Use my Search Websuite to scan PubMed, PMCentral, Journal Hosts and Journal Archives, FullText. Kick-your-searchterm to multiple Engines kick-your-query now !>

A dictionary by aggregated review articles of nephrology, medicine and the life sciences Your one-stop-run pathway from word to the immediate pdf of peer-reviewed on-topic knowledge.

10.1016/j.ajogmf.2020.100127 http://scihub22266oqcxt.onion/10.1016/j.ajogmf.2020.100127 32342041!7182514!32342041     free     free     free Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       Am+J+Obstet+Gynecol+MFM 2020 ; 2 (3): 100127 Nephropedia Template TP {{tp|p=32342041|t=2020. Forecasting the impact of coronavirus disease during delivery hospitalization: an aid for resource utilization |pdf=|usr=}}{{32342041}} gab.com Text Forecasting the impact of coronavirus disease during delivery hospitalization: an aid for resource utilization JO: Am J Obstet Gynecol MFM http://www.kidney.de/pget.php?&tw=1&pmid=32342041 #FOAvip BACKGROUND: The ongoing coronavirus disease 2019 pandemic has severely affected the United States. During infectious disease outbreaks, forecasting models are often developed to inform resource utilization. Pregnancy and delivery pose unique challenges, given the altered maternal immune system and the fact that most American women choose to deliver in the hospital setting. OBJECTIVE: This study aimed to forecast the first pandemic wave of coronavirus disease 2019 in the general population and the incidence of severe, critical, and fatal coronavirus disease 2019 cases during delivery hospitalization in the United States. STUDY DESIGN: We used a phenomenological model to forecast the incidence of the first wave of coronavirus disease 2019 in the United States. Incidence data from March 1, 2020, to April 14, 2020, were used to calibrate the generalized logistic growth model. Subsequently, Monte Carlo simulation was performed for each week from March 1, 2020, to estimate the incidence of coronavirus disease 2019 for delivery hospitalizations during the first pandemic wave using the available data estimate. RESULTS: From March 1, 2020, our model forecasted a total of 860,475 cases of coronavirus disease 2019 in the general population across the United States for the first pandemic wave. The cumulative incidence of coronavirus disease 2019 during delivery hospitalization is anticipated to be 16,601 (95% confidence interval, 9711-23,491) cases, 3308 (95% confidence interval, 1755-4861) cases of which are expected to be severe, 681 (95% confidence interval, 1324-1038) critical, and 52 (95% confidence interval, 23-81) fatal. Assuming similar baseline maternal mortality rate as the year 2018, we projected an increase in maternal mortality rate in the United States to at least 18.7 (95% confidence interval, 18.0-19.5) deaths per 100,000 live births as a direct result of coronavirus disease 2019. CONCLUSION: Coronavirus disease 2019 in pregnant women is expected to severely affect obstetrical care. From March 1, 2020, we forecast 3308 severe and 681 critical cases with about 52 coronavirus disease 2019-related maternal mortalities during delivery hospitalization for the first pandemic wave in the United States. These results are significant for informing counseling and resource allocation. Twit Text FOAVip Forecasting the impact of coronavirus disease during delivery hospitalization: an aid for resource utilization ????Am J Obstet Gynecol MFM http://www.kidney.de/pget.php?&tw=1&pmid=32342041 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=32342041 #FOAvip English Wikipedia <ref>{{Cite pmid|32342041}}</ref> Forecasting the impact of coronavirus disease during delivery hospitalization: an aid for resource utilization #MMPMID32342041 Putra M; Kesavan M; Brackney K; Hackney DN; Roosa KM Am J Obstet Gynecol MFM 2020[Aug]; 2 (3): 100127 PMID32342041show ga BACKGROUND: The ongoing coronavirus disease 2019 pandemic has severely affected the United States. During infectious disease outbreaks, forecasting models are often developed to inform resource utilization. Pregnancy and delivery pose unique challenges, given the altered maternal immune system and the fact that most American women choose to deliver in the hospital setting. OBJECTIVE: This study aimed to forecast the first pandemic wave of coronavirus disease 2019 in the general population and the incidence of severe, critical, and fatal coronavirus disease 2019 cases during delivery hospitalization in the United States. STUDY DESIGN: We used a phenomenological model to forecast the incidence of the first wave of coronavirus disease 2019 in the United States. Incidence data from March 1, 2020, to April 14, 2020, were used to calibrate the generalized logistic growth model. Subsequently, Monte Carlo simulation was performed for each week from March 1, 2020, to estimate the incidence of coronavirus disease 2019 for delivery hospitalizations during the first pandemic wave using the available data estimate. RESULTS: From March 1, 2020, our model forecasted a total of 860,475 cases of coronavirus disease 2019 in the general population across the United States for the first pandemic wave. The cumulative incidence of coronavirus disease 2019 during delivery hospitalization is anticipated to be 16,601 (95% confidence interval, 9711-23,491) cases, 3308 (95% confidence interval, 1755-4861) cases of which are expected to be severe, 681 (95% confidence interval, 1324-1038) critical, and 52 (95% confidence interval, 23-81) fatal. Assuming similar baseline maternal mortality rate as the year 2018, we projected an increase in maternal mortality rate in the United States to at least 18.7 (95% confidence interval, 18.0-19.5) deaths per 100,000 live births as a direct result of coronavirus disease 2019. CONCLUSION: Coronavirus disease 2019 in pregnant women is expected to severely affect obstetrical care. From March 1, 2020, we forecast 3308 severe and 681 critical cases with about 52 coronavirus disease 2019-related maternal mortalities during delivery hospitalization for the first pandemic wave in the United States. These results are significant for informing counseling and resource allocation. |*COVID-19/epidemiology/prevention & control[MESH] |*Delivery, Obstetric/methods/statistics & numerical data/trends[MESH] |*Health Care Rationing/methods/trends[MESH] |*Hospitalization/statistics & numerical data/trends[MESH] |*Obstetrics/organization & administration/statistics & numerical data/trends[MESH] |*Pregnancy Complications, Infectious/epidemiology/prevention & control[MESH] |*Resource Allocation/methods/trends[MESH] |Adult[MESH] |Female[MESH] |Forecasting[MESH] |Humans[MESH] |Incidence[MESH] |Maternal Mortality/trends[MESH] |Monte Carlo Method[MESH] |Patient Acceptance of Health Care[MESH] |Pregnancy[MESH] |SARS-CoV-2[MESH]Forecasting the impact of coronavirus disease during delivery hospital(epmc).pdf DeepDyve Pubget Overpricing