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http://scihub22266oqcxt.onion/ 33774948!ä!33774948 Deprecated: Implicit conversion from float 231.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 231.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 231.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 231.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 231.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 231.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 231.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 265.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 265.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 265.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 265.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 265.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 265.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 265.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 265.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       J+Ayub+Med+Coll+Abbottabad 2021 ; 33 (1): 20-25 Nephropedia Template TP {{tp|p=33774948|t=2021. Isaric 4c Mortality Score As A Predictor Of In-Hospital Mortality In Covid-19 Patients Admitted In Ayub Teaching Hospital During First Wave Of The Pandemic |pdf=|usr=}}{{33774948}} gab.com Text Isaric 4c Mortality Score As A Predictor Of In-Hospital Mortality In Covid-19 Patients Admitted In Ayub Teaching Hospital During First Wave Of The Pandemic JO: J Ayub Med Coll Abbottabad http://www.kidney.de/pget.php?&tw=1&pmid=33774948 #FOAvip BACKGROUND: Many factors have been identified which can predict severe outcomes and mortality in hospitalized patients of COVID-19. This study was conducted with the objective of finding out the association of various clinical and laboratory parameters as used by International Severe Acute Respiratory and emerging Infections Consortium (ISARIC) World Health Organization (WHO)- ISARIC/WHO 4C Mortality score in predicting high risk patients of COVID-19. Ascertaining the parameters would help in triage of patients of severe disease at the outset, and shall prove beneficial in improving the standard of care. METHODS: This cross-sectional study was carried out in COVID-19 Department of Ayub Teaching Hospital, Abbottabad. All COVID-19 patients admitted from 15th April to 15th July 2020 were included. RESULTS: A total of 347 patients were included in the study. The mean age was 56.46+/-15.44 years. Male patients were 225 (65%) and female 122 (35%). Diabetes (36%) was the most common co-morbidity, followed by hypertension (30.8%). Two hundred & six (63.8%) patients recovered and 117 (36.2%) patients died. Shortness of breath (80%), fever (79%) and cough (65%) were the most common presenting symptoms. Patients admitted with a 4C Mortality score of 0-3 (Low Risk Category), the patients who recovered were 36 (90%) and those who died were 4 (10.0%). In patients admitted with a 4C Mortality score of more than 14 (Very High-Risk Category), the number of patients who recovered was 1 (20%), and those who died were 4 (80%). The difference in mortality among the categories was statistically significant (p<0.001). Hypertension was a risk factor for death in patients of COVID-19 (Odds ratio=1.24, 95% CI [0.76-2.01]). Lymphopenia was not associated with statistically significant increased risk for mortality. CONCLUSIONS: The ISARIC 4C mortality score can be used for stratifying and predicting mortality in COVID-19 patients on arrival in hospital. We propose that it should be used in every patient of COVID-19 presenting to the hospital. Those falling in Low and Intermediate Risk Category should be managed in ward level. Those falling in High and Very High Category should be admitted in HDU/ICU with aggressive treatment from the start. Twit Text FOAVip Isaric 4c Mortality Score As A Predictor Of In-Hospital Mortality In Covid-19 Patients Admitted In Ayub Teaching Hospital During First Wave Of The Pandemic ????J Ayub Med Coll Abbottabad http://www.kidney.de/pget.php?&tw=1&pmid=33774948 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=33774948 #FOAvip English Wikipedia <ref>{{Cite pmid|33774948}}</ref> Isaric 4c Mortality Score As A Predictor Of In-Hospital Mortality In Covid-19 Patients Admitted In Ayub Teaching Hospital During First Wave Of The Pandemic #MMPMID33774948 Ali R; Qayyum F; Ahmed N; Haroon MZ; Irshad R; Sajjad S; Malik SQ; Saleem S; Hussain R; Zahid A; Farooq U J Ayub Med Coll Abbottabad 2021[Jan]; 33 (1): 20-25 PMID33774948show ga BACKGROUND: Many factors have been identified which can predict severe outcomes and mortality in hospitalized patients of COVID-19. This study was conducted with the objective of finding out the association of various clinical and laboratory parameters as used by International Severe Acute Respiratory and emerging Infections Consortium (ISARIC) World Health Organization (WHO)- ISARIC/WHO 4C Mortality score in predicting high risk patients of COVID-19. Ascertaining the parameters would help in triage of patients of severe disease at the outset, and shall prove beneficial in improving the standard of care. METHODS: This cross-sectional study was carried out in COVID-19 Department of Ayub Teaching Hospital, Abbottabad. All COVID-19 patients admitted from 15th April to 15th July 2020 were included. RESULTS: A total of 347 patients were included in the study. The mean age was 56.46+/-15.44 years. Male patients were 225 (65%) and female 122 (35%). Diabetes (36%) was the most common co-morbidity, followed by hypertension (30.8%). Two hundred & six (63.8%) patients recovered and 117 (36.2%) patients died. Shortness of breath (80%), fever (79%) and cough (65%) were the most common presenting symptoms. Patients admitted with a 4C Mortality score of 0-3 (Low Risk Category), the patients who recovered were 36 (90%) and those who died were 4 (10.0%). In patients admitted with a 4C Mortality score of more than 14 (Very High-Risk Category), the number of patients who recovered was 1 (20%), and those who died were 4 (80%). The difference in mortality among the categories was statistically significant (p<0.001). Hypertension was a risk factor for death in patients of COVID-19 (Odds ratio=1.24, 95% CI [0.76-2.01]). Lymphopenia was not associated with statistically significant increased risk for mortality. CONCLUSIONS: The ISARIC 4C mortality score can be used for stratifying and predicting mortality in COVID-19 patients on arrival in hospital. We propose that it should be used in every patient of COVID-19 presenting to the hospital. Those falling in Low and Intermediate Risk Category should be managed in ward level. Those falling in High and Very High Category should be admitted in HDU/ICU with aggressive treatment from the start. |*Pandemics[MESH] |*SARS-CoV-2[MESH] |COVID-19/*mortality[MESH] |Comorbidity[MESH] |Cross-Sectional Studies[MESH] |Female[MESH] |Hospital Mortality/trends[MESH] |Hospitalization/trends[MESH] |Hospitals, Teaching/*statistics & numerical data[MESH] |Humans[MESH] |Male[MESH] |Middle Aged[MESH] |Pakistan/epidemiology[MESH]Isaric 4c Mortality Score As A Predictor Of In-Hospital Mortality In C(epmc).pdf DeepDyve Pubget Overpricing