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10.34172/aim.2021.47 http://scihub22266oqcxt.onion/10.34172/aim.2021.47 34196195!ä!34196195 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       Arch+Iran+Med 2021 ; 24 (4): 333-338 Nephropedia Template TP {{tp|p=34196195|t=2021. Prognostic Factors Associated with Survival in Patients Infected with COVID-19: A Retrospective Study on 214 Patients from Iran |pdf=|usr=}}{{34196195}} gab.com Text Prognostic Factors Associated with Survival in Patients Infected with COVID-19: A Retrospective Study on 214 Patients from Iran JO: Arch Iran Med http://www.kidney.de/pget.php?&tw=1&pmid=34196195 #FOAvip BACKGROUND: Decision-making on allocating scarce medical resources is crucial in the context of a strong health system reaction to the coronavirus disease 2019 (COVID-19) pandemic. Therefore, understanding the risk factors related to a high mortality rate can enable the physicians for a better decision-making process. METHODS: Information was collected regarding clinical, demographic, and epidemiological features of the definite COVID-19 cases. Through Cox regression and statistical analysis, the risk factors related to mortality were determined. The Kaplan-Meier curve was used to estimate survival function and measure the mean length of living time in the patients. RESULTS: Among about 3000 patients admitted in the Taleghani hospital as outpatients with suspicious signs and symptoms of COVID-19 in 2 months, 214 people were confirmed positive for this virus using the polymerase chain reaction (PCR) technique. Median time to death was 30 days. In this population, 24.29% of the patients died and 24.76% of them were admitted to the ICU (intensive care unit) during hospitalization. The results of Multivariate Cox regression Analysis showed that factors including age (HR, 1.031; 95% CI, 1.001-1.062; P value=0.04), and C-reactive protein (CRP) (HR, 1.007; 95% CI, 1.000-1.015; P value=0.04) could independently predict mortality. Furthermore, the results showed that age above 59 years directly increased mortality rate and decreased survival among our study population. CONCLUSION: Predictor factors play an important role in decisions on public health policy-making. Our findings suggested that advanced age and CRP were independent mortality rate predictors in the admitted patients. Twit Text FOAVip Prognostic Factors Associated with Survival in Patients Infected with COVID-19: A Retrospective Study on 214 Patients from Iran ????Arch Iran Med http://www.kidney.de/pget.php?&tw=1&pmid=34196195 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=34196195 #FOAvip English Wikipedia <ref>{{Cite pmid|34196195}}</ref> Prognostic Factors Associated with Survival in Patients Infected with COVID-19: A Retrospective Study on 214 Patients from Iran #MMPMID34196195 Sadeghi A; Eslami P; Dooghaie Moghadam A; Moazzami B; Pirsalehi A; Ilkhani S; Banar S; Feizollahi F; Vahidi M; Abdi S; Asadzadeh Aghdaei H; Zali MR; Nasserinejad M Arch Iran Med 2021[Apr]; 24 (4): 333-338 PMID34196195show ga BACKGROUND: Decision-making on allocating scarce medical resources is crucial in the context of a strong health system reaction to the coronavirus disease 2019 (COVID-19) pandemic. Therefore, understanding the risk factors related to a high mortality rate can enable the physicians for a better decision-making process. METHODS: Information was collected regarding clinical, demographic, and epidemiological features of the definite COVID-19 cases. Through Cox regression and statistical analysis, the risk factors related to mortality were determined. The Kaplan-Meier curve was used to estimate survival function and measure the mean length of living time in the patients. RESULTS: Among about 3000 patients admitted in the Taleghani hospital as outpatients with suspicious signs and symptoms of COVID-19 in 2 months, 214 people were confirmed positive for this virus using the polymerase chain reaction (PCR) technique. Median time to death was 30 days. In this population, 24.29% of the patients died and 24.76% of them were admitted to the ICU (intensive care unit) during hospitalization. The results of Multivariate Cox regression Analysis showed that factors including age (HR, 1.031; 95% CI, 1.001-1.062; P value=0.04), and C-reactive protein (CRP) (HR, 1.007; 95% CI, 1.000-1.015; P value=0.04) could independently predict mortality. Furthermore, the results showed that age above 59 years directly increased mortality rate and decreased survival among our study population. CONCLUSION: Predictor factors play an important role in decisions on public health policy-making. Our findings suggested that advanced age and CRP were independent mortality rate predictors in the admitted patients. |Adult[MESH] |Age Factors[MESH] |Aged[MESH] |COVID-19/complications/*diagnosis/*mortality[MESH] |Clinical Decision-Making[MESH] |Female[MESH] |Hospital Mortality[MESH] |Hospitalization[MESH] |Humans[MESH] |Iran[MESH] |Male[MESH] |Middle Aged[MESH] |Prognosis[MESH] |Proportional Hazards Models[MESH] |Retrospective Studies[MESH] |Risk Factors[MESH]Prognostic Factors Associated with Survival in Patients Infected with (epmc).pdf DeepDyve Pubget Overpricing