Agent Service · x402 · early usage

AHA/ACC 2018 Table 4 very high-risk ASCVD for known clinical ASCVD

by api.magentlab.com · discovered, not yet claimed by its owner · updated 2026-10-12

30d calls5

30d payers2

MethodPOST

Outputjson

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

AHA/ACC 2018 Table 4 very high-risk ASCVD for known clinical ASCVD. Very high-risk if ≥2 major events (recent ACS, prior MI, ischemic stroke, symptomatic PAD) or 1 major event and ≥2 high-risk conditions (age ≥65, heterozygous FH, CABG/PCI outside those events, diabetes, hypertension, CKD eGFR 15-59, current smoking, LDL-C ≥100 on max statin and ezetimibe, congestive HF). Not PCE. Not a statin, ezetimibe, or PCSK9 order. magent does not diagnose ASCVD or measure ABI or LDL-C.

Tags: ascvd · very-high-risk · aha-acc-2018 · lipids · cholesterol · bazaar

Call contract

Method: POST
Input: HTTP request
Output: json
Last paid call: 2026-10-12

Input example from Bazaar metadata

{
  "items": [
    {
      "age": 70,
      "ckd_egfr_15_to_59": false,
      "congestive_hf": false,
      "current_smoking": false,
      "diabetes": true,
      "heterozygous_fh": false,
      "history_mi": true,
      "hypertension": false,
      "ischemic_stroke": false,
      "ldl_c_ge_100_on_max_statin_ezetimibe": false,
      "prior_cabg_or_pci_outside_major": false,
      "recent_acs": false,
      "symptomatic_pad": false
    },
    {
      "age": 70,
      "ckd_egfr_15_to_59": false,
      "congestive_hf": false,
      "current_smoking": false,
      "diabetes": true,
      "heterozygous_fh": false,
      "history_mi": true,
      "hypertension": false,
      "ischemic_stroke": false,
      "ldl_c_ge_100_on_max_statin_ezetimibe": false,
      "prior_cabg_or_pci_outside_major": false,
      "recent_acs": false,
      "symptomatic_pad": false
    }
  ]
}

Output example

{
  "count": 2,
  "items": [
    {
      "age": 70,
      "citation": {
        "authors": "Grundy SM, Stone NJ, Bailey AL, et al.",
        "doi": "10.1161/CIR.0000000000000625",
        "id": "grundy-2018-aha-acc-cholesterol",
        "pmid": "30586774",
        "source": "Circulation. 2019;139(25):e1082-e1143",
        "title": "2018 AHA/ACC/AACVPR/AAPA/ABC/ACPM/ADA/AGS/APhA/ASPC/NLA/PCNA Guideline on the Management of Blood Cholesterol"
      },
      "classifying_rule": "one_major_and_multiple_high_risk_conditions",
      "criteria": [
        {
          "factor": "recent_acs",
          "met": false
        },
        {
          "factor": "history_mi",
          "met": true
        },
        {
          "factor": "ischemic_stroke",
          "met": false
        },
        {
          "factor": "symptomatic_pad",
          "met": false
        },
        {
          "factor": "age_ge_65",
          "met": true,
          "value": 70
        },
        {
          "factor": "heterozygous_fh",
          "met": false
        },
        {
          "factor": "prior_cabg_or_pci_outside_major",
          "met": false
        },
        {
          "factor": "diabetes",
          "met": true
        },
        {
          "factor": "hypertension",
          "met": false
        },
        {
          "factor": "ckd_egfr_15_to_59",
          "met": false
        },
        {
          "factor": "current_smoking",
          "met": false
        },
        {
          "factor": "ldl_c_ge_100_on_max_statin_ezetimibe",
          "met": false
        },
        {
          "factor": "congestive_hf",
          "met": 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": "ascvd_vhr",
      "formula_expression": "very_high_risk iff major_event_count ≥ 2 or (major_event_count = 1 and high_risk_condition_count ≥ 2) (AHA/ACC 2018 Table 4 / Figure 1). Major events (caller-assigned): recent ACS within 12 months; history of MI other than that recent ACS; history of ischemic stroke; symptomatic PAD (claudication with ABI <0.85, or prior revascularization or amputation). High-risk conditions: age ≥65 years; heterozygous familial hypercholesterolemia; prior CABG or PCI outside the major ASCVD event(s); diabetes mellitus; hypertension; CKD (eGFR 15–59 mL/min/1.73 m²); current smoking; persistently elevated LDL-C ≥100 mg/dL (≥2.6 mmol/L) despite maximally tolerated statin and ezetimibe; history of congestive HF. Not PCE 10-year risk. Not a statin, ezetimibe, or PCSK9 order. magent does not diagnose ASCVD or measure ABI or LDL-C",
      "high_risk_condition_count": 2,
      "major_event_count": 1,
      "very_high_risk": true
    },
    {
      "age": 70,
      "citation": {
        "authors": "Grundy SM, Stone NJ, Bailey AL, et al.",
        "doi": "10.1161/CIR.0000000000000625",
        "id": "grundy-2018-aha-acc-cholesterol",
        "pmid": "30586774",
        "source": "Circulation. 2019;139(25):e1082-e1143",
        "title": "2018 AHA/ACC/AACVPR/AAPA/ABC/ACPM/ADA/AGS/APhA/ASPC/NLA/PCNA Guideline on the Management of Blood Cholesterol"
      },
      "classifying_rule": "one_major_and_multiple_high_risk_conditions",
      "criteria": [
        {
          "factor": "recent_acs",
          "met": false
        },
        {
          "factor": "history_mi",
          "met": true
        },
        {
          "factor": "ischemic_stroke",
          "met": false
        },
        {
          "factor": "symptomatic_pad",
          "met": false
        },
        {
          "factor": "age_ge_65",
          "met": true,
          "value": 70
        },
        {
          "factor": "heterozygous_fh",
          "met": false
        },
        {
          "factor": "prior_cabg_or_pci_outside_major",
          "met": false
        },
        {
          "factor": "diabetes",
          "met": true
        },
        {
          "factor": "hypertension",
          "met": false
        },
        {
          "factor": "ckd_egfr_15_to_59",
          "met": false
        },
        {
          "factor": "current_smoking",
          "met": false
        },
        {
          "factor": "ldl_c_ge_100_on_max_statin_ezetimibe",
          "met": false
        },
        {
          "factor": "congestive_hf",
          "met": 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": "ascvd_vhr",
      "formula_expression": "very_high_risk iff major_event_count ≥ 2 or (major_event_count = 1 and high_risk_condition_count ≥ 2) (AHA/ACC 2018 Table 4 / Figure 1). Major events (caller-assigned): recent ACS within 12 months; history of MI other than that recent ACS; history of ischemic stroke; symptomatic PAD (claudication with ABI <0.85, or prior revascularization or amputation). High-risk conditions: age ≥65 years; heterozygous familial hypercholesterolemia; prior CABG or PCI outside the major ASCVD event(s); diabetes mellitus; hypertension; CKD (eGFR 15–59 mL/min/1.73 m²); current smoking; persistently elevated LDL-C ≥100 mg/dL (≥2.6 mmol/L) despite maximally tolerated statin and ezetimibe; history of congestive HF. Not PCE 10-year risk. Not a statin, ezetimibe, or PCSK9 order. magent does not diagnose ASCVD or measure ABI or LDL-C",
      "high_risk_condition_count": 2,
      "major_event_count": 1,
      "very_high_risk": true
    }
  ],
  "path": "/api/calc/ascvd_vhr"
}

Use with an agent

Discover. Agents find this listing with GET https://bazaar.saylorinnovations.com/discovery/search?query=…, the MCP tool search_resources, or /discovery/resources.
Inspect. Fetch /resources/39302.json for the price and payment options.
Pay. Call GET https://api.magentlab.com/api/calc/ascvd_vhr. The provider answers 402 with its payment requirements. An x402 client signs one of the options below and retries with PAYMENT-SIGNATURE.
Execute. The provider returns 200 with 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

curl "https://api.magentlab.com/api/calc/ascvd_vhr"
# -> 402 Payment Required, accepts[] lists how to pay
# retry with a PAYMENT-SIGNATURE (or PAYMENT header) once paid

JavaScript

const res = await fetch("https://api.magentlab.com/api/calc/ascvd_vhr");
if (res.status === 402) {
  const { accepts } = await res.json();
  // pay one of accepts[] via an x402 client, then retry with the payment header
}

Python

import httpx
res = httpx.get("https://api.magentlab.com/api/calc/ascvd_vhr")
if res.status_code == 402:
    accepts = res.json()["accepts"]
    # pay one of accepts[] via an x402 client, then retry with the payment header

Details

Provider: api.magentlab.com
Endpoint: https://api.magentlab.com/api/calc/ascvd_vhr
Machine-readable: /resources/39302.json