Calc Scarf

{
  "count": 2,
  "items": [
    {
      "citation": {
        "authors": "Hardin KS, Leasia KN, Haenel J, Moore EE, Burlew CC, Pieracci FM",
        "doi": "10.1097/TA.0000000000002480",
        "id": "hardin-2019",
        "pmid": "31425473",
        "source": "J Trauma Acute Care Surg. 2019;87(6):1260-1268",
        "title": "The Sequential Clinical Assessment of Respiratory Function (SCARF) score: A dynamic pulmonary physiologic score that predicts adverse outcomes in critically ill rib fracture patients"
      },
      "components": [
        {
          "factor": "incentive_spirometry_lt_50_predicted",
          "points": 0,
          "present": false
        },
        {
          "factor": "respiratory_rate_gt_20",
          "points": 0,
          "present": false
        },
        {
          "factor": "pain_score_ge_5",
          "points": 0,
          "present": false
        },
        {
          "factor": "inadequate_cough",
          "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": "scarf",
      "formula_expression": "SCARF = incentive_spirometry_lt_50_predicted + respiratory_rate_gt_20 + pain_score_ge_5 + inadequate_cough; each 1; Hardin 2019; max 4; proposed threshold score > 2 (scarf_gt_2); caller-assigned flags; magent does not measure spirometry or examine the chest",
      "max_score": 4,
      "scarf_gt_2": false,
      "score": 0
    },
    {
      "citation": {
        "authors": "Hardin KS, Leasia KN, Haenel J, Moore EE, Burlew CC, Pieracci FM",
        "doi": "10.1097/TA.0000000000002480",
        "id": "hardin-2019",
        "pmid": "31425473",
        "source": "J Trauma Acute Care Surg. 2019;87(6):1260-1268",
        "title": "The Sequential Clinical Assessment of Respiratory Function (SCARF) score: A dynamic pulmonary physiologic score that predicts adverse outcomes in critically ill rib fracture patients"
      },
      "components": [
        {
          "factor": "incentive_spirometry_lt_50_predicted",
          "points": 0,
          "present": false
        },
        {
          "factor": "respiratory_rate_gt_20",
          "points": 0,
          "present": false
        },
        {
          "factor": "pain_score_ge_5",
          "points": 0,
          "present": false
        },
        {
          "factor": "inadequate_cough",
          "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": "scarf",
      "formula_expression": "SCARF = incentive_spirometry_lt_50_predicted + respiratory_rate_gt_20 + pain_score_ge_5 + inadequate_cough; each 1; Hardin 2019; max 4; proposed threshold score > 2 (scarf_gt_2); caller-assigned flags; magent does not measure spirometry or examine the chest",
      "max_score": 4,
      "scarf_gt_2": false,
      "score": 0
    }
  ],
  "path": "/api/calc/scarf"
}

# bash or zsh: see the payment challenge. Nothing is charged.
curl -sS -g -i -X POST 'https://api.magentlab.com/api/calc/scarf' \
  -H 'content-type: application/json' \
  --data-raw '{"items":[{"inadequate_cough":false,"incentive_spirometry_lt_50_predicted":false,"pain_score_ge_5":false,"respiratory_rate_gt_20":false},{"inadequate_cough":false,"incentive_spirometry_lt_50_predicted":false,"pain_score_ge_5":false,"respiratory_rate_gt_20":false}]}'

# x402 v2 sends the challenge base64-encoded in the PAYMENT-REQUIRED header (v1 sends it in the body).
# To read the header:
curl -sS -g -o /dev/null -D - -X POST 'https://api.magentlab.com/api/calc/scarf' \
  -H 'content-type: application/json' \
  --data-raw '{"items":[{"inadequate_cough":false,"incentive_spirometry_lt_50_predicted":false,"pain_score_ge_5":false,"respiratory_rate_gt_20":false},{"inadequate_cough":false,"incentive_spirometry_lt_50_predicted":false,"pain_score_ge_5":false,"respiratory_rate_gt_20":false}]}' \
  | grep -i '^payment-required:' | cut -d' ' -f2 | tr -d '\r' | base64 --decode

// npm i @x402/fetch @x402/evm viem
import { wrapFetchWithPayment, x402Client } from "@x402/fetch";
import { registerExactEvmScheme } from "@x402/evm/exact/client";
import { privateKeyToAccount } from "viem/accounts";

// Pays at most $0.007 per call.
const client = new x402Client().setSpendControls({ maxAmountPerPayment: "$0.007" });
registerExactEvmScheme(client, { signer: privateKeyToAccount(process.env.EVM_PRIVATE_KEY) });
const pay = wrapFetchWithPayment(fetch, client);

// Not sure it's safe to pay? ToolVet checks it first for $0.005. Pay for that from a separate
// client: this one is capped at $0.007 per payment. GET https://toolvet.app/api/v1/check?url=https%3A%2F%2Fapi.magentlab.com%2Fapi%2Fcalc%2Fscarf&method=POST
const res = await pay("https://api.magentlab.com/api/calc/scarf", {
  method: "POST",
  headers: { "content-type": "application/json" },
  body: JSON.stringify({
    "items": [
      {
        "inadequate_cough": false,
        "incentive_spirometry_lt_50_predicted": false,
        "pain_score_ge_5": false,
        "respiratory_rate_gt_20": false
      },
      {
        "inadequate_cough": false,
        "incentive_spirometry_lt_50_predicted": false,
        "pain_score_ge_5": false,
        "respiratory_rate_gt_20": false
      }
    ]
  }),
});
console.log(res.status, await res.text());

# pip install "x402[requests,evm]"
import os
from eth_account import Account
from x402 import x402ClientSync
from x402.http.clients import x402_requests
from x402.mechanisms.evm import EthAccountSigner
from x402.mechanisms.evm.exact.register import register_exact_evm_client

# Pays at most $0.007 per call.
client = x402ClientSync().set_spend_controls({"max_amount_per_payment": "$0.007"})
register_exact_evm_client(client, EthAccountSigner(Account.from_key(os.environ["EVM_PRIVATE_KEY"])))

with x402_requests(client) as session:
    res = session.post(
        "https://api.magentlab.com/api/calc/scarf",
        json={
            "items": [
                {
                    "inadequate_cough": False,
                    "incentive_spirometry_lt_50_predicted": False,
                    "pain_score_ge_5": False,
                    "respiratory_rate_gt_20": False,
                },
                {
                    "inadequate_cough": False,
                    "incentive_spirometry_lt_50_predicted": False,
                    "pain_score_ge_5": False,
                    "respiratory_rate_gt_20": False,
                },
            ],
        },
    )
    print(res.status_code, res.text)