scholarly journals The Surgical Safety Huddle: Novel Quality Improvement Patient Safety Initiative

2021 ◽  
pp. 66-77
Author(s):  
Carolyn Cullinane ◽  
Catharina Healy ◽  
Mary Doyle ◽  
Helen McCarthy ◽  
Claire Costigan ◽  
...  
Keyword(s):  
Cardiac Arrest ◽  
Quality Improvement ◽  
Early Recognition ◽  
University Teaching ◽  
Early Warning Score ◽  
Surgical Safety ◽  
Poor Outcome ◽  
Surgical Ward ◽  
Deteriorating Patient ◽  
Poor Outcomes

Background: Acutely deteriorating patients are entitled to the best possible care which includes early recognition and timely appropriate intervention to reduce adverse events, unnecessary admissions to intensive care and/or cardiac arrest. Aim: To reduce the number of poor outcomes for surgical patients with a National Early Warning Score (NEWS) score ≥7 in our institution by 50%. A poor outcome was defined as: 1. Cardiac arrest 2. NEWS >7 not improving after 72 hours 3. Transfer to ICU >6 hours Methods: Surgical inpatients from a variety of surgical specialties (general, vascular, breast, colorectal, hepatobiliary, and plastic surgery) in a large university teaching hospital were included. Quality improvement tools were used to generate regular dialogue with the clinical teams, resulting in the concept of the surgical safety huddle being proposed. Deteriorating patients were highlighted at the daily huddle and a plan of early intervention was implemented. An incremental approach with continuous PDSA [Plan- Do-Study-Act] cycles and subsequent feedback was adopted on the surgical ward to develop the huddle. Poor patient outcomes were analysed prospectively via chart reviews. Results: Prior to the introduction of the “surgical huddle” 110 patients with NEWS >7 were audited. Twenty-eight of these patients had a poor outcome at 72 hours (25%). Following the introduction of the surgical huddle supported by the deteriorating patient team, 64 patients with NEWS >7 were reviewed. Three of these patients had a poor outcome at 72 hours (4.7%). The introduction of the surgical huddle increased the interval between cardiac arrests more than sixfold on the surgical ward. Discussion: The introduction of the surgical safety huddle supported by the deteriorating patient response team reduced the number of cardiac arrests and poor outcomes in a surgical inpatient cohort.

Abstract 3752: Performance Of Color ADC Maps As A Prognostic Tool In Comatose Post-cardiac Arrest Patients

Stroke ◽  
2012 ◽  
Vol 43 (suppl_1) ◽  
Author(s):  
Michael Mlynash ◽  
Jonathan T Kleinman ◽  
Anna Finley Caulfield ◽  
Chitra Ventkatasubramanian ◽  
Marion Buckwalter ◽  
...  
Keyword(s):  
Cardiac Arrest ◽  
Therapeutic Hypothermia ◽  
Predictive Performance ◽  
Post Processing ◽  
Poor Outcome ◽  
Apparent Diffusion ◽  
Predicting Outcome ◽  
Poor Outcomes ◽  
Predictive Rate ◽  
A Prospective Study

Background: Predicting outcome for comatose post-cardiac arrest survivors is challenging and compounded by the use of therapeutic hypothermia and sedative agents in recent years. Previous studies suggest that brain abnormalities on MRI are predictive for poor outcome. MRI based predictive factors are attractive because they are not affected by drugs or metabolic derangements; however, most of the methods proposed require image post-processing with specialized software. We assessed the prognostic value of color apparent diffusion coefficient (ADC) maps in a prospective study. Methods: Consecutive patients who remained comatose after cardiac arrest were prospectively enrolled. Color ADC maps were created by assigning computed ADC values to 8 colors of spectrum ranging from red to blue ( Figure ). The color ADC maps were not available to the clinical teams caring for the patient. Two raters (a neurocritical care/stroke neurologist and a medical student) independently and blinded reviewed the color ADC maps and predicted 3 month outcome as poor (Glasgow Outcome Scale (GOS) 1 or 2), impaired (GOS=3) or good (GOS of 4 or 5). Both raters were “trained” by viewing 4 examples of patients with good, impaired and poor outcomes. A 3 month GOS of 3-5 was considered a favorable outcome. The agreement between raters and the predictive performance of the color ADC maps were assessed. Results: 112 color ADC maps of 94 patients (56% with poor, 12% with impaired, and 32% with good outcome) were reviewed: age 59±15 years, 36% females, 69% underwent therapeutic hypothermia, median (IQR) arrest duration 20min (14-30), and time between the arrest and MRI 82hours (60-141). Kappa with quadratic weighting for agreement on predicting all 3 levels of outcomes was 0.74, while kappa for favorable vs. unfavorable outcome was 0.76. For the two reviewers, the sensitivity for predicting poor outcome was 0.85 (95%CI 0.73-0.92) and 0.78 (0.66-0.87), the specificity 0.81(0.66-0.90) and 0.74(0.59-0.86), and the true positive predictive rate 86% (74-93%) and 81% (69-89%), respectively. After excluding early (≤24 hours) and late (>120 hours) scans (ADC changes are time dependent and most apparent after day 1 and before day 6), the specificity improved to 0.87 (0.68-0.96) and 0.77 (0.57-0.89), respectively. Conclusion: MRI color ADC maps hold promise as a useful and easy to interpret adjunct for predicting outcome of comatose post-cardiac arrest patients in the first few days after the arrest. Since these maps do not require post-processing and can be created in real-time, they can easily be implemented in the clinical setting.

scholarly journals Prognostic value of diffusion-weighted MRI for post-cardiac arrest coma

Neurology ◽  
2020 ◽  
Vol 94 (16) ◽  
pp. e1684-e1692 ◽  
Author(s):  
Karen G. Hirsch ◽  
Nancy Fischbein ◽  
Michael Mlynash ◽  
Stephanie Kemp ◽  
Roland Bammer ◽  
...  
Keyword(s):  
Cardiac Arrest ◽  
Brain Tissue ◽  
Characteristic Curve ◽  
Area Under The Curve ◽  
Poor Outcome ◽  
Diffusion Weighted ◽  
Blinded Study ◽  
Apparent Diffusion ◽  
Adc Values ◽  
Poor Outcomes

ObjectiveTo validate quantitative diffusion-weighted imaging (DWI) MRI thresholds that correlate with poor outcome in comatose cardiac arrest survivors, we conducted a clinician-blinded study and prospectively obtained MRIs from comatose patients after cardiac arrest.MethodsConsecutive comatose post-cardiac arrest adult patients were prospectively enrolled. MRIs obtained within 7 days after arrest were evaluated. The clinical team was blinded to the DWI MRI results and followed a prescribed prognostication algorithm. Apparent diffusion coefficient (ADC) values and thresholds differentiating good and poor outcome were analyzed. Poor outcome was defined as a Glasgow Outcome Scale score of ≤2 at 6 months after arrest.ResultsNinety-seven patients were included, and 75 patients (77%) had MRIs. In 51 patients with MRI completed by postarrest day 7, the prespecified threshold of >10% of brain tissue with an ADC <650 ×10−6 mm2/s was highly predictive for poor outcome with a sensitivity of 0.63 (95% confidence interval [CI] 0.42–0.80), a specificity of 0.96 (95% CI 0.77–0.998), and a positive predictive value (PPV) of 0.94 (95% CI 0.71–0.997). The mean whole-brain ADC was higher among patients with good outcomes. Receiver operating characteristic curve analysis showed that ADC <650 ×10−6 mm2/s had an area under the curve of 0.79 (95% CI 0.65–0.93, p < 0.001). Quantitative DWI MRI data improved prognostication of both good and poor outcomes.ConclusionsThis prospective, clinician-blinded study validates previous research showing that an ADC <650 ×10−6 mm2/s in >10% of brain tissue in an MRI obtained by postarrest day 7 is highly specific for poor outcome in comatose patients after cardiac arrest.

Abstract 10: Early Neuroprognostication After Refractory VF/VT Cardiac Arrest Requiring ECPR

Circulation ◽  
2019 ◽  
Vol 140 (Suppl_2) ◽  
Author(s):  
Jason A Bartos ◽  
Lindsay Nutting ◽  
Claire Carlson ◽  
Ganesh Raveendran ◽  
Tom P Aufderheide ◽  
...  
Keyword(s):  
Cardiac Arrest ◽  
Hospital Admission ◽  
Near Infrared ◽  
Neuron Specific Enolase ◽  
Extracorporeal Cardiopulmonary Resuscitation ◽  
Head Ct ◽  
Poor Outcome ◽  
Anoxic Injury ◽  
Continuous Eeg ◽  
Poor Outcomes

Background: Extracorporeal cardiopulmonary resuscitation (ECPR) can improve survival for refractory ventricular fibrillation (VF) cardiac arrest. Early prognostication will be critical to focus this resource-intensive care to patients likely to benefit. Objectives: The aim of this study is to examine the efficacy of current neuroprognostication tools early in the setting of ECPR for refractory VF. Methods: Consecutive patients transported for the University of Minnesota ECPR program and surviving to hospital admission between December 2015 and May 2019 were assessed. All patients received neurologic assessment with head CT, continuous EEG, cerebral near-infrared spectroscopy (NIRS), biomarkers including S100B and neuron specific enolase (NSE), and neurologic exam. All patients were considered viable unless they developed refractory shock, devastating brain injury, or family requested cessation of efforts. For this analysis, patients were divided into two groups: 1) neurologically favorable survival (CPC 1-2) and 2) those who died or had CPC 3-4. Data from the first 24 hours of hospital admission were used. Results: Of 168 patients, 130 patients survived to hospital admission. Of these, 42% (54/130) survived neurologically favorable. Abnormalities on admission head CT were predictive of poor outcomes; cerebral edema was 100% specific and 30% sensitive for poor outcomes while anoxic injury provided 98% specificity and 39% sensitivity. Admission NSE levels greater than three times the upper limit of normal were predictive with 98% specificity and 26% sensitivity for poor outcome. Admission S100B was highly variable failing to discriminate patient outcome. Absence of brainstem reflexes at 24 hours had 100% specificity and 32% sensitivity. An isoelectric EEG at 24 hours had 100% specificity and 20% sensitivity. NIRS did not predict poor outcomes. When combined, ≥ 1 of the following: anoxic injury on CT, edema on CT, NSE, absence of brainstem reflexes, isoelectric EEG have a specificity of 96% and sensitivity of 67% for poor outcome. Conclusions: Neuroprognostication after 24 hours of hospital admission may be possible in the refractory VF population requiring ECPR. High specificity is possible but sensitivity is limited. Further study is needed.

scholarly journals Standards for Studies of Neurological Prognostication in Comatose Survivors of Cardiac Arrest: A Scientific Statement From the American Heart Association

Circulation ◽  
2019 ◽  
Vol 140 (9) ◽  
Author(s):  
Romergryko G. Geocadin ◽  
Clifton W. Callaway ◽  
Ericka L. Fink ◽  
Eyal Golan ◽  
David M. Greer ◽  
...  
Keyword(s):  
Cardiac Arrest ◽  
Brain Injury ◽  
American Heart Association ◽  
American Heart ◽  
Heart Association ◽  
Poor Outcome ◽  
Writing Group ◽  
Life Sustaining Treatment ◽  
Poor Outcomes

Significant improvements have been achieved in cardiac arrest resuscitation and postarrest resuscitation care, but mortality remains high. Most of the poor outcomes and deaths of cardiac arrest survivors have been attributed to widespread brain injury. This brain injury, commonly manifested as a comatose state, is a marker of poor outcome and a major basis for unfavorable neurological prognostication. Accurate prognostication is important to avoid pursuing futile treatments when poor outcome is inevitable but also to avoid an inappropriate withdrawal of life-sustaining treatment in patients who may otherwise have a chance of achieving meaningful neurological recovery. Inaccurate neurological prognostication leading to withdrawal of life-sustaining treatment and deaths may significantly bias clinical studies, leading to failure in detecting the true study outcomes. The American Heart Association Emergency Cardiovascular Care Science Subcommittee organized a writing group composed of adult and pediatric experts from neurology, cardiology, emergency medicine, intensive care medicine, and nursing to review existing neurological prognostication studies, the practice of neurological prognostication, and withdrawal of life-sustaining treatment. The writing group determined that the overall quality of existing neurological prognostication studies is low. As a consequence, the degree of confidence in the predictors and the subsequent outcomes is also low. Therefore, the writing group suggests that neurological prognostication parameters need to be approached as index tests based on relevant neurological functions that are directly related to the functional outcome and contribute to the quality of life of cardiac arrest survivors. Suggestions to improve the quality of adult and pediatric neurological prognostication studies are provided.

Abstract 9724: Variance of the Intracranial Pressure Over Time and Relationship With Neurologic Prognosis in Cardiac Arrest Survivors Who Underwent Targeted Temperature Management

Circulation ◽  
2021 ◽  
Vol 144 (Suppl_2) ◽  
Author(s):  
Hogul Song ◽  
Yeonho You ◽  
Changshin Kang ◽  
Jung Soo Park
Keyword(s):  
Cardiac Arrest ◽  
Intracranial Pressure ◽  
Temperature Management ◽  
Poor Outcome ◽  
The Poor ◽  
Poor Outcome Group ◽  
Outcome Group ◽  
Poor Outcomes ◽  
Over Time ◽  
Center Study

Introduction: Increased intracranial pressure (ICP) is one of the most serious post-cardiac arrest (CA) complications, and is associated with poor outcomes. However, only a few studies have described the changes in ICP over time according to neurologic outcomes during targeted temperature management (TTM) after CA. We aimed to investigate the changes in the ICP over time and neurologic prognosis in out-of-hospital cardiac arrest (OHCA) survivors who received TTM. Methods: This retrospective single-center study included OHCA survivors who underwent TTM between May 2018 and December 2020. ICP was measured immediately after the return of spontaneous circulation (ROSC) (Day 1), and after 24 h (Day 2), 48 h (Day 3), and 72 h (Day 4) by connecting a lumbar drain. The neurologic outcome was determined 3 months after the ROSC, and the Cerebral Performance Category (CPC) was dichotomized into good (CPC 1-2) and poor (CPC 3-5) outcomes. Results: We included 91 patients (males, 67; 74%); of whom 51 (56%) had a poor outcome. The ICP was significantly higher in the poor outcome group at each time point, except for Day 4. Moreover, the peak ICP levels were also higher in the poor outcome group (17.0 vs. 14.8; P = 0.002). The change in ICP levels was highest between Day 2 and Day 3 in the good outcome group, but between Day 1 and Day 2 in the poor outcome group. However, there was no difference in the total ICP change between the poor and good outcome groups (3.00 vs 3.09; P = 0.52). Using receiver operating characteristic analyses, the optimal cutoff values of the ICP levels for the prediction of poor outcomes were determined as: day 1, > 11.8; day 2, > 14.0; day 3, > 15.0; and day 4, > 14.8. Conclusions: All OHCA survivors who received TTM had an elevated ICP, regardless of the neurologic prognosis. However, peak ICP levels and the change in the ICP level on the first day after the ROSC was significantly higher in the poor outcome group. A prospective, multi-center study is required to confirm these results.

In situ deteriorating patient simulation in general practice

2020 ◽  
Vol 70 (suppl 1) ◽  
pp. bjgp20X711425
Author(s):  
Joanna Lawrence ◽  
Petronelle Eastwick-Field ◽  
Anne Maloney ◽  
Helen Higham
Keyword(s):  
Life Support ◽  
Early Recognition ◽  
Phase 1 ◽  
Patient Simulation ◽  
Medical Emergency ◽  
Phase 2 ◽  
Action Plans ◽  
Integrated Simulation ◽  
Deteriorating Patient

BackgroundGP practices have limited access to medical emergency training and basic life support is often taught out of context as a skills-based event.AimTo develop and evaluate a whole team integrated simulation-based education, to enhance learning, change behaviours and provide safer care.MethodPhase 1: 10 practices piloted a 3-hour programme delivering 40 minutes BLS and AED skills and 2-hour deteriorating patient simulation. Three scenarios where developed: adult chest pain, child anaphylaxis and baby bronchiolitis. An adult simulation patient and relative were used and a child and baby manikin. Two facilitators trained in coaching and debriefing used the 3D debriefing model. Phase 2: 12 new practices undertook identical training derived from Phase 1, with pre- and post-course questionnaires. Teams were scored on: team working, communication, early recognition and systematic approach. The team developed action plans derived from their learning to inform future response. Ten of the 12 practices from Phase 2 received an emergency drill within 6 months of the original session. Three to four members of the whole team integrated training, attended the drill, but were unaware of the nature of the scenario before. Scoring was repeated and action plans were revisited to determine behaviour changes.ResultsEvery emergency drill demonstrated improved scoring in skills and behaviour.ConclusionA combination of: in situ GP simulation, appropriately qualified facilitators in simulation and debriefing, and action plans developed by the whole team suggests safer care for patients experiencing a medical emergency.

Alanine Aminotransferase Predicts Outcomes in Elderly Patients with Aneurysmal Subarachnoid Hemorrhage

2019 ◽  
Vol 16 (1) ◽  
pp. 89-95
Author(s):  
Jianfeng Zheng ◽  
Rui Xu ◽  
Zongduo Guo ◽  
Xiaochuan Sun
Keyword(s):  
Subarachnoid Hemorrhage ◽  
Elderly Patients ◽  
Clinical Outcomes ◽  
Aneurysmal Subarachnoid Hemorrhage ◽  
Laboratory Data ◽  
Cardiac Complications ◽  
World Population ◽  
Systemic Complications ◽  
Poor Outcome ◽  
Poor Outcomes

Objective: With the aging of the world population, the number of elderly patients suffering from aneurysmal subarachnoid hemorrhage (aSAH) is gradually growing. We aim to investigate the potential association between plasma ALT level and clinical complications of elderly aSAH patients, and explore its predictive value for clinical outcomes of elderly aSAH patients. Methods: Between January 2013 and March 2018, 152 elderly aSAH patients were analyzed in this study. Clinical information, imaging findings and laboratory data were reviewed. According to the Glasgow Outcome Scale (GOS), clinical outcomes at 3 months were classified into favorable outcomes (GOS 4-5) and poor outcomes (GOS 1-3). Logistic regression analysis was used to assess the indicators associated with poor outcomes, and receiver curves (ROC) and corresponding area under the curve (AUC) were used to detect the accuracy of the indicator. Results: A total of 48 (31.6 %) elderly patients with aSAH had poor outcome at 3 months. In addition to ICH, IVH, Hunt-Hess 4 or 5 Grade and Modified Fisher 3 or 4 Grade, plasma ALT level was also strongly associated with poor outcome of elderly aSAH patients. After adjusting for other covariates, plasma ALT level remained independently associated with pulmonary infection (OR 1.05; 95% CI 1.00–1.09; P = 0.018), cardiac complications (OR 1.05; 95% CI 1.01–1.08; P = 0.014) and urinary infection (OR 1.04; 95% CI 1.00–1.08; P = 0.032). Besides, plasma ALT level had a predictive ability in the occurrence of systemic complications (AUC 0.676; 95% CI: 0.586– 0.766; P<0.001) and poor outcome (AUC 0.689; 95% CI: 0.605–0.773; P<0.001) in elderly aSAH patients. Conclusion: Plasma ALT level of elderly patients with aSAH was significantly associated with systemic complications, and had additional clinical value in predicting outcomes. Given that plasma ALT levels on admission could help to identify high-risk elderly patients with aSAH, these findings are of clinical relevance.

Development of A Pharmaceutical Early Warning Scoring Model for Cardiac Arrest Using Deep Learning: Retrospective Cohort Study (Preprint)

2020 ◽  
Author(s):  
Hsiao-Ko Chang ◽  
Hui-Chih Wang ◽  
Chih-Fen Huang ◽  
Feipei Lai
Keyword(s):  
Time Series ◽  
Cardiac Arrest ◽  
Early Warning ◽  
Time Series Data ◽  
Predictive Accuracy ◽  
Vital Signs ◽  
Sliding Window ◽  
Early Warning Score ◽  
Series Data ◽  
Dynamic Time

BACKGROUND In most of Taiwan’s medical institutions, congestion is a serious problem for emergency departments. Due to a lack of beds, patients spend more time in emergency retention zones, which make it difficult to detect cardiac arrest (CA). OBJECTIVE We seek to develop a pharmaceutical early warning model to predict cardiac arrest in emergency departments via drug classification and medical expert suggestion. METHODS We propose a new early warning score model for detecting cardiac arrest via pharmaceutical classification and by using a sliding window; we apply learning-based algorithms to time-series data for a Pharmaceutical Early Warning Scoring Model (PEWSM). By treating pharmaceutical features as a dynamic time-series factor for cardiopulmonary resuscitation (CPR) patients, we increase sensitivity, reduce false alarm rates and mortality, and increase the model’s accuracy. To evaluate the proposed model we use the area under the receiver operating characteristic curve (AUROC). RESULTS Four important findings are as follows: (1) We identify the most important drug predictors: bits, and replenishers and regulators of water and electrolytes. The best AUROC of bits is 85%; that of replenishers and regulators of water and electrolytes is 86%. These two features are the most influential of the drug features in the task. (2) We verify feature selection, in which accounting for drugs improve the accuracy: In Task 1, the best AUROC of vital signs is 77%, and that of all features is 86%. In Task 2, the best AUROC of all features is 85%, which demonstrates that thus accounting for the drugs significantly affects prediction. (3) We use a better model: For traditional machine learning, this study adds a new AI technology: the long short-term memory (LSTM) model with the best time-series accuracy, comparable to the traditional random forest (RF) model; the two AUROC measures are 85%. (4) We determine whether the event can be predicted beforehand: The best classifier is still an RF model, in which the observational starting time is 4 hours before the CPR event. Although the accuracy is impaired, the predictive accuracy still reaches 70%. Therefore, we believe that CPR events can be predicted four hours before the event. CONCLUSIONS This paper uses a sliding window to account for dynamic time-series data consisting of the patient’s vital signs and drug injections. In a comparison with NEWS, we improve predictive accuracy via feature selection, which includes drugs as features. In addition, LSTM yields better performance with time-series data. The proposed PEWSM, which offers 4-hour predictions, is better than the National Early Warning Score (NEWS) in the literature. This also confirms that the doctor’s heuristic rules are consistent with the results found by machine learning algorithms.

Sign in / Sign up

Export Citation Format

Share Document