Background: The unpredictability of the progression of coronavirus disease 2019 (COVID-19) may be attributed to the low precision of the tools used to predict the prognosis of this disease. Objective: To identify the predictors associated with poor clinical outcomes in patients with COVID-19. Methods: Relevant articles from PubMed, Embase, Cochrane, and Web of Science were searched and extracted as of April 5, 2020. Data of interest were collected and evaluated for their compatibility for the meta-analysis. Cumulative calculations to determine the correlation and effect estimates were performed using the Z test. Results: In total, 19 papers recording 1,934 mild and 1,644 severe cases of COVID-19 were included. Based on the initial evaluation, 62 potential risk factors were identified for the meta-analysis. Several comorbidities, including chronic respiratory disease, cardiovascular disease, diabetes mellitus, and hypertension were observed more frequent among patients with severe COVID-19 than with the mild ones. Compared to the mild form, severe COVID-19 was associated with symptoms such as dyspnea, anorexia, fatigue, increased respiratory rate, and high systolic blood pressure. Lower levels of lymphocytes and hemoglobin; elevated levels of leukocytes, aspartate aminotransferase, alanine aminotransferase, blood creatinine, blood urea nitrogen, high-sensitivity troponin, creatine kinase, high-sensitivity C-reactive protein, interleukin 6, D-dimer, ferritin, lactate dehydrogenase, and procalcitonin; and a high erythrocyte sedimentation rate were also associated with severe COVID-19. Conclusion: More than 30 risk factors are associated with a higher risk of severe COVID-19. These may serve as useful baseline parameters in the development of prediction tools for COVID-19 prognosis.

Background: The unpredictability of the progression of coronavirus disease 2019 (COVID-19) may be attributed to the low precision of the tools used to predict the prognosis of this disease. Objective: To identify the predictors associated with poor clinical outcomes in patients with COVID-19. Methods: Relevant articles from PubMed, Embase, Cochrane, and Web of Science were searched as of April 5, 2020. The quality of the included papers was appraised using the Newcastle-Ottawa scale (NOS). Data of interest were collected and evaluated for their compatibility for the meta-analysis. Cumulative calculations to determine the correlation and effect estimates were performed using the Z test. Results: In total, 19 papers recording 1,934 mild and 1,644 severe cases of COVID-19 were included. Based on the initial evaluation, 62 potential risk factors were identified for the meta-analysis. Several comorbidities, including chronic respiratory disease, cardiovascular disease, diabetes mellitus, and hypertension were observed more frequent among patients with severe COVID-19 than with the mild ones. Compared to the mild form, severe COVID-19 was associated with symptoms such as dyspnea, anorexia, fatigue, increased respiratory rate, and high systolic blood pressure. Lower levels of lymphocytes and hemoglobin; elevated levels of leukocytes, aspartate aminotransferase, alanine aminotransferase, blood creatinine, blood urea nitrogen, high-sensitivity troponin, creatine kinase, high-sensitivity C-reactive protein, interleukin 6, D-dimer, ferritin, lactate dehydrogenase, and procalcitonin; and a high erythrocyte sedimentation rate were also associated with severe COVID-19. Conclusion: More than 30 risk factors are associated with a higher risk of severe COVID-19. These may serve as useful baseline parameters in the development of prediction tools for COVID-19 prognosis.

Laundry services are rapidly becoming ubiquitous in rural and urban areas, generating high domestic waste volumes. Their growth has raised concerns about the quality of natural waters, particularly the rivers into which most laundry businesses discharge their wastewater. The research set out to study laundry wastewater characteristics and their relationship with the river water quality as water pollution indicators in Code Watershed (Indonesia). It lies in three administrative units where many human activities take place in the watershed’s upper to the lower reaches. BOD and COD of 25 sampled laundry businesses were analyzed descriptively and compared to the laundry wastewater standards stipulated in Regulation No. 7 of 2016 and the class II water quality standards issued in Governor Regulation No. 20 of 2008. The results showed that the BOD of four laundry businesses and the COD of 18 laundry businesses exceeded the predetermined standards. Overall, rivers in Code Watershed meet the class II river water criteria for BOD at three of the seven sampling points and COD at all points.

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ABSTRAKIndonesia merupakan negara maritim dengan ribuan gugusan kepulauan yang terbentang dari Pulau Sabang di ujung barat hingga Pulau Merauke di ujung timur. Wilayah pesisir menjadi kawasan strategis untuk menunjang pembangunan nasional ditinjau dari segi lokasinya maupun keunikan karakteristik di setiap pesisirnya. Ibu kota negara Jakarta dan beberapa kota metropolitan Indonesia juga terletak strategis di wilayah pesisir seperti Surabaya, Semarang, Bali, dan Makassar. Namun, limpahan potensi materiil dan non materiil tersebut menghadapi tantangan besar akibat letak Indonesia yang berada di jalur subduksi.Bencana seperti gempabumi, tsunami, dan banjir rob dapat datang sewaktu-waktu. Penelitian ini bertujuan mengetahui karakteristik bentuklahan pesisir di Indonesia, potensi sumberdaya dan ancaman bencana di setiap tipologi, dan yang terakhir mewujudkan manajemen kepesisiran berbasis sustainable coastal area berdasarkan tiga tujuan di atas. Data karakteristik pesisir diperoleh dengan survey lapangan, studi literature, dan interpretasi citra satelit GeoEye.Karakteristik bentuklahan mencakup morfologi, material, dan proses yang khas di setiap unitnya sehingga potensi sumberdaya dan ancaman bencananya pun juga tidak dapat disamakan tiap unitnya. Penelitian dilakukan di karakteristik pesisir yang dominan di Indonesia yaitu marine deposition coast, subaerial deposition coast, dan karst coast. Perbedaan karakteristik tersebut menjadikan perwujudan pengelolaan pesisir secara sustainable coastal dapat menjadi sebuah solusi, selain mengetahui karakteristik, potensi sumberdaya, dan ancaman bencananya hal yang dapat dilakukan adalah dengan melakukan zonasi berdasarkan karakteristik bentuklahan dan peruntukan yang tepat untuk mewujudkan kawasan pesisir yang lestari.