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This is a non-core endpoint: only basic statistics are computed.

See these related core endpoints for full statistics:

Other fluke infections

EFO Endpoint Browser

AB1_OTHER_FLUKE

Endpoint definition

↥

Endpoint definition steps

FinnGen

Phenotype data

520210

1. Apply sex-specific rule

None

520210

2. Check conditions

None

520210

3. Check pre-conditions, main-only, mode, registry filters

Registry filters:

  • Hospital discharge: ICD-10 — B66
  • Hospital discharge: ICD-9 — 121
  • Hospital discharge: ICD-8 — 121
  • Cause of death: ICD-10 — B66
  • Cause of death: ICD-9 — 121
  • Cause of death: ICD-8 — 121

2 out of 7 registries used, show all original rules.

15

4. Check minimum number of events

None

15

5. Include endpoints

None

15

6. Filter based on genotype QC (FinnGen only)

15

Control definitions (FinnGen only)

Control exclude
AB1_HELMINTIASES

Extra metadata

Level in the ICD hierarchy
3
First used in FinnGen datafreeze
DF5

Case counts by codes

↥

FinnGen case counts by registry codes:

Not enough data for upset plot.

Not enough data for upset table.

Summary Statistics

↥

-FinRegistry-

Key figures

All Female Male
Number of individuals
Whole population 177 94 81
Only index persons 136 77 59
Unadjusted period prevalence (%)
Whole population 0.00 0.00 0.00
Only index persons 0.00 0.00 0.00
Median age at first event (years)
Whole population 40.22 39.27 40.55
Only index persons 34.81 35.57 33.82

-FinnGen-

Key figures

All Female Male
Number of individuals 15 10 5
Unadjusted period prevalence (%) 0.00 0.00 0.00
Median age at first event (years) 30.60 30.92 29.98

-FinRegistry-

Age distribution of first events

-FinnGen-

Age distribution of first events

-FinRegistry-

Year distribution of first events

-FinnGen-

Year distribution of first events

-FinRegistry-

Cumulative Incidence Function

No data

-FinnGen-

Cumulative Incidence Function

Not a core endpoint, no data to show.

CodeWAS (R11)

↥

CodeWAS is a tool for exploring the associations between an endpoint and all of the medical codes and drug codes.

This is a new tool, please reach out using the contact form for feedback and improvement ideas.

First, a cohort is built by matching controls to the endpoint cases using year of birth and sex. Then, a Fisher test is done for all the medical codes and drug codes between the cases and controls of this cohort. Codes are reported in the table below if they have −log10(p-value) ≥ 6.

No data available

LabWAS

↥
OMOP Concept
People with measurements
Mean N measurements
Mean measured value
(ID) Name
N Cases
N Controls
OR
-log10(p)
cases
controls
cases
controls
unit
-log10(p)
N cases
N controls
6
11
8.23
2.86
1.2
1.2
—
—
—
0
0
5
9
7.65
2.41
1.2
1.2
—
—
—
0
0
7
25
4.32
1.95
1.3
1.5
—
—
—
0
0
9
43
3.70
1.72
1.4
1.4
—
—
—
0
0
6
22
3.84
1.63
1.3
1.3
—
—
—
0
0
7
31
3.33
1.33
1.3
1.8
—
—
—
0
0
5
26
2.37
0.79
6.6
6.6
—
—
—
0
0
6
34
2.26
0.70
4.7
2.9
—
—
—
0
0
5
31
1.91
0.49
2.2
3.7
—
—
—
0
0
0
15
0.00
0.44
0.0
2.1
—
—
—
0
0
0
16
0.00
0.44
0.0
9.6
—
102.5
—
0
16
0
16
0.00
0.44
0.0
4.3
—
0.4
—
0
5
15
136
+∞
0.43
12.3
15.1
66.5
70.1
umol/l
0.39
15
136
0
14
0.00
0.43
0.0
2.1
—
—
—
0
0
6
42
1.71
0.43
10.7
6.1
—
—
—
0
0
5
72
0.54
0.38
2.0
4.8
6.0
6.5
mmol/l
—
5
66
7
55
1.51
0.24
3.1
3.0
—
—
—
0
0
10
88
1.41
0.23
5.2
3.7
18.9
10.2
mm/h
—
10
76
0
10
0.00
0.22
0.0
5.6
—
—
—
0
0
0
10
0.00
0.22
0.0
4.6
—
—
—
0
0
0
10
0.00
0.22
0.0
2.1
—
5.2
—
0
10
15
140
+∞
0.22
7.9
12.5
—
—
—
0
0
0
12
0.00
0.22
0.0
13.4
—
122.2
—
0
12
0
12
0.00
0.22
0.0
2.8
—
5.8
—
0
12
0
12
0.00
0.22
0.0
13.3
—
12.9
—
0
12
0
12
0.00
0.22
0.0
13.4
—
5.4
—
0
12
0
12
0.00
0.22
0.0
3.3
—
—
—
0
0
0
12
0.00
0.22
0.0
13.5
—
97.2
—
0
12
0
13
0.00
0.21
0.0
4.6
—
1.1
—
0
13
10
99
1.03
0.00
2.7
5.2
13.3
15.0
pmol/l
—
10
92
0
5
0.00
0.00
0.0
1.4
—
—
—
0
0
0
6
0.00
0.00
0.0
6.0
—
—
—
0
0
0
9
0.00
0.00
0.0
3.4
—
—
—
0
0
0
5
0.00
0.00
0.0
6.2
—
10.6
—
0
5
0
9
0.00
0.00
0.0
5.0
—
—
—
0
0
0
5
0.00
0.00
0.0
2.0
—
—
—
0
0
0
6
0.00
0.00
0.0
9.3
—
0.8
—
0
6
0
5
0.00
0.00
0.0
22.4
—
625.4
—
0
5
0
9
0.00
0.00
0.0
1.1
—
—
—
0
0
0
5
0.00
0.00
0.0
6.2
—
107.2
—
0
5
0
6
0.00
0.00
0.0
8.7
—
1.0
—
0
6
0
8
0.00
0.00
0.0
13.0
—
1.0
—
0
8
0
9
0.00
0.00
0.0
1.1
—
—
—
0
0
0
5
0.00
0.00
0.0
1.2
—
—
—
0
0
0
7
0.00
0.00
0.0
2.9
—
6.3
—
0
7
0
9
0.00
0.00
0.0
3.4
—
26.4
—
0
9
0
5
0.00
0.00
0.0
26.8
—
1392.4
—
0
5
0
9
0.00
0.00
0.0
3.1
—
127.3
—
0
9
0
7
0.00
0.00
0.0
1.3
—
—
—
0
0
0
6
0.00
0.00
0.0
2.7
—
—
—
0
0
0
7
0.00
0.00
0.0
8.6
—
26.0
—
0
7
0
9
0.00
0.00
0.0
15.2
—
25.5
—
0
9
0
7
0.00
0.00
0.0
2.9
—
0.9
—
0
7
0
9
0.00
0.00
0.0
2.9
—
3.6
—
0
9
0
8
0.00
0.00
0.0
12.6
—
1.7
—
0
8

Mortality – FinRegistry

↥

Association

Association between endpoint AB1_OTHER_FLUKE and mortality.

Females

No data

Males

No data

Mortality risk

Mortality risk for people of age

years, who have AB1_OTHER_FLUKE.

N-year risk Females Males
1 No data No data
5 No data No data
10 No data No data
15 No data No data
20 No data No data

Relationships between endpoints

↥

Index endpoint: AB1_OTHER_FLUKE – Other fluke infections

GWS hits: -

Endpoint
Case Overlap
Survival Analysis
Genetic Correlations
Genetic Signals
N (Jaccard index)
HR [CI]
rg [CI]
Hits
Coloc Hits
FinRegistry
FinnGen
FinRegistry
FinnGen
FinnGen
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