acute kidney tubular necrosis: Acute renal failure caused by the cell death of the renal tubules. Causes include nephrotoxins, cytotoxic drugs, and antibiotics.
Drug- and heavy-metal-induced tubulo-interstitial and tubular conditions
DOID EFO PheWeb R13 (public) Endpoint Browser PheWeb
N14_DRUGSANDHEAVYMETAL
Endpoint definition
↥Report an error or suggest an improvement for this endpoint codes
Endpoint definition steps |
FinnGen |
|---|---|
Phenotype data |
519870 |
1. Apply sex-specific ruleNone |
519870 |
2. Check conditionsNone |
519870 |
3. Check pre-conditions, main-only, mode, registry filtersRegistry filters: 2 out of 7 registries used, show all original rules. |
111 |
4. Check minimum number of eventsNone |
111 |
5. Include endpointsNone |
111 |
6. Filter based on genotype QC (FinnGen only) |
106 |
Control definitions (FinnGen only)
- Control exclude
- N14_RENALTUB
Extra metadata
- Level in the ICD hierarchy
- 3
- First used in FinnGen datafreeze
- DF2
- Parent code in ICD-10
- N10-N16
- Name in latin
- Condiciones tubulo-interstitiales et tubulares ex medicamentis et metallis gravibus
Similar endpoints
↥List of similar endpoints to
Drug- and heavy-metal-induced tubulo-interstitial and tubular conditions
based on the number of shared cases.
Similar with more cases:
- Renal tubulo-interstitial diseases
- All kidney diseases
- Genitourinary diseases
- Any operation in hilmo
- Any prescribed medicine buy
Similar with less cases:
Case counts by codes
↥Summary Statistics
↥-FinRegistry-
Key figures
| All | Female | Male | |
|---|---|---|---|
| Number of individuals | |||
| Whole population | 684 | 289 | 389 |
| Only index persons | 549 | 241 | 308 |
| Unadjusted period prevalence (%) | |||
| Whole population | 0.01 | 0.01 | 0.01 |
| Only index persons | 0.01 | 0.01 | 0.01 |
| Median age at first event (years) | |||
| Whole population | 64.13 | 65.48 | 62.95 |
| Only index persons | 62.02 | 64.29 | 60.25 |
-FinnGen-
Key figures
| All | Female | Male | |
|---|---|---|---|
| Number of individuals | 106 | 44 | 62 |
| Unadjusted period prevalence (%) | 0.02 | 0.02 | 0.03 |
| Median age at first event (years) | 60.32 | 62.43 | 58.82 |
-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
-FinnGen-
Cumulative Incidence Function
CodeWAS
↥CodeWAS is a tool for exploring the associations between an endpoint and all of the medical codes and drug codes.
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.
Matched cohort
- Matched cases
- 111
- Matched controls
- 1110
TimeCodeWAS
↥TimeCodeWAS is a tool for exploring time-dependent associations between an endpoint and health codes (diagnoses, lab tests, procedures, etc.).
The TimeCodeWAS analysis is done in three steps:
- Build a matched case-control set for this endpoint. Each case is matched to 5–10 controls on sex and year of birth, and controls must be at risk at the same age as the case's age of onset. TimeCodeWAS allows for controls to be reused.
- Count cases and controls. For each health code, and for each time window: tally the counts into a 2×2 table. To be eligible in a time window, a case or control must have data coverage for at least 50% of that time window.
- Perform association tests. If all cells of the 2×2 table have N≥10, then a χ² test is performed, otherwise a Fisher's exact test is done. The corresponding p-value and confidence interval are reported below, along with the standard odds ratio when a χ² test is done, or Fisher's MLE odds ratio otherwise.
TimeCodeWAS currently uses the same default set of time windows for all the endpoints. Please reach out to us if you have suggestions for better time windows for some endpoints.
The default time windows are:
LabWAS
↥Mortality – FinRegistry
↥Association
Association between endpoint N14_DRUGSANDHEAVYMETAL and mortality.
Females
| Parameter | HR [95% CI] | p-value |
|---|---|---|
| N14_DRUGSANDHEAVYMETAL | 3.362 [2.25, 5.03] | < 0.001 |
| Birth year | 0.996 [0.99, 1.0] | 0.349 |
During the follow-up period (1.1.1998 — 31.12.2019), 99 out of 233 females with N14_DRUGSANDHEAVYMETAL died.
Males
| Parameter | HR [95% CI] | p-value |
|---|---|---|
| N14_DRUGSANDHEAVYMETAL | 3.426 [2.35, 4.99] | < 0.001 |
| Birth year | 0.984 [0.97, 0.99] | 0.001 |
During the follow-up period (1.1.1998 — 31.12.2019), 143 out of 306 males with N14_DRUGSANDHEAVYMETAL died.
Mortality risk
Mortality risk for people of age
years, who have N14_DRUGSANDHEAVYMETAL.| N-year risk | Females | Males |
|---|---|---|
| 1 | 0.39% | 0.579% |
| 5 | 1.968% | 3.236% |
| 10 | 4.881% | 8.516% |
| 15 | 9.146% | 16.055% |
| 20 | 15.779% | 26.508% |
Relationships between endpoints
↥Index endpoint: N14_DRUGSANDHEAVYMETAL – Drug- and heavy-metal-induced tubulo-interstitial and tubular conditions
GWS hits: -