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Spyropoulos 2011 7-factor associative IMPROVE VTE score during hospitalization: previou…

Spyropoulos 2011 7-factor associative IMPROVE VTE score during hospitalization: previous VTE 3, known thrombophilia 2, lower-limb paralysis 2, current cancer 2, immobilized >=7 days 1, ICU/CCU stay 1, age >60 1. Max 12. Bands: 0-1; 2-3 (observed VTE 1.5%); >=…

by api.magentlab.com · discovered, not yet claimed by its owner · updated 2026-10-13

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

Spyropoulos 2011 7-factor associative IMPROVE VTE score during hospitalization: previous VTE 3, known thrombophilia 2, lower-limb paralysis 2, current cancer 2, immobilized >=7 days 1, ICU/CCU stay 1, age >60 1. Max 12. Bands: 0-1; 2-3 (observed VTE 1.5%); >=4 (observed VTE 5.7%). Not a VTE diagnosis or prophylaxis order. Not the 4-factor admission predictive model. Not IMPROVEDD. magent does not examine the patient.

Tags: improve-vte · vte · thrombosis · hospital · score · bazaar

Call contract

Method
POST
Input
HTTP request
Output
json
Last paid call
2026-10-13
Input example from Bazaar metadata
{
  "items": [
    {
      "age": 50,
      "current_cancer": false,
      "icu_ccu_stay": false,
      "immobilized_ge_7_days": false,
      "known_thrombophilia": false,
      "lower_limb_paralysis": false,
      "previous_vte": false
    },
    {
      "age": 50,
      "current_cancer": false,
      "icu_ccu_stay": false,
      "immobilized_ge_7_days": false,
      "known_thrombophilia": false,
      "lower_limb_paralysis": false,
      "previous_vte": false
    }
  ]
}
Output example
{
  "count": 2,
  "items": [
    {
      "age_years": 50,
      "citation": {
        "authors": "Spyropoulos AC, Anderson FA Jr, FitzGerald G, Decousus H, Pini M, Chong BH, Zotz RB, Bergmann JF, Tapson VF, Froehlich JB, Monreal M, Merli GJ, Pavanello R, Turpie AGG, Nakamura M, Piovella F, Kakkar AK, Spencer FA, IMPROVE Investigators",
        "doi": "10.1378/chest.10-1944",
        "id": "spyropoulos-2011",
        "pmid": "21436241",
        "source": "Chest. 2011;140(3):706-714",
        "title": "Predictive and associative models to identify hospitalized medical patients at risk for VTE"
      },
      "components": [
        {
          "factor": "previous_vte",
          "points": 0,
          "present": false
        },
        {
          "factor": "known_thrombophilia",
          "points": 0,
          "present": false
        },
        {
          "factor": "lower_limb_paralysis",
          "points": 0,
          "present": false
        },
        {
          "factor": "current_cancer",
          "points": 0,
          "present": false
        },
        {
          "factor": "immobilized_ge_7_days",
          "points": 0,
          "present": false
        },
        {
          "factor": "icu_ccu_stay",
          "points": 0,
          "present": false
        },
        {
          "factor": "age_gt_60",
          "points": 0,
          "present": false,
          "value": 50
        }
      ],
      "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": "improve_vte",
      "formula_expression": "IMPROVE VTE (Spyropoulos 2011 7-factor associative during hospitalization) = previous_vte (3) + known_thrombophilia (2) + lower_limb_paralysis (2) + current_cancer (2) + immobilized_ge_7_days (1) + icu_ccu_stay (1) + age>60 (1); max 12; 0-1, 2-3 (observed VTE 1.5%), >=4 (observed VTE 5.7%); not the 4-factor admission predictive model; not IMPROVEDD",
      "max_score": 12,
      "score": 0,
      "vte_band": "0-1"
    },
    {
      "age_years": 50,
      "citation": {
        "authors": "Spyropoulos AC, Anderson FA Jr, FitzGerald G, Decousus H, Pini M, Chong BH, Zotz RB, Bergmann JF, Tapson VF, Froehlich JB, Monreal M, Merli GJ, Pavanello R, Turpie AGG, Nakamura M, Piovella F, Kakkar AK, Spencer FA, IMPROVE Investigators",
        "doi": "10.1378/chest.10-1944",
        "id": "spyropoulos-2011",
        "pmid": "21436241",
        "source": "Chest. 2011;140(3):706-714",
        "title": "Predictive and associative models to identify hospitalized medical patients at risk for VTE"
      },
      "components": [
        {
          "factor": "previous_vte",
          "points": 0,
          "present": false
        },
        {
          "factor": "known_thrombophilia",
          "points": 0,
          "present": false
        },
        {
          "factor": "lower_limb_paralysis",
          "points": 0,
          "present": false
        },
        {
          "factor": "current_cancer",
          "points": 0,
          "present": false
        },
        {
          "factor": "immobilized_ge_7_days",
          "points": 0,
          "present": false
        },
        {
          "factor": "icu_ccu_stay",
          "points": 0,
          "present": false
        },
        {
          "factor": "age_gt_60",
          "points": 0,
          "present": false,
          "value": 50
        }
      ],
      "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": "improve_vte",
      "formula_expression": "IMPROVE VTE (Spyropoulos 2011 7-factor associative during hospitalization) = previous_vte (3) + known_thrombophilia (2) + lower_limb_paralysis (2) + current_cancer (2) + immobilized_ge_7_days (1) + icu_ccu_stay (1) + age>60 (1); max 12; 0-1, 2-3 (observed VTE 1.5%), >=4 (observed VTE 5.7%); not the 4-factor admission predictive model; not IMPROVEDD",
      "max_score": 12,
      "score": 0,
      "vte_band": "0-1"
    }
  ],
  "path": "/api/calc/improve_vte"
}

Use with an agent

  1. Discover. Agents find this listing with GET https://bazaar.saylorinnovations.com/discovery/search?query=…, the MCP tool search_resources, or /discovery/resources.
  2. Inspect. Fetch /resources/39093.json for the price and payment options.
  3. Pay. Call GET https://api.magentlab.com/api/calc/improve_vte. The provider answers 402 with its payment requirements. An x402 client signs one of the options below and retries with PAYMENT-SIGNATURE.
  4. 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

SchemeNetworkAssetAmountPay toTimeout
exactBase
eip155:8453		USDC$0.0050x836Be278f1739fB4308091cD1852F7971Bc19Ee2600s
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/improve_vte"
# -> 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/improve_vte");
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/improve_vte")
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/improve_vte
Machine-readable
/resources/39093.json