tetano
Editor, Senior Moderator
Infect Control Hosp Epidemiol
. 2024 Feb 14:1-8.
doi: 10.1017/ice.2024.3. Online ahead of print. Differentiating patients admitted primarily due to coronavirus disease 2019 (COVID-19) from those admitted with incidentally detected severe acute respiratory syndrome corona-virus type 2 (SARS-CoV-2) at hospital admission: A cohort analysis of German hospital records
Ralf Strobl[SUP] #[/SUP][SUP] 1 2 [/SUP], Martin Misailovski[SUP] #[/SUP][SUP] 3 [/SUP], Sabine Blaschke[SUP] #[/SUP][SUP] 4 [/SUP], Milena Berens[SUP] 3 [/SUP], Andreas Beste[SUP] 3 [/SUP], Manuel Krone[SUP] 5 6 [/SUP], Michael Eisenmann[SUP] 5 6 [/SUP], Sina Ebert[SUP] 5 6 [/SUP], Anna Hoehn[SUP] 5 6 [/SUP], Juliane Mees[SUP] 6 [/SUP], Martin Kaase[SUP] 3 [/SUP], Dhia J Chackalackal[SUP] 3 [/SUP], Daniela Koller[SUP] 1 [/SUP], Julia Chrampanis[SUP] 3 [/SUP], Jana-Michelle Kosub[SUP] 3 [/SUP], Nikita Srivastava[SUP] 3 [/SUP], Fady Albashiti[SUP] 7 [/SUP], Uwe Groß[SUP] 8 [/SUP], Andreas Fischer[SUP] 9 [/SUP], Eva Grill[SUP] #[/SUP][SUP] 1 2 [/SUP], Simone Scheithauer[SUP] #[/SUP][SUP] 3 [/SUP]
Affiliations
Objective: The number of hospitalized patients with severe acute respiratory syndrome coronavirus type 2 (SARS-CoV-2) does not differentiate between patients admitted due to coronavirus disease 2019 (COVID-19) (ie, primary cases) and incidental SARS-CoV-2 infection (ie, incidental cases). We developed an adaptable method to distinguish primary cases from incidental cases upon hospital admission.
Design: Retrospective cohort study.
Setting: Data were obtained from 3 German tertiary-care hospitals.
Patients: The study included patients of all ages who tested positive for SARS-CoV-2 by a standard quantitative reverse-transcription polymerase chain reaction (RT-PCR) assay upon admission between January and June 2022.
Methods: We present 2 distinct models: (1) a point-of-care model that can be used shortly after admission based on a limited range of parameters and (2) a more extended point-of-care model based on parameters that are available within the first 24-48 hours after admission. We used regression and tree-based classification models with internal and external validation.
Results: In total, 1,150 patients were included (mean age, 49.5±28.5 years; 46% female; 40% primary cases). Both point-of-care models showed good discrimination with area under the curve (AUC) values of 0.80 and 0.87, respectively. As main predictors, we used admission diagnosis codes (ICD-10-GM), ward of admission, and for the extended model, we included viral load, need for oxygen, leucocyte count, and C-reactive protein.
Conclusions: We propose 2 predictive algorithms based on routine clinical data that differentiate primary COVID-19 from incidental SARS-CoV-2 infection. These algorithms can provide a precise surveillance tool that can contribute to pandemic preparedness. They can easily be modified to be used in future pandemic, epidemic, and endemic situations all over the world.
. 2024 Feb 14:1-8.
doi: 10.1017/ice.2024.3. Online ahead of print. Differentiating patients admitted primarily due to coronavirus disease 2019 (COVID-19) from those admitted with incidentally detected severe acute respiratory syndrome corona-virus type 2 (SARS-CoV-2) at hospital admission: A cohort analysis of German hospital records
Ralf Strobl[SUP] #[/SUP][SUP] 1 2 [/SUP], Martin Misailovski[SUP] #[/SUP][SUP] 3 [/SUP], Sabine Blaschke[SUP] #[/SUP][SUP] 4 [/SUP], Milena Berens[SUP] 3 [/SUP], Andreas Beste[SUP] 3 [/SUP], Manuel Krone[SUP] 5 6 [/SUP], Michael Eisenmann[SUP] 5 6 [/SUP], Sina Ebert[SUP] 5 6 [/SUP], Anna Hoehn[SUP] 5 6 [/SUP], Juliane Mees[SUP] 6 [/SUP], Martin Kaase[SUP] 3 [/SUP], Dhia J Chackalackal[SUP] 3 [/SUP], Daniela Koller[SUP] 1 [/SUP], Julia Chrampanis[SUP] 3 [/SUP], Jana-Michelle Kosub[SUP] 3 [/SUP], Nikita Srivastava[SUP] 3 [/SUP], Fady Albashiti[SUP] 7 [/SUP], Uwe Groß[SUP] 8 [/SUP], Andreas Fischer[SUP] 9 [/SUP], Eva Grill[SUP] #[/SUP][SUP] 1 2 [/SUP], Simone Scheithauer[SUP] #[/SUP][SUP] 3 [/SUP]
Affiliations
- PMID: 38351873
- DOI: 10.1017/ice.2024.3
Objective: The number of hospitalized patients with severe acute respiratory syndrome coronavirus type 2 (SARS-CoV-2) does not differentiate between patients admitted due to coronavirus disease 2019 (COVID-19) (ie, primary cases) and incidental SARS-CoV-2 infection (ie, incidental cases). We developed an adaptable method to distinguish primary cases from incidental cases upon hospital admission.
Design: Retrospective cohort study.
Setting: Data were obtained from 3 German tertiary-care hospitals.
Patients: The study included patients of all ages who tested positive for SARS-CoV-2 by a standard quantitative reverse-transcription polymerase chain reaction (RT-PCR) assay upon admission between January and June 2022.
Methods: We present 2 distinct models: (1) a point-of-care model that can be used shortly after admission based on a limited range of parameters and (2) a more extended point-of-care model based on parameters that are available within the first 24-48 hours after admission. We used regression and tree-based classification models with internal and external validation.
Results: In total, 1,150 patients were included (mean age, 49.5±28.5 years; 46% female; 40% primary cases). Both point-of-care models showed good discrimination with area under the curve (AUC) values of 0.80 and 0.87, respectively. As main predictors, we used admission diagnosis codes (ICD-10-GM), ward of admission, and for the extended model, we included viral load, need for oxygen, leucocyte count, and C-reactive protein.
Conclusions: We propose 2 predictive algorithms based on routine clinical data that differentiate primary COVID-19 from incidental SARS-CoV-2 infection. These algorithms can provide a precise surveillance tool that can contribute to pandemic preparedness. They can easily be modified to be used in future pandemic, epidemic, and endemic situations all over the world.