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 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 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 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.

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 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.

scholarly journals Prediction of successful de-cannulation of tracheostomised patients in medical intensive care units

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Chul Park ◽  
Ryoung-Eun Ko ◽  
Jinhee Jung ◽  
Soo Jin Na ◽  
Kyeongman Jeon
Keyword(s):  
Logistic Regression ◽  
Regression Analysis ◽  
Logistic Regression Analysis ◽  
Goodness Of Fit ◽  
Characteristic Curve ◽  
Multivariable Logistic Regression Analysis ◽  
Limited Data ◽  
Underlying Malignancy ◽  
Medical Intensive Care ◽  
Good Calibration

Abstract Background Limited data are available on practical predictors of successful de-cannulation among the patients who undergo tracheostomies. We evaluated factors associated with failed de-cannulations to develop a prediction model that could be easily be used at the time of weaning from MV. Methods In a retrospective cohort of 346 tracheostomised patients managed by a standardized de-cannulation program, multivariable logistic regression analysis identified variables that were independently associated with failed de-cannulation. Based on the logistic regression analysis, the new predictive scoring system for successful de-cannulation, referred to as the DECAN score, was developed and then internally validated. Results The model included age > 67 years, body mass index < 22 kg/m2, underlying malignancy, non-respiratory causes of mechanical ventilation (MV), presence of neurologic disease, vasopressor requirement, and presence of post-tracheostomy pneumonia, presence of delirium. The DECAN score was associated with good calibration (goodness-of-fit, 0.6477) and discrimination outcomes (area under the receiver operating characteristic curve 0.890, 95% CI 0.853–0.921). The optimal cut-off point for the DECAN score for the prediction of the successful de-cannulation was ≤ 5 points, and was associated with the specificities of 84.6% (95% CI 77.7–90.0) and sensitivities of 80.2% (95% CI 73.9–85.5). Conclusions The DECAN score for tracheostomised patients who are successfully weaned from prolonged MV can be computed at the time of weaning to assess the probability of de-cannulation based on readily available variables.

scholarly journals Prevalence of postural deviations and associated factors in children and adolescents: a cross-sectional study

2016 ◽  
Vol 29 (4) ◽  
pp. 777-786 ◽  
Author(s):  
Mariana Vieira Batistão ◽  
Roberta de Fátima Carreira Moreira ◽  
Helenice Jane Cote Gil Coury ◽  
Luis Ernesto Bueno Salasar ◽  
Tatiana de Oliveira Sato
Keyword(s):  
Physical Activity ◽  
Logistic Regression ◽  
Regression Analysis ◽  
Logistic Regression Analysis ◽  
Associated Factors ◽  
Multiple Logistic Regression Analysis ◽  
Extrinsic Factors ◽  
Cross Sectional ◽  
Postural Changes ◽  
Intrinsic And Extrinsic Factors

Abstract Introduction: Postural deviations are frequent in childhood and may cause pain and functional impairment. Previously, only a few studies have examined the association between body posture and intrinsic and extrinsic factors. Objective: To assess the prevalence of postural changes in school children, and to determine, using multiple logistic regression analysis, whether factors such as age, gender, BMI, handedness and physical activity might explain these deviations. Methods: The posture of 288 students was assessed by observation. Subjects were aged between 6 and 15 years, 59.4% (n = 171) of which were female. The mean age was 10.6 (± 2.4) years. Mean body weight was 38.6 (± 12.7) kg and mean height was 1.5 (± 0.1) m. A digital scale, a tapeline, a plumb line and standardized forms were used to collect data. The data were analyzed descriptively using the chi-square test and logistic regression analysis (significance level of 5%). Results: We found the following deviations to be prevalent among schoolchildren: forward head posture, 53.5%, shoulder elevation, 74.3%, asymmetry of the iliac crests, 51.7%, valgus knees, 43.1%, thoracic hyperkyphosis, 30.2%, lumbar hyperlordosis, 37.2% and winged shoulder blades, 66.3%. The associated factors were age, gender, BMI and physical activity. Discussion: There was a high prevalence of postural deviations and the intrinsic and extrinsic factors partially explain the postural deviations. Conclusion: These findings contribute to the understanding of how and why these deviations develop, and to the implementation of preventive and rehabilitation programs, given that some of the associated factors are modifiable.

scholarly journals Analysis and Factors Associated with Measles in Larut, Matang and Selama Districts, Perak, Malaysia

2020 ◽  
Vol 27 (5) ◽  
pp. 130-140
Author(s):  
Asraf Ahmad Qamruddin ◽  
Reza Qamruddin ◽  
Ayu Malik
Keyword(s):  
Logistic Regression ◽  
Regression Analysis ◽  
Incidence Rate ◽  
Logistic Regression Analysis ◽  
Protective Factor ◽  
Multiple Logistic Regression Analysis ◽  
Prior History ◽  
Multiple Logistic Regression ◽  
Case Definitions ◽  
Factors Associated

Objectives: To determine the incidence rate of measles and the factors associated with confirmed measles cases in Larut, Matang and Selama districts. Methods: Cross-sectional analysis was carried out looking at all suspected and laboratoryconfirmed measles cases in Larut, Matang and Selama districts between 2015 and 2019. Multiple logistic regression analysis was used to determine the associated factors for laboratory-confirmed measles cases. Results: The incidence rate for suspected measles showed an increasing trend from 2015–2019. For laboratory-confirmed measles cases, the incidence rate showed more variation with an increase to 36.11 per million population in 2017 from 5.67 per million population in 2015. The incidence rate later decreased to 10.99 per million population in 2018 and increased again to 24.47 per million population in 2019. From multiple logistic regression analysis, cases that fulfilled the case definition of measles were more likely to be laboratory-confirmed measles. On the other hand, a prior history of measles immunisation was a protective factor. Conclusion: Measles incidence is increasing in trend. Any suspected measles cases that fulfilled the clinical case definitions need to be further investigated. Immunisation should be promoted as they are effective in preventing and eliminating measles.

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