Bibliographic record
Abstract
Survival after cardiac arrest varies fivefold across the country, with patients in Alabama facing lower odds than those in Seattle, for instance, but researchers said EMS protocols can vastly improve those rates. Data revealed the variance in surviving to discharge in eight U.S. and two Canadian emergency medical services, a finding so large it surprised researchers. “The take-home message is that every community needs to monitor and improve its response to cardiac arrest,” said Graham Nichol, MD, MPH, a professor of medicine, the Medic One Foundation Endowed Chair, and the director of the University of Washington-Harborview Center for Prehospital Emergency Care.Figure“Most communities are not monitoring cardiac arrest, and cannot tell their citizens how often these firefighters and medics are able to resuscitate people. We need to make it a reportable disease so everyone can know how his city did. If you don't measure it, you can't improve it,” said Dr. Nichol, the first author of the Journal of the American Medical Association study. (2008; 300[12]:1423.) The trial took place at 10 sites: Alabama, Dallas, Iowa, Milwaukee, Ottawa, Pittsburgh, Portland, Seattle, Toronto, and Vancouver. Emergency medical services personnel attempted resuscitation in 11,898 of 20,520 cases. Some 2,729 patients with ventricular fibrillation, ventricular tachycardia, or rhythms were shocked by an automated external defibrillator. Overall, 954 were discharged alive. Rates varied greatly by population, however. EMS-treated cardiac arrest per 100,000 population ranged from 40.3 to 86.7. For ventricular fibrillation, the EMS treatment rate ranged from 9.3 to 19 per 100,000 population. EMS-treated cardiac arrest survival ranged from three percent in Alabama to 16.3 percent in Seattle. For ventricular fibrillation, survival ranged from 7.7 percent to 39.9 percent. “It's a huge variation,” said Dr. Nichol. “We've reported a variation of 500 percent in survival. What was unexpected was the magnitude of the differences from city to city.” The best results demonstrate that cardiac arrest is a treatable condition, but it's also clear that the message is not getting through everywhere. “As is often the case, it's partly resources and also a lack of awareness that people can survive cardiac arrest,” Dr. Nichol said. “We need to tell people that, but it requires many people take part. It requires bystander CPR, emergency medical services providing high-quality prehospital care, hospitals providing cooling to patients, and following protocols when they get to the hospital.” In an accompanying editorial, Arthur B. Sanders, MD, a professor of emergency medicine at the University of Arizona at Tucson, and Karl B. Kern, MD, a professor of medicine at the University of Arizona at Tucson, pointed out that the magnitude of the cardiac arrest problem means that even small improvements in survival statistics could be important. “Out-of-hospital cardiac arrest is primarily a systems problem in local communities,” they wrote. “It is important that clinicians advocate in their communities to establish an optimal response and treatment system for patients to have a reasonable chance of resuscitation.” (JAMA 2008; 300[12]:1462.) “There are huge variations in the quality of emergency medical services,” said Dr. Sanders. It is important to recommend that emergency medical services organizations record key outcome measures, he said, but many cities don't do that. “One remarkable statistic in this study is that 42 percent of those with cardiac arrest did not have resuscitation attempted,” he said. “I think that's a remarkable number. That means that in about four of 10 out-of-hospital cardiac arrests, resuscitation is not attempted by emergency medical services.” In some cases, Dr. Sanders said, this may occur because of advanced directives. “Emergency medical technicians and paramedics are smart,” said Dr. Nichol. “They can say that this person is clearly dead, or family members may say, ‘He did not want to be resuscitated.’” Dr. Sanders pointed to a small study by Michael Kellum, MD, in rural Wisconsin that called for an EMS protocol consisting of uninterrupted chest compressions followed by passive oxygen administration with no active ventilation, rhythm analysis with a single shock, 200 immediate post-shock chest compressions, and delayed endotracheal intubation. In the three years before the protocol, 15 percent of patients with shockable rhythms survived. After the protocol was put into effect, the percentage increased to 39 percent. (Ann Emerg Med 2008;52[3]:244.) He said another major advance is therapeutic hypothermia, which improves neurological outcome. Meanwhile, Dr. Nichol is working with the American Heart Association to make cardiac arrest and other acute cardiovascular events reportable so that each city can monitor its response and improve it.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".