Background: Reliable and timely data on maternal and neonatal mortality is required to implement health interventions, monitor progress, and evaluate health programs at national and sub-national levels. In most South Asian countries, including Pakistan, vital civil registration and health information systems are inadequate. The aim of this study is to determine accurate maternal and perinatal mortality through enhanced surveillance of births and deaths, compared with prior routinely collected data.
Methods: An enhanced surveillance system was established that measured maternal, perinatal and neonatal mortality rates through more complete enumeration of births and deaths in a rural district of Pakistan. Data were collected over a period of 1 year (2015/16) from augmentation of the existing health information system covering public healthcare facilities (n = 19), and the community through 273 existing Lady Health Workers; and with the addition of private healthcare facilities (n = 10), and 73 additional Community Health Workers to cover a total study population of 368,454 consisting of 51,690 eligible women aged 18 to 49 years with 7580 pregnancies and 7273 live births over 1 year. Maternal, neonatal, perinatal and stillbirth rates and ratios were calculated, with comparisons to routine reporting from the previous period (2014-15).
Results: Higher maternal mortality, perinatal mortality and neonatal mortality rates were observed through enhanced surveillance compared to mortality rates in the previous 1.5 years from the routine monitoring system from increased completeness and coverage. Maternal mortality was 247 compared to 180 per 100, 000 live births (p = 0.36), neonatal mortality 40 compared to 20 per 1, 000 live births (p < 0.001), and perinatal mortality 60 compared to 47 per 1000 live births (p < 0.001). All the mortality rates were higher than provincial and national estimates proffered by international agencies based on successive Pakistan Demographic and Health Surveys and projections.
Conclusion: Extension of coverage and improvement in completeness through reconciliation of data from health information systems is possible and required to obtain accurate maternal, perinatal and neonatal mortality for assessment of health service interventions at a local level.
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http://dx.doi.org/10.1186/s12889-018-5363-3 | DOI Listing |
Sci Rep
December 2024
National Centre for Diseases Prevention and Health Promotion, Istituto Superiore di Sanità, Rome, Italy.
This study aimed to calculate Italy's first national maternal mortality ratio (MMR) through an innovative record-linkage approach within the enhanced Italian Obstetric Surveillance System (ItOSS). A record-linkage retrospective cohort study was conducted nationwide, encompassing all women aged 11-59 years with one or more hospitalizations related to pregnancy or pregnancy outcomes from 2011 to 2019. Maternal deaths were identified by integrating data from the Death Registry and national and regional Hospital Discharge Databases supported by the integration of findings from confidential enquiries conducted through active surveillance.
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December 2024
Department of Biochemistry and Molecular Biology, Medical University of Lublin, 20-093, Lublin, Poland.
Using Fourier Transform Infrared spectroscopy (FTIR), it is possible to show chemical composition of materials and / or profile chemical changes occurring in tissues, cells, and body fluids during onset and progression of diseases. For diagnostic application, the use of blood would be the most appropriate in biospectroscopy studies since, (i) it is easily accessible and, (ii) enables frequent analyses of biochemical changes occurring in pathological states. At present, different studies have investigated potential of serum, plasma and sputum being alternative biofluids for lung cancer detection using FTIR.
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December 2024
Department of Applied Mathematics, Faculty of Mathematical Science, Ferdowsi University of Mashhad, Mashhad, Iran.
This study presents a web application for predicting cardiovascular disease (CVD) and hypertension (HTN) among mine workers using machine learning (ML) techniques. The dataset, collected from 699 participants at the Gol-Gohar mine in Iran between 2016 and 2020, includes demographic, occupational, lifestyle, and medical information. After preprocessing and feature engineering, the Random Forest algorithm was identified as the best-performing model, achieving 99% accuracy for HTN prediction and 97% for CVD, outperforming other algorithms such as Logistic Regression and Support Vector Machines.
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December 2024
Department of Thyroid Surgery, Affiliated Hospital of Guizhou Medical University, Guiyang, Guizhou, China.
Although CCL17 has been reported to exert a vital role in many cancers, the related studies in the thyroid carcinoma have never reported. As a chemokine, CCL17 plays a positive role by promoting the infiltration of immune cells into the tumor microenviroment (TME) to influence tumor invasion and metastasis. Therefore, this study is aimed to investigate the association of CCL17 level with potential prognostic value on tumor immunity in the thyroid carcinoma (THCA) based on the bioinformatics analysis.
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December 2024
Boyd Orr Centre for Population and Ecosystem Health, School of Biodiversity, One Health & Veterinary Medicine, College of Medical, Veterinary & Life Sciences, University of Glasgow, Glasgow, UK.
Rabies is a viral zoonosis that kills thousands of people annually in low- and middle-income countries across Africa and Asia where domestic dogs are the reservoir. 'Zero by 30', the global strategy to end dog-mediated human rabies, promotes a One Health approach underpinned by mass dog vaccination, post-exposure vaccination of bite victims, robust surveillance and community engagement. Using Integrated Bite Case Management (IBCM) and whole genome sequencing (WGS), we enhanced rabies surveillance to detect an outbreak in a formerly rabies-free island province in the Philippines.
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