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Time-of-day determines neuronal damage and mortality after cardiac arrest.

ABSTRACT: Ischemic events in humans are not evenly distributed across the day. To discriminate between temporal differences in the incidence of ischemia and susceptibility to ischemic events, we examined the outcome of global ischemia in a murine model at three time points during the day. Global cerebral ischemia in mice during the light phase impairs survival and exacerbates outcome compared to ischemia at other times of the day. Specifically, mice that underwent cardiac arrest during the light phase had greater numbers of degenerating neurons, greater microglial activation, and increased proinflammatory cytokine production in the ischemia-vulnerable hippocampus, as well as increased locomotor activity. Time-of-day differences were not altered by the melatonin receptor antagonist luzindole. Our results document that brain tissue displays endogenous fluctuations in susceptibility to ischemic damage and demonstrate that small differences in time of onset can significantly influence ischemic outcomes.

SUBMITTER: Weil ZM

PROVIDER: S-EPMC2760634 | biostudies-literature | 2009 Nov

REPOSITORIES: biostudies-literature

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Time-of-day determines neuronal damage and mortality after cardiac arrest.

Weil Zachary M ZM Karelina Kate K Su Alan J AJ Barker Jacqueline M JM Norman Greg J GJ Zhang Ning N Devries A Courtney AC Nelson Randy J RJ

Neurobiology of disease 20090805 2

Ischemic events in humans are not evenly distributed across the day. To discriminate between temporal differences in the incidence of ischemia and susceptibility to ischemic events, we examined the outcome of global ischemia in a murine model at three time points during the day. Global cerebral ischemia in mice during the light phase impairs survival and exacerbates outcome compared to ischemia at other times of the day. Specifically, mice that underwent cardiac arrest during the light phase had ...[more]

PMID: 19664712

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Project description:BackgroundInternationally, hospital survival is lower for patients admitted at weekends and at night. Data from the UK National Cardiac Arrest Audit (NCAA) indicate that crude hospital survival was worse after in-hospital cardiac arrest (IHCA) at night versus day, and at weekends versus weekdays, despite similar frequency of events.ObjectiveTo describe IHCA demographics during three day/time periods-weekday daytime (Monday to Friday, 08:00 to 19:59), weekend daytime (Saturday and Sunday, 08:00 to 19:59) and night-time (Monday to Sunday, 20:00 to 07:59)-and to compare the associated rates of return of spontaneous circulation (ROSC) for >20 min (ROSC>20 min) and survival to hospital discharge, adjusted for risk using previously developed NCAA risk models. To consider whether any observed difference could be attributed to differences in the case mix of patients resident in hospital and/or the administered care.MethodsWe performed a prospectively defined analysis of NCAA data from 27 700 patients aged ≥16 years receiving chest compressions and/or defibrillation and attended by a hospital-based resuscitation team in response to a resuscitation (2222) call in 146 UK acute hospitals.ResultsRisk-adjusted outcomes (OR (95% CI)) were worse (p<0.001) for both weekend daytime (ROSC>20 min 0.88 (0.81 to 0.95); hospital survival 0.72 (0.64 to 0.80)), and night-time (ROSC>20 min 0.72 (0.68 to 0.76); hospital survival 0.58 (0.54 to 0.63)) compared with weekday daytime. The effects were stronger for non-shockable than shockable rhythms, but there was no significant interaction between day/time of arrest and age, or day/time of arrest and arrest location. While many daytime IHCAs involved procedures, restricting the analyses to IHCAs in medical admissions with an arrest location of ward produced results that are broadly in line with the primary analyses.ConclusionsIHCAs attended by the hospital-based resuscitation team during nights and weekends have substantially worse outcomes than during weekday daytimes. Organisational or care differences at night and weekends, rather than patient case mix, appear to be responsible.

Project description:BACKGROUND:The incidence, prediction and mortality outcomes of intraoperative and postoperative cardiac arrest requiring cardiopulmonary resuscitation (CPR) in surgical patients are under investigated and have not been studied concurrently in a single study. METHODS:A retrospective cohort study was conducted using the American College of Surgeons National Surgical Quality Improvement Program data between 2008 and 2012. Firth's penalized logistic regression was used to study the incidence and identify risk factors for intra- and postoperative CPR and 30-day mortality. simplified prediction model was constructed and internally validated to predict the studied outcomes. RESULTS:Among about 1.86 million non-cardiac operations, the incidence rate of intraoperative CPR was 0.03%, and for postoperative CPR was 0.33%. The 30-day mortality incidence rate was 1.25%. The incidence rate of events decreased overtime between 2008-2012. Of the 29 potential predictors, 14 were significant for intraoperative CPR, 23 for postoperative CPR, and 25 for 30-day mortality. The five strongest predictors (highest odd ratios) of intraoperative CPR were the American Society of Anesthesiologists (ASA) physical status, Systemic Inflammatory Response Syndrome (SIRS)/sepsis, surgery type, urgent/emergency case and anesthesia technique. Intraoperative CPR, ASA, age, functional status and end stage renal disease were the most significant predictors for postoperative CPR. The most significant predictors of 30-day mortality were ASA, age, functional status, SIRS/sepsis, and disseminated cancer. The predictions with the simplified five-factor model performed well and was comparable to the full prediction model. Postoperative cardiac arrest requiring CPR, compared to intraoperative, was associated with much higher mortality. CONCLUSIONS:The incidence of cardiac arrest requiring CPR in surgical patients decreased overtime. Risk factors for intraoperative CPR, postoperative CPR and perioperative mortality are overlapped. We proposed a simplified approach compromised of five-factor model to identify patients at high risk. Postoperative, compare to intraoperative, cardiac arrest requiring CPR was associated with much higher mortality.

Project description:BackgroundCOVID-19 infection carries significant morbidity and mortality. Current risk prediction for complications in COVID-19 is limited, and existing approaches fail to account for the dynamic course of the disease.ObjectivesThe purpose of this study was to develop and validate the COVID-HEART predictor, a novel continuously updating risk-prediction technology to forecast adverse events in hospitalized patients with COVID-19.MethodsRetrospective registry data from patients with severe acute respiratory syndrome coronavirus 2 infection admitted to 5 hospitals were used to train COVID-HEART to predict all-cause mortality/cardiac arrest (AM/CA) and imaging-confirmed thromboembolic events (TEs) (n = 2,550 and n = 1,854, respectively). To assess COVID-HEART's performance in the face of rapidly changing clinical treatment guidelines, an additional 1,100 and 796 patients, admitted after the completion of development data collection, were used for testing. Leave-hospital-out validation was performed.ResultsOver 20 iterations of temporally divided testing, the mean area under the receiver operating characteristic curve were 0.917 (95% confidence interval [CI]: 0.916-0.919) and 0.757 (95% CI: 0.751-0.763) for prediction of AM/CA and TE, respectively. The interquartile ranges of median early warning times were 14 to 21 hours for AM/CA and 12 to 60 hours for TE. The mean area under the receiver operating characteristic curve for the left-out hospitals were 0.956 (95% CI: 0.936-0.976) and 0.781 (95% CI: 0.642-0.919) for prediction of AM/CA and TE, respectively.ConclusionsThe continuously updating, fully interpretable COVID-HEART predictor accurately predicts AM/CA and TE within multiple time windows in hospitalized COVID-19 patients. In its current implementation, the predictor can facilitate practical, meaningful changes in patient triage and resource allocation by providing real-time risk scores for these outcomes. The potential utility of the predictor extends to COVID-19 patients after hospitalization and beyond COVID-19.

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Time-of-day determines neuronal damage and mortality after cardiac arrest.

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Time-of-day determines neuronal damage and mortality after cardiac arrest.

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