Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

[pull] master from spiros:master #3

Open
wants to merge 57 commits into
base: master
Choose a base branch
from
Open
Show file tree
Hide file tree
Changes from all commits
Commits
Show all changes
57 commits
Select commit Hold shift + click to select a range
c9155eb
naming harmonization
spiros Sep 6, 2019
73fbbdb
harmonization
spiros Sep 6, 2019
475b3b5
harmonization
spiros Sep 6, 2019
4746ad0
harmonization
spiros Sep 6, 2019
c0349b5
harmonization
spiros Sep 9, 2019
cf0d50b
harmonization
spiros Sep 9, 2019
5c14fa7
consistent header information for procedures
spiros Sep 9, 2019
dddb6e6
removed additional column
spiros Sep 9, 2019
db9135b
removed additional column
spiros Sep 9, 2019
c1f09cb
removed additional column
spiros Sep 9, 2019
6d940e5
cleaned up file
spiros Sep 9, 2019
28dcfb7
cleaned up file
spiros Sep 9, 2019
a0979bc
cleaned up file
spiros Sep 9, 2019
e549684
streamline columns
spiros Sep 9, 2019
562d7f8
renamed file
spiros Sep 9, 2019
81fed38
utf8 fun
spiros Sep 9, 2019
12cb9a4
name fix
spiros Sep 9, 2019
c94ffc4
name fix
spiros Sep 9, 2019
d0079ab
renamed phenotype
spiros Sep 9, 2019
b587533
consistent naming
spiros Sep 9, 2019
cc595c1
consistent naming
spiros Sep 9, 2019
7f7158a
consistent naming
spiros Sep 9, 2019
ce502f2
consistent naming
spiros Sep 9, 2019
13d5f9f
renamed to align
spiros Sep 18, 2019
6ae98ce
renamed to align
spiros Sep 18, 2019
67127ab
renamed to align
spiros Sep 18, 2019
eb073f2
renamed to align
spiros Sep 18, 2019
854675d
updated readme file
spiros Sep 18, 2019
39b1a62
Merge pull request #3 from spiros/harmonization
spiros Sep 18, 2019
13b8deb
renamed branch in github file links
spiros Sep 18, 2019
ad0d9c6
top level CSV dictionary
spiros Sep 18, 2019
6d6b3c5
update data dictionary
spiros Nov 14, 2019
828a522
phenotype files for CALIBER phenotypes
spiros Nov 14, 2019
9cb5462
CALIBER phenotype implemention Read/ICD codes from @GFatemifar
spiros Nov 19, 2019
33e2264
updated dictionary file with hypertension
spiros Nov 19, 2019
7141d9f
Updated README file
spiros Nov 25, 2019
71d4eff
added note that GH will not render markdown file
spiros Jan 7, 2020
194de19
Methods file
spiros Jan 24, 2020
dbe2005
References
spiros Jan 24, 2020
f3997b8
spacing
spiros Jan 24, 2020
f7718d6
git ignore
spiros Mar 23, 2020
32d55e4
git ignore
spiros Mar 23, 2020
45a864f
chmod -x
spiros Jun 22, 2020
07594b8
chmod -x
spiros Jun 22, 2020
26e795a
expanded README to include information on the terminology used in eac…
spiros Feb 9, 2021
0e38142
Update ICD_stable_angina.csv
nels Mar 8, 2021
3ac04ef
Update ICD_unstable_angina.csv
nels Mar 8, 2021
7d268d5
Update ICD_peripheral_arterial_disease.csv
nels Mar 8, 2021
f07197b
Update ICD_AAA.csv
nels Mar 8, 2021
6056a3c
Update ICD_CHD_NOS.csv
nels Mar 8, 2021
b2d449f
add mapping of phenotypes to categories
tomlincr Jul 13, 2021
031e586
Merge pull request #6 from tomlincr/master
spiros Jul 27, 2021
b210723
Merge pull request #5 from nels/patch-1
spiros Jul 27, 2021
4a87637
fixed typo in CKD stage 3 definition
spiros Jul 10, 2023
eaf1b6d
Merge pull request #15 from spiros/ckdtypo
spiros Jul 10, 2023
c110953
removed lines where the Phenotype was missing - closes #16
spiros Jun 14, 2024
f4f614f
added information on the existing CALIBER phenotype components used i…
spiros Jun 28, 2024
File filter

Filter by extension

Filter by extension

Conversations
Failed to load comments.
Loading
Jump to
The table of contents is too big for display.
Diff view
Diff view
  •  
  •  
  •  
1 change: 1 addition & 0 deletions .gitignore
Original file line number Diff line number Diff line change
@@ -0,0 +1 @@
.DS_Store
25 changes: 25 additions & 0 deletions METHODS.md
Original file line number Diff line number Diff line change
@@ -0,0 +1,25 @@
# Selection of health conditions
The number of finished consultant episodes (FCEs) (the time spent under the care of one consultant whilst an inpatient) for all diagnoses in England from 1 April 2014 to 31 March 2015 was obtained from inpatient activity reports published by NHS Digital [1]. Diagnoses were coded using three and four character International Classification of Diseases, tenth revision (ICD-10) codes. The FCEs for codes in ICD-10 chapters I-XIV and XVI-XVII were examined. Pregnancy-related conditions, symptoms, signs, abnormal clinical and laboratory findings, and external causes of morbidity and mortality were excluded. Three or four character ICD-10 codes were assigned to specific conditions in the different disease categories as agreed between Dr Valerie Kuan and: Professor Aroon Hingorani (benign neoplastic, cancers, cardiovascular, digestive, ear, endocrine, eye, genitourinary, haematological or immunological, infections, musculoskeletal, neurological, perinatal or congenital, psychiatric, respiratory, and skin), Dr Osman Bhatti (benign neoplastic, cancers, ear, endocrine, eye, haematological or immunological, musculoskeletal, neurological, perinatal or congenital, psychiatric, respiratory, and skin), Dr Shanaz Husain (benign neoplastic, cancers, ear, endocrine, eye, haematological or immunological, musculoskeletal, neurological, perinatal or congenital, psychiatric, respiratory, and skin), Dr Shailen Sutaria (infections), Professor Dorothea Nitsch (genitourinary), Mrs Melanie Hingorani (eye), Dr Constantinos Parisinos (digestive), Dr Tom Lumbers (cardiovascular) and Dr Reecha Sofat (cardiovascular).

Conditions with codes that had more than 10,000 FCEs were included. If a condition had fewer than 10,000 FCEs but it was considered to be clinically important, it was included in the study.

Infections were categorized by organ system and causal organism. Chronic infections with long-term sequelae included were HIV, chronic viral hepatitis, tuberculosis, and rheumatic fever. Acute infections were limited to hospital admissions. Obesity was only considered for individuals above the age of 18 years.

308 physical and mental health conditions involving intensive use of healthcare resources were selected. These included health conditions from QOF, with modifications for more granular phenotypes reflecting distinct pathological pathways where applicable, such as type 1 diabetes mellitus, type 2 diabetes mellitus and diabetes mellitus (‘other’ or ‘unspecified’).

# Derivation of phenotyping algorithms
Health conditions were harmonised across primary and secondary care coding systems and organised into 16 disease categories corresponding closely to ICD-10 chapters.

Phenotyping algorithms defining 302 of the 308 conditions were based on diagnosis or procedural codes. The case definitions for the remaining six conditions used blood test values or other measures, namely: estimated glomerular filtration rate (eGFR) for chronic kidney disease, total cholesterol (TC) for raised total cholesterol, low density lipoprotein-cholesterol (LDL-C) for raised LDL-C, high density lipoprotein-cholesterol (HDL-C) for low HDL-C, triglyceride (TG) for raised triglyceride and body mass index (BMI) for obesity. Phenotyping algorithms for eleven conditions (stable angina, unstable angina, myocardial infarction, coronary heart disease not otherwise specified, hypertension, peripheral arterial disease, atrial fibrillation, abdominal aortic aneurysm, type 1 diabetes, type 2 diabetes and diabetes other or not specified) were adapted from algorithms and codelists that had previously been defined in the CALIBER portal.

Diagnoses and procedures are recorded in CPRD using Read codes. ICD-10 diagnosis codes and Office of the Population Censuses and Surveys Classification of Interventions and Procedures version 4 (OPCS-4) procedural codes are used in HES-APC.

The selection of ICD-10 codes for the ICD-10 codelists has been described above. These ICD-10 codes were mapped to Read codes as follows: cross-maps provided by NHS Digital were used to look up similar terms between ICD-10 and Read codes [2]; a list of keywords for each condition was constructed in agreement with the clinicians responsible for diseases in the respective categories; keyword searches were performed on a lookup file provided by CPRD (medical.txt) which contains Read codes, CPRD medcodes and a verbal description common to both codes; Read codes with their corresponding descriptive terms identified from the cross-mapping and keyword searches were concatenated into a long list; the long list was further supplemented by Read codes in the Read code hierarchy that were adjacent to the codes identified from the cross-mapping and keyword searches, which were considered possible candidates for inclusion in the respective codelists; finally, this long list was pruned in collaboration with the clinicians responsible for the respective categories to obtain the final Read codelists for each condition.

Where procedures were identified in Read codes for a specific condition, a keyword search for these procedures was performed in the OPCS-4 dictionary. These terms were concatenated with adjacent terms within the OPCS-4 hierarchy that were considered potentially relevant to the specific condition to form a long list. The final OPCS-4 codelist was constructed from this long list together with the clinicians responsible for diseases in the respective categories.

# References
1. NHS Digital, https://digital.nhs.uk/data-and-information/publications/statistical/hospital-admitted-patient-care-activity/hospital-episode-statistics-admitted-patient-care-england-2014-15

2. https://isd.digital.nhs.uk/trud3/user/guest/group/0/pack/9/subpack/255/releases

Loading