scholarly journals A comprehensive evaluation of early potential risk factors for disease aggravation in patients with COVID-19

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Qiang Tang ◽  
Yanwei Liu ◽  
Yingfeng Fu ◽  
Ziyang Di ◽  
Kailiang Xu ◽  
...  
Keyword(s):  
Risk Factors ◽  
Regression Analysis ◽  
Serum Ferritin ◽  
Potential Risk ◽  
Comprehensive Evaluation ◽  
Organ Damage ◽  
Kaplan Meier ◽  
Public Crisis ◽  
Potential Risk Factors ◽  
Multivariable Regression

AbstractThe 2019 Coronavirus Disease (COVID-19) has become an unprecedented public crisis. We retrospectively investigated the clinical data of 197 COVID-19 patients and identified 88 patients as disease aggravation cases. Compared with patients without disease aggravation, the aggravation cases had more comorbidities, including hypertension (25.9%) and diabetes (20.8%), and presented with dyspnoea (23.4%), neutrophilia (31.5%), and lymphocytopenia (46.7%). These patients were more prone to develop organ damage in liver, kidney, and heart (P < 0.05). A multivariable regression analysis showed that advanced age, comorbidities, dyspnea, lymphopenia, and elevated levels of Fbg, CTnI, IL-6, and serum ferritin were significant predictors of disease aggravation. Further, we performed a Kaplan–Meier analysis to evaluate the prognosis of COVID-19 patients, which suggested that 64.9% of the patients had not experienced ICU transfers and survival from the hospital.

scholarly journals Risk Factors and Prediction of Leptospiral Seropositivity Among Dogs and Dog Handlers in Malaysia

2019 ◽  
Vol 16 (9) ◽  
pp. 1499 ◽  
Author(s):  
Soon Heng Goh ◽  
Rosnah Ismail ◽  
Seng Fong Lau ◽  
Puteri Azaziah Megat Abdul Rani ◽  
Taznim Begam Mohd Mohidin ◽  
...  
Keyword(s):  
Risk Factors ◽  
Logistic Regression ◽  
Regression Analysis ◽  
Small Mammal ◽  
Potential Risk ◽  
Contact Time ◽  
Agglutination Test ◽  
Housing Area ◽  
Common Area ◽  
Potential Risk Factors

This study determined the potential risk factors that may contribute to seropositivity among dogs and dog handlers from working dog and dog shelter institutions. Data was collected from dogs (n = 266) and dog handlers (n = 161) using a standardised guided questionnaire. Serum obtained from the dogs and dog handlers was tested using the microscopic agglutination test (MAT). A logistic regression analysis was used to predict leptospiral seropositivity of dogs and dog handlers based on potential risk factors. A total of 22.2% of dogs and 21.7% of dog handlers were seropositive. The significant predictors for the dogs’ seropositivity were presence of rats (OR = 4.61 (95% CI: 1.05, 20.33), p = 0.043) and shared common area (OR = 5.12 (95% CI: 1.94, 13.46), p = 0.001) within the organisation. Significant predictor for dog handler seropositivity was contact time with the dogs of more than six hours/day (OR = 3.28 (95% CI: 1.28, 8.40), p = 0.013) after controlling for the effect of other risk factors such as small mammal contact, rat infestation at home, flooding at housing area (within three months) and urban locality. The exposure to various disease sources identified poses risk to dogs and dog handlers. Risk could be reduced with adequate application of protection at work while handling dogs and thus limiting contact with these sources and reducing exposure to infection.

scholarly journals Clinical Risk Factors for Long-term Hospital Stay in Common Patients with coronavirus disease 2019(COVID-19)

2020 ◽  
Author(s):  
Wei Lu ◽  
Junjie Fang ◽  
Bin Chen ◽  
Dan Wu ◽  
Chunyao Yu ◽  
...  
Keyword(s):  
Risk Factors ◽  
Hospital Stay ◽  
Potential Risk ◽  
Clinical Laboratory ◽  
Short Term ◽  
Factors Associated ◽  
Regression Methods ◽  
Potential Risk Factors ◽  
Multivariable Regression

Abstract Background This study aimed to investigate the potential risk factors associated with hospital stay in mild patients with COVID-19. Methods A total of 109 laboratory-confirmed COVID patients with initial common subtype diseased by real-time RT-PCR that meet discharge standards were retrospectively included from January 16 to March 15 of 2020. Baseline demographic, clinical, laboratory examination was extracted from electronic medical records at the first day of admission and compared between short-term hospital stay and long-term hospital stay. Univariable and multivariable logistic regression methods were used to explore the risk factors associated with hospital stay. Results Of 109 COVID-19 patients, 61 patients were short-term stay (≤ 10 days) and 48 patients were long-term stay (> 10 days). The average age of patients in short-term stay were younger than those long-term stay(P = 0.01). Hypertension was the most common comorbidity (34%, 21/61), followed by diabetes (15%,9/61) and Cardiopathy (8%, 5/61). Fever and cough were the typical clinical manifestation in two group. Decreased WBC, Hemoglobin and increased Monocyte, MLR (Monocyte Lymphocyte ratio) and Hypersensitive CRP showed a long-term stay (all P < 0.05). The treatment of Resochin and Human immunoglobulin had a shorter hospital stay. Multivariable regression showed that MLR and CRP on admission were risk factors for predicting the hospital stay, with the HR (hazard ratio 2.03, 1.02–5.39; P = 0.022) and (1.32,1.05–3.24, P = 0.045) respectively. Conclusions The potential risk factors of MLR and CRP may help clinicians to predict the hospital stay of COVID-19 patients.

scholarly journals 1650. Clinical Features and Risk Factors of Active Tuberculosis in Patients with Behçet’s Disease

2020 ◽  
Vol 7 (Supplement_1) ◽  
pp. S812-S813
Author(s):  
Yaxu Liu ◽  
Lifan Zhang ◽  
Ziyue Zhou ◽  
Luxi Sun ◽  
Baotong Zhou ◽  
...  
Keyword(s):  
Risk Factors ◽  
Weight Loss ◽  
Logistic Regression ◽  
Regression Analysis ◽  
Logistic Regression Analysis ◽  
Potential Risk ◽  
Behcet’S Disease ◽  
Active Tuberculosis ◽  
Unexplained Weight Loss ◽  
Potential Risk Factors

Abstract Background Understanding the clinical characteristics and risk factors of active tuberculosis (ATB) in Behçet’s disease (BD) is of great significance to improve the treatment efficacy and guide the preventive treatment. However, the relevant studies are very limited. Methods We retrospectively reviewed medical records of BD patients admitted to our institute from 2010 to 2019. BD patients with ATB were enrolled as the case group, and the control group was selected by random number sampling from the remaining BD patients. Multivariate logistic regression analysis was performed to explore the potential risk factors of ATB in BD patients. Figure 1. Flowchart of the study Results Twenty-one ATB cases were identified from 386 BD patients, including four (19.0%) microbiologically confirmed and 17 (81.0%) clinically diagnosed. ATB patients can present with systemic symptoms (fever, night sweating, unexplained weight loss) and/or symptoms related to the infection site. Logistic regression analysis revealed that ESR&gt;60mm/h (OR=13.710, 95%CI (1.101, 170.702)), increased IgG (OR=1.226, 95%CI (1.001, 1.502)), and positive T-SPOT.TB (OR=7.793, 95%CI (1.312, 48.464), for 24-200 SFC/106PBMC; OR=17.705 (2.503, 125.260), for &gt;200 SFC/106PBMC) were potential risk factors for ATB in BD patients. Table 1. Past medical history and medication of BD patients with and without ATB Table 2. Clinical presentation and laboratory results of BD patients with and without ATB Table 3. Potential risk factors for ATB in BD patients Conclusion When BD patients have fever, night sweating, unexplained weight loss, or manifestations rarely occurred in BD, the diagnosis of ATB should be considered. Significantly elevated T-SPOT.TB indicates a high risk of ATB in BD patients. Disclosures All Authors: No reported disclosures

Tricuspid valve replacement: an appraisal of 45 years of experience

2020 ◽  
Vol 30 (6) ◽  
pp. 896-903 ◽  
Author(s):  
Kevin M Veen ◽  
Thijs J M Quanjel ◽  
Mostafa M Mokhles ◽  
Ad J J C Bogers ◽  
Johanna J M Takkenberg
Keyword(s):  
Risk Factors ◽  
Patient Outcome ◽  
Regression Analysis ◽  
Valve Replacement ◽  
Tricuspid Valve ◽  
Potential Risk ◽  
Carcinoid Heart Disease ◽  
Tricuspid Valve Replacement ◽  
Potential Risk Factors ◽  
Over Time

Abstract OBJECTIVES This study provides an overview of the change over a 45-year time period in the characteristics and outcome of patients with tricuspid valve disease undergoing surgical tricuspid valve replacement (TVR). METHODS The characteristics and outcomes of all consecutive TVRs from November 1972 to November 2017 at Erasmus MC were collected retrospectively. A logistic regression analysis was conducted to identify the significant predictors of 30-day mortality. Multivariable Cox regression analysis was used to identify the potential risk factors of patient outcome and the effect of time on these factors. RESULTS Ninety-eight patients with tricuspid valve dysfunction underwent 114 consecutive TVRs at a mean age of 50.1 ± 17.2 years (68.5% female). Aetiology changed over time from predominantly functional regurgitation (42.9% in 1972-1985) to predominantly carcinoid heart disease (47.7% in 2001-2017). Early mortality declined significantly from 35% in 1972–1985 to 6.7% in 2001–2017 (P &lt; 0.001). Over time, the hazard ratio of late mortality decreased for higher New York Heart Association class, lower preoperative haemoglobin, and high central venous pressure and increased for the presence of preoperative leg oedema, higher creatinine and alkaline phosphatase. The late survival was 43.8% ± 5.89% at 10 years and was comparable among eras (P = 0.44). The cumulative incidence of reoperation at 10 years was 14.1% (2.3–26.0) in biological valves and 4.9% (0.1–10.3) in mechanical valves (P = 0.25). CONCLUSIONS Patient characteristics, potential risk factors and patient outcome changed considerably over time in patients undergoing TVR. Notably, there was a shift in aetiology, completely altering the patient population and their characteristics.

Clinical features of and risk factors for intracranial aneurysms associated with moyamoya disease

2020 ◽  
pp. 174749302096722
Author(s):  
Hecheng Yang ◽  
Limin Zhang ◽  
Menghan Wang ◽  
Jingtao Wang ◽  
Lijie Chen ◽  
...  
Keyword(s):  
Risk Factors ◽  
Logistic Regression ◽  
Regression Analysis ◽  
Clinical Features ◽  
Moyamoya Disease ◽  
Logistic Regression Analysis ◽  
Potential Risk ◽  
Intracranial Aneurysms ◽  
Age Of Onset ◽  
Potential Risk Factors

Background The clinical features of aneurysms associated with moyamoya disease (MMD) and risk factors for the formation and rupture of aneurysms are not well defined. Aims In this study, we retrospectively analyzed clinical data of MMD patients and examined the potential risk factors for the formation and rupture of aneurysms in these patients. Methods The medical records of all MMD patients in our hospital from April 2012 to May 2019 were reviewed. The logistic regression analysis was used to determine the independent association between various potential risk factors and the presence or rupture of intracranial aneurysms in MMD patients. Results Of 2230 MMD patients, 182 (8.2%) cases had intracranial aneurysms. The mean age of onset in patients with aneurysms was 47.2 years, which was significantly higher when compared with those without aneurysms ( p < 0.001). In logistic regression analysis, age of onset remained significantly associated with the presence of intracranial aneurysms, while female gender, hypertension, diabetes mellitus, and coronary artery disease were not. Besides, intracranial aneurysms were significantly associated with intracranial hemorrhage in MMD patients (odds ratio [OR] = 5.19; 95% confidence interval [CI], 3.80–7.09). About 60% aneurysms >5 mm in size, and 62.1% aneurysms with irregularly shaped morphology were ruptured. Aneurysms located in basilar tip, collateral or moyamoya vessels were more likely to present with rupture. Conclusions Age was an important risk factor for intracranial aneurysms formation in MMD patients. Aneurysms increased the risk of intracerebral hemorrhage in MMD patients, and their ruptures were correlated with aneurysms size, location, and morphology.

scholarly journals A Comprehensive Evaluation of Early Predictors of Disease Progression in Patients with COVID-19: A Case Control Study

2020 ◽  
Author(s):  
Qiang Tang ◽  
Yanwei Liu ◽  
Yingfeng Fu ◽  
Ziyang Di ◽  
Kailiang Xu ◽  
...  
Keyword(s):  
Disease Progression ◽  
Serum Ferritin ◽  
Elevated Level ◽  
Clinical Laboratory ◽  
Comprehensive Evaluation ◽  
Clinical Information ◽  
Organ Damage ◽  
Advanced Age ◽  
Health Crisis ◽  
Kaplan Meier

Abstract Background: The 2019 coronavirus disease (COVID-19) has become an unprecedented public health crisis with nearly 16 million confirmed cases and 630,000 deaths worldwide. Methods: We retrospectively investigated the demographic, clinical, laboratory, radiological and treatment data of COVID-19 patients consecutively enrolled from January 18 to May 15, 2020, in Taihe and Jinzhou central hospital. Results: Of all 197 patients, the median age was 66.5 years (IQR 7-76), and 120 (60.9%) patients were males. We identified 88 (44.7%) of 197 COVID-19 patients as the disease progression (aggravation) cases. The aggravation cases tend to have more medical comorbidity: hypertension (34.1%), diabetes (30.7%), and presented with dyspnea (34.1%), neutrophilia (60.2%), and lymphocytopenia (73.9%), compared with those without. And the patients with disease progression showed significantly higher level of Fibrinogen (Fbg), D-dimer, IL-6, C-reactive protein (CRP), procalcitonin (PCT), and serum ferritin, and were more prone to develop organ damage in the liver, kidney, and heart (P<0.05). Multivariable regression showed that advanced age, comorbidities, lymphopenia, and elevated level of Fbg, lactate dehydrogenase (LDH), Cardiac troponin (CTnI), IL-6, serum ferritin were the significant predictors of disease progression. Further, we investigated antibody responses to SARS-CoV-2 and found that the levels of IgM and IgG were significantly higher in the disease progression cases compared to non-progression cases from 3 weeks after symptom onset. In addition, the disease progression group tended to peak later and has a more vigorous IgM/IgG response against SARS-CoV-2. Further, we performed Kaplan-Meier analysis and found that 61.6% of patients had not experienced ICU transfer or survival from hospital within 25 days from admission.Conclusions: Investigating the potential factors of advanced age, comorbidities and elevated level of IL-6, serum ferritin and Kaplan-Meier analysis enables early identification and management of patients with poor prognosis. Detection of the dynamic antibody may offer vital clinical information during the course of SARS-CoV-2 and provide prognostic value for patients infection.

Diabetes Induced Factors Prediction Based on Various Improved Machine Learning Methods

2021 ◽  
Vol 16 ◽  
Author(s):  
Jun Wu ◽  
Guoping Yang ◽  
Lulu Qu ◽  
Nan Han
Keyword(s):  
Machine Learning ◽  
Risk Factors ◽  
Potential Risk ◽  
Class Imbalance ◽  
The Elderly ◽  
Organ Damage ◽  
Initial Diagnosis ◽  
Machine Learning Algorithms ◽  
Data Set ◽  
Potential Risk Factors

Background: with the increasing quality of life of people, people begin to have more time and energy to pay attention to their own health problems. Among them, diabetes, as one of the most common and fastest-growing diseases, has attracted widespread attention from experts in bioinformatics. People of different ages all over the world suffer from diabetes which can shorten the life span of patients. Diabetes has a significant impact on human health, so that the accuracy of the initial diagnosis becomes essential. Diabetes can bring some serious complications, especially in the elderly, such as cardiovascular and cerebrovascular diseases, stroke, and multiple organ damage. The initial diagnosis of diabetes can reduce the possibility of deterioration. Identifying and analyzing potential risk factors for different physical attributes can help diagnose the prevalence of diabetes. The more accurate the prevalence, the more likely it is to reduce the incidence of complications. Methods: In this paper, we use the open source NHANES data set to analyze and determine potential risk factors relevant to diabetes by an improved version of Logistic Regression, SVM, and other improved machine learning algorithms. Results: Experimental results show that the improved version of Random Forest has the best effect, with a classification accuracy of 92%, and it can be found that age, blood-related diabetes, high blood pressure, cholesterol and BMI are the most important risk factors related to diabetes. Conclusion: Through the proposed method of machine learning, we can cope with the class imbalance and outlier detection problems.

Premature Arterial Disease Associated with Familial Antithrombin III Deficiency

1990 ◽  
Vol 63 (01) ◽  
pp. 013-015 ◽  
Author(s):  
E J Johnson ◽  
C R M Prentice ◽  
L A Parapia
Keyword(s):  
Risk Factors ◽  
Venous Thromboembolism ◽  
Potential Risk ◽  
Antithrombin Iii ◽  
Arterial Disease ◽  
Coagulation System ◽  
Early Age ◽  
Arterial Thromboembolism ◽  
Potential Risk Factors ◽  
Antithrombin Iii Deficiency

SummaryAntithrombin III (ATIII) deficiency is one of the few known abnormalities of the coagulation system known to predispose to venous thromboembolism but its relation to arterial disease is not established. We describe two related patients with this disorder, both of whom suffered arterial thrombotic events, at an early age. Both patients had other potential risk factors, though these would normally be considered unlikely to lead to such catastrophic events at such an age. Thrombosis due to ATIII deficiency is potentially preventable, and this diagnosis should be sought more frequently in patients with arterial thromboembolism, particularly if occurring at a young age. In addition, in patients with known ATIII deficiency, other risk factors for arterial disease should be eliminated, if possible. In particular, these patients should be counselled against smoking.

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