Severe maternal outcomes: World health organization maternal near-miss and maternal mortality criteria in University Tertiary Hospital Egypt by Ahmed Samy El-Agwany

“…Background: The World Health Organization (WHO) maternal near-miss (MNM) approach was developed to evaluate and improve the quality of obstetric care worldwide. …”
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Missed Feelings by Henrike Kohpeiß

“… ‘Missed Feelings’ addresses the complex repercussions of traumatic experience Lauren Berlant lays out in their article “Structures of Unfeeling” (2015). …”
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WORLD ECONOMY AFTER THE GREAT RECESSION: WEAK DYNAMICS, IMPACT OF THE COLD WAR ECHO by Ruslan I. Khasbulatov

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Identifying Missing and Spurious Interactions in Directed Networks by Xue Zhang, Chengli Zhao, Xiaojie Wang, Dongyun Yi

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THE MISSING AS A SPECIFIC ASPECT OF ENSURING THE SECURITY OF SOCIETY DEMOGRAPHIC by Mikhail V. Karmanov, Pavel A. Smelov, Elena A. Egorova

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Neonatal Near Miss among Newborns of Women with Type 1 Diabetes Mellitus by Luiza R. Morais, Beatriz C. Patz, Felipe F. Campanharo, Patricia M. Dualib, Sue Y. Sun, Rosiane Mattar

“…This was a cross-sectional retrospective study from a secondary analysis of data retrieved from medical records of pregnant women with T1DM cared at a Brazilian university hospital between 2005 and 2015. Maternal near miss (MNM) and potentially life-threatening conditions (PTLC) were classified according to the World Health Organization criteria. …”
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Effects of missed anti-tuberculosis therapy doses on treatment outcome: a multi-center cohort studyResearch in context by Isabella B.B. Ferreira, Rodrigo C. Menezes, Mariana Araújo-Pereira, Valeria C. Rolla, Afrânio L. Kritski, Marcelo Cordeiro-Santos, Timothy R. Sterling, Cody Staats, Gustavo Amorim, Anete Trajman, Bruno B. Andrade, A. Benjamin, Q. Medeiros, F. Ridolfi, A. Gomes-Silva, J. Oliveira, J. Marine, B. Durovni, S. Cavalcante, A. Rezende, A. Bezerra, A. Carvalho, A. Brito, A. Costa, R. Spener-Gomes, M. Rocha, V. Nascimento, B. Nogueira, A. Andrade, E. Silva

“…Although directly observed therapy (DOT) has been widely implemented to improve adherence, nonadherence continues to compromise treatment success rates, especially in real-world settings. Therefore, this study aims to assess the impact of missed doses on TB treatment outcomes. …”
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Prediction of pulmonary embolism by an explainable machine learning approach in the real world by Qiao Zhou, Ruichen Huang, Xingyu Xiong, Zongan Liang, Wei Zhang

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Deprescribing oral antidiabetics in elderly patients: Do electronic leaflets across the world address it? by Kitete Tunda Bunnel, Silvio José Elisei Carvalho, Jr, Mariana Linhares Pereira, Renê Oliveira Couto, André Oliveira Baldoni

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Assessment of Health and Community Services Provided for Families in Internal Displaced Camps in Baghdad City by Huda Baqer Hassan, Karim Ghadban Sagam

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Identifying and characterising asthma subgroups at high risk of severe exacerbations using machine learning and longitudinal real-world data by Patrick Long, Andres Quintero, Javier Lopez-Molina, Merina Su, Nicola Boulter, Cindy Weber, Ralica Dimitrova

“…Notably, there was considerable between-cluster variability in the predicted likelihood of AE, with some subgroups comprised of patients who posed a challenge for the predictive model and would have been missed with predictive modelling alone.Discussion By identifying distinct subgroups among patients with asthma experiencing AE, this study highlights the heterogeneity within this population and emphasises the need for more personalised management of AE.Conclusion Applying predictive modelling and clustering to real-world data can help identify discrete phenotypes of patients and offer an important source of information for developing risk assessment and mitigation efforts.…”
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Analysis of the problem of low adherence of patients to attendance at outpatient clinics and cardiorehabilitation programs according to the data from published studies by Yu. V. Semenova, N. P. Kutishenko, S. Yu. Martsevich

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A Deep Learning–Enabled Workflow to Estimate Real-World Progression-Free Survival in Patients With Metastatic Breast Cancer: Study Using Deidentified Electronic Health Records by Gowtham Varma, Rohit Kumar Yenukoti, Praveen Kumar M, Bandlamudi Sai Ashrit, K Purushotham, C Subash, Sunil Kumar Ravi, Verghese Kurien, Avinash Aman, Mithun Manoharan, Shashank Jaiswal, Akash Anand, Rakesh Barve, Viswanathan Thiagarajan, Patrick Lenehan, Scott A Soefje, Venky Soundararajan

“…Clinician-confirmed cancer progression, namely real-world PFS (rwPFS) in unstructured text (ie, clinical notes), serves as a reasonable surrogate for real-world indicators in ascertaining progression endpoints. …”
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Current state of evidence and future direction for Knowledge Attitude and Practice studies in antimicrobial resistance - a novel conceptual framework by Miss Alison Shutt, Dr Arunima Sehgal Mukherjee, Dr Vrinda Nampoothiri, Professor Alison Holmes, Associate Professor Esmita Charani

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The Productivity Dilemma in Workplace Health Promotion by Martin Cherniack

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A Long Time Ago in a Library Far, Far Away ... The Adventures of the Gladiatoria Manuscript from New Haven by Hagedorn Dierk

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Experimental Research Testbeds for Large-Scale WSNs: A Survey from the Architectural Perspective by Hiecheol Kim, Won-Kee Hong, Joonhyuk Yoo, Seong-eun Yoo

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The Tuberculosis Cascade of Care in India's Public Sector: A Systematic Review and Meta-analysis. by Ramnath Subbaraman, Ruvandhi R Nathavitharana, Srinath Satyanarayana, Madhukar Pai, Beena E Thomas, Vineet K Chadha, Kiran Rade, Soumya Swaminathan, Kenneth H Mayer

“…<h4>Background</h4>India has 23% of the global burden of active tuberculosis (TB) patients and 27% of the world's "missing" patients, which includes those who may not have received effective TB care and could potentially spread TB to others. …”
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Mowgli’s Poetic Schooling: On Lyrical Parts of Kipling’s Jungle Books by Elena V. Haltrin-Khalturina

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Enhancing AI-driven forecasting of diabetes burden: a comparative analysis of deep learning and statistical models by Rasool Esmaeilyfard, Mohsen Bayati

“…While deep learning models have demonstrated superior predictive capabilities, their real-world applicability is constrained by computational complexity and data quality challenges. …”
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