Version Of Data Research Articles

IMK–IAA MIPAS retrieval version 8: CH4 and N2O

Abstract. Using the IMK–IAA data processor, methane and nitrous oxide distributions were retrieved from version-8 limb emission spectra recorded with the Michelson Interferometer for Passive Atmospheric Sounding (MIPAS). The dataset includes measurements from the nominal, upper troposphere–lower stratosphere, middle-atmosphere, upper-atmosphere and noctilucent-cloud observation modes. The processing differs from the previous version-5 data with respect to the atmospheric state variables that are jointly retrieved along with the target gases CH4 and N2O, the treatment of the radiance offset, the selection of microwindows, the regularization, the spectroscopic data used and the treatment of horizontal variability of the atmospheric state. Besides the regular data product, a coarse-grid representation of the profiles with unity averaging kernels is available, as well as a specific research product for middle-atmosphere measurements resulting from a slightly different retrieval approach. The CH4 errors are dominated by the large spectroscopic uncertainty for line intensities, which probably is too pessimistic, and estimated to be 21 %–34 % in the altitude range 6–68 km for northern midlatitude summer day conditions. The N2O errors are 7 %–17 % below 45 km. At higher altitudes they increase strongly due to nearly vanishing N2O amounts. Analysis of the horizontal averaging kernels reveals that for both gases the horizontal resolution is sampling-limited; i.e., information is not smeared over consecutive limb scans. Zonal-mean seasonal composites of both CH4 and N2O exhibit the typical distribution of source gases with strong upwelling in the tropics and subsidence above the winter poles. Comparison with the previous data version shows several improvements: first, the vertical resolution of the retrieved CH4 (N2O) profiles has generally been significantly enhanced and varies between 2.5 (2.5) and 4 (5) km at altitudes between 10 and 60 km, with the best resolution around 30 km for both species. Secondly, the number of non-converged retrievals has been clearly reduced, and thirdly, formerly strongly oscillating profiles are now considerably smoother.

Assessment of mothers’ satisfaction towards child vaccination service in South Omo zone, South Ethiopia region: a survey on clients’ perspective

BackgroundEven though childhood vaccination is a common and cost-effective public health intervention in preventing and reducing childhood disease and death, significant numbers of children do not complete vaccination within the first year of life. Studies indicated that user satisfaction influences service utilization and used as a key indicator of quality care. However, evidence on the level of mothers’ satisfaction with immunization service are limited in urban and accessible places and not well investigated among remote and pastoral communities. As such, this study aimed to address this gap and investigated mothers’ satisfaction towards child vaccination in a pastoralist and agrarian community of the South Omo zone in Southern region of Ethiopia.MethodsAn institution-based cross-sectional study was conducted among 1221 randomly selected mothers with children eligible for childhood vaccination using a structured, pretested, and interviewer-administered questionnaire. Maternal positive evaluations of the overall vaccination service were measured using 5-point Likert scale questions. Data were entered into Epi data version 3.5.1 and analyzed using IBM SPSS statistical package version 25. Exploratory factor analysis was used for Likert scale questions to extract factor scores which facilitate treatment of variables as continuous for further analysis. Bivariate and multivariable logistic regression analysis was employed to identify factors associated with the outcome variable. A P-value < 0.05 and adjusted odds ratio with 95% CI respectively were used to declare statistical significance and degree of association.ResultA total of 849 (69.53%) study participants were satisfied with the vaccination care provided for their children. Factors associated with mother’s satisfaction with child vaccination care include maternal age less than 30 years (AOR = 2.12; 95% CI = 1.61–2.79), infants age between 8 and 12 months (AOR = 1.83; 95% CI = 1.28, 2.62), not having history of adverse events following immunization (AOR = 1.57; 95% CI = 1.01–2.45), having 1 child under the age of 5 years (AOR = 1.34; 95% CI = 1.02–1.76), waiting 30 min or less to get the service (AOR = 1.39; 95% CI = 1.05–1.85), traveling 30 min or less to the vaccination center (AOR = 1.46; 95% CI = 1.08–1.98), having poor knowledge about the importance of vaccination (AOR = 1.51; 95% CI = 1.06–2.16), and having moderate knowledge about the importance of vaccination (AOR = 1.52; 95% CI = 1.06–2.18).ConclusionInterestingly, mothers’ satisfaction with their children’s vaccination service was relatively higher in a predominantly pastoral community compared with most of previous studies conducted in Ethiopia. Maternal and child age, number of children under the age of 5 years, history of adverse events following immunization, distance to the vaccination center, waiting time to get service and maternal knowledge were factors significantly associated with mothers’ satisfaction. Proactive measures with focus on increasing access to vaccination service, improving waiting time and raising awareness among mothers were recommended.

Elevation dependent climate assessment and its influence on snow cover variability in Hindu Kush Himalayan region using Google Earth Engine for the period of 2003–2021

The Hindu Kush Himalayan (HKH) regions are taken for this study, which is predominantly characterized by amplified climatic uncertainty and rapid snow melting. Because at the present there is a lack of studies estimating the elevation dependent and climate influenced snow cover variability in the HKH region. This present study examines elevation-dependent (2003–2021) distribution and trends in precipitation, temperature, and snow cover area (SCA) by employing numerous non-parametric statistical applications using the Google Earth Engine (GEE). The Modified Moderate Resolution Imaging Spectroradiometer (MODIS) Terra and Aqua snow cover data is employed to estimate SCA along with the Climate Hazards Group Infrared Precipitation with Station Data version 2.0 (CHIRPS-V2.0) for precipitation and MODIS land surface temperature (LST). The study reveals statistically significant decreasing annual, seasonal, and monthly trends of SCA in most of the elevation zones typically during winter season (−0.256%/year), whereas temperature and precipitation exhibit strong spatial variability. Inclusive investigation portrays maximum mean annual and seasonal increased precipitation at the low-elevated regions, whereas seasonal disparities in temperature ostensible marginal decreased at high-elevation, albeit increased at lowland. Moreover, topographic importance on SCA distribution showcases maximum snow (43.4%) at north-facing less surface inclination with flat topography (14.6%). The comprehensive elevation wise analysis improves our understanding of the overall hydrological challenge and assist in the development of more reliable flood forecasting and water resource management.

Revisiting the quantification of power plant CO2 emissions in the United States and China from satellite: A comparative study using three top-down approaches

Top-down constraints of CO2 emissions from coal-fired power plants are critical to improving the accuracy of CO2 emission inventory and designing carbon reduction strategies. Different top-down models based on satellite observation have been proposed in previous studies, but discrepancies between these models and the underlying drivers are rarely explored, limiting the confidence of their application for monitoring point-source CO2 emissions from satellite. Here, we apply three top-down models to estimate CO2 emissions from individual coal-fired power plants in the United States (US) and China in 2014–2021 from Orbiting Carbon Observatory 2 (OCO-2) satellite observations. The first one applies the Gaussian plume model to optimize emissions by fitting modeled CO2 enhancement to the observation. The second and third methods apply the same inversion framework using the maximum likelihood estimation, but with WRF-Chem and WRF-FLEXPART as forward models, respectively. We evaluate consistency between the three methods in estimating emissions of 10 power plants in the US, using daily reported values from the US Environmental Protection Agency (EPA) as a benchmark, and then apply the three methods to quantify emissions of 13 power plants in China. Results show that the WRF-Chem and WRF-FLEXPART based inversion results are consistent with the EPA reported emission rates, with correlation coefficients (r) of 0.76 and 0.85 and mean biases (MB) of 4.06 and 3.97 ktCO2/d relative to EPA reports at all 10 power plants, respectively. The Gaussian plume model driven by wind fields from WRF-Chem model without the wind rotation shows comparable ability in reproducing the EPA reported emission rates at 7 power plants (r = 0.82, MB = 6.17), but is not applicable for the other three cases. We find that application of the high-resolution three-dimensional wind fields can better capture the shape of observed plumes, especially under complex wind conditions, compared to the Gaussian plume model which relies on wind field at a single point, and thus the Gaussian plume model has difficulty to optimize emissions under inhomogeneous wind fields or when observations are far away from the power plant. In general, using the WRF-FLEXPART model as the forward model in the inverse analysis shows advanced capability to simulate narrow-shape plumes in the absence of numerical diffusion which is inherent in Eulerian model such as WRF-Chem. Emissions estimated by the three top-town methods show a moderate consistency at 13 coal-fired power plant cases in China, with 8 of 13 cases showing differences of <30% between at least two methods. However, large differences emerge when wind fields are inhomogeneous and number of available observations is limited. Using different meteorological wind fields and OCO-2 data versions can also bring substantial differences to the posterior emissions for all three approaches. We find that the posterior CO2 emissions, though only reflecting instantaneous emission rates at satellite overpass time, are not proportional to the reported capacities of these power plants, indicating that attributing CO2 emissions simply based on the capacity of power plants in some bottom-up approaches may have significant discrepancies. Our study exposes the capability and limitation of different top-down approaches in quantifying point-source CO2 emissions, advancing their application for better serving increasing constellations of point-source imagers in the future.

Spiritual well-being and associated factor among adult cancer patients in Hawassa University Comprehensive Specialized Hospital, Oncology Center, Hawassa, Ethiopia

Spiritual well-being and associated factor among adult cancer patients in Hawassa University Comprehensive Specialized Hospital, Oncology Center, Hawassa, Ethiopia

Investigating factors associated to HBV/HIV co-infected patients in antiretroviral treatment clinic, in Northeast Ethiopia.

Existing research in Ethiopia has primarily focused on the individual epidemiology of HIV and HBV, often overlooking the intricate dynamics of co-infection. This study aims to address this gap by comprehensively exploring the prevalence of HBV and HIV co-infection and the associated factors influencing co-infection rates within the specific context of ART clinics. The existing study provides limited insights into the unique challenges posed by this dual infection in the Ethiopian population receiving ART. An institutional-based cross-sectional study was conducted among people living with HIV aged 18 years and above attending ART clinics in northeast Ethiopia from April to May 2022. A sample size of 350(97% response rate) participants was selected by using a systematic random sampling method. Data were collected using a pre-tested interviewer-administered structured questionnaire. Data was entered into Epi Data version software and was exported to SPSS version 25 for further analysis. Descriptive statistics using Frequency, proportion, and summary measures were done. Binary logistic regressions were done to identify independent variables associated with HBV infection among HIV patients. A P-value less than 0.05 and adjusted odds ratio with a 95% confidence interval non-inclusive of one was considered statistically significant. The prevalence of Hepatitis B Surface Antigen (HBsAg) was identified constituting 7.14% of the study population. Females [AOR] 0.14; 95% Confidence Interval [CI] [0.041-0.478]). Participants with an educational status of only reading and writing (AOR 8.7; 95% CI [1.143-66.5]). Single individuals (AOR 2.04; 95% CI [1.346-28.6]) were associated factors. Moreover, participants with a viral load exceeding 1000 copies/ml were 6.5 times more likely to be infected with HBV compared to those with undetectable viral loads (AOR 6.53, 95% CI [1.87-22.72]). Additionally, individuals with a CD4 count ranging from 351 to 500 cells/ml were 1.2 times more likely to be infected with HBV compared to those with a CD4 count of 500 cells/ml or above (AOR 10.4, 95% CI [1.28-85]). The prevalence of HBV infection was found to be intermediate in HIV-infected patients in the study area. Being male, marital status of single and divorced, educational level was only read and written, current viral load of > 1000 copies/ml &<1000 copies/ml, and current CD4 < 250 cells/ml were found statistically associated factors for HBV infection. Thus, we recommend the provision of routine screening for HBsAg and appropriate treatment with accurate information on risk factors for HBV to improve quality of life and reduce morbidity.

Determinants of birth asphyxia among new born babies in Bekoji public hospital, Arsi zone, Oromia regional state, Ethiopia, 2023

Background: Birth asphyxia stands out as a significant factor contributing to morbidity and mortality among newborns. However, the determinants of birth asphyxia have not been thoroughly investigated within the local context, particularly in this specific area. Hence, this study aims to identify these determinants to tackle the issue effectively. Objectives: The goal of this study is to pinpoint the determinants of birth asphyxia at Bekoji Public Hospital in Bekoji Town, Arsi Zone, Oromia Region, Southeast Ethiopia, in 2023. Methods: A case-control study was conducted between June 1, 2023, and August 30, 2023. A total of 198 newborns (75 cases and 123 controls) at Bekoji Public Hospital were selected using a systematic random sampling technique. Data collection involved a checklist for record review and an interviewer-administered questionnaire. The data were entered into Epi Data version 7.1 and analyzed using SPSS version 25. Variables with a P-value &lt; 0.25 were subjected to multivariable regression analysis. The Odds Ratio estimated with a 95% Confidence Interval was utilized to indicate the strength of association, with a significance level set at P &lt; 0.05. Results: 196 mothers of newborns (73 cases and 123 controls) were interviewed, resulting in a response rate of 98.9%. Factors such as prolonged duration of labor (AOR=2.54; [95% CI: 1.78, 6.39]), delivery by Caesarean section (AOR=0.64; [95% CI: 0.004, 1.114]), presence of stained amniotic fluid (AOR=0.473; [95% CI: 0.180, 1.242]), and non-cephalic fetal presentation (AOR=2.12; [95% CI: 1.019, 3.80]) were identified as predictors of birth asphyxia. Additionally, being male (AOR=1.885; [95% CI: 0.899, 3.950]) was also found to be a predictive factor for birth asphyxia. Conclusion and recommendations: Duration of labor, fetal presentation, type of amniotic fluid, mode of delivery, and the gender of newborns emerged as significantly associated factors with birth asphyxia. As a result, interventions targeting these factors, particularly focusing on duration of labor and fetal presentation, should be rigorously implemented.

Survival status and its predictors among undernourished children on antiretroviral therapy in Bahir Dar city, Northwest Ethiopia, 2010 – 2020, a multicenter retrospective cohort study

BackgroundIn environments with limited resources, undernutrition is a serious public health risk. Its dual relationship to human immunodeficiency virus infection (HIV) leads to crises in a child's physical, emotional, social, and economic spheres of life. Nevertheless, little research has been done on the survival rate and risk factors that lead to poor survival outcomes in undernourished children receiving antiretroviral therapy. This study sought to evaluate survival status and its predictors among undernourished children on antiretroviral therapy (ART) in public health facilities, Bahir Dar city, September 1, 2010 – December 31, 2020.MethodsAn institution-based retrospective cohort study design was used among 414 study participants from September 1, 2010 – December 31, 2020. A simple random sampling method was applied to select study participants. All collected data were entered into epi data version 4.6 and exported to STATA version 14.0 for analysis. Each independent predictor variable with a p-value < 0.05 in the multivariable Cox proportional hazard regression was considered statistically significant.ResultsThe overall incidence of mortality was 11.6 deaths per 1000 child year observation (95%CI: 7.7- 17.5). Baseline weight for age < -3 Z score (adjusted hazard ratio (AHR) = 4.9, 95% CI: 1.30–18.98), height for age < -3 Z score (AHR = 4.34, 95%CI 1.13–16.6), cotrimoxazole prophylaxis given (AHR = 0.27, 95%CI 0.08–0.87), hemoglobin level < 10 g/dl (AHR = 3.7, 95%CI 1.1–12.7), CD4 cells < threshold (AHR = 4.86, 95%CI 1.9–12.7), and WHO clinical disease stage III and IV (AHR = 8.1, 95%CI 1.97–33) were found independent predictors of mortality.Conclusion and recommendationThe incidence of mortality was determined in the study to be 11.6 per 1000 child years. Mortality was predicted by severe stunting, severe underweight, a low hemoglobin level, a low CD4 count, and WHO clinical stages III and IV. But the risk of death is reduced by starting cotrimoxazole preventative therapy early. The risk factors that result in a low survival status should be the primary focus of all concerned bodies, and early cotrimoxazole preventive treatment initiation is strongly recommended.

Tripled likelihood: polypharmacy increases the occurrence of drug therapy problems in hospitalized pediatric patients.

A drug therapy problem (DTP) is any undesirable event experienced by a patient that accompanies drug therapy, prevents the patient from achieving their desired therapeutic goals, and requires expert judgment to resolve. Pediatric populations are at a higher risk of DTP than adults due to their immature organ systems, including the liver and kidneys, which play crucial roles in drug metabolism and excretion. Most previous studies have focused on only one element of DTP. Therefore, by considering all elements of DTP, we aimed to assess the prevalence of DTP and associated factors among pediatric patients admitted to the Wolaita Sodo University Comprehensive Specialized Hospital. An institution-based cross-sectional study was conducted among pediatric patients admitted to Wolaita Sodo University Comprehensive Specialized Hospital from 8 July 2020, to 7 July 2021. A simple random sampling technique was employed to select study participants. Cipolle's and Strand's classification method of drug therapy problems was used to identify and categorize DTP. Data were obtained by reviewing the patient's medical records using a data abstraction checklist, entered into Epi data version 4.6, and exported to SPSS version 25 for analysis. Binary logistic regression analysis was performed to identify independent predictors of DTP. Medical records of 369 pediatric patients were reviewed, and the overall prevalence of DTP was 60.2% (95% CI:55.2%, 65.2%) with a total of 281 identified DTPs. Among them, 164 (74.2%) had only one DTP. Need additional drug therapy was the most common (140 [49.8%]) DTP identified. The number of disease conditions (AOR = 2.13, 95% CI:1.16, 3.92), polypharmacy (AOR = 3.01, 95% CI:1.70, 5.32), and duration of hospital stay (AOR = 1.80, 95% CI:1.04, 3.10) were independent predictors of DTP among admitted pediatric patients. The prevalence of DTP in pediatric patients in the current setting was high. The number of disease conditions, polypharmacy, and duration of hospital stay were independent predictors of DTP. Enhancements to pharmaceutical care services, optimized dosage practices, improved deprescribing by clinicians, and efficient, comprehensive diagnostic procedures have the potential to significantly reduce specific drug therapy problems in hospitalized pediatrics.

Predictors of husbands in supporting wives to use obstetrics care services by health professionals, Dire Dawa administration, Ethiopia: a community based cross sectional study

Background: Husbands’ support in obstetric care services is a process of social and behavioral change that husbands must undergo to prevent obstetric complications. But so far, studies across Ethiopia have been inconsistent and lacking in the study area. Therefore, this study was aimed at assessing husbands’ predictors, which could help in interventions. Methods: A community-based cross-sectional study was conducted in the Dire Dawa administration, Ethiopia, from July 1-30, 2022. Participants were selected using a systematic sampling technique. Data were collected through interviews using a structured questionnaire, entered into EPI data (Version 3.1), and analyzed using SPSS (Version 22). A p=0.05 or less at multivariate with 95% confidence intervals was considered statistically significant. Results: Of a total of 610, 51.8% of husbands support wives in using obstetrics care services. The predictors were urban residence (AOR=2.55, 95% CI: 1.75-3.73), education level of diploma and above (AOR=2.00, 95%CI: 1.10-3.74), perceived importance (AOR=1.98, 95% CI: 1.30-3.00), antenatal care visit accompanying experience (AOR=1.79, 95% CI: 1.04-3.07), and institutional delivery accompanying experience (AOR=6.20, 95% CI: 3.4-1.33). Conclusions: One in two husbands supports wives to use obstetrics care services provided by health professionals. Findings are helpful in advancing knowledge of husbands’ factors and highlight the need for health facilities and stakeholders to strengthen and create continuous community awareness.

Burden and Predictors of Diabetic Nephropathy in an Adult With Diabetes Mellitus Patients on Follow up at Ambo University Referral Hospital Central Ethiopia

BACKGROUND: Despite the growing evidence of Diabetic Nephropathy in adult patients with long-standing diabetes in sub-Saharan Africa, data on its burden and correlates in adult African patients with diabetes are limited. We, therefore, undertook this study to determine the burden and predictors of Diabetic Nephropathy n an adult population with diabetes in Hospital. OBJECTIVE: We, therefore, undertook this study to determine the burden and predictors of Diabetic Nephropathy n an adult population with diabetes in Hospital. METHODS: A Hospital-based cross-sectional study was conducted from June to August, 2023 and a systematic random sampling method used to recruit participants. A total of 4,300 diabetics are under observation. The interviewer used structured questionnaires to gather data from the study subjects. For data entry and analysis, Epi Data version 3.1.1 and SPSS version 25 were used. Multivariable logistic regression analysis was done after descriptive statistics. 95% confidence intervals (CI) and crude and adjusted odds ratios were presented. RESULTS: Diabetic Nephropathy (DN) was documented in population was 24.9% from the 369 participants (95%; CI 23.37– 26.43) participants among the study). Male sex [AOR = 2.215; 95% CI: 1.34, 3.45, p = 0.002], physically inactive [AOR = 1.983; 95% CI: 1.05, 3.70), P = 0.034], dyslipidaemia [AOR: 1.98, CI: 1.009, 3.5), P = 0.024] and poor controlled glycemia [AOR= 2.70; 1.40, 5.2), P = 0.003] were significant determinants for the development of Diabetic Nephropathy. Therefore, it is advised that healthcare professionals pay close attention to patients who have recognized related factors during follow-up in order to reduce the likelihood of DN. CONCLUSION: Among DM patients, sex, physical inactivity, dyslipidaemia, and poor glycemic control were discovered to be the predictors of diabetic nephropathy. By enhancing programs for health information, education, and promotion, diabetes management should be better equipped to achieve glycaemic control and prevent diabetic nephropathy. Male sex, sedentary lifestyles, dyslipidemia, and patients with poor glycemic control need to receive more attention.

Common mental disorders and associated factors among mothers of children attending severe acute malnutrition treatment in Gedio Zone, Southern Ethiopia, 2022: a cross-sectional study

BackgroundCommon mental disorders describe the physical, mental, and social disturbances that are more prevalent in low and middle-income countries. Mothers are among the more vulnerable groups especially mothers having children with under-nutrition. However, there are limited studies about the magnitude of common mental disorders among mothers of undernourished children in Ethiopia. Therefore, we aimed to assess the magnitude of common mental disorders and associated factors among mothers of children attending severe acute malnutrition treatment in Gedio Zone, Southern Ethiopia.MethodsA cross-sectional study was employed on 405 systematically selected participants. The outcome variable was assessed by a self-reporting questionnaire (SRQ-20) which was applicable and validated in Ethiopia. Data were entered and analyzed by EPi data version 5 software and SPSS version 25 respectively. Model fitness was checked by Hosmer Lemeshow’s test. Logistic regression was employed to identify significant determinants. A p-value < 0.05 was used to declare association and expressed by odds ratio with a 95% CI.ResultIn this study, the magnitude of common mental disorders was 33.16% (95% CI [28.5–38])). In multivariable analysis, six factors poor social support [AOR: 14.0, 95% CI (5.45, 35.9)], educational status [AOR: 1.95, 95% CI (1.07. 3.55)], cigarette smoking [AOR: 10.9, 95% CI (1.78, 67.01)], mother of a child with another chronic disease [AOR: 3.19, 95% CI (1.13, 8.99)], sexual violence [AOR: 4.14, 95% CI (1.38, 12.4)] and mothers with chronic disease [AOR: 3.44, 95% CI (1.72, 6.86)] were significantly associated with common mental disorders.ConclusionThe magnitude of common mental disorders was high. Six factors were significantly associated with common mental disorders; social support, sexual violence, maternal chronic illness, educational status, smoking, and mother of child with other chronic disease. Community awareness regarding the effect of violence, substance use, and social support on mental health should be created by the local stakeholders.

HIV seroconversion and associated factors among seronegative pregnant women attending ANC in Ethiopia: an institution-based cross-sectional study.

In countries with limited resources, including Ethiopia, HIV is diagnosed using a rapid serological test, which does not detect the infection during the window period. Pregnant women who test negative for HIV on the first test may seroconvert throughout pregnancy. Women who are seroconverted during pregnancy may not have received interventions, as they are considered HIV-negative unless they are retested for HIV at the end of their pregnancy. Due to limited data on HIV seroconversion, this study aimed to measure the extent of HIV seroconversion and to identify associated factors among seronegative pregnant women attending ANC in Ethiopia. Institution-based cross-sectional study was conducted among HIV-negative pregnant women attending the ANC in Ethiopia between June and July 2020. Socio-demographic, clinical, and behavioral data were collected through face-to-face questionnaires and participants' records review. HIV retesting was performed to determine the current HIV status of pregnant women. The data collected were entered into Epi data version 4.4.1 and were exported and analyzed by SPSS version 25. A p-value < 0.25 in the bivariate analysis was entered into multivariable logistic regression analysis and a p-value of < 0.05 was considered statistically significant. Of the 494 pregnant women who tested negative for HIV on their first ANC test, six (1.2%) tested positive on repeat testing. Upon multivariable logistic regression, pregnant women who have had a reported history of sexually transmitted infections [AOR = 7.98; 95% CI (1.21, 52.82)], participants' partners reported travel history for work frequently [AOR = 6.00; 95% CI (1.09, 32.99)], and sexually abused pregnant women [AOR = 7.82; 95% CI (1.194, 51.24)] were significantly associated with HIV seroconversion. The seroconversion rate in this study indicates that pregnant women who are HIV-negative in early pregnancy are at an ongoing risk of seroconversion throughout their pregnancy. Thus, this study highlights the benefit of a repeat HIV testing strategy in late pregnancy, particularly when the risk of seroconversion or new infection cannot be convincingly excluded. Therefore, repeated testing of HIV-negative pregnant women in late pregnancy provides an opportunity to detect seroconverted pregnant women to enable the timely use of ART to prevent mother-to-child transmission of HIV infection.

Standardised Versioning of Datasets: a FAIR–compliant Proposal

This paper presents a standardised dataset versioning framework for improved reusability, recognition and data version tracking, facilitating comparisons and informed decision-making for data usability and workflow integration. The framework adopts a software engineering-like data versioning nomenclature (“major.minor.patch”) and incorporates data schema principles to promote reproducibility and collaboration. To quantify changes in statistical properties over time, the concept of data drift metrics (d) is introduced. Three metrics (dP, dE,PCA, and dE,AE) based on unsupervised Machine Learning techniques (Principal Component Analysis and Autoencoders) are evaluated for dataset creation, update, and deletion. The optimal choice is the dE,PCA metric, combining PCA models with splines. It exhibits efficient computational time, with values below 50 for new dataset batches and values consistent with seasonal or trend variations. Major updates (i.e., values of 100) occur when scaling transformations are applied to over 30% of variables while efficiently handling information loss, yielding values close to 0. This metric achieved a favourable trade-off between interpretability, robustness against information loss, and computation time.

Performances and determinants of proficiency testing in clinical laboratory services at comprehensive specialized hospitals, northwest Ethiopia

Proficiency testing (PT) is an impartial laboratory performance-evaluating system using an independent body. It is a mandatory accreditation requirement and means for improving the laboratory’s performance. The study aimed to evaluate the performance of PT, with a focus on identifying and discussing determinants that influence PT performance at comprehensive specialized hospitals in northwest Ethiopia. A retrospective cross-sectional study was carried out from 2020 to 2022. Using a convenient sampling technique, laboratory tests with recorded PT results in each hospital laboratory were included. A data collection template and customized checklists were used to collect the data. Epi Data Version 3.1 for data entry and STATA Version 14.1 for cleaning and analysis were used. Binary logistic regression analyses were used. Variables with p < 0.05 in the multivariable logistic regression were considered to be statistically significant. Over nine cycles, 3807 PT challenges were distributed. The total failure rate of the laboratories was 32.4%, with a peak failure rate of 40.3% in 2020, after which the failure rate was decline to 20.6% in 2022. Among the five laboratory sections, molecular biology had the lowest failure rate (22.2%), while microbiology had the highest failure rate (56.5%). Multivariate logistic regression revealed that PT results reported without appropriate unit of measurement (AOR 7.5), lack of corrective action for PT nonconformance (AOR 7.1), and reagent unavailability (AOR 6.1) had significant effects on PT performance (p < 0.001). The results of this study showed that the overall performance of the laboratory was lower. Reporting PT results without appropriate units of measurement and not taking corrective action for PT nonconformance were the major aggravating factors for high failure rates.

Adverse fetal birth outcomes and its associated factors among mothers with premature rupture of membrane in Amhara region, Ethiopia.

Adverse birth outcomes are the leading cause of neonatal mortality worldwide. Ethiopia is one of the countries struggling to reduce neonatal mortality through different strategies, but neonatal mortality remains high for many reasons. Despite adverse birth outcomes being a public health problem in Ethiopia, the contribution of Premature rupture of the membrane to the adverse fetal birth outcome is neglected and not well explained in our country. This study aims to assess fetal birth outcomes and associated factors among mothers with all types of PROM at Specialized Hospitals in Amhara Region, Ethiopia. A facility-based cross-sectional study design was applied among 538 mothers with premature rapture of the membrane at Amhara region specialized hospitals. A simple random sampling technique was employed to select the medical charts diagnosed with all types of PROM and giving birth in the hospital within the period from July 8, 2019, to July 7, 2021. The data was collected using a checklist, entered into EPI Data version 3.1, and analyzed using SPSS version 23. A binary logistic regression model was used to see the association between independent and dependent variables. A P-value <0.05 was used to declare the statistical significance. The AOR with 95% CI was used to measure the strength of the association. Adverse birth outcome among all types of Premature rupture of membrane mothers was 33.1% [95% CI 29.2-37.2]. Rural residents [AOR = 2.94, 95% CI:1.73-4.97], have a history of urinary tract infection [AOR = 6.87, 95% CI: 2.77-17.01], anemia [AOR = 7.51, 95% CI: 2.88-19.62], previous history of adverse birth outcome [AOR = 3.54, 95% CI: 1.32-9.47] and less than two years interpregnancy interval [AOR = 6.07, 95% CI: 2.49-14.77] were positively associated with adverse birth outcome compared to their counterparts. The adverse birth outcome was high in the Amhara region as compared to the World Health Organization's estimated figure and target; the target is less than 15%. History of the previous adverse birth outcome, residence, urinary tract infection, Anemia, and interpregnancy interval had an association with adverse birth outcomes. Therefore, strengthening close follow-up for mothers who had previous adverse birth outcomes, screening and treatment of urinary tract infection, anemia prevention, and maximizing birth interval are recommended for reducing adverse birth outcomes.

Prevalence of Undiagnosed Hypertension and its Associated Factors Among Adult Peoples Living in Enemor Woreda, South Ethiopia, 2021. Community Based Cross Sectional Study

Background: Hypertension is defined as two or more readings of systolic blood pressure measurement of 130 mm Hg or higher or diastolic blood pressure measurement of 80 mm Hg or higher. In the early stages, symptoms of HTN are often not detectable and thus many people with the disease are left undiagnosed. Undiagnosed HTN increases the risk of complications such as renal failure, myocardial infarction, heart failure, stroke and premature death. There was a high prevalence of undiagnosed HTN among adolescents. Objective: To assess the prevalence of undiagnosed hypertension and its associated factors among adult peoples living in Enemor Woreda, Ethiopia, 2021. Method: A community based cross-sectional study design was conducted from April to May, 2021. Data were collected using a structured self-administered English version questionnaire; which translated to the national Amharic language. The data were collected from 630 households using systematic random sampling technique at K=7. The data were entered to epi data version 3.4 and analyzed by SPSS version 26. Bivariate and multivariable logistic regression with 95% CI was hold to determine the significance of variables. Result: In this finding 260 (45.3%) of respondents were identified as having undiagnosed hypertension. Respondents having sedentary life style (AOR=2.24, 95%CI (1.37, 3.67)], BMI ≥25 (AOR=2.42, 95%CI (1.43, 4.09)], smokers [AOR: 0.45, 95%CI(0.28, 0.73)], health seeking behavior [AOR: 0.41, 95%CI(0.25, 0.66)], monthly income &lt;2000 ETB [AOR: 0.68, 95%CI(0.48,0.97)] and respondents dietary habit Enjera with Wot [AOR: 0.57, 95%CI(0.40, 0.83)] were significantly associated with undiagnosed hypertension. Conclusion: The overall prevalence of undiagnosed hypertension was 45.3%. respondents with BMI kg/m2 &gt;25, having sedentary life style, cigarette smoking, health seeking behavior, dietary habit and monthly income were significance predictors of undiagnosed HTN; therefore, people should follow Life style modification and have health seeking behavior to early detect and manage undiagnosed HTN with in the community.

Version 8 IMK/IAA MIPAS measurements of CFC-11, CFC-12, and HCFC-22

Abstract. The Michelson Interferometer for Passive Atmospheric Sounding (MIPAS) on Envisat provided infrared limb emission spectra, which were used to infer global distributions of CFC-11, CFC-12, and HCFC-22. Spectra were analysed using constrained non-linear least-squares fitting. Changes with respect to earlier data versions refer to the use of version 8 spectra, the altitude range where the background continuum is considered, details of the regularization and microwindow selection, and the occasional joint fitting of interfering species, the use of new spectroscopic data, the joint fit of a tangent-height-dependent spectral offset, and the use of 2D temperature fields. In the lower stratosphere the error budget is dominated by uncertainties in spectroscopic data, while above this measurement noise is the leading error source. The vertical resolution of CFC-11 and CFC-12 is 2–3 km near the tropopause, about 4 km at 30 km altitude, and 6–10 km at 50 km. The vertical resolution of HCFC-22 is somewhat coarser, 3–4 km at the tropopause and 10–12 km at 35 km altitude. In the altitude range of interest, the horizontal resolution is typically limited by the horizontal sampling of the measurements, not by the smearing of the retrievals. Horizontal information displacement does not exceed 150 km, which can become an issue only for comparisons with model simulations with high horizontal resolution or localized in situ observations. Along with the regular data product, an alternative representation of the data on a coarser vertical grid is offered. These data can be used without consideration of the averaging kernels. The new data version provides improvement with respect to reduction of biases and improved consistency between the full- and reduced-resolution mission period of MIPAS.

DRANetSplicer: A Splice Site Prediction Model Based on Deep Residual Attention Networks.

The precise identification of splice sites is essential for unraveling the structure and function of genes, constituting a pivotal step in the gene annotation process. In this study, we developed a novel deep learning model, DRANetSplicer, that integrates residual learning and attention mechanisms for enhanced accuracy in capturing the intricate features of splice sites. We constructed multiple datasets using the most recent versions of genomic data from three different organisms, Oryza sativa japonica, Arabidopsis thaliana and Homo sapiens. This approach allows us to train models with a richer set of high-quality data. DRANetSplicer outperformed benchmark methods on donor and acceptor splice site datasets, achieving an average accuracy of (96.57%, 95.82%) across the three organisms. Comparative analyses with benchmark methods, including SpliceFinder, Splice2Deep, Deep Splicer, EnsembleSplice, and DNABERT, revealed DRANetSplicer's superior predictive performance, resulting in at least a (4.2%, 11.6%) relative reduction in average error rate. We utilized the DRANetSplicer model trained on O. sativa japonica data to predict splice sites in A. thaliana, achieving accuracies for donor and acceptor sites of (94.89%, 94.25%). These results indicate that DRANetSplicer possesses excellent cross-organism predictive capabilities, with its performance in cross-organism predictions even surpassing that of benchmark methods in non-cross-organism predictions. Cross-organism validation showcased DRANetSplicer's excellence in predicting splice sites across similar organisms, supporting its applicability in gene annotation for understudied organisms. We employed multiple methods to visualize the decision-making process of the model. The visualization results indicate that DRANetSplicer can learn and interpret well-known biological features, further validating its overall performance. Our study systematically examined and confirmed the predictive ability of DRANetSplicer from various levels and perspectives, indicating that its practical application in gene annotation is justified.

Abstract 4933: A workflow for cloud-based AI development of multiplex IF image analysis using the OMERO Plus platform

Abstract Background: The advancement of AI in digital pathology is essential for analyzing image data containing billions of cells. This is true for digital pathology workflows using bright-field images, but this is even more critical for multiplex immunofluorescence (mIF) whole-slides due to the increased number of fluorescent channels and bit-depth per pixel. These complexities necessitate improved data management, and efficient visualization for both the mIF image and AI-based analysis results. We present a workflow using OMERO Plus, AWS SageMaker, and Ultivue software for AI model development in mIF. Method: Images were uploaded to AWS S3 and imported to the data management system OMERO Plus, where they were organized into training and validation groups. Annotations: PathViewer was used to place rectangular fields of view (FOV) in locations selected by the pathologist where all positive cells for each target marker were manually annotated. Data Preparation: Using the OMERO Plus API, annotation coordinates, image tiles, and image metadata were extracted and formatted for model training. All training data is under a version control system using Gitlab and Data Version Control tools using AWS S3. Additionally, strict quality checks were performed to ensure data integrity. Training: For both semantic segmentation and cell object detection, the training data was used in a customized training workflow using AWS SageMaker, including modern deep learning architectures, data augmentation, training logging, evaluation, and deployment. All AI models were trained using Pytorch and deployed with the open model format ONNX. Results Visualization: AI segmentation results of cells and regions are visualized using PathViewer as overlays on the original images by converting them to the OME-NGFF label image format that uses Zarr multidimensional arrays. Results: We utilized 58 and 24 mIF images for training and validation, respectively, on 15 markers using ISP Ultivue technology with 1681 and 296 FOVs, encompassing over 60K cells. Using this data and methodology we trained 3 semantic segmentation models and over five object detection models suitable for all twenty-four OmniVUE markers. For instance, the CD3 positive cell detection model, trained with 390 FOVs, achieved highly accurate results: f1-score of 0.915 evaluated on 34 FOVs. Conclusions: The combination of OMERO Plus, PathViewer, AWS SageMaker, and internal tools can successfully address mIF Big Data data management complexities in a cloud environment for digital pathology. The architecture is highly scalable, cost effective, and reliable, enabling a very efficient AI workflow. Citation Format: Ruben Cardenes, Erin Diel, Douglas Wood, Je Lee, Angela Vasaturo, Martin Schulze, Lorenz Rognoni. A workflow for cloud-based AI development of multiplex IF image analysis using the OMERO Plus platform [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 4933.