Clinical Characteristics, Serum Uric Acid and Bullosis Diabeticorum Outcomes in Patients With Diabetes Mellitus

Abstract Background: Bullosis diabeticorum (BD) is a spontaneous, non-inflammatory vesicular disease of diabetes, with the observed risk of infection, including diabetic skin ulcers, osteomyelitis and even leading to amputation. However, the exact cause of BD is not well understood. So the aim of this study is to explore the high-risk factors of BD for preventing its occurrence.Methods: A retrospective study was conducted, including baseline characteristics, laboratory data, and bullosis diabeticorum outcomes of 602 patients with bullosis diabeticorum. Besides, 904 diabetic patients without bullosis diabeticorum in the same period were randomly selected as the control group. The indicators of the two groups were compared. Multivariable logistic regression analysis was performed to investigate which indicator was most associated with bullosis diabeticorum outcomes.Results: SCr[145.00(69.00-195.00) μmol/L, n = 602 vs. 81.00(27.40-35.60) μmol/L, n= 904, p=0.032], BUA [674.00(372.50-758.50) µmol/L, n = 602 vs. 318.50(241.75-415.25) µmol/L, n= 904, p = 0.003] and Cys-C[1.96(1.10-2.95) mg/L, n = 602 vs. 1.49(1.10-1.62) mg/L, n = 904, p=0.004] was significantly higher in BD-positive patients than that in BD-negative patients, whereas eGFR [67.38(45.33-87.53) ml/min, n = 602 vs. 75.86(56.80-95.69) ml/min, n = 904, p=0.038] of patients with BD was significantly lower than that of patients without BD. Multiple logistic regression analysis showed that BUA, but not SCr, Cys-C and eGFR, was independently and significantly associated in a positive manner with BD (odds ratio: 8.569, 95% confidence interval: 1.136-55.250, p=0.004).Conclusion: We found a positive and independent association of BUA with BD, which provides a great clinical predictive factor for BD and helps to prevent the appearance of diabetic foot.

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Comparison of Hospitalized Patients with Severe Pneumonia Caused by COVID-19 and Highly Pathogenic Avian Influenza (H7N9): A Retrospective Study from A Designated Hospital

10.21203/rs.3.rs-28119/v1 ◽

2020 ◽

Author(s):

Binbin Gu ◽

Lin Yao ◽

XinYun Zhu ◽

Pei-jun Tang ◽

Cheng Chen

Keyword(s):

Logistic Regression ◽

Regression Analysis ◽

Logistic Regression Analysis ◽

Multiple Logistic Regression Analysis ◽

Severe Pneumonia ◽

Multivariable Logistic Regression Analysis ◽

Fisher Exact Test ◽

Exact Test ◽

Viral Shedding ◽

Medical Supplies

Abstract Background Considerable attention has been focused on clinical features of Coronavirus Disease 2019 (COVID-19), it is also important for clinicians to differentiate it from influenza virus infections. Methods The clinical data of 23 cases of H7N9 and 23 cases of COVID-19 with severe pneumonia were collected. The comparisons were performed with the t test, Mann-Whitney U test, Fisher exact test or the chi-squared test, and multivariable logistic regression analysis. Results All of the cases were under the circumstance of sufficient medical staff and medical supplies. The rate of coexisting disease was lower in the severe COVID-19 group than in the severe H7N9 group (p < 0.05). Radiologically, severe COVID-19 patients had less consolidation and pleural effusion, but more crazy-paving pattern than severe H7N9 patients (p < 0.05). Clinically, compared to severe H7N9, severe COVID-19 patients were more inclined to surfer to relative better disease severity score, less secondary bacterial infection, a shorter time to beginning absorption on CT, but a longer duration of viral shedding from the admission (p < 0.05). Although more severe H7N9 patients needed non-invasive respiratory support, these two groups ultimately yielded comparable mortality. Based on multiple logistic regression analysis, severe COVID-19 infection was associated with a lower risk of the presence of severe ARDS (OR 0.964, 95% [CI] 0.931–0.998, p = 0.040), but exhibited longer duration of viral shedding (OR 0.734, 95% [CI] 0.550–0.980, p = 0.036) than severe H7N9 infection. Conclusion Although the conditions of severe H7N9 patients seemed to be more critical than those of severe COVID-19 patients, the relatively lower mortality of these two severe cases is to be expected in context of sufficient medical supplies.

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Contribution of rs1799998 polymorphism in CYP11B2 gene in susceptibility to preeclampsia

Revista Brasileira de Saúde Materno Infantil ◽

10.1590/1806-93042020000200008 ◽

2020 ◽

Vol 20 (2) ◽

pp. 467-471

Author(s):

Kaio Raffael Valotta Bezerra ◽

Sarah Cristina Sato Vaz Tanaka ◽

Vanessa Resende Souza Silva ◽

Marina Carvalho Paschoinni ◽

Roseane Lopes da Silva Grecco ◽

...

Keyword(s):

Logistic Regression ◽

Regression Analysis ◽

Logistic Regression Analysis ◽

Multiple Logistic Regression Analysis ◽

Recessive Model ◽

Control Group ◽

Study Group ◽

Genotypic Frequency ◽

Multiple Logistic Regression ◽

Significant Difference

Abstract Objectives: the present study aimed to evaluate the association between the rs1799998 polymorphism of the CYP11B2 gene and the susceptibility to preeclampsia (PE) in a Brazilian population. Methods: the study group comprised 61 women who were diagnosed with PE. The control group included 116 women who did not show changes in their blood pressure levels during their pregnancies. The rs1799998 polymorphism of the CYP11B2 gene was amplified by allele-specific polymerase chain reaction (PCR). A multiple logistic regression analysis was performed using the SNPStat program to evaluate the risk of the CYP11B2 gene rs1799998 polymorphism contributing to PE. Results: the PE group had the following genotypes: 1.64% CC, 91.80% CT, and 6.56% TT. In the control group, the observed genotypic frequencies were: 11% CC, 73% CT, and 16% TT. The genotypic frequency distribution did not fit the Hardy Weinberg Equilibrium (HWE) in either study group. The multiple logistic regression analysis showed a statistically significant difference for the rs1799998 polymorphism in the recessive model. Conclusion: the results suggest an association between the recessive model of C/C genotype of the rs1799998 polymorphism of the CYP11B2 gene and susceptibility to PE.

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Associated Factors of Plasmodium Knowlesi Malaria among Registered Malaria Cases in Terengganu, Malaysia 2011- September 2019 via Vekpro Online Database

Journal of Clinical and Health Sciences ◽

10.24191/jchs.v6i2.13052 ◽

2021 ◽

Vol 6 (2) ◽

pp. 23-35

Author(s):

Faizul Haris Hatta ◽

Zaliha Ismail ◽

Zahir Izuan Azhar ◽

Nurhuda Ismail ◽

Norafidah Abdul Rashid ◽

...

Keyword(s):

Logistic Regression ◽

Regression Analysis ◽

Logistic Regression Analysis ◽

Mixed Infection ◽

Associated Factors ◽

Plasmodium Knowlesi ◽

Multiple Logistic Regression Analysis ◽

Weather Data ◽

Multivariable Logistic Regression Analysis ◽

Online Database

Introduction: Plasmodium knowlesi (P. knowlesi), zoonotic malaria cases had been increasing in trend in Terengganu, Malaysia. This study aimed to determine the associated factors of P. knowlesi malaria among registered malaria cases in Terengganu from 2011 to September 2019 via the Vekpro Online Database. Methods: A cross-sectional study was conducted using registered malaria cases in Terengganu from 2011 to September 2019 extracted from the Vekpro Online database and secondary weather data from the Malaysian Meteorological Department. A total sample of 247 malaria cases [(P. knowlesi (n=187), P. falciparum (n=23), P. vivax (n=37), P. malariae (n=4), mixed infection (n=3)] were analysed. The cases were grouped into P. knowlesi group (P. knowlesi, P. malariae, mixed infection) and non-P. knowlesi group (P. falciparum, P. vivax) for comparison of their risk factors. Multiple Logistic Regression analysis was used to identify the associated factors. Results: Plasmodium knowlesi group contributed to 187 out of 247 (75.7%) of all malaria cases. Four factors were found to be significantly associated with P. knowlesi group in the final multivariable logistic regression analysis. Age [AOR=1.04 (95% CI: 1.01,1.08)], Malay race [AOR=39.43 (95% CI: 13.99,111.18)], agriculture and forestry worker [AOR=14.95 (95% CI: 4.10,54.51)] and Passive Case Detection [AOR=11.70 (95% CI: 2.60,52.63)] were the significant associated factors. Conclusion: Identified significant associated factors and characteristics of the high-risk group for P. knowlesi infection can help medical and health front liners in Terengganu in early diagnosis and prompt treatment of the cases. The factors also will help in the planning and development of health interventions in targeting P. knowlesi infection.

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Association between ALDH2 Variant and Alcohol Dependence in South Indian Population.

10.21203/rs.3.rs-1046349/v1 ◽

2021 ◽

Author(s):

A Umamageswari ◽

C Adithan ◽

Aarthi Manoharan ◽

Iyanar Kannan

Keyword(s):

Logistic Regression ◽

Regression Analysis ◽

Environmental Factors ◽

Alcohol Dependence ◽

Logistic Regression Analysis ◽

Multiple Logistic Regression Analysis ◽

Multivariate Logistic Regression Analysis ◽

Control Group ◽

South Indian Population ◽

South Indian

Abstract Background: Alcohol dependence (AD) poses a serious medical problem and significant public health issue contributing to morbidity and mortality throughout the world. The aim of the study is to test the association of rs698 (ADH1C) and rs671(ALDH2) with the risk of alcohol dependence and to further assess the influence of environmental factors on altering the genetic susceptibility to alcoholism in south Indian Tamilian population.Methods& Results: A total of 150 alcohol dependent cases aged between 18- and 65-years fulfilling DSM-V criteria were recruited from de addiction center. Subjects in control group (n=150) had history of alcohol intake with AUDIT score less than 8. The alleles were genotyped using TaqMan SNP genotyping assays by quantitative PCR. Association with alcohol dependence was evaluated with various genetic models using chi-square test. Multiple logistic regression analysis was performed to explore the effect of covariates. The dominant (OR=0.5811,95% CI: 0.372-0.9224, p<0.01) and allelic genetic model (OR=0.6228,95% CI: 0.4328-0.9009, p<0.01) of ALDH2, rs671 between cases and controls showed a significant association of the genetic variant with AD. Multivariate logistic regression analysis revealed education level, family history, marital status were significantly associated with AD but there was no association between rs671 genotypes in the presence of these co-variates.Conclusions: Genetic factors play an important role in alcohol dependence. Combined analysis of functional genetic variants and environmental factors is warranted in future studies.

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STUDY ON PRE-HYPERTENSION PREVALENCE AND RELATIONSHIP WITH DYSLIPIDEMIA IN ADULTS AT QUANG NAM PROVINCE

Journal of Medicine and Pharmacy ◽

10.34071/jmp.2019.4.10 ◽

2019 ◽

pp. 71-77

Author(s):

Muoi To ◽

Khanh Hoang ◽

Van Minh Huynh

Keyword(s):

Blood Pressure ◽

Logistic Regression ◽

Regression Analysis ◽

Logistic Regression Analysis ◽

Multiple Logistic Regression Analysis ◽

Blood Cholesterol ◽

Multivariable Logistic Regression Analysis ◽

Cholesterol Levels ◽

Optimal Blood Pressure ◽

High Triglyceride

Objectives: To investigate the prevalence, risk factors of prehypertension in QuangNam province of Vietnam. Methods: A case-control study of 3,237 adults (aged ≥ 25 years) was conducted in Quang Nam province, Vietnam in 2017, using questionnaire interviews, clinical examinations, and laboratory tests. Blood pressure, anthropometry, plasma glucose and lipids were measured. The variables contributing significantly to pre-hypertension were analyzed by multiple logistic regression analysis. Results: The prevalence of prehypertension was 30.7%, hypertension 31.6% and normal blood pressure was 37.7%. Lipid disorders such as high total cholesterol levels, high triglyceride levels, high LDL-C levels were significantly higher in prehypertensive than optimal blood pressure (BP). Multivariable logistic regression analysis revealed strong positive associations of pre-hypertension with high triglyceride levels (OR = 1.41, CI 95%: 1.13 - 1.75, p = 0.002); high LDL-C levels (OR = 1.42; CI 95%: 1.03 - 1.97; p = 0,034). The area under the ROC curve of triglyceride, cholesterol, LDL-C was 0.578; 0.566; 0.549, respectively. There was a positive correlation of blood cholesterol, blood triglyceride, blood LDL-C with changes in systolic BP, diastolic BP, and average BP. Conclusions: The prevalence of prehypertension in Quang Nam province of Vietnam was 30.7%. High cholesterol, high triglycerides, high LDL-C level were significantly associated with prehypertension. Key words: Lipid – prehypertension

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521. Predictors of Hospitalization Due to Coronavirus Disease 2019 (COVID-19) at a Veterans Affairs Medical Center

Open Forum Infectious Diseases ◽

10.1093/ofid/ofab466.720 ◽

2021 ◽

Vol 8 (Supplement_1) ◽

pp. S361-S362

Author(s):

Macy Ho ◽

Sarah Le ◽

Rajkumar J Sevak ◽

Jamie G Chapman-Bueno ◽

Stephen M Berman ◽

...

Keyword(s):

Logistic Regression ◽

Regression Analysis ◽

Logistic Regression Analysis ◽

Clinical Decision Making ◽

Diastolic Pressure ◽

Multiple Logistic Regression Analysis ◽

Laboratory Data ◽

Veterans Affairs ◽

Shortness Of Breath ◽

Unit Increase

Abstract Background During the COVID-19 pandemic, the Veterans Affairs Long Beach Healthcare System (VALB HCS) saw a surge of patients with a positive SARS-CoV-2 test. There is a lack of guidance on triaging patients with COVID-19 in the clinical literature. To address this need, our study evaluated factors that predicted hospitalization of patients due to COVID-19. Methods This was a retrospective cohort study of patients with a positive SARS-CoV-2 test and medical evaluation at the VALB HCS between August 1 and December 31, 2020. SARS-CoV-2 positive patients admitted to the hospital for a non-COVID-19 related diagnosis were excluded. At the time of initial evaluation, demographic, clinical, and laboratory data, and PCR cycle threshold were collected and compared between patients admitted to the hospital and those managed in the community. A multiple logistic regression analysis was conducted to evaluate predictors for hospitalization due to COVID-19. Results Of 748 patients, 94 were admitted to the hospital and 654 were community-managed. The outcomes from the logistic regression analysis indicated that the model explained 58.8% of variance and was a significant predictor of hospitalization (X2 [8, 737] = 277.5, p< 0.0001). Patients with self-reported shortness of breath (OR=12.14, 95% CI=6.43-22.92) or diarrhea (OR=2.78, 95% CI=1.33-5.84) were more likely to be hospitalized, whereas patients with sore throat (OR=0.095, 95% CI=0.017-0.53) or body ache (OR=0.42, 95% CI=0.20-0.89) were less likely to be hospitalized than patients not having such symptoms. Every unit increase in patients’ age and temperature increased the likelihood of hospitalization by 7.6% and 62.7%, respectively. Every unit increase in patients’ diastolic pressure and SpO2% decreased the likelihood of hospitalization by 6.1% and 3.6%, respectively. Conclusion Our findings indicate that patients with shortness of breath, diarrhea, temperature, and old age were more likely to be hospitalized due to COVID-19. The results may help providers in clinical decision making regarding whether to admit the patient or not. These findings may be especially helpful when hospital bed availability is limited. Disclosures All Authors: No reported disclosures

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RISK FACTORS OF PREECLAMPSIA WITH SEVERE FEATURES AND ITS COMPLICATIONS

Indonesian Midwifery and Health Sciences Journal ◽

10.20473/imhsj.v5i1.2021.29-37 ◽

2021 ◽

Vol 5 (1) ◽

pp. 29

Author(s):

Eka Suci Wulandari ◽

Ernawati Ernawati ◽

Djohar Nuswantoro

Keyword(s):

Risk Factors ◽

Logistic Regression ◽

Regression Analysis ◽

Logistic Regression Analysis ◽

Gestational Age ◽

Multiple Logistic Regression Analysis ◽

Severe Preeclampsia ◽

Control Group ◽

P Value ◽

Multiple Logistic Regression

Abstract.Background : The maternal mortality rate in Indonesia is dominated by preeclampsia as the second highest cause after bleeding. Several predictors can be categorized as risk factors that can be used to increase alertness in the care of pregnant women with severe preeclampsia to avoid complications. The purpose of this study was to study the relationship between risk factors for severe preeclampsia and its complications. Methods: This study used an observational analytic method with a case control design. The sampling technique is simple random sampling. The number of samples in this study were 80 samples, with 40 samples in each group. The case group was severe preeclampsia with one complication and the control group was severe preeclampsia without complications. Statistical analysis used was chi square and multiple logistic regression analysis. Results: The results showed that there was a significant relationship between age variables (p value = 0.001 < 0.05; OR = 5.318; CI = 2.118 – 13,356), BMI (p value = 0.002 < 0.05; OR = 6.000; CI = 1.958 – 18.384 ) and gestational age (p value = 0.039 < 0.05; OR = 2.636; CI = 1.040 – 6.685). Multiple logistic regression analysis showed that BMI (p = 0.003), age (p = 0.001) and gestational age (p = 0.048) were variables included in the final modeling of the regression analysis with the incidence of severe preeclampsia complications. Conclusion: BMI is the variable that has the strongest relationship with the incidence of severe preeclampsia complications.

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Comparison of Hospitalized Patients with Severe Pneumonia Caused by COVID-19 and Highly Pathogenic Avian Influenza (H7N9): A Retrospective Study from A Designated Hospital

10.21203/rs.3.rs-135753/v1 ◽

2020 ◽

Author(s):

Binbin Gu ◽

Lin Yao ◽

XinYun Zhu ◽

Pei-jun Tang ◽

Cheng Chen

Keyword(s):

Logistic Regression ◽

Regression Analysis ◽

Logistic Regression Analysis ◽

Multiple Logistic Regression Analysis ◽

Severe Pneumonia ◽

Multivariable Logistic Regression Analysis ◽

Fisher Exact Test ◽

Exact Test ◽

Viral Shedding ◽

Medical Supplies

Abstract Background: Considerable attention has been focused on clinical features of Coronavirus Disease 2019 (COVID-19), it is also important for clinicians to differentiate it from influenza virus infections.Methods: The clinical data of 23 cases of H7N9 and 23 cases of COVID-19 with severe pneumonia were collected. The comparisons were performed with the t test, Mann-Whitney U test, Fisher exact test or the chi-squared test, and multivariable logistic regression analysis.Results: All of the cases were under the circumstance of sufficient medical staff and medical supplies. Radiologically, severe COVID-19 patients had less consolidation and pleural effusion, but more crazy-paving pattern than severe H7N9 patients (p<0.05). Clinically, compared to severe H7N9, severe COVID-19 patients were more inclined to surfer to relative better disease severity score, less secondary bacterial infection, a shorter time to beginning absorption on CT, but a longer duration of viral shedding from the admission (p<0.05). Although more severe H7N9 patients needed non-invasive respiratory support, these two groups ultimately yielded comparable mortality. Based on multiple logistic regression analysis, severe COVID-19 infection was associated with a lower risk of the presence of severe ARDS (OR 0.964, 95% [CI] 0.931-0.998, p=0.040), but exhibited longer duration of viral shedding (OR 0.734, 95% [CI] 0.550-0.980, p=0.036) than severe H7N9 infection.Conclusion: Although the conditions of severe H7N9 patients seemed to be more critical than those of severe COVID-19 patients, the relatively lower mortality of these two severe cases is to be expected in context of sufficient medical supplies.

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Association between obesity and chronic rhinosinusitis with nasal polyps: a national population-based study

BMJ Open ◽

10.1136/bmjopen-2020-047230 ◽

2021 ◽

Vol 11 (5) ◽

pp. e047230

Author(s):

Jae-Sung Nam ◽

Yun Ho Roh ◽

Wasan Almazouq Fahad ◽

Hae-Eun Noh ◽

Jong-Gyun Ha ◽

...

Keyword(s):

Logistic Regression ◽

Regression Analysis ◽

Chronic Rhinosinusitis ◽

Logistic Regression Analysis ◽

Central Obesity ◽

Nasal Polyps ◽

Control Group ◽

Cross Sectional ◽

Cross Sectional Analysis ◽

Sectional Analysis

ObjectivesWe performed a cross-sectional analysis of data from the nationwide Korea National Health and Nutrition Examination Survey to evaluate the association between obesity and chronic rhinosinusitis with nasal polyps (CRSwNP) or without nasal polyp (CRSsNP).DesignRetrospective cross-sectional analysis of health survey data.SettingVoluntary survey of representative South Korean populations.ParticipantsIn total, 32 384 individuals aged 19 years or older with available data on CRS and obesity were included.Primary and secondary outcome measuresDiagnosis of CRSwNP or CRSsNP was performed by trained otolaryngologists through sinus endoscopy and surveys of medical history. General and central obesity was diagnosed using body mass index (BMI) and waist circumference (WC), respectively.MethodsA multivariate logistic regression analysis was used to clarify the association between CRSwNP or CRSsNP and obesity according to BMI and WC. Non-obese individuals were recruited as controls.ResultsThe prevalence of CRSwNP was higher in the general (OR, 1.438; 95% CI, 1.170 to 1.768; p<0.001) and central (OR, 1.251; 95% CI, 1.031 to 1.520; p=0.033) obesity groups than in the control group. Prevalence of CRSsNP was not correlated with obesity. In a logistic regression analysis, olfactory dysfunction (OR, 1.329; 95% CI, 1.137 to 1.553; p<0.001) and purulent discharge (OR, 1.383; 95% CI, 1.193 to 1.603; p<0.001) showed a higher incidence in the central obesity group than in the control group.ConclusionsWe demonstrated an association between CRSwNP and general and central obesity. Further investigations on the mechanism underlying this correlation are necessary for an improved understanding of the pathogenesis of CRSwNP.

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Annual Disease Experience by Type and Correlations with Unmet Healthcare Needs among ROK Military Personnel

Military Medicine ◽

10.1093/milmed/usz458 ◽

2020 ◽

Vol 185 (7-8) ◽

pp. e944-e951

Author(s):

Hwi Jun Kim ◽

Sarah So Yeon Oh ◽

Dong Woo Choi ◽

Sun Yeong Won ◽

Hae Jung Kim ◽

...

Keyword(s):

Logistic Regression ◽

Regression Analysis ◽

Logistic Regression Analysis ◽

Military Personnel ◽

Private Insurance ◽

Multiple Logistic Regression Analysis ◽

Healthcare Needs ◽

Unmet Healthcare Needs ◽

Number Of Patients ◽

Disease Experience

Abstract Introduction The National Statistical Yearbook of Defense 2018 issued by the Republic of Korea (ROK) Ministry of National Defense reported that the number of patients using military hospitals steadily increased from 2008 to 2017. However, in the outpatient clinic statistics for years 2015–2017 from the ROK Armed Forces Medical Command, the amount of medical care received from some medical departments, such as the infection medicine, surgery, and anesthesiology departments, decreased. Therefore, the purpose of this study was to observe the differences in incidence of military personnel’s unmet healthcare needs according to number of diseases by type. Materials and Methods The study used data from the Military Health Survey, which was conducted from 2014 to 2015 and included 5162 responses from ROK military personnel. The number of diseases by type and unmet healthcare needs were self-reported. A multiple logistic regression analysis was used to examine the validity of the annual disease experience by type and correlations with unmet healthcare needs. Results Of the 5162 military personnel, 25.2% experienced unmet healthcare needs, and the more people with the number of disease by type, the more likely they were to experience unmet healthcare needs (1: 13.4%, 2: 22.9%, 3: 29.2%, 4: 34.5%, 5: 41.4%). The logistic regression analysis also revealed significant differences (1 = REF, 2 odds ratio (OR) = 1.83, 95% confidence interval (CI): 1.50–2.24; 3 OR = 2.53, 95% CI: 2.05–3.11, 4 OR = 3.10, 95% CI = 2.49–3.85; ≥5 OR = 3.85, 95% CI = 3.08–4.81). In addition, subgroup analysis showed that female military personnel are more likely to experience unmet healthcare needs than are male military personnel. We have also confirmed that working areas and private insurance can affect unmet healthcare needs. Conclusion This study suggests that unmet healthcare needs are influenced by the number of disease by the type of ROK military personnel. It is therefore necessary to strive to reduce the number of military personnel who experience unmet healthcare needs through this data.

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