correction to probabilities of icu admission and hospital discharge according to CORD-Papers-2022-06-02 (Version 1)

Title: Correction to: Probabilities of ICU admission and hospital discharge according to patient characteristics in the designated COVID-19 hospital of Kuwait
Published: 2021-06-22
Journal: BMC Public Health
DOI: 10.1186/s12889-021-11146-4
Author Name: Kipourou Dimitra Kleio
Author link:
Author Name: Leyrat Clmence
Author link:
Author Name: Alsheridah Nourah
Author link:
Author Name: Almazeedi Sulaiman
Author link:
Author Name: Al Youha Sarah
Author link:
Author Name: Jamal Mohammad H
Author link:
Author Name: Al Haddad Mohannad
Author link:
Author Name: Al Sabah Salman
Author link:
Author Name: Rachet Bernard
Author link:
Author Name: Belot Aurlien
Author link:
sha: 1aed6fd90edd7d5ab4a9880bbba8381edf06c1d3
license: cc-by
source_x: Medline; PMC; WHO
pubmed_id: 34157992
pmcid: PMC8218567
has_full_text: TRUE
Keywords Extracted from Text Content: β j causespecific λ j −F j P(T ≤ t S1.1 Event-specific −
Extracted Text Content in Record: First 5000 Characters:S1.1 Event-specific cumulative probabilities 1 The cumulative progression over time to the event of interest is known as the causespecific cumulative probability F j (t) and it is defined as the probability of progressing to event j in the presence of other events between time 0 and t as a function of time since diagnosis This quantity is determined by all event -specific hazards hence, the probability of 2 event j is defined as 3 F j (t) = P(T ≤ t, event = j) t 0 λ j (u)S (u)du (1) where S (t) is the overall survival, S (t) = exp − t 0 J j=1 λ j (u)du [1, 2] . 4 Non-Parametric estimation of probabilities 5 We can use the Aalen -Johansen estimator for the non -parametric estimation of the 6 event -specific cumulative probabilities as follows With this estimator we are able to compute the cumulative probability of a specific 10 event for a population or a subgroup but not for individuals. Estimation with Flexible Regression Models (FRM) 1 Conversely, using a modelling approach we are able to predict for specific covariate combinations allowing for individual (and population) predictions. Here, we employ an FRM for the (logarithm of) the (event j)-specific hazard expressed as where β j is a vector of regression parameters used which includes the parameters for 2 (i) the baseline hazard and (ii) the time-dependent (cause j)-specific hazard ratios, i.e. where Ω = exp ±z α s.e. log − log(F j (t, x;β)) , z α is the (1-α/2) quantile of the 1 standard normal distribution. We could also use the 1 −F j (t, x;β) instead to avoid issues with the denominator. Fig. 3 : ICU -specific hazard ratios with confidence intervals based on the full cohort (using Cox and FRM) and separately for Kuwaiti and non -Kuwaiti population (using FRM).
PDF JSON Files: document_parses/pdf_json/1aed6fd90edd7d5ab4a9880bbba8381edf06c1d3.json
G_ID: correction_to_probabilities_of_icu_admission_and_hospital_discharge_according_to