from the literature, preprints, and patents.
This enhances the reproducibility and accuracy of research, ultimately leading to better patient outcomes.
When conducting research on cardiopulmonary arrest, researchers may utilize various tools and software, such as RealTime HIV-1 RNA PCR for genetic analysis, SPSS version 15.0 and Stata Statistical Software for data analysis, Research Electronic Data Capture (REDCap) for electronic data capture, SAS 9.4 for statistical modeling, and Excel 2007 for data management.
Additionally, techniques like the use of a 16-G catheter may be employed in clinical studies.
By leveraging the power of AI and incorporating a comprehensive understanding of the related terms, abbreviations, and key subtopics, researchers can optimize their cardiopulmonary arrest research protocols and enhance the overall quality and impact of their work.
This holistic approach, combined with the use of cutting-edge tools and software, can significantly contribute to the advancement of our understanding and treatment of this critical medical condition.