Aerts 2017 INTERCHEST: six equally weighted predictors for CAD in primary-care chest pa…
Aerts 2017 INTERCHEST: six equally weighted predictors for CAD in primary-care chest pain (age ≥55 male or ≥65 female +1; physician suspected serious +1; history of CAD +1; pain on exertion +1; pressure quality +1; pain reproducible on palpation −1). Range −1…
by api.magentlab.com · discovered, not yet claimed by its owner · updated 2026-10-13
Mirrored from Coinbase's public x402 Bazaar. The description is the provider's own text and has not been reviewed here; the payment requirements are copied as published.
What it does
Aerts 2017 INTERCHEST: six equally weighted predictors for CAD in primary-care chest pain (age ≥55 male or ≥65 female +1; physician suspected serious +1; history of CAD +1; pain on exertion +1; pressure quality +1; pain reproducible on palpation −1). Range −1 to 5. CAD considered absent iff score <2. Published CAD probability 2.1% (95% CI 1.1–3.9) when <2 and 43.0% (35.8–50.4) when ≥2 in the 13.2% prevalence setting. Not HEART, not EDACS. magent does not examine the chest.
Tags: interchest · acs · chest-pain · primary-care · calculator · bazaar
Call contract
- Method
- POST
- Input
- HTTP request
- Output
- json
- Last paid call
- 2026-10-13
{
"items": [
{
"age": 40,
"history_of_cad": false,
"pain_on_exertion": false,
"pain_reproducible_on_palpation": false,
"physician_suspected_serious": false,
"pressure_quality": false,
"sex": "female"
},
{
"age": 40,
"history_of_cad": false,
"pain_on_exertion": false,
"pain_reproducible_on_palpation": false,
"physician_suspected_serious": false,
"pressure_quality": false,
"sex": "female"
}
]
}{
"count": 2,
"items": [
{
"age_years": 40,
"cad_absent": true,
"cad_probability_ci_high_percent": 3.9,
"cad_probability_ci_low_percent": 1.1,
"cad_probability_percent": 2.1,
"citation": {
"authors": "Aerts M, Minalu G, Bösner S, Buntinx F, Burnand B, Haasenritter J, Herzig L, Knottnerus JA, Nilsson S, Renier W, Sox C, Sox H, Donner-Banzhoff N, International Working Group on Chest Pain in Primary Care (INTERCHEST)",
"doi": "10.1016/j.jclinepi.2016.09.011",
"id": "aerts-2017",
"pmid": "27773828",
"source": "J Clin Epidemiol. 2017;81:120-128",
"title": "Pooled individual patient data from five countries were used to derive a clinical prediction rule for coronary artery disease in primary care"
},
"components": [
{
"factor": "age_sex",
"points": 0,
"present": false,
"value": 40
},
{
"factor": "physician_suspected_serious",
"points": 0,
"present": false
},
{
"factor": "history_of_cad",
"points": 0,
"present": false
},
{
"factor": "pain_on_exertion",
"points": 0,
"present": false
},
{
"factor": "pressure_quality",
"points": 0,
"present": false
},
{
"factor": "pain_reproducible_on_palpation",
"points": 0,
"present": false
}
],
"disclaimer": "Not a medical device. Deterministic published-formula or published-code output for autonomous agents. A licensed clinician remains responsible for patient care and billing submissions.",
"formula": "interchest",
"formula_expression": "INTERCHEST = (age ≥55 if male or ≥65 if female) + physician_suspected_serious + history_of_cad + pain_on_exertion + pressure_quality − pain_reproducible_on_palpation; each ±1; range −1 to 5; CAD considered absent iff score <2 (Aerts 2017); CAD probability 2.1% (95% CI 1.1–3.9) when <2 and 43.0% (35.8–50.4) when ≥2 in the 13.2% prevalence setting",
"max_score": 5,
"min_score": -1,
"prevalence_setting_percent": 13.2,
"score": 0,
"sex": "female"
},
{
"age_years": 40,
"cad_absent": true,
"cad_probability_ci_high_percent": 3.9,
"cad_probability_ci_low_percent": 1.1,
"cad_probability_percent": 2.1,
"citation": {
"authors": "Aerts M, Minalu G, Bösner S, Buntinx F, Burnand B, Haasenritter J, Herzig L, Knottnerus JA, Nilsson S, Renier W, Sox C, Sox H, Donner-Banzhoff N, International Working Group on Chest Pain in Primary Care (INTERCHEST)",
"doi": "10.1016/j.jclinepi.2016.09.011",
"id": "aerts-2017",
"pmid": "27773828",
"source": "J Clin Epidemiol. 2017;81:120-128",
"title": "Pooled individual patient data from five countries were used to derive a clinical prediction rule for coronary artery disease in primary care"
},
"components": [
{
"factor": "age_sex",
"points": 0,
"present": false,
"value": 40
},
{
"factor": "physician_suspected_serious",
"points": 0,
"present": false
},
{
"factor": "history_of_cad",
"points": 0,
"present": false
},
{
"factor": "pain_on_exertion",
"points": 0,
"present": false
},
{
"factor": "pressure_quality",
"points": 0,
"present": false
},
{
"factor": "pain_reproducible_on_palpation",
"points": 0,
"present": false
}
],
"disclaimer": "Not a medical device. Deterministic published-formula or published-code output for autonomous agents. A licensed clinician remains responsible for patient care and billing submissions.",
"formula": "interchest",
"formula_expression": "INTERCHEST = (age ≥55 if male or ≥65 if female) + physician_suspected_serious + history_of_cad + pain_on_exertion + pressure_quality − pain_reproducible_on_palpation; each ±1; range −1 to 5; CAD considered absent iff score <2 (Aerts 2017); CAD probability 2.1% (95% CI 1.1–3.9) when <2 and 43.0% (35.8–50.4) when ≥2 in the 13.2% prevalence setting",
"max_score": 5,
"min_score": -1,
"prevalence_setting_percent": 13.2,
"score": 0,
"sex": "female"
}
],
"path": "/api/calc/interchest"
}Use with an agent
- Discover. Agents find this listing with
GET https://bazaar.saylorinnovations.com/discovery/search?query=…, the MCP toolsearch_resources, or/discovery/resources. - Inspect. Fetch
/resources/39090.jsonfor the price and payment options. - Pay. Call
GET https://api.magentlab.com/api/calc/interchest. The provider answers402with its payment requirements. An x402 client signs one of the options below and retries withPAYMENT-SIGNATURE. - Execute. The provider returns
200with the data. Agent Bazaar is not in the request path and never sees your payment.
For humans
You don't need an account or an API key; you need a wallet holding a small amount of USDC on Base, and an x402-capable client (see the examples below). Call the endpoint unpaid first to see exactly what it asks for.
Pricing & payment
- Price
- $0.005 / request
- Protocol
- x402 v2
- Auth
- No account or API key. Pay per request.
- Networks
- Base
- Demand
- 5 calls · 2 unique payers in 30d (public x402 Bazaar data)
x402 payment requirements
| Scheme | Network | Asset | Amount | Pay to | Timeout |
|---|---|---|---|---|---|
| exact | Base eip155:8453 | USDC | $0.005 | 0x836Be278f1739fB4308091cD1852F7971Bc19Ee2 | 600s |
accepts[] (raw JSON)
[
{
"scheme": "exact",
"network": "eip155:8453",
"payTo": "0x836Be278f1739fB4308091cD1852F7971Bc19Ee2",
"asset": "0x833589fCD6eDb6E08f4c7C32D4f71b54bdA02913",
"amount": "5000",
"amountUsd": 0.005,
"maxTimeoutSeconds": 600
}
]Schemas
Output schema (JSON Schema)
{
"properties": {
"example": {
"type": "object"
},
"type": {
"type": "string"
}
},
"required": [
"type"
],
"type": "object"
}Example shape — generated from the schema, not a captured live response
{
"example": {},
"type": "string"
}Examples
curl "https://api.magentlab.com/api/calc/interchest"
# -> 402 Payment Required, accepts[] lists how to pay
# retry with a PAYMENT-SIGNATURE (or PAYMENT header) once paidconst res = await fetch("https://api.magentlab.com/api/calc/interchest");
if (res.status === 402) {
const { accepts } = await res.json();
// pay one of accepts[] via an x402 client, then retry with the payment header
}import httpx
res = httpx.get("https://api.magentlab.com/api/calc/interchest")
if res.status_code == 402:
accepts = res.json()["accepts"]
# pay one of accepts[] via an x402 client, then retry with the payment headerDetails
- Provider
- api.magentlab.com
- Endpoint
- https://api.magentlab.com/api/calc/interchest
- Machine-readable
/resources/39090.json