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10.1111/joim.13241 http://scihub22266oqcxt.onion/10.1111/joim.13241 33452824!8013754!33452824     free     free     free Deprecated: Implicit conversion from float 209.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 209.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 209.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 209.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 209.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 209.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 243.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       J+Intern+Med 2021 ; 290 (1): 157-165 Nephropedia Template TP {{tp|p=33452824|t=2021. Assessment of thirty-day readmission rate, timing, causes and predictors after hospitalization with COVID-19 |pdf=|usr=}}{{33452824}} gab.com Text Assessment of thirty-day readmission rate, timing, causes and predictors after hospitalization with COVID-19 JO: J Intern Med http://www.kidney.de/pget.php?&tw=1&pmid=33452824 #FOAvip BACKGROUND: There are limited data on the characteristics of 30-day readmission after hospitalization with coronavirus disease 2019 (COVID-19). OBJECTIVES: To examine the rate, timing, causes, predictors and outcomes of 30-day readmission after COVID-19 hospitalization. METHODS: From 13 March to 9 April 2020, all patients hospitalized with COVID-19 and discharged alive were included in this retrospective observational study. Multivariable logistic regression was used to identify the predictors of 30-day readmission, and a restricted cubic spline function was utilized to assess the linearity of the association between continuous predictors and 30-day readmission. RESULTS: A total of 1062 patients were included in the analysis, with a median follow-up time of 62 days. The mean age of patients was 56.5 years, and 40.5% were women. At the end of the study, a total of 48 (4.5%) patients were readmitted within 30 days of discharge, and a median time to readmission was 5 days. The most common primary diagnosis of 30-day readmission was a hypoxic respiratory failure (68.8%) followed by thromboembolism (12.5%) and sepsis (6.3%). The patients with a peak serum creatinine level of >/=1.29 mg/dL during the index hospitalization, compared to those with a creatinine of <1.29 mg/dL, had 2.4 times increased risk of 30-day readmission (adjusted odds ratio: 2.41; 95% CI: 1.23-4.74). The mortality rate during the readmission was 22.9%. CONCLUSION: With 4.5% of the thirty-day readmission rate, COVID-19 survivors were readmitted early after hospital discharge, mainly due to morbidities of COVID-19. One in five readmitted COVID-19 survivors died during their readmission. Twit Text FOAVip Assessment of thirty-day readmission rate, timing, causes and predictors after hospitalization with COVID-19 ????J Intern Med http://www.kidney.de/pget.php?&tw=1&pmid=33452824 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=33452824 #FOAvip English Wikipedia <ref>{{Cite pmid|33452824}}</ref> Assessment of thirty-day readmission rate, timing, causes and predictors after hospitalization with COVID-19 #MMPMID33452824 Yeo I; Baek S; Kim J; Elshakh H; Voronina A; Lou MS; Vapnik J; Kaler R; Dai X; Goldbarg S J Intern Med 2021[Jul]; 290 (1): 157-165 PMID33452824show ga BACKGROUND: There are limited data on the characteristics of 30-day readmission after hospitalization with coronavirus disease 2019 (COVID-19). OBJECTIVES: To examine the rate, timing, causes, predictors and outcomes of 30-day readmission after COVID-19 hospitalization. METHODS: From 13 March to 9 April 2020, all patients hospitalized with COVID-19 and discharged alive were included in this retrospective observational study. Multivariable logistic regression was used to identify the predictors of 30-day readmission, and a restricted cubic spline function was utilized to assess the linearity of the association between continuous predictors and 30-day readmission. RESULTS: A total of 1062 patients were included in the analysis, with a median follow-up time of 62 days. The mean age of patients was 56.5 years, and 40.5% were women. At the end of the study, a total of 48 (4.5%) patients were readmitted within 30 days of discharge, and a median time to readmission was 5 days. The most common primary diagnosis of 30-day readmission was a hypoxic respiratory failure (68.8%) followed by thromboembolism (12.5%) and sepsis (6.3%). The patients with a peak serum creatinine level of >/=1.29 mg/dL during the index hospitalization, compared to those with a creatinine of <1.29 mg/dL, had 2.4 times increased risk of 30-day readmission (adjusted odds ratio: 2.41; 95% CI: 1.23-4.74). The mortality rate during the readmission was 22.9%. CONCLUSION: With 4.5% of the thirty-day readmission rate, COVID-19 survivors were readmitted early after hospital discharge, mainly due to morbidities of COVID-19. One in five readmitted COVID-19 survivors died during their readmission. |*Hospitalization[MESH] |COVID-19/*therapy[MESH] |Female[MESH] |Humans[MESH] |Male[MESH] |Middle Aged[MESH] |Pandemics[MESH] |Patient Readmission/*statistics & numerical data[MESH] |Pneumonia, Viral/*therapy/virology[MESH] |Prognosis[MESH] |Retrospective Studies[MESH] |Risk Factors[MESH] |SARS-CoV-2[MESH]Assessment of thirty-day readmission rate, timing, causes and predicto(epmc).pdf DeepDyve Pubget Overpricing