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10.1016/j.heliyon.2021.e06650 http://scihub22266oqcxt.onion/10.1016/j.heliyon.2021.e06650 33817359!8006191!33817359     free     free     free Deprecated: Implicit conversion from float 233.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 233.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 233.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 233.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 233.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 233.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 233.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 233.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 267.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 267.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 267.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 267.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 267.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 267.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 267.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 267.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       Heliyon 2021 ; 7 (4): e06650 Nephropedia Template TP {{tp|p=33817359|t=2021. SARS-CoV-2 molecular identification and clinical data analysis of associated risk factors from a COVID-19 testing laboratory of a coastal region in Bangladesh |pdf=|usr=}}{{33817359}} gab.com Text SARS-CoV-2 molecular identification and clinical data analysis of associated risk factors from a COVID-19 testing laboratory of a coastal region in Bangladesh JO: Heliyon http://www.kidney.de/pget.php?&tw=1&pmid=33817359 #FOAvip BACKGROUND AND AIM: Outbreak of COVID-19 seems to have exacerbated across the globe, including Bangladesh. Scientific literature on the clinical data record of COVID-19 patients in Bangladesh is inadequate. Our study analyzes the clinical data of COVID-19 positive patients based on molecular identification and risk factor correlated with three variables (age, sex, residence) and COVID-19 prevalence in the four districts of Chattogram Division (Noakhali, Feni, Lakshmipur and Chandpur) with an aim to understand the trajectory of this pandemic in Chattogram, Southern Bangladesh. METHODS: A cross-sectional study is conducted in the context of RT-PCR-based COVID-19 positive 5,589 individuals diagnosed with SARS-CoV-2 infection from the COVID-19 testing laboratory, Abdul Malek Ukil Medical College, Noakhali-3800, Bangladesh. For molecular confirmation of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), standard diagnostic protocols through real-time reverse transcriptase-polymerase chain reaction (RT-qPCR) were conducted. Different patient demographics were analyzed using SPSS version 22 for exploring the relationship of three factors - age, sex, and residence with a cumulative number of COVID-19 positive cases and prevalence of COVID-19 in four districts in Chattogram division. The data was recorded between May to July, 2020. RESULTS: Among the three parameters, the present study revealed that 20-40 cohort had the highest incidence of infection rate (51.80%, n = 2895) among the different age groups. Among the infected individuals, 56.8% (n = 3177) were male and 43.2% (n = 2412) were female, denoting males being the most susceptible to this disease. Urban residents (52.7%, n = 2948) were more vulnerable to SARS-CoV-2 infection than those residing in rural areas (47.3%, n = 2641). The prevalence of COVID-19 positive cases among the four districts was recorded highest in the Noakhali district with 36.8% (n = 2057), followed by the Feni, Lakshmipur and Chandpur districts with 25.9% (n = 1448), 20.8% (n = 1163) and 16.5% (n = 921), respectively. CONCLUSIONS: This study presents a statistical correlation of certain factors linked to Bangladesh with confirmed COVID-19 patients, which will enable health practitioners and policy makers to take proactive steps to control and mitigate disease transmission. Twit Text FOAVip SARS-CoV-2 molecular identification and clinical data analysis of associated risk factors from a COVID-19 testing laboratory of a coastal region in Bangladesh ????Heliyon http://www.kidney.de/pget.php?&tw=1&pmid=33817359 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=33817359 #FOAvip English Wikipedia <ref>{{Cite pmid|33817359}}</ref> SARS-CoV-2 molecular identification and clinical data analysis of associated risk factors from a COVID-19 testing laboratory of a coastal region in Bangladesh #MMPMID33817359 Ali MR; Chowdhury MR; Mas-Ud MA; Islam S; Shimu AS; Mina FB; Sharmin NE; Hasan MF Heliyon 2021[Apr]; 7 (4): e06650 PMID33817359show ga BACKGROUND AND AIM: Outbreak of COVID-19 seems to have exacerbated across the globe, including Bangladesh. Scientific literature on the clinical data record of COVID-19 patients in Bangladesh is inadequate. Our study analyzes the clinical data of COVID-19 positive patients based on molecular identification and risk factor correlated with three variables (age, sex, residence) and COVID-19 prevalence in the four districts of Chattogram Division (Noakhali, Feni, Lakshmipur and Chandpur) with an aim to understand the trajectory of this pandemic in Chattogram, Southern Bangladesh. METHODS: A cross-sectional study is conducted in the context of RT-PCR-based COVID-19 positive 5,589 individuals diagnosed with SARS-CoV-2 infection from the COVID-19 testing laboratory, Abdul Malek Ukil Medical College, Noakhali-3800, Bangladesh. For molecular confirmation of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), standard diagnostic protocols through real-time reverse transcriptase-polymerase chain reaction (RT-qPCR) were conducted. Different patient demographics were analyzed using SPSS version 22 for exploring the relationship of three factors - age, sex, and residence with a cumulative number of COVID-19 positive cases and prevalence of COVID-19 in four districts in Chattogram division. The data was recorded between May to July, 2020. RESULTS: Among the three parameters, the present study revealed that 20-40 cohort had the highest incidence of infection rate (51.80%, n = 2895) among the different age groups. Among the infected individuals, 56.8% (n = 3177) were male and 43.2% (n = 2412) were female, denoting males being the most susceptible to this disease. Urban residents (52.7%, n = 2948) were more vulnerable to SARS-CoV-2 infection than those residing in rural areas (47.3%, n = 2641). The prevalence of COVID-19 positive cases among the four districts was recorded highest in the Noakhali district with 36.8% (n = 2057), followed by the Feni, Lakshmipur and Chandpur districts with 25.9% (n = 1448), 20.8% (n = 1163) and 16.5% (n = 921), respectively. CONCLUSIONS: This study presents a statistical correlation of certain factors linked to Bangladesh with confirmed COVID-19 patients, which will enable health practitioners and policy makers to take proactive steps to control and mitigate disease transmission. äSARS-CoV-2 molecular identification and clinical data analysis of asso(epmc).pdf DeepDyve Pubget Overpricing