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

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

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

2021 ◽  
Author(s):  
Yulan Cai ◽  
Shili Zhang ◽  
Ying Cao ◽  
Fang Gao ◽  
Mengchen Zou
Keyword(s):  
Logistic Regression ◽  
Regression Analysis ◽  
Logistic Regression Analysis ◽  
Multiple Logistic Regression Analysis ◽  
Laboratory Data ◽  
Control Group ◽  
Multivariable Logistic Regression Analysis ◽  
Diabetic Patients ◽  
Patients With Diabetes ◽  
Bullosis Diabeticorum

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.

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

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.

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

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.

scholarly journals Is insulin an independent predictor of mortality in hemodialysis patients?

2004 ◽  
Vol 23 (1) ◽  
pp. 43-49
Author(s):  
Zorica Rasic-Milutinovic ◽  
Gordana Perunicic ◽  
Steva Pljesa ◽  
Vanja Ristic ◽  
Gordana Ristic ◽  
...  
Keyword(s):  
Blood Pressure ◽  
Logistic Regression ◽  
Regression Analysis ◽  
Logistic Regression Analysis ◽  
Cardiovascular Mortality ◽  
Serum Proteins ◽  
Multiple Logistic Regression Analysis ◽  
Multiple Logistic Regression ◽  
C Peptide ◽  
Lipids And Lipoproteins

Reduced insulin sensitivity is present in patients with end-stage renal failure (ERF). It has been established in general population that insulin resistance is a cardiovascular risk factor. The present study examines the potential effect of insulin action and secretion on over-all and cardiovascular mortality in non-diabetic haemodialysis (HD) patients. Sixty two patents (age 52.5 ? 10.3 year) on maintenance haemodialysis (5.4 ? 3.1 year) were recruited in June, 1994 and were followed-up over a 5-year period. At the end of the study we had two those who survived and those who died: survivals and deaths. All basic clinical indicators (age, gender, duration of dialysis prior to entry into the study, blood pressure, serum proteins, albumins, lipids and lipoproteins, urea, creatinine, dialysis dose defined by Kt/V, protein catabolic rate-nPCR, glucose, insulin, C peptide, IR-HOMA and % b- HOMA) were screened for a significant relation to outcome by univariante logistic regression models. Multiple logistic regression analysis was used to evaluate potentional independent predictors of death. Patients of both groups, survivals (n=42) and deaths (n=20), had a comparable duration of HD before the study, and as to blood pressure, serum proteins, albumines, lipids and lipoproteins A and B 100, lipoprotein (a), glucose, glycosylated haemoglobin, and Kt/V there were no significant differences. Patients who died were significantly older, and they had lower values of urea, creatinine, insulin, C-peptide and nPCR. Multiple logistic regression analysis indicated that only insulin and nPCR were significantly and independently associated with all-cause mortality and cardiovascular mortality, and age was an important confounding factor. These results suggest that we need an early procedure to preserve beta-cell function, besides positive nitrogen balance, to reduce cardiovascular and over-all mortality in haemodialysis patients.

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

2019 ◽  
pp. 51-57
Author(s):  
Muoi To ◽  
Khanh Hoang ◽  
Van Minh Huynh
Keyword(s):  
Risk Factors ◽  
Blood Pressure ◽  
Logistic Regression ◽  
Regression Analysis ◽  
Cardiovascular Risk ◽  
Alcohol Abuse ◽  
Cardiovascular Risk Factors ◽  
Logistic Regression Analysis ◽  
Abdominal Circumference ◽  
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, hypertension and normal blood pressure was 30.7%, 31.6% and 37.7%, respectively. Cardiovascular risk factors such as overweight and obesity, family history of hypertension, alcohol abuse, smoking, diabetes, high total cholesterol levels, high triglyceride levels, high LDL-C levels were significantly greater in prehypertensive compared to optimal blood pressure (BP). Multivariable logistic regression analysis revealed strong positive associations of pre-hypertension with alcohol abuse (OR = 1.68; CI 95%: 1.29-2.20; p < 0.001), diabetes (OR = 3.39; CI 95%: 1.32 - 8.65; p=0.011); 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). There was a positive correlation of cardiovascular risk factors such as BMI, abdominal circumference, blood glucose, 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%. Risk factors such as alcohol abuse, diabetes, high triglycerides, high LDL-C were significantly associated with prehypertension. Key words: cardiovascular risk factors - hypertension – prehypertension

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

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.

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

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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