scholarly journals Prevalence and determinants of incomplete or not at all vaccination among children aged 12–36 months in Dabat and Gondar districts, northwest of Ethiopia: findings from the primary health care project

BMJ Open ◽  
2020 ◽  
Vol 10 (12) ◽  
pp. e041163
Author(s):  
Asmamaw Atnafu ◽  
Gashaw Andargie ◽  
Mezgebu Yitayal ◽  
Tadesse Awoke Ayele ◽  
Kassahun Alemu ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Regression Analysis ◽  
Logistic Regression Analysis ◽  
Child Death ◽  
Multivariable Analysis ◽  
Northwest Ethiopia ◽  
Systematic Sampling ◽  
P Value ◽  
Vaccine Preventable Disease ◽  
Preventable Disease

ObjectiveEthiopia is one of the Africa’s signatory countries for implementation of the primary healthcare strategy including immunisation. In Ethiopia, however, 16% of child death is due to vaccine-preventable disease. Thus, this study aimed to assess the prevalence and determinants of incomplete or not at all vaccination among children aged 12–36 months in Dabat and Gondar districts, Northwest Ethiopia.Study designThe study is community-based cross-sectional study.Study settingDabat and Gondar Zuria districts, Northwest Ethiopia.ParticipantsMothers/caregivers with children aged 12–36 months were enrolled in the study. Participants were randomly selected through systematic sampling and a total of 603 participants were included in the analysis.MethodsA binary logistic regression analysis was done. In the multivariable logistic regression analysis, a p value of <0.05 and adjusted OR (AOR) with 95% CI were used to identify statistically associated factors with incomplete or not at all vaccination.OutcomesIncomplete or not at all vaccination.ResultsThe prevalence of incomplete or not at all vaccinated children was 23.10% (95% CI 16.50 to 29.70). The multivariable analysis revealed that the odds of incomplete or not at all vaccination were higher among mothers who had no antenatal care (ANC) visit (AOR: 1.81, 95% CI 1.21 to 4.03) and no postnatal care (PNC) visit (AOR=1.52, 95% CI 1.05 to 2.25).ConclusionsIn the study area, nearly one-fourth of children are incompletely or not at all vaccinated. Our finding suggests that ANC and PNC visits are key determinants of incomplete or not at all vaccination. Thus, in low-resource settings like Ethiopia, the health system approaches to improved ANC and PNC services should be intensified with more effective advice on child immunisation to reduce vaccine preventable disease.

scholarly journals Post-cesarean section surgical site infection and associated factors in East Gojjam zone primary hospitals, Amhara region, North West Ethiopia, 2020

PLoS ONE ◽  
2021 ◽  
Vol 16 (12) ◽  
pp. e0261951
Author(s):  
Hulubante Bizuayew ◽  
Haimanot Abebe ◽  
Getachew Mullu ◽  
Likinaw Bewuket ◽  
Daniel Tsega ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Regression Analysis ◽  
Cesarean Section ◽  
Surgical Site Infection ◽  
Logistic Regression Analysis ◽  
Multivariable Analysis ◽  
Outcome Variable ◽  
P Value ◽  
Multivariable Logistic Regression Analysis ◽  
Site Infection

Purpose Maternal surgical site infection after cesarean delivery is a clinical problem which contributes to significant morbidity and mortality. In Ethiopia admissions following cesarean section due to surgical site infection have been routine activities of health care institutions but there is limited scientific evidence on both the magnitude of the problem and factors associated with it making prevention mechanisms less effective. Therefore, this study aimed to assess magnitude and risk factors of post-cesarean section surgical site infection at primary hospitals of East Gojjam Zone, Northwest Ethiopia. Methods Institution-based cross sectional study with retrospective chart review was conducted from September 10–30 /2020 at 3 randomly selected primary hospitals of east Gojjam zone. The data were entered in Epi data version 3.1 and exported to Statistical Package for Social Science Software version 26. Post-cesarean section surgical site infection was measured based on disease classification and definition of the term by Center for Disease Control and Prevention. After checking for presence of multicollinarity, presence and degree of association of factors with outcome variable were computed through logistic regression analysis. Factors with P value ≤ 0.2 in bi-variable logistic regression analysis were included in the multivariable logistic regression analysis and those variables with P-value of <0.05 in multivariable analysis were considered statistically significant. Result From 622 medical records of women who underwent cesarean section, 77 (12.4%) of them developed surgical site infection. Rural residence [(AOR = 2.30, 95%CI: (1.29, 4.09)], duration of labor greater than 24hrs [(AOR = 3.48, 95%CI: (1.49, 8.09)], rupture of membrane>12hrs[(AOR = 4.61,95%CI:(2.34,9.09)], hypertension[(AOR = 3.14,95%CI:(1.29,7.59)] and preoperative Hematocrit ≤30%[(AOR = 3.22,95%CI:(1.25,8.31)] were factors significantly associated with post-cesarean section surgical site infections. Conclusion Magnitude of post-cesarean section surgical site infection was a significant problem in primary hospitals. Minimizing prolonged labor; minimize early rupture of membrane, properly managing patients with comorbidities like hypertension, strengthen prophylaxis and treatment for anemia during antenatal care and raising awareness for rural residents can reduce the problem. Zonal police makers should give emphasis to reduce its burden.

scholarly journals Post-cesarean section surgical site infection and associated factors in East Gojjam zone primary hospitals, Amhara region, North West Ethiopia, 2020

2021 ◽  
Author(s):  
Haimanot Geletie Abebe ◽  
Hulubante fetene bizuayew ◽  
Getachew Kassa Mullu ◽  
Likinaw Zeleke Bewuket ◽  
Daniel Tefera Tsega ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Regression Analysis ◽  
Cesarean Section ◽  
Surgical Site Infection ◽  
Logistic Regression Analysis ◽  
Multivariable Analysis ◽  
Outcome Variable ◽  
P Value ◽  
Multivariable Logistic Regression Analysis ◽  
Site Infection

Abstract Background Women after cesarean section have a five to twenty-times greater chance of getting an infection compared with women who give birth vaginally. Even though many efforts tried by the government and non-government organization in Ethiopia, a non-significant decline achieved and post cesarean section surgical site infection is still a problem. Scientific evidence on this is a step ahead for preventing and reducing post cesarean section surgical site infection. Therefore this study aimed to assess magnitude and risk factors of post cesarean section surgical site infection at primary hospitals of East Gojjam Zone, Northwest Ethiopia. Methods Institution based cross sectional study with retrospective chart review was conducted from September 10–30 /2020 at primary hospitals of east Gojjam zone. The data was entered in Epi data version3.1 and exported to Statistical Package for Social Science Software version 26. Presence and degree of association of factors with outcome variable were computed through logistic regression analysis. Factors with P value ≤ 0.2 in bi variable logistic regression analysis were included in the multivariable logistic regression analysis and those variables with P-value of < 0.05 in multivariable analysis were considered statistically significant. Result From 622 medical records of women who underwent cesarean section, 77 (12.4%) of them were developed surgical site infection. Rural residence [(AOR = 2.30, 95%CI :( 1.295, 4.098)], duration of labor greater than 24hrs [(AOR = 3.48, 95%CI :( 1.495, 8.086)], rupture of

scholarly journals Clinical profile and factors determining outcome of intramural very low birth weight babies in a tertiary care centre: a retrospective study

2017 ◽  
Vol 5 (2) ◽  
pp. 520
Author(s):  
Devi Meenakshi K. ◽  
Arasar Seeralar A. T. ◽  
Srinivasan Padmanaban
Keyword(s):  
Risk Factors ◽  
Logistic Regression ◽  
Regression Analysis ◽  
Birth Weight ◽  
Low Birth Weight ◽  
Logistic Regression Analysis ◽  
Very Low Birth Weight ◽  
Tertiary Care ◽  
P Value ◽  
Increased Risk

Background: Very low birth weight (VLBW) babies are at increased risk of a number of complications both immediate and late. Worldwide it has been observed that these babies contribute to a significant extent to neonatal mortality and morbidity. Aim of the study was to study the risk factors contributing to mortality in VLBW babies and to evaluate the morbidity pattern in these infants.Methods: A retrospective analysis of data retrieved from the case records of VLBW babies admitted in the NICU of Kilpauk Medical College between January 2015 to December 2015. Out of the 2360 intramural babies admitted during the study period, 99 babies were less than 1500 gms. The risk factors for these babies were analyzed for their association with the outcome. Data were statistically analyzed.Results: In present study, we found that sex of the baby, gestational age, obstetric score, birth asphyxia, pulmonary haemorrhage, ROP and presence of shock were found to be associated with increased mortality. By logistic regression analysis it was observed that birth weight of the baby (p value 0.002), duration of stay (p value 0.0006), presence of shock (p<0.0001), were the risk factors significantly associated with poor outcome.Conclusions: Among the maternal and neonatal factors analyzed in the study using logistic regression analysis, birth weight, duration of hospital stay and presence of shock were significantly related to poor outcome. Of these presence of shock was the single most important factor that predicted increased mortality.

scholarly journals Factors affecting the occurrence of proximal endoleak after endovascular abdominal aortic repair for abdominal aneurysms

2020 ◽  
Vol 48 (11) ◽  
pp. 030006052097151
Author(s):  
Daniela Mazzaccaro ◽  
Girolomina Mazzeo ◽  
Gianmarco Zuccon ◽  
Alfredo Modafferi ◽  
Giovanni Malacrida ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Regression Analysis ◽  
Logistic Regression Analysis ◽  
Aortic Aneurysms ◽  
P Value ◽  
Chi Square ◽  
Factors Affecting ◽  
Axial Diameter ◽  
Abdominal Aortic ◽  
Type Ia

Objective This retrospective study was performed to assess the clinical and radiological variables associated with proximal type IA endoleak (EL) in patients treated with elective endovascular repair for abdominal aortic aneurysms. Methods The chi-square test, t-test, and logistic regression analysis were performed as appropriate. A P value of <0.05 was considered statistically significant. Results The data of 79 patients were analyzed. No mortality occurred. During follow-up (median, 28.5 months; interquartile range, 12.8–43.0 months), 10 patients developed type IA EL. In the logistic regression analysis, undersizing of the endograft diameter by <10% significantly affected the occurrence of type IA EL. When the diameter was used for measurements, less oversizing was significantly associated with a higher risk of type IA EL. When the area was used for measurements, oversizing of >20% significantly affected the occurrence of type IA EL. Conclusion When sizing endografts, a discrepancy was noted between the measurements of the diameter and area of the proximal neck. The area might represent a more accurate measurement than the axial diameter to optimize the proximal sealing and lower the risk of developing type IA EL.

scholarly journals Spatial Logistic Regression Modeling With Inverse Weighting Distance For Open Unemployment In Districts/Cities On The Island Of Sulawesi

2020 ◽  
Vol 9 (1) ◽  
Author(s):  
Broklyn Pippo Marchegiani Baebae ◽  
Nur’eni Nur’eni ◽  
Iman Setiawan
Keyword(s):  
Logistic Regression ◽  
Regression Analysis ◽  
Logistic Regression Analysis ◽  
Moran’S I ◽  
P Value ◽  
Moran's I ◽  
Weighting Matrix ◽  
Inverse Weighting ◽  
Spatial Influence ◽  
Logistic Regression Method

Unemployment is a condition where a person does not have a job, but is looking for a job. To see the unemployment situation in an area, logistic regression analysis can be used. Logistic regression is an analysis used to see the relationship between the response variable (Y) which is binary and the explanatory variable (X) which is categorical or continuous. The application of logistic regression often has a spatial influence on the model. In this study to model the open unemployment rate the spatial logistic regression method is used. Spatial logistic regression is logistic regression analysis by incorporating spatial influences into the model. Spatial dependency testing is used by Moran’s I Test. The weighting matrix used is the distance inverse weighting matrix. The results obtained, the value of Moran's I Test with a p-value of 2.14 x 10-12 <α (0.05), meaning that there is a spatial influence on the level of open unemployment on the island of Sulawesi. So the spatial logistic regression model is obtained as follows : g(x)    = 4,848 0,000002885(X1) 0,0473(X2) 0,006669(X3) 0,04263(X4) 0,269(X5) 0,1642(X6) 1,531(X7) 0,1581(X8) 0,2208(X9) 0,009732(X10) 0,01871(Z) Spatial factors affect the level of open unemployment based on the significance value <α (0.05)

scholarly journals Prevalence and Risk Factors for Mortality among COVID-19 Patients Hospitalized in Karachi City Pakistan

2021 ◽  
Vol 2 (3) ◽  
pp. 66-71
Author(s):  
Salman Imtiaz ◽  
Ashar Alam ◽  
Faiza Saeed ◽  
Beena Salman ◽  
Shoukat Memon ◽  
...  
Keyword(s):  
Risk Factors ◽  
Logistic Regression ◽  
Regression Analysis ◽  
Logistic Regression Analysis ◽  
Virus Disease ◽  
Multivariate Logistic Regression Analysis ◽  
Ethical Review ◽  
P Value ◽  
Age Group ◽  
Continuous Variables

Background: Corona virus disease (Covid -19) is the most contagious form of the disease of present time. Therefore, the risk factors which proliferate the spread and hinders the better outcome should be identified. There is gross difference in the spread and outcome of covid 19 in different region of the world. There is need to identify these factors in different communities of the globe. Material and method: This is a retrospective observational cohort study of Covid -19 patients admitted during the study period. Institutional and ethical review board permission was taken prior to the study. Univariate and multivariate binary logistic regression was run and odds ratio with 95% confidence intervals were obtained. P value of ≤ 0.05 was considered significant. Outcome variables were recovery and death. Results: There were 840 patients admitted between the study duration, while 704 (83.8%) were included in our study. There were 491(69.7%) males and 213(30.3%) females. The mean age of the population was 54.6±15.5 years. All continuous variables were categorized according to binary outcome (recovered and death) of patients. In Logistic regression analysis we found that patients in age group of 51-65 years died 2.5 time more than patients of age ≤ 50 years. Similarly, the patients within age group of > 65 died 4.5 times higher than ≤ 50 years of age (p<0.001). Male patients died 1.5 times more than females. Among all comorbid conditions HTN had significant effect on death, they died 1.5 times more than normotensive patients. In multivariate logistic regression analysis, the age groups had same significant effect on death when adjusted with other parameters, while effect of gender vanished. Similarly, the effect of HTN was also abolished when other factors were included in analysis. Conclusion: We concluded that there is an urgent need of reevaluation of the traditional risk factors associated with viral epidemic and understanding the changing paradigm of epidemiology emerging out from this epidemic in both developed and developing counties. There is need of more data from developing world to elucidate the risk factors.

scholarly journals Cancer Patients at Risk for Medication-Related Osteonecrosis of the Jaw. A Case and Control Study Analyzing Predictors of MRONJ Onset

2021 ◽  
Vol 10 (20) ◽  
pp. 4762
Author(s):  
Antonia Marcianò ◽  
Ylenia Ingrasciotta ◽  
Valentina Isgrò ◽  
Luca L’Abbate ◽  
Saveria Serena Foti ◽  
...  
Keyword(s):  
Risk Factors ◽  
Risk Assessment ◽  
Logistic Regression ◽  
Regression Analysis ◽  
Zoledronic Acid ◽  
Cancer Patients ◽  
Logistic Regression Analysis ◽  
Osteonecrosis Of The Jaw ◽  
P Value ◽  
Multiple Variables

The goal of this investigation was to identify potential risk factors to predict the onset of medication-related osteonecrosis of the jaw (MRONJ). Through the identification of the multiple variables positively associated to MRONJ, we aim to write a paradigm for integrated MRONJ risk assessment built on the combined analysis of systemic and local risk factors. The characteristics of a cohort of cancer patients treated with zoledronic acid and/or denosumab were investigated; beyond the set of proven risk factors a new potential one, the intake of new molecules for cancer therapy, was addressed. Registered data were included in univariate and multivariate logistic regression analysis in order to individuate significant independent predictors of MRONJ; a propensity score-matching method was performed adjusting by age and sex. Univariate logistic regression analysis showed a significant effect of the parameters number of doses of zoledronic acid and/or denosumab (OR = 1.03; 95% CI = 1.01–1.05; p = 0.008) and chemotherapy (OR = 0.35; 95% CI = 0.17–0.71; p = 0.008). The multiple logistic regression model showed that breast, multiple myeloma, and prostate cancer involved a significantly higher risk compared to lung cancer; a significant effect of the combined variables number of doses of zoledronic acid and/or denosumab (OR = 1.03; 95% CI = 1.01–1.06); p-value = 0.03) and exposure to novel molecule treatment (OR = 34.74; 95% CI = 1.39–868.11; p-value = 0.03) was observed. The results suggest that a risk assessment paradigm is needed for personalized prevention strategies in the light of patient-centered care.

scholarly journals Facemask wearing to prevent COVID-19 transmission and associated factors among taxi drivers in Dessie City and Kombolcha Town, Ethiopia

PLoS ONE ◽  
2021 ◽  
Vol 16 (3) ◽  
pp. e0247954
Author(s):  
Tarikuwa Natnael ◽  
Yeshiwork Alemnew ◽  
Gete Berihun ◽  
Masresha Abebe ◽  
Atsedemariam Andualem ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Regression Analysis ◽  
Logistic Regression Analysis ◽  
Odds Ratio ◽  
Associated Factors ◽  
Multivariable Analysis ◽  
World Health ◽  
Multivariable Logistic Regression Analysis ◽  
Taxi Drivers ◽  
Targeted Interventions

Background The World Health Organization (WHO) has pointed out that urban taxi drivers and their passengers are at higher risk of transmitting coronavirus disease 19 (COVID-19) due to frequent contact among many people. Facemask wearing is one of the preventive measures recommended to control the transmission of the virus. A lack of evidence of the proportion of facemask wearing among taxi drivers and associated factors in Ethiopia, including Dessie City and Kombolcha Town, hinders the design of targeted interventions to advocate for facemask use. This study was designed to address this gap. Methods A cross-sectional study was conducted among 417 taxi drivers in Dessie City and Kombolcha Town from July to August, 2020. The study participants were selected using a simple random sampling technique after proportionally allocating the sample size from the total number of taxi drivers working in Dessie City and Kombolcha Town. The data were collected by trained data collectors using a structured questionnaire and an on-the-spot observational checklist. The collected data were checked, coded and entered to EpiData version 4.6 and exported to Statistical Package for Social Sciences (SPSS) version 25.0 for data cleaning and analysis. Bivariate (Crude Odds Ratio [COR]) and multivariable (Adjusted Odds Ratio [AOR]) logistic regression analyses were employed using 95% CI (confidence interval). From bivariate logistic regression analysis, variables with p-value < 0.250 were retained into multivariable logistic regression analysis. Then, from the multivariable analysis, variables with p-value < 0.050 were declared as factors significantly associated with facemask wearing among taxi drivers in Dessie City and Kombolcha Town. Main findings The proportion of taxi drivers who wore a facemask was 54.68% [95%CI: 50.10–59.7%]. The majority (58.3%) of drivers were using cloth facemasks, followed by N95 facemasks (24.5%) and surgical facemasks (17.3%). Out of the total 417 taxi drivers, more than two-thirds (69.8%) of them had a good knowledge about COVID-19 and 67.6% of taxi drivers had a positive attitude towards taking precautions against transmission of COVID-19. Three-fourths (74.1%) of the taxi drivers believed that wearing a facemask could prevent COVID-19. More than half (52.5%) felt discomfort when wearing a facemask. Almost three-fourths (72.2%) of taxi drivers felt that the presence of local government pressure helped them to wear a facemask. We found that marital status [AOR = 3.14, 95%CI: 1.97–5.01], fear of the disease [AOR = 2.1, 95%CI: 1.28–3.47], belief in the effectiveness of a facemask [AOR = 5.6, 95%CI: 3.1–10.16] and feeling government pressure [AOR = 3.6, 95%CI: 2.16–6.13] were factors significantly associated with wearing a facemask. Conclusion We found that the proportion of facemask wearers among taxi drivers was relatively low in Dessie City and Kombolcha Town. In order to increase that number, government bodies should work aggressively to encourage more taxi drivers to wear a facemask. We also recommend that government and non-government organizations work very closely together to implement strategies that promote facemask use, including increasing the availability of inexpensive facemasks, and monitoring and controlling facemask use.

Identifying the Outliers Among Gene Expression Profiling (GEP)-Defined Low-Risk Myeloma Patients Treated with Total Therapy 2 and 3 (TT2, TT3)

Blood ◽  
2012 ◽  
Vol 120 (21) ◽  
pp. 195-195
Author(s):  
Frits van Rhee ◽  
Sarah Waheed ◽  
Saad Z Usmani ◽  
Joshua Epstein ◽  
Adam Rosenthal ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Regression Analysis ◽  
High Risk ◽  
Logistic Regression Analysis ◽  
Conflicts Of Interest ◽  
Low Risk ◽  
P Value ◽  
Cytogenetic Abnormalities ◽  
Stepwise Selection ◽  
Cut Point

Abstract Abstract 195 GEP analysis is a robust method to distinguish low- and high-risk multiple myeloma (MM), pertaining to 85% and 15% of newly diagnosed patients, respectively (Shaughnessy et al., Blood, 2007; 109:2276–84). As developed in TT2 and validated in TT3A and TT3B, we are now examining, similar to previous work in high-risk MM, whether we can define outliers among low-risk MM, i.e., patients not living up to the low-risk prediction model. Toward this end, we scrutinized early relapses in TT3A and TT3B within three years of protocol entry. Using logistic regression analysis, we identified baseline parameters including GEP, en route for distinguishing this high-risk subset among low-risk MM. Also examined was whether a new model could be built within low-risk disease that allowed for the identification of a high-risk subset. Our database was interrogated for patients known to have GEP-defined low-risk in the GEP-70 model. Table 1 summarizes the 3-year events among GEP-70 low-risk subjects per protocol. An optimal cut-point at +0.146 distinguished, among the combined TT2 and TT3 patients, inferior progression-free survival (PFS) and overall survival (OS) (Figure 1a). Next, we examined outcomes among all TT2 and TT3 patients with GEP data, including those with traditionally-defined high-risk (>=0.66). Here, we were able to distinguish three subgroups with distinctly different PFS and OS (Figure 1b). Utilizing logistic regression analysis, limited to traditionally-defined GEP-70 low-risk MM (=<0.66), three-year progression events during the this period were adversely dominated by the following: GEP-70 scores >0.146 (HR=2.61, p=0.0005), the presence of cytogenetic abnormalities (CA) (HR=1.93, p=0.018), B2M >5.5mg/L (HR=1.95, p=0.04) and LDH >190U/L (HR=1.93, 0.02). These are all reported in Table 2. In conclusion, we have identified, within GEP-70 low-risk patients, a new cut-point. This allows a better categorization of patients having truly low risk disease. Also, above which a prognosis intermediate to the traditional high-risk prognostic group (>=0.66) could be identified. GEP >0.146 dominated a multivariate logistic regression model. Further efforts will be presented on unique genes characterizing this intermediate risk group in relationship to low and high-risk subsets. Table 1. Three-year Events Among GEP-70 Subjects Per Protocol Protocol Total with GEP GEP-70 low-risk GEP-70 low-risk, event within first 3 years TT2 - thalidomide 176 156 55 TT2 + thalidomide 175 149 36 TT3A 275 235 39 TT3B 166 129 23 Table 2. Logistic Regression for 3-year Event Factors, TT2+3 GEP-70 Low-Risk (<0.66) Event in first three years on protocol Variable N With Factor Without Factor OR (95% CI) P - value Multivariate B2M > 5.5 mg/L 666 24/69 (35%) 59/328 (18%) 1.95 (1.03, 3.69) 0.0401 LDH >= 190 U/L 668 33/99 (33%) 50/298 (17%) 1.93 (1.10, 3.40) 0.0229 Cytogenetic abnormalities 665 35/116 (30%) 48/281 (17%) 1.93 (1.12, 3.32) 0.0182 GEP-70 score > 0.146 669 37/104 (36%) 46/293 (16%) 2.61 (1.52, 4.47) 0.0005 OR - Odds Ratio, 95% CI - 95% Confidence Interval, P - value from Wald Chi - Square Test in Logistic Regression. NS2 - Multivariate results not statistically significant at 0.05 level. Univariate p - values reported regardless of significance. Multivariate model uses stepwise selection with entry level 0.1 and variable remains if meets the 0.05 level. A multivariate p - value greater than 0.05 indicates variable forced into model with significant variables chosen using stepwise selection. Disclosures: No relevant conflicts of interest to declare.

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