Calc Cgram

{
  "count": 2,
  "items": [
    {
      "age": 30,
      "cancer_history": false,
      "chest_xray_abnormal": false,
      "citation": {
        "authors": "Liang W, Liang H, Ou L, Chen B, Chen A, Li C, et al.",
        "doi": "10.1001/jamainternmed.2020.2033",
        "id": "liang-2020-covid-gram",
        "pmid": "32396163",
        "source": "JAMA Intern Med. 2020;180(8):1081-1089",
        "title": "Development and Validation of a Clinical Risk Score to Predict the Occurrence of Critical Illness in Hospitalized Patients With COVID-19"
      },
      "direct_bilirubin_umol_l": 3,
      "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.",
      "dyspnea": false,
      "estimated_probability_percent": 0.7,
      "formula": "covid_gram",
      "formula_expression": "lp = 1.2205*chest_xray_abnormal + 0.0276*age + 1.5116*hemoptysis + 0.632*dyspnea + 1.5494*unconsciousness + 0.4668*number_of_comorbidities + 1.4037*cancer_history + 0.0562*nlr + 0.0024*ldh_u_l + 0.1376*direct_bilirubin_umol_l - 6.6127; probability = exp(lp)/(1+exp(lp)); Liang 2020 Table 3 logistic (printed ORs; intercept -6.6127 matches constant 0.001); critical illness = ICU, invasive ventilation, or death; LDH U/L; direct bilirubin umol/L; magent does not read the chest film or count comorbidities; Liang 2020 did not publish low/medium/high cutoffs",
      "hemoptysis": false,
      "ldh_u_l": 150,
      "logit": -4.8995,
      "nlr": 2,
      "number_of_comorbidities": 0,
      "unconsciousness": false
    },
    {
      "age": 30,
      "cancer_history": false,
      "chest_xray_abnormal": false,
      "citation": {
        "authors": "Liang W, Liang H, Ou L, Chen B, Chen A, Li C, et al.",
        "doi": "10.1001/jamainternmed.2020.2033",
        "id": "liang-2020-covid-gram",
        "pmid": "32396163",
        "source": "JAMA Intern Med. 2020;180(8):1081-1089",
        "title": "Development and Validation of a Clinical Risk Score to Predict the Occurrence of Critical Illness in Hospitalized Patients With COVID-19"
      },
      "direct_bilirubin_umol_l": 3,
      "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.",
      "dyspnea": false,
      "estimated_probability_percent": 0.7,
      "formula": "covid_gram",
      "formula_expression": "lp = 1.2205*chest_xray_abnormal + 0.0276*age + 1.5116*hemoptysis + 0.632*dyspnea + 1.5494*unconsciousness + 0.4668*number_of_comorbidities + 1.4037*cancer_history + 0.0562*nlr + 0.0024*ldh_u_l + 0.1376*direct_bilirubin_umol_l - 6.6127; probability = exp(lp)/(1+exp(lp)); Liang 2020 Table 3 logistic (printed ORs; intercept -6.6127 matches constant 0.001); critical illness = ICU, invasive ventilation, or death; LDH U/L; direct bilirubin umol/L; magent does not read the chest film or count comorbidities; Liang 2020 did not publish low/medium/high cutoffs",
      "hemoptysis": false,
      "ldh_u_l": 150,
      "logit": -4.8995,
      "nlr": 2,
      "number_of_comorbidities": 0,
      "unconsciousness": false
    }
  ],
  "path": "/api/calc/cgram"
}

# bash or zsh: see the payment challenge. Nothing is charged.
curl -sS -g -i -X POST 'https://api.magentlab.com/api/calc/cgram' \
  -H 'content-type: application/json' \
  --data-raw '{"items":[{"age":30,"cancer_history":false,"chest_xray_abnormal":false,"direct_bilirubin_umol_l":3,"dyspnea":false,"hemoptysis":false,"ldh_u_l":150,"nlr":2,"number_of_comorbidities":0,"unconsciousness":false},{"age":30,"cancer_history":false,"chest_xray_abnormal":false,"direct_bilirubin_umol_l":3,"dyspnea":false,"hemoptysis":false,"ldh_u_l":150,"nlr":2,"number_of_comorbidities":0,"unconsciousness":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/cgram' \
  -H 'content-type: application/json' \
  --data-raw '{"items":[{"age":30,"cancer_history":false,"chest_xray_abnormal":false,"direct_bilirubin_umol_l":3,"dyspnea":false,"hemoptysis":false,"ldh_u_l":150,"nlr":2,"number_of_comorbidities":0,"unconsciousness":false},{"age":30,"cancer_history":false,"chest_xray_abnormal":false,"direct_bilirubin_umol_l":3,"dyspnea":false,"hemoptysis":false,"ldh_u_l":150,"nlr":2,"number_of_comorbidities":0,"unconsciousness":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%2Fcgram&method=POST
const res = await pay("https://api.magentlab.com/api/calc/cgram", {
  method: "POST",
  headers: { "content-type": "application/json" },
  body: JSON.stringify({
    "items": [
      {
        "age": 30,
        "cancer_history": false,
        "chest_xray_abnormal": false,
        "direct_bilirubin_umol_l": 3,
        "dyspnea": false,
        "hemoptysis": false,
        "ldh_u_l": 150,
        "nlr": 2,
        "number_of_comorbidities": 0,
        "unconsciousness": false
      },
      {
        "age": 30,
        "cancer_history": false,
        "chest_xray_abnormal": false,
        "direct_bilirubin_umol_l": 3,
        "dyspnea": false,
        "hemoptysis": false,
        "ldh_u_l": 150,
        "nlr": 2,
        "number_of_comorbidities": 0,
        "unconsciousness": 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/cgram",
        json={
            "items": [
                {
                    "age": 30,
                    "cancer_history": False,
                    "chest_xray_abnormal": False,
                    "direct_bilirubin_umol_l": 3,
                    "dyspnea": False,
                    "hemoptysis": False,
                    "ldh_u_l": 150,
                    "nlr": 2,
                    "number_of_comorbidities": 0,
                    "unconsciousness": False,
                },
                {
                    "age": 30,
                    "cancer_history": False,
                    "chest_xray_abnormal": False,
                    "direct_bilirubin_umol_l": 3,
                    "dyspnea": False,
                    "hemoptysis": False,
                    "ldh_u_l": 150,
                    "nlr": 2,
                    "number_of_comorbidities": 0,
                    "unconsciousness": False,
                },
            ],
        },
    )
    print(res.status_code, res.text)