Calc Pc Ptsd 5

{
  "count": 2,
  "items": [
    {
      "at_or_above_sensitive_cutoff": false,
      "citation": {
        "authors": "Prins A, Bovin MJ, Smolenski DJ, Marx BP, Kimerling R, Jenkins-Guarnieri MA, Kaloupek DG, Schnurr PP, Pless Kaiser A, Leyva YE, Tiet QQ",
        "doi": "10.1007/s11606-016-3703-5",
        "id": "prins-2016",
        "pmid": "27170304",
        "source": "J Gen Intern Med. 2016;31(10):1206-1211",
        "title": "The Primary Care PTSD Screen for DSM-5 (PC-PTSD-5): Development and Evaluation Within a Veteran Primary Care Sample"
      },
      "components": [
        {
          "factor": "nightmare_or_intrusion",
          "points": 0,
          "present": false
        },
        {
          "factor": "avoidance",
          "points": 0,
          "present": false
        },
        {
          "factor": "hypervigilance_or_startle",
          "points": 0,
          "present": false
        },
        {
          "factor": "numbing_or_detachment",
          "points": 0,
          "present": false
        },
        {
          "factor": "guilt_or_blame",
          "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": "pc_ptsd_5",
      "formula_expression": "If trauma_exposure is false, PC-PTSD-5 = 0 (five past-month items are required but not counted). If trauma_exposure is true, PC-PTSD-5 = nightmare_or_intrusion + avoidance + hypervigilance_or_startle + numbing_or_detachment + guilt_or_blame; each 1 if true; max 5; at_or_above_sensitive_cutoff iff score ≥ 3 (Prins 2016 optimally sensitive cut; 4 maximized efficiency; 5 maximized specificity)",
      "max_score": 5,
      "score": 0,
      "trauma_exposure": false
    },
    {
      "at_or_above_sensitive_cutoff": false,
      "citation": {
        "authors": "Prins A, Bovin MJ, Smolenski DJ, Marx BP, Kimerling R, Jenkins-Guarnieri MA, Kaloupek DG, Schnurr PP, Pless Kaiser A, Leyva YE, Tiet QQ",
        "doi": "10.1007/s11606-016-3703-5",
        "id": "prins-2016",
        "pmid": "27170304",
        "source": "J Gen Intern Med. 2016;31(10):1206-1211",
        "title": "The Primary Care PTSD Screen for DSM-5 (PC-PTSD-5): Development and Evaluation Within a Veteran Primary Care Sample"
      },
      "components": [
        {
          "factor": "nightmare_or_intrusion",
          "points": 0,
          "present": false
        },
        {
          "factor": "avoidance",
          "points": 0,
          "present": false
        },
        {
          "factor": "hypervigilance_or_startle",
          "points": 0,
          "present": false
        },
        {
          "factor": "numbing_or_detachment",
          "points": 0,
          "present": false
        },
        {
          "factor": "guilt_or_blame",
          "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": "pc_ptsd_5",
      "formula_expression": "If trauma_exposure is false, PC-PTSD-5 = 0 (five past-month items are required but not counted). If trauma_exposure is true, PC-PTSD-5 = nightmare_or_intrusion + avoidance + hypervigilance_or_startle + numbing_or_detachment + guilt_or_blame; each 1 if true; max 5; at_or_above_sensitive_cutoff iff score ≥ 3 (Prins 2016 optimally sensitive cut; 4 maximized efficiency; 5 maximized specificity)",
      "max_score": 5,
      "score": 0,
      "trauma_exposure": false
    }
  ],
  "path": "/api/calc/pc_ptsd_5"
}

# bash or zsh: see the payment challenge. Nothing is charged.
curl -sS -g -i -X POST 'https://api.magentlab.com/api/calc/pc_ptsd_5' \
  -H 'content-type: application/json' \
  --data-raw '{"items":[{"avoidance":false,"guilt_or_blame":false,"hypervigilance_or_startle":false,"nightmare_or_intrusion":false,"numbing_or_detachment":false,"trauma_exposure":false},{"avoidance":false,"guilt_or_blame":false,"hypervigilance_or_startle":false,"nightmare_or_intrusion":false,"numbing_or_detachment":false,"trauma_exposure":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/pc_ptsd_5' \
  -H 'content-type: application/json' \
  --data-raw '{"items":[{"avoidance":false,"guilt_or_blame":false,"hypervigilance_or_startle":false,"nightmare_or_intrusion":false,"numbing_or_detachment":false,"trauma_exposure":false},{"avoidance":false,"guilt_or_blame":false,"hypervigilance_or_startle":false,"nightmare_or_intrusion":false,"numbing_or_detachment":false,"trauma_exposure":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%2Fpc_ptsd_5&method=POST
const res = await pay("https://api.magentlab.com/api/calc/pc_ptsd_5", {
  method: "POST",
  headers: { "content-type": "application/json" },
  body: JSON.stringify({
    "items": [
      {
        "avoidance": false,
        "guilt_or_blame": false,
        "hypervigilance_or_startle": false,
        "nightmare_or_intrusion": false,
        "numbing_or_detachment": false,
        "trauma_exposure": false
      },
      {
        "avoidance": false,
        "guilt_or_blame": false,
        "hypervigilance_or_startle": false,
        "nightmare_or_intrusion": false,
        "numbing_or_detachment": false,
        "trauma_exposure": 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/pc_ptsd_5",
        json={
            "items": [
                {
                    "avoidance": False,
                    "guilt_or_blame": False,
                    "hypervigilance_or_startle": False,
                    "nightmare_or_intrusion": False,
                    "numbing_or_detachment": False,
                    "trauma_exposure": False,
                },
                {
                    "avoidance": False,
                    "guilt_or_blame": False,
                    "hypervigilance_or_startle": False,
                    "nightmare_or_intrusion": False,
                    "numbing_or_detachment": False,
                    "trauma_exposure": False,
                },
            ],
        },
    )
    print(res.status_code, res.text)