6 research outputs found

    Peran Map, Rot, Imt dalam Skrining Preeklampsia di Indonesia

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    Latar Belakang : Preeklampsia tetap menempati peringkat pertama sebagai penyebab tingginya Angka Kematian Ibu (AKI) di Surabaya dari tahun 2013-2017 sebesar 28.92 %. Tingginya angka preeklampsia bisa dicegah dengan dilakukannya skrining preeklampsia yang mudah dilakukan pada trimester I dan II yaitu dengan dilakukannya skrining Mean Arterial Presure (MAP), Roll Over Test (ROT), Indeks Masa Tubuh (IMT) di Fasilitas kesehatan dasar. Tujuan dari penelitian ini untuk mengetahui hubungan antara Skrining Preeklampsia (MAP, ROT, IMT) yang dilakukan pada ibu hamil trimester I dan trimester II serta kejadian preeklampsia. Metode : Penelitian ini adalah penelitian Retrospektif, Case Control dengan sampel pada kelompok kasus yaitu pasien preeklampsia pada saat trimester I dan II yang dilakukan skrining preeklampsia sedangkan untuk kelompok kontrol, ibu hamil normal yang juga dilakukan skrining preeklampsia pada trimester I dan II. Hasil : Didapatkan besar sampel 189 ibu hamil dengan preeklampsia selama 1 tahun, pengambilan sampel dengan teknik consecutive sampling. Hasil pemeriksaan diperoleh pada kelompok kasus didapatkan pasien dengan MAP (+), ROT (+), IMT (+) berturut-turut adalah 43 (95.6 %), 18 (40 %) dan 18 (40 %), sedangkan pada kelompok kontrol diperoleh hasil 18 (40 %) sampel MAP (+), 26 (57.8 %) ROT (+), 5 (11.1 %) IMT (+). Hasil uji statistik Chi Square menunjukan adanya hubungan signifikan antara skrining MAP dan IMT dengan kejadian preeklampsia dengan nilai p berturut-turut (p 0.0001, OR = 32.250 dan p 0.002, OR = 5.333 ), namun tidak didapatkan hubungan antara skrining ROT dengan kejadian preeklampsia (p 0.092 OR = 0.487). Didapatkan hubungan ketiga skrining (MAP, ROT, IMT) dengan kejadian preeklampsia (p 0.001, OR 4.529). Kesimpulan : Pasien MAP (+) dan IMT (+) mempunyai resiko sebesar 32 kali dan 5 kali pada preeklampsia. Skrining ROT (+) tidak mempunyai hubungan dengan kejadian preeklampsia

    Characteristics and outcomes of an international cohort of 600 000 hospitalized patients with COVID-19

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    Background: We describe demographic features, treatments and clinical outcomes in the International Severe Acute Respiratory and emerging Infection Consortium (ISARIC) COVID-19 cohort, one of the world's largest international, standardized data sets concerning hospitalized patients. Methods: The data set analysed includes COVID-19 patients hospitalized between January 2020 and January 2022 in 52 countries. We investigated how symptoms on admission, co-morbidities, risk factors and treatments varied by age, sex and other characteristics. We used Cox regression models to investigate associations between demographics, symptoms, co-morbidities and other factors with risk of death, admission to an intensive care unit (ICU) and invasive mechanical ventilation (IMV). Results: Data were available for 689 572 patients with laboratory-confirmed (91.1%) or clinically diagnosed (8.9%) SARS-CoV-2 infection from 52 countries. Age [adjusted hazard ratio per 10 years 1.49 (95% CI 1.48, 1.49)] and male sex [1.23 (1.21, 1.24)] were associated with a higher risk of death. Rates of admission to an ICU and use of IMV increased with age up to age 60 years then dropped. Symptoms, co-morbidities and treatments varied by age and had varied associations with clinical outcomes. The case-fatality ratio varied by country partly due to differences in the clinical characteristics of recruited patients and was on average 21.5%. Conclusions: Age was the strongest determinant of risk of death, with a ∌30-fold difference between the oldest and youngest groups; each of the co-morbidities included was associated with up to an almost 2-fold increase in risk. Smoking and obesity were also associated with a higher risk of death. The size of our international database and the standardized data collection method make this study a comprehensive international description of COVID-19 clinical features. Our findings may inform strategies that involve prioritization of patients hospitalized with COVID-19 who have a higher risk of death

    ISARIC-COVID-19 dataset: A Prospective, Standardized, Global Dataset of Patients Hospitalized with COVID-19

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    The International Severe Acute Respiratory and Emerging Infection Consortium (ISARIC) COVID-19 dataset is one of the largest international databases of prospectively collected clinical data on people hospitalized with COVID-19. This dataset was compiled during the COVID-19 pandemic by a network of hospitals that collect data using the ISARIC-World Health Organization Clinical Characterization Protocol and data tools. The database includes data from more than 705,000 patients, collected in more than 60 countries and 1,500 centres worldwide. Patient data are available from acute hospital admissions with COVID-19 and outpatient follow-ups. The data include signs and symptoms, pre-existing comorbidities, vital signs, chronic and acute treatments, complications, dates of hospitalization and discharge, mortality, viral strains, vaccination status, and other data. Here, we present the dataset characteristics, explain its architecture and how to gain access, and provide tools to facilitate its use

    Characteristics and outcomes of COVID-19 patients admitted to hospital with and without respiratory symptoms