Smoking, SARS-CoV-2 and COVID-19: a review of reviews considering implications for public health policy and practice

IntroductionThere has been significant speculation regarding the association between Severe Acute RespiratorySyndrome Coronavirus 2 (SARS-CoV-2) pathogen, coronavirus disease (COVID-19) and smoking.We provide an overview of the available literature regarding the association between smoking, risk ofSARS-CoV-2 infection, and risk of severe COVID-19 and poor clinical outcomes, with the aim ofinforming public health policy and practice in England.MethodsPublications were identified utilising a systematic search approach on PUBMED and Google Scholar.Publications presenting a systematic review or meta-analysis considering the association betweensmoking and SARS-COV-2 infection or COVID-19 outcomes were included.ResultsEight studies were identified. One considered the relationship between smoking and the probability ofSARS-CoV-2 infection, three considered the association between COVID-19 hospitalisation andsmoking history and six reviewed the association between smoking history and development ofsevere COVID-19. One study specifically investigated the risk of mortality. The studies consideringrisk of severe disease indicate that there is a significant association between COVID-19 and currentor ever smoking.ConclusionsThis is a rapidly evolving topic. Current analysis remains limited due to the quality of primary data,although early results indicate an association between smoking and COVID-19 severity. We highlyrecommend public health messaging to continue focusing on smoking cessation efforts

Electroencephalography (EEG) for neurological prognostication after cardiac arrest and targeted temperature management; rationale and study design.

BACKGROUND: Electroencephalography (EEG) is widely used to assess neurological prognosis in patients who are comatose after cardiac arrest, but its value is limited by varying definitions of pathological patterns and by inter-rater variability. The American Clinical Neurophysiology Society (ACNS) has recently proposed a standardized EEG-terminology for critical care to address these limitations. METHODS/DESIGN: In the TTM-trial, 399 post cardiac arrest patients who remained comatose after rewarming underwent a routine EEG. The presence of clinical seizures, use of sedatives and antiepileptic drugs during the EEG-registration were prospectively documented. DISCUSSION: A well-defined terminology for interpreting post cardiac arrest EEGs is critical for the use of EEG as a prognostic tool. TRIAL REGISTRATION: The TTM-trial is registered at ClinicalTrials.gov (NCT01020916)

Postanoxic electrographic status epilepticus and serum biomarkers of brain injury

AIM: To explore if electrographic status epilepticus (ESE) after cardiac arrest causes additional secondary brain injury reflected by serum levels of two novel biomarkers of brain injury: neurofilament light chain (NfL) originating from neurons and glial fibrillary acidic protein (GFAP) from glial cells. METHODS: Simplified continuous EEG (cEEG) and serum levels of NfL and GFAP, sampled at 24, 48 and 72 h after cardiac arrest, were collected during the Target Temperature Management (TTM)-trial. Two statistical methods were used: multivariable regresssion analysis; and a matched control group of patients without ESE matched for early predictors of poor neurological outcome. RESULTS: 128 patients had available biomarkers and cEEG. Twenty-six (20%) patients developed ESE, the majority (69%) within 24 h. ESE was an independent predictor of elevated serum NfL (p < 0.001) but not of serum GFAP (p = 0.16) at 72 h after cardiac arrest. Compared to a control group matched for early predictors of poor neurological outcome, patients who developed ESE had higher levels of serum NfL (p = 0.03) and GFAP (p = 0.04) at 72 h after cardiac arrest. CONCLUSION: ESE after cardiac arrest is associated with higher levels of serum NfL which may suggest increased secondary neuronal injury compared to matched patients without ESE but similar initial brain injury. Associations with GFAP reflecting glial injury are less clear. The study design cannot exclude imperfect matching or other mechanisms of secondary brain injury contributing to the higher levels of biomarkers of brain injury seen in the patients with ESE

Serial soluble neurofilament heavy chain in plasma as a marker of brain injury after cardiac arrest

ABSTRACT: INTRODUCTION: Induced hypothermia has been shown to improve outcome after cardiac arrest, but early prognostication is hampered by the need for sedation. Here we tested whether a biomarker for neurodegeneration, the neurofilament heavy chain (NfH), may improve diagnostic accuracy in the first days after cardiac arrest. METHODS: This prospective study included 90 consecutive patients treated with hypothermia after cardiac arrest. Plasma levels of phosphorylated NfH (SMI35) were quantified using standard ELISA over a period of 72 h after cardiac arrest. The primary outcome was the dichotomized Cerebral Performance Categories scale (CPC). A best CPC 1-2 during 6 months follow-up was considered a good outcome, a best CPC of 3-4 a poor outcome. Receiver operator characteristics and area under the curve were calculated. RESULTS: The median age of the patients was 65 years, and 63 (70%) were male. A cardiac aetiology was identified in 62 cases (69%). 77 patients (86%) had out-of-hospital cardiac arrest. The outcome was good in 48 and poor in 42 patients. Plasma NfH levels were significantly higher 2 and 36 hours after cardiac arrest in patients with poor outcome (median 0.28 ng/mL and 0.5 ng/mL, respectively) compared to those with good outcome (0 ng/mL, p = 0.016, p < 0.005, respectively). The respective AUC were 0.72 and 0.71. CONCLUSIONS: Plasma NfH levels correlate to neurological prognosis following cardiac arrest. In this study, 15 patients had neurological co-morbidities and there was a considerable overlap of data. As such, neurofilament should not be used for routine neuroprognostication until more data are available

Brain injury after cardiac arrest: pathophysiology, treatment, and prognosis

Post-cardiac arrest brain injury (PCABI) is caused by initial ischaemia and subsequent reperfusion of the brain following resuscitation. In those who are admitted to intensive care unit after cardiac arrest, PCABI manifests as coma, and is the main cause of mortality and long-term disability. This review describes the mechanisms of PCABI, its treatment options, its outcomes, and the suggested strategies for outcome prediction

Prediction of poor neurological outcome in comatose survivors of cardiac arrest: a systematic review.

To assess the ability of clinical examination, blood biomarkers, electrophysiology, or neuroimaging assessed within 7 days from return of spontaneous circulation (ROSC) to predict poor neurological outcome, defined as death, vegetative state, or severe disability (CPC 3-5) at hospital discharge/1 month or later, in comatose adult survivors from cardiac arrest (CA). PubMed, EMBASE, Web of Science, and the Cochrane Database of Systematic Reviews (January 2013-April 2020) were searched. Sensitivity and false-positive rate (FPR) for each predictor were calculated. Due to heterogeneities in recording times, predictor thresholds, and definition of some predictors, meta-analysis was not performed. Ninety-four studies (30,200 patients) were included. Bilaterally absent pupillary or corneal reflexes after day 4 from ROSC, high blood values of neuron-specific enolase from 24 h after ROSC, absent N20 waves of short-latency somatosensory-evoked potentials (SSEPs) or unequivocal seizures on electroencephalogram (EEG) from the day of ROSC, EEG background suppression or burst-suppression from 24 h after ROSC, diffuse cerebral oedema on brain CT from 2 h after ROSC, or reduced diffusion on brain MRI at 2-5 days after ROSC had 0% FPR for poor outcome in most studies. Risk of bias assessed using the QUIPS tool was high for all predictors. In comatose resuscitated patients, clinical, biochemical, neurophysiological, and radiological tests have a potential to predict poor neurological outcome with no false-positive predictions within the first week after CA. Guidelines should consider the methodological concerns and limited sensitivity for individual modalities. (PROSPERO CRD42019141169)

Short-term abstinence from alcohol and changes in cardiovascular risk factors, liver function tests and cancer-related growth factors: a prospective observational study

OBJECTIVE: To assess changes in metabolic risk factors and cancer-related growth factors associated with short-term abstinence from alcohol. DESIGN: Prospective, observational study. SETTING: Single tertiary centre. PARTICIPANTS: Healthy subjects were recruited based on intention to: (1) abstain from alcohol for 1 month (abstinence group), or (2) continue to drink alcohol (control group). Inclusion criteria were baseline alcohol consumption >64 g/week (men) or >48 g/week (women). Exclusion criteria were known liver disease or alcohol dependence. PRIMARY AND SECONDARY OUTCOME MEASURES: The primary outcome was change in insulin resistance (homeostatic model assessment (HOMA) score). Secondary outcomes were changes in weight, blood pressure (BP), vascular endothelial growth factor (VEGF), epidermal growth factor (EGF) and liver function tests. Primary and secondary outcomes were adjusted for changes in diet, exercise and cigarette smoking. RESULTS: The abstinence group comprised 94 participants (mean age 45.5 years, SD ±1.2) and the control group 47 participants (mean age 48.7 years, SD ±1.8). Baseline alcohol consumption in the abstinence group was 258.2 g/week, SD ±9.4, and in the control group 233.8 g, SD ±19.0. Significant reductions from baseline in the abstinence group (all p<0.001) were found in: HOMA score (-25.9%, IQR -48.6% to +0.3%), systolic BP (-6.6%, IQR -11.8% to 0.0%), diastolic BP (-6.3%, IQR -14.1% to +1.3%), weight (-1.5%, IQR -2.9% to -0.4%), VEGF (-41.8%, IQR -64.9% to -17.9%) and EGF (-73.9%, IQR -86.1% to -36.4%). None of these changes were associated with changes in diet, exercise or cigarette smoking. No significant changes from baseline in primary or secondary outcomes were noted in the control group. CONCLUSION: These findings demonstrate that abstinence from alcohol in moderate-heavy drinkers improves insulin resistance, weight, BP and cancer-related growth factors. These data support an independent association of alcohol consumption with cancer risk, and suggest an increased risk of metabolic diseases such as type 2 diabetes and fatty liver disease

Plasma neurofilament light is a predictor of neurological outcome 12 h after cardiac arrest

Background: Previous studies have reported high prognostic accuracy of circulating neurofilament light (NfL) at 24–72 h after out-of-hospital cardiac arrest (OHCA), but performance at earlier time points and after in-hospital cardiac arrest (IHCA) is less investigated. We aimed to assess plasma NfL during the first 48 h after OHCA and IHCA to predict long-term outcomes. Methods: Observational multicentre cohort study in adults admitted to intensive care after cardiac arrest. NfL was retrospectively analysed in plasma collected on admission to intensive care, 12 and 48 h after cardiac arrest. The outcome was assessed at two to six months using the Cerebral Performance Category (CPC) scale, where CPC 1–2 was considered a good outcome and CPC 3–5 a poor outcome. Predictive performance was measured with the area under the receiver operating characteristic curve (AUROC). Results: Of 428 patients, 328 (77%) suffered OHCA and 100 (23%) IHCA. Poor outcome was found in 68% of OHCA and 55% of IHCA patients. The overall prognostic performance of NfL was excellent at 12 and 48 h after OHCA, with AUROCs of 0.93 and 0.97, respectively. The predictive ability was lower after IHCA than OHCA at 12 and 48 h, with AUROCs of 0.81 and 0.86 (p ≤ 0.03). AUROCs on admission were 0.77 and 0.67 after OHCA and IHCA, respectively. At 12 and 48 h after OHCA, high NfL levels predicted poor outcome at 95% specificity with 70 and 89% sensitivity, while low NfL levels predicted good outcome at 95% sensitivity with 71 and 74% specificity and negative predictive values of 86 and 88%. Conclusions: The prognostic accuracy of NfL for predicting good and poor outcomes is excellent as early as 12 h after OHCA. NfL is less reliable for the prediction of outcome after IHCA

Predicting neurological outcome after out-of-hospital cardiac arrest with cumulative information; development and internal validation of an artificial neural network algorithm

BACKGROUND: Prognostication of neurological outcome in patients who remain comatose after cardiac arrest resuscitation is complex. Clinical variables, as well as biomarkers of brain injury, cardiac injury, and systemic inflammation, all yield some prognostic value. We hypothesised that cumulative information obtained during the first three days of intensive care could produce a reliable model for predicting neurological outcome following out-of-hospital cardiac arrest (OHCA) using artificial neural network (ANN) with and without biomarkers. METHODS: We performed a post hoc analysis of 932 patients from the Target Temperature Management trial. We focused on comatose patients at 24, 48, and 72 h post-cardiac arrest and excluded patients who were awake or deceased at these time points. 80% of the patients were allocated for model development (training set) and 20% for internal validation (test set). To investigate the prognostic potential of different levels of biomarkers (clinically available and research-grade), patients' background information, and intensive care observation and treatment, we created three models for each time point: (1) clinical variables, (2) adding clinically accessible biomarkers, e.g., neuron-specific enolase (NSE) and (3) adding research-grade biomarkers, e.g., neurofilament light (NFL). Patient outcome was the dichotomised Cerebral Performance Category (CPC) at six months; a good outcome was defined as CPC 1-2 whilst a poor outcome was defined as CPC 3-5. The area under the receiver operating characteristic curve (AUROC) was calculated for all test sets. RESULTS: AUROC remained below 90% when using only clinical variables throughout the first three days in the ICU. Adding clinically accessible biomarkers such as NSE, AUROC increased from 82 to 94% (p < 0.01). The prognostic accuracy remained excellent from day 1 to day 3 with an AUROC at approximately 95% when adding research-grade biomarkers. The models which included NSE after 72 h and NFL on any of the three days had a low risk of false-positive predictions while retaining a low number of false-negative predictions. CONCLUSIONS: In this exploratory study, ANNs provided good to excellent prognostic accuracy in predicting neurological outcome in comatose patients post OHCA. The models which included NSE after 72 h and NFL on all days showed promising prognostic performance