When a patient fulfils the study criteria and written informed consent is obtained, clinical data such as age, height, weight before pregnancy, ethnicity, highest finished education and social economic status based on postal code are collected at study-entry [ 44].
Additionally, education and income by zip-code was collected instead of individual education and income.
Zip codes were collected from Yahoo Finance and from HighBeam.Com.
These binary codes are collected in two separate histograms, and as a last step, the histograms are concatenated to form the LTP feature vector [21].
During the ICU stay, details regarding the need for IMV, vasopressors, RRT, occurrence of neutropenia (neutrophils < 0.5 G/L), and do not resuscitate (DNR) codes were collected daily.
The codes were collected in coding sheets and then organised by comparing the codes.
Baseline demographic characteristics including age, race, payor status, treatment, and zip codes were collected.
During ICU stay, SOFA scores, need for mechanical ventilation, vasopressors, RRT, and do-not-resuscitate codes were collected on a daily base.
For each scheduled, same-day, or urgent care patient encounter, ICD-9 codes are collected, recorded, and stored in a standardized electronic format, which fulfills the second criterion.
Common themes and codes were collected and analysed by two assessors (MM, AAS) using directed and summative qualitative content analysis [ 36] methods.
In the original UKADS data, patient post-codes were collected, which were linked to the area specific Carstairs deprivation index, with higher scores representing elevated deprivation and vice versa [ 23].
