scholarly journals Clinical Characteristics, Outcomes, and Risk Factors of Disease Severity in Patients With COVID-19 and With a History of Cerebrovascular Disease in Wuhan, China: A Retrospective Study

2022 ◽  
Vol 12 ◽  
Author(s):  
Mengzhen Li ◽  
Zehui He ◽  
Jiecong Yang ◽  
Qihua Guo ◽  
Heng Weng ◽  
...  
Keyword(s):  
Risk Factors ◽  
Cerebrovascular Disease ◽  
Blood Urea Nitrogen ◽  
Clinical Characteristics ◽  
Adverse Outcomes ◽  
Chronic Obstructive ◽  
Urea Nitrogen ◽  
Nitrogen Levels ◽  
Retrospective Clinical Study ◽  
History Of

Background and Purpose: Coronavirus disease 2019 (COVID-19) rapidly resulted in a pandemic. Information on patients with a history of cerebrovascular disease (CVD) infected with severe acute respiratory syndrome coronavirus 2 (SARS-COV-2) is limited. This study investigated the clinical features and the risk factors of developing adverse outcomes in patients with COVID-19 and with previous CVD.Methods: This was a single-center retrospective clinical study including all the confirmed cases of COVID-19 at Wuhan Huoshenshan Hospital from February 4 to April 7, 2020. Differences in clinical characteristics were compared between patients with and without a history of CVD. The incidences of severe events comprising all-cause death, intensive care unit admission, shock, and mechanical ventilation usage during hospitalization in two groups were compared using propensity score matching analysis and multivariate logistic regression analyses. Besides, the risk factors of developing severe events in patients with COVID-19 who also have history of CVD were analyzed.Results: A total of 2,554 consecutive patients were included in our study, of whom 109 (4.27%) had a medical history of CVD. Patients with CVD tend to be older and with more comorbidities, including hypertension, diabetes, coronary heart disease, and chronic obstructive pulmonary disease. The levels of white blood cell, neutrophil, C-reactive protein, creatine kinase isoenzymes, and lactate dehydrogenase were higher, whereas the levels of lymphocyte and albumin were lower in the CVD group. Compared to those without CVD, patients with CVD were more likely to have severe events after age matching (12.8 vs. 5.7%, P = 0.012). After adjusting for the confounding effects of age, sex, smoking, and comorbidities, the odds ratio for developing severe events with a history of CVD was 2.326 (95% CI, 1.168–4.630; P = 0.016). Besides, patients with CVD, either with decreased lymphocyte count (OR 9.192, 95% CI, 1.410–59.902, P = 0.020) or increased blood urea nitrogen (OR 5.916, 95% CI, 1.072–32.641, P = 0.041), had a higher risk of developing severe events during hospitalization.Conclusions: Patients with CVD history tend to have adverse clinical outcomes after being infected with SARS-COV-2. Decreased lymphocyte counts and increased blood urea nitrogen levels may be risk factors for adverse outcomes in patients with COVID-19, and had CVD.

scholarly journals Clinical Characteristics and Risk Factors for Myocardial Injury and Arrhythmia in COVID-19 patients

2020 ◽  
Author(s):  
Hong Gang Ren ◽  
Xingyi Guo ◽  
Lei Tu ◽  
Qinyong Hu ◽  
Kevin Blighe ◽  
...  
Keyword(s):  
Risk Factors ◽  
Clinical Characteristics ◽  
Myocardial Injury ◽  
Heart Diseases ◽  
Chronic Obstructive ◽  
Cross Sectional ◽  
Obstructive Pulmonary Disease ◽  
Increased Risk ◽  
History Of ◽  
Cross Sectional Design

ABSTRACTBackgroundPatients with COVID-19 can develop myocardial injury and arrhythmia during the course of their illness. However, the underlying risk factors for the development of cardiovascular related manifestations are unclear.MethodsUsing a register-based multi-center cross-sectional design, we analyzed 80 patients with myocardial injury and 401 controls, as well as 71 patients with arrhythmia and 409 controls, all admitted with COVID-19. Putative risk factors for myocardial injury and arrhythmia were evaluated with logistic regression with adjustment for potential confounders.ResultsCOVID-19 patients with myocardial injury had fatigue (66.2%) and dyspnea (63.7%), while those with arrhythmia had dyspnea (71.8%). Patients with myocardial injury and arrhythmia had a significant mortality of 92.5% and 94.4%, respectively. A history of chronic obstructive pulmonary disease (COPD) or heart diseases was associated with an increased risk of myocardial injury (odds ratio [OR] = 1.94, 95% confidence interval [CI]: 1.01-3.71; OR = 7.43, 95% CI: 3.99-13.83) and arrhythmia (OR = 1.94, 95% CI: 1.00-3.75; OR = 13.16, 95% CI: 6.75-25.68). In addition, we found that gamma glutamyltranspeptidase (GGT) >50U/L (OR = 2.14, 95% CI: 1.37-3.32; OR = 1.85, 95% CI: 1.19-2.85), serum creatinine >111μmol/L (OR = 8.96, 95% CI: 4.4-18.23; OR = 3.71, 95% CI: 2.01-6.85), serum sodium <136 mmol/L (OR = 4.68, 95% CI: 2.46-8.91; OR = 2.06; 95% CI: 1.06-4.00) were all associated with increased risk of myocardial injury and arrhythmia, respectively.ConclusionOur reported clinical characteristics and identified risk factors are important for clinical study of COVID-19 patients developing myocardial injury and arrhythmia.

scholarly journals Acute cerebrovascular disease following COVID-19: a single center, retrospective, observational study

2020 ◽  
Vol 5 (3) ◽  
pp. 279-284 ◽  
Author(s):  
Yanan Li ◽  
Man Li ◽  
Mengdie Wang ◽  
Yifan Zhou ◽  
Jiang Chang ◽  
...  
Keyword(s):  
Risk Factors ◽  
Cerebrovascular Disease ◽  
Management Strategy ◽  
Clinical Characteristics ◽  
C Reactive Protein ◽  
Laboratory Findings ◽  
Reactive Protein ◽  
Negative Prognostic Factor ◽  
History Of ◽  
New Onset

Background and purposeCOVID-19 is an infectious disease caused by Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2). Apart from respiratory complications, acute cerebrovascular disease (CVD) has been observed in some patients with COVID-19. Therefore, we described the clinical characteristics, laboratory features, treatment and outcomes of CVD complicating SARS-CoV-2 infection.Materials and methodsDemographic and clinical characteristics, laboratory findings, treatments and clinical outcomes were collected and analysed. Clinical characteristics and laboratory findings of patients with COVID-19 with or without new-onset CVD were compared.ResultsOf 219 patients with COVID-19, 10 (4.6%) developed acute ischaemic stroke and 1 (0.5%) had intracerebral haemorrhage. COVID-19 with new onset of CVD were significantly older (75.7±10.8 years vs 52.1±15.3 years, p<0.001), more likely to present with severe COVID-19 (81.8% vs 39.9%, p<0.01) and were more likely to have cardiovascular risk factors, including hypertension, diabetes and medical history of CVD (all p<0.05). In addition, they were more likely to have increased inflammatory response and hypercoagulable state as reflected in C reactive protein (51.1 (1.3–127.9) vs 12.1 (0.1–212.0) mg/L, p<0.05) and D-dimer (6.9 (0.3–20.0) vs 0.5 (0.1–20.0) mg/L, p<0.001). Of 10 patients with ischemic stroke; 6 received antiplatelet treatment with aspirin or clopidogrel; and 3 of them died. The other four patients received anticoagulant treatment with enoxaparin and 2 of them died. As of 24 March 2020, six patients with CVD died (54.5%).ConclusionAcute CVD is not uncommon in COVID-19. Our findings suggest that older patients with risk factors are more likely to develop CVD. The development of CVD is an important negative prognostic factor which requires further study to identify optimal management strategy to combat the COVID-19 outbreak.

scholarly journals Predicting COVID-19 mortality with electronic medical records

2021 ◽  
Vol 4 (1) ◽  
Author(s):  
Hossein Estiri ◽  
Zachary H. Strasser ◽  
Jeffy G. Klann ◽  
Pourandokht Naseri ◽  
Kavishwar B. Wagholikar ◽  
...  
Keyword(s):  
Risk Factors ◽  
Medical Information ◽  
Age Groups ◽  
Prognostic Models ◽  
Smoking History ◽  
Risk Scores ◽  
Gradient Boosting ◽  
Chronic Obstructive ◽  
Clinical Expertise ◽  
History Of

AbstractThis study aims to predict death after COVID-19 using only the past medical information routinely collected in electronic health records (EHRs) and to understand the differences in risk factors across age groups. Combining computational methods and clinical expertise, we curated clusters that represent 46 clinical conditions as potential risk factors for death after a COVID-19 infection. We trained age-stratified generalized linear models (GLMs) with component-wise gradient boosting to predict the probability of death based on what we know from the patients before they contracted the virus. Despite only relying on previously documented demographics and comorbidities, our models demonstrated similar performance to other prognostic models that require an assortment of symptoms, laboratory values, and images at the time of diagnosis or during the course of the illness. In general, we found age as the most important predictor of mortality in COVID-19 patients. A history of pneumonia, which is rarely asked in typical epidemiology studies, was one of the most important risk factors for predicting COVID-19 mortality. A history of diabetes with complications and cancer (breast and prostate) were notable risk factors for patients between the ages of 45 and 65 years. In patients aged 65–85 years, diseases that affect the pulmonary system, including interstitial lung disease, chronic obstructive pulmonary disease, lung cancer, and a smoking history, were important for predicting mortality. The ability to compute precise individual-level risk scores exclusively based on the EHR is crucial for effectively allocating and distributing resources, such as prioritizing vaccination among the general population.

Abstract WP244: Applicability of the Compass Trial Criteria Among Stable Outpatients With Established Atherothrombotic Disease or Major Risk Factors

Stroke ◽  
2020 ◽  
Vol 51 (Suppl_1) ◽  
Author(s):  
Carlos Cantu-Brito ◽  
Erwin Chiquete ◽  
Jose L Ruiz-Sandoval ◽  
Fernando Flores-Silva
Keyword(s):  
Risk Factors ◽  
Cerebrovascular Disease ◽  
Selection Criteria ◽  
Vascular Risk Factors ◽  
Cox Proportional Hazards Model ◽  
Vascular Risk ◽  
Similar Frequency ◽  
History Of ◽  
Atherothrombotic Disease

Background and Purpose: The objective of this study were to describe the proportion of patients eligible for the COMPASS trial among stable outpatients with either established atherothrombotic disease or major vascular risk factors, and to analyze 6-month incident stroke risk according vascular risk factors at baseline. Methods: We prospectively recruited 5,101 stable outpatients in 172 sites, within the Mexican INDAGA cohort study. Inclusion criteria were age >18 years and established atherothrombotic disease [history of either acute coronary syndromes (ACS), acute ischemic stroke (AIS)/transient ischemic attack (TIA) or peripheral artery disease (PAD)] or major vascular risk factors (age <55 years plus ≥2 major vascular risk factors, or age ≥55 years plus ≥1 vascular risk factors). Among these patients, we applied the selection criteria of the COMPASS trial for analysis, dividing the population in no COMPASS criteria met and COMPASS criteria met, and this last group subdivided among patients with previous AIS/TIA and without this antecedent, in order to stratify the risk for stroke during 6-month follow-up (incident AIS/TIA). Results: Among 5,101 stable outpatients with either established atherothrombotic disease (n=2,827) or major vascular risk factors (n=2,274), a total of 1,927 (37.8%) met COMPASS trial criteria: 1,054 (54.7%) with established cerebrovascular disease (past history of AIS/TIA) and 873 (45.3%) without. During 6-month follow-up, there were 89 incident AIS/TIA (39 AIS and 54 TIA): 1.7% among the whole population and 2.2% among the COMPASS subgroup. AIS/TIA occurred in a similar frequency among the COMPASS subgroup with established cerebrovascular disease (1.6%) and COMPASS without cerebrovascular disease (0.9%) (P=0.18). After a Cox-proportional hazards model, independent predictors of incident AIS/TIA were age ≥65 years (HR: 1.99, 95% CI: 1.29-3.07) and established cerebrovascular disease at baseline (HR: 1.61, 95% CI: 1.02-2.53). Conclusions: The majority of stable outpatients at vascular risk met COMPASS selection criteria and could be good candidates for low-dose rivaroxaban in addition to aspirin. Short-term predictors of AIS/TIA were old age and history of cerebrovascular disease

scholarly journals Epidemiological characteristics, clinical characteristics, and prognostic factors of children with atopy hospitalised with adenovirus pneumonia

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Miao Li ◽  
Xiao-Hua Han ◽  
Li-Yun Liu ◽  
Hui-Sheng Yao ◽  
Li-Li Yi
Keyword(s):  
Risk Factors ◽  
Disease Severity ◽  
Clinical Characteristics ◽  
Severe Infection ◽  
Small Airway ◽  
Personal History ◽  
Factors Associated ◽  
History Of ◽  
Radiological Changes ◽  
Epidemiological Characteristics

Abstract Background Atopy may be associated with disease severity and a poor prognosis of human adenovirus (HAdV) pneumonia in children. Our aim was to observe the clinical characteristics and pulmonary radiological changes in children with atopy and HAdV pneumonia in China. Methods Children hospitalised with HAdV pneumonia from June 2018 to December 2019 were analysed. All children were divided into atopic with HAdV, non-atopic with HAdV, and atopic without HAdV infection group. Each group was further divided into the mild and severe pneumonia groups according to disease severity. Standard treatment was initiated after admission, and regular follow-up evaluations were conducted at 1 month after discharge. Baseline and clinical characteristics and pulmonary radiological changes in children with and without atopy were evaluated. Risk factors associated with small airway lesions in patients with HAdV pneumonia were analysed. Results The eosinophil count in the atopic group was significantly higher than that in the non-atopic group (P < 0.05). Severe coughing, wheezing, and small airway lesions on chest high-resolution computed tomography (HRCT) upon admission, after discharge and 1 month after discharge were significantly higher in the atopic group (with or without HAdV infection) than in the non-atopic group (P < 0.05). There were significant differences in the number of patients with wheezing and small airway lesions during hospitalisation and after discharge among the three groups (P < 0.05). The risks of small airway lesions in children with a family or personal history of asthma, severe infection, atopy, and HAdV infection were 2.1-, 2.7-, 1.9-, 2.1-, and 1.4-times higher than those in children without these characteristics, respectively. Conclusions Children with atopy and HAdV pneumonia may experience severe coughing in mild cases and wheezing in mild and severe cases. Children with atopy are more susceptible to the development of small airway lesions, recurrent wheezing after discharge and slower recovery of small airway lesions as observed on pulmonary imaging than non-atopic children after HAdV infection. A family or personal history of asthma, atopy, severe infection, and HAdV infection are independent risk factors associated with the development of small airway lesion as observed on chest HRCT.

scholarly journals Incidence, clinical characteristics and prognostic factor of patients with COVID-19: a systematic review and meta-analysis

2020 ◽  
Author(s):  
Chaoqun Ma ◽  
Jiawei Gu ◽  
Pan Hou ◽  
Liang Zhang ◽  
Yuan Bai ◽  
...  
Keyword(s):  
Risk Factors ◽  
Disease Severity ◽  
Old Age ◽  
Clinical Characteristics ◽  
Early Stage ◽  
Meta Analysis ◽  
Blood Platelet ◽  
Clinical Feature ◽  
Chronic Obstructive ◽  
Medicine Research

AbstractBackgroundRecently, Coronavirus Disease 2019 (COVID-19) outbreak started in Wuhan, China. Although the clinical features of COVID-19 have been reported previously, data regarding the risk factors associated with the clinical outcomes are lacking.ObjectivesTo summary and analyze the clinical characteristics and identify the predictors of disease severity and mortality.MethodsThe PubMed, Web of Science Core Collection, Embase, Cochrane and MedRxiv databases were searched through February 25, 2020. Meta-analysis of Observational Studies in Epidemiology (MOOSE) recommendations were followed. We extracted and pooled data using random-e□ects meta-analysis to summary the clinical feature of the confirmed COVID-19 patients, and further identify risk factors for disease severity and death. Heterogeneity was evaluated using the I2 method and explained with subgroup analysis and meta-regression.ResultsA total of 30 studies including 53000 patients with COVID-19 were included in this study, the mean age was 49.8 years (95% CI, 47.5-52.2 yrs) and 55.5% were male. The pooled incidence of severity and mortality were 20.2% (95% CI, 15.1-25.2%) and 3.1% (95% CI, 1.9-4.2%), respectively. The predictor for disease severity included old age (≥ 50 yrs, odds ratio [OR] = 2.61; 95% CI, 2.29-2.98), male (OR =1.348, 95% CI, 1.195-1.521), smoking (OR =1.734, 95% CI, 1.146-2.626) and any comorbidity (OR = 2.635, 95% CI, 2.098-3.309), especially chronic kidney disease (CKD, OR = 6.017; 95% CI, 2.192-16.514), chronic obstructive pulmonary disease (COPD, OR = 5.323; 95% CI, 2.613-10.847) and cerebrovascular disease (OR = 3.219; 95% CI, 1.486-6.972). In terms of laboratory results, increased lactate dehydrogenase (LDH), C-reactive protein (CRP) and D-dimer and decreased blood platelet and lymphocytes count were highly associated with severe COVID-19 (all for P < 0.001). Meanwhile, old age (≥ 60 yrs, RR = 9.45; 95% CI, 8.09-11.04), followed by cardiovascular disease (RR = 6.75; 95% CI, 5.40-8.43) hypertension (RR = 4.48; 95% CI, 3.69-5.45) and diabetes (RR = 4.43; 95% CI, 3.49-5.61) were found to be independent prognostic factors for the COVID-19 related death.ConclusionsTo our knowledge, this is the first evidence-based medicine research to explore the risk factors of prognosis in patients with COVID-19, which is helpful to identify early-stage patients with poor prognosis and adapt effective treatment.

Prediction and network modelling of self-harm through daily self-report and history of self-injury

2020 ◽  
pp. 1-11 ◽  
Author(s):  
Michael J. Kyron ◽  
Geoff R. Hooke ◽  
Andrew C. Page
Keyword(s):  
Risk Factors ◽  
Psychological Distress ◽  
Daily Basis ◽  
Adverse Outcomes ◽  
Self Report ◽  
Public Health Issue ◽  
Short Term ◽  
Wish To Die ◽  
History Of ◽  
Self Harm

Abstract Background Self-harm is a significant public health issue, and both our understanding and ability to predict adverse outcomes are currently inadequate. The current study explores how preventative efforts could be aided through short-term prediction and modelling of risk factors for self-harm. Methods Patients (72% female, Mage = 40.3 years) within an inpatient psychiatric facility self-reported their psychological distress, interpersonal circumstances, and wish to live and die on a daily basis during 3690 unique admissions. Hierarchical logistic regressions assessed whether daily changes in self-report and history of self-harm could predict self-harm, with machine learning used to train and test the model. To assess interrelationships between predictors, network and cross-lagged panel models were performed. Results Increases in a wish to die (β = 1.34) and psychological distress (β = 1.07) on a daily basis were associated with increased rates of self-harm, while a wish to die on the day prior [odds ratio (OR) 3.02] and a history of self-harm (OR 3.02) was also associated with self-harm. The model detected 77.7% of self-harm incidents (positive predictive value = 26.6%, specificity = 79.1%). Psychological distress, wish to live and die, and interpersonal factors were reciprocally related over the prior day. Conclusions Short-term fluctuations in self-reported mental health may provide an indication of when an individual is at-risk of self-harm. Routine monitoring may provide useful feedback to clinical staff to reduce risk of self-harm. Modifiable risk factors identified in the current study may be targeted during interventions to minimise risk of self-harm.

scholarly journals Investigation of the Prevalence and Diagnosis of Chronic Obstructive Pulmonary Disease in a Group of Elderly Individuals Residing in an Island Area of Ningbo

2019 ◽  
Vol 2019 ◽  
pp. 1-9
Author(s):  
Wei Sheng ◽  
Youchang Huang ◽  
Zaichun Deng ◽  
Hongying Ma
Keyword(s):  
Risk Factors ◽  
Chronic Obstructive Pulmonary Disease ◽  
Pulmonary Disease ◽  
Diagnosis And Treatment ◽  
Chronic Obstructive ◽  
Obstructive Pulmonary Disease ◽  
Elderly Individuals ◽  
Island Area ◽  
History Of ◽  
Missed Diagnosis

Objective. This epidemiological investigation aimed at determining the current situation regarding the diagnosis and treatment of chronic obstructive pulmonary disease (COPD), especially missed diagnosis and missed treatment, in a group of individuals residing in an island area of Ningbo. Methods. Adults ≥60 years of age were selected from an island area of Ningbo. All participants completed a COPD-Screening Questionnaire and underwent a post-bronchodilator pulmonary function test. COPD-positive individuals then completed a questionnaire surveying the status of diagnosis and treatment of COPD and the reasons for missed diagnosis and treatment. The data were collated and analyzed using SPSS version 22.0 (IBM Corporation, Armonk, NY, USA). Findings. (1) A total of 1526 individuals were screened, of whom 1371 (89.8%) were eventually included in data analysis. From these, 254 were diagnosed with spirometry-defined COPD, corresponding to an overall prevalence of 18.5%. Prevalence was higher in men (28.9%) than in women (8.3%) among the sample. (2) According to chi-squared test results, risk factors for COPD included sex, age, smoking history (pack-years), cough, and dyspnea. Body mass index, family history of respiratory diseases, and exposure to biomass smoke from cooking were not risk factors for COPD. (3) Multivariate logistic regression analysis revealed that age and smoking were independent risk factors for COPD. (4) Receiver operating curve analysis revealed that, at a cutoff of 19.5, the highest sum of sensitivity and specificity was 69.7% and 75.5%, respectively. The COPD-Screening Questionnaire could be used as a preselection method to screen for COPD in primary care settings. (5) Of 254 individuals diagnosed with COPD, only 10 had a history of COPD and only 35 had a previous diagnosis of pneumonia or bronchitis. These data revealed that the rate of missed diagnosis of COPD in the Ningbo island area was 96.1%. Conclusion. The prevalence of COPD among elderly individuals in the Ningbo island area was significantly higher than in other parts of China. Moreover, the rate of missed diagnosis of COPD in the Ningbo island area was extremely high. Smoking and age were independent factors for the occurrence of COPD.

Clinical characteristics and long-term clinical course of patients with Brugada syndrome without previous cardiac arrest: a multiparametric risk stratification approach

EP Europace ◽  
2019 ◽  
Author(s):  
Konstantinos P Letsas ◽  
George Bazoukis ◽  
Michael Efremidis ◽  
Stamatis Georgopoulos ◽  
Panagiotis Korantzopoulos ◽  
...  
Keyword(s):  
Risk Factors ◽  
Risk Stratification ◽  
Brugada Syndrome ◽  
Clinical Characteristics ◽  
Clinical Course ◽  
Electrophysiological Study ◽  
Rank Test ◽  
History Of ◽  
Event Rates

Abstract Aims Risk stratification in Brugada syndrome (BrS) still represents an unsettled issue. In this multicentre study, we aimed to evaluate the clinical characteristics and the long-term clinical course of patients with BrS. Methods and results A total of 111 consecutive patients (86 males; aged 45.3 ± 13.3 years) diagnosed with BrS were included and followed-up in a prospective fashion. Thirty-seven patients (33.3%) were symptomatic at enrolment (arrhythmic syncope). An electrophysiological study (EPS) was performed in 59 patients (53.2%), and ventricular arrhythmias were induced in 32 (54.2%). A cardioverter defibrillator was implanted in 34 cases (30.6%). During a mean follow-up period of 4.6 ± 3.5 years, appropriate device therapies occurred in seven patients. Event-free survival analysis (log-rank test) showed that spontaneous type-1 electrocardiogram pattern (P = 0.008), symptoms at presentation (syncope) (P = 0.012), family history of sudden cardiac death (P < 0.001), positive EPS (P = 0.024), fragmented QRS (P = 0.004), and QRS duration in lead V2 > 113 ms (P < 0.001) are predictors of future arrhythmic events. Event rates were 0%, 4%, and 60% among patients with 0–1 risk factor, 2–3 risk factors, and 4–5 risk factors, respectively (P < 0.001). Current multiparametric score models exhibit an excellent negative predictive value and perform well in risk stratification of BrS patients. Conclusions Multiparametric models including common risk factors appear to provide better risk stratification of BrS patients than single factors alone.

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