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McGinnis 2024 VACS-CCI Table 2 Model 7 linear predictor from sex, age, hemoglobin, FIB-…

McGinnis 2024 VACS-CCI Table 2 Model 7 linear predictor from sex, age, hemoglobin, FIB-4, eGFR, albumin, WBC, BMI, hepatitis C, and caller-assigned Charlson groupings. CCI group is those weights (0/1/2/3+) times age band. The 0-100 score needs unpublished dev…

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

30d calls3
30d payers1
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

McGinnis 2024 VACS-CCI Table 2 Model 7 linear predictor from sex, age, hemoglobin, FIB-4, eGFR, albumin, WBC, BMI, hepatitis C, and caller-assigned Charlson groupings. CCI group is those weights (0/1/2/3+) times age band. The 0-100 score needs unpublished development min/max Xbeta; magent does not invent it. Paper prints score 30 to 1/3/8/18% and 45 to 6/14/35/61% at 1/2/5/10 years. Not a diagnosis or individual prognosis. magent does not code the chart.

Tags: vacs-cci · charlson · mortality · comorbidity · calculator · bazaar

Call contract

Method
POST
Input
HTTP request
Output
json
Last paid call
2026-10-12
Input example from Bazaar metadata
{
  "items": [
    {
      "age": 55,
      "albumin_g_dl": 4,
      "any_malignancy": false,
      "bmi_kg_m2": 25,
      "cerebrovascular_disease": false,
      "chronic_pulmonary_disease": false,
      "congestive_heart_failure": false,
      "dementia": false,
      "diabetes_with_complications": false,
      "diabetes_without_complications": false,
      "egfr_ml_min_1_73m2": 90,
      "fib4": 1,
      "hemiplegia_or_paraplegia": false,
      "hemoglobin_g_dl": 14,
      "hepatitis_c": false,
      "kidney_mild_to_moderate": false,
      "kidney_severe": false,
      "liver_mild": false,
      "liver_moderate_to_severe": false,
      "metastatic_solid_tumor": false,
      "myocardial_infarction": false,
      "peptic_ulcer_disease": false,
      "peripheral_vascular_disease": false,
      "rheumatic_disease": false,
      "sex": "male",
      "wbc_10e9_l": 4
    },
    {
      "age": 55,
      "albumin_g_dl": 4,
      "any_malignancy": false,
      "bmi_kg_m2": 25,
      "cerebrovascular_disease": false,
      "chronic_pulmonary_disease": false,
      "congestive_heart_failure": false,
      "dementia": false,
      "diabetes_with_complications": false,
      "diabetes_without_complications": false,
      "egfr_ml_min_1_73m2": 90,
      "fib4": 1,
      "hemiplegia_or_paraplegia": false,
      "hemoglobin_g_dl": 14,
      "hepatitis_c": false,
      "kidney_mild_to_moderate": false,
      "kidney_severe": false,
      "liver_mild": false,
      "liver_moderate_to_severe": false,
      "metastatic_solid_tumor": false,
      "myocardial_infarction": false,
      "peptic_ulcer_disease": false,
      "peripheral_vascular_disease": false,
      "rheumatic_disease": false,
      "sex": "male",
      "wbc_10e9_l": 4
    }
  ]
}
Output example
{
  "count": 2,
  "items": [
    {
      "age": 55,
      "age_band": "50_64",
      "albumin_g_dl": 4,
      "any_malignancy": false,
      "bmi_kg_m2": 25,
      "cci_group": "0",
      "cci_score": 0,
      "cerebrovascular_disease": false,
      "chronic_pulmonary_disease": false,
      "citation": {
        "authors": "McGinnis KA, Justice AC, Marconi VC, et al.",
        "doi": "10.3389/fmed.2023.1342466",
        "id": "mcginnis-2024-vacs-cci",
        "pmid": "38356736",
        "source": "Front Med (Lausanne). 2024;10:1342466",
        "title": "Combining Charlson comorbidity and VACS indices improves prognostic accuracy for all-cause mortality for patients with and without HIV in the Veterans Health Administration"
      },
      "congestive_heart_failure": false,
      "dementia": false,
      "diabetes_with_complications": false,
      "diabetes_without_complications": 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.",
      "egfr_ml_min_1_73m2": 90,
      "fib4": 1,
      "formula": "vacs_cci",
      "formula_expression": "lp = sex_female -0.513 + age_poly(X=age-50, 0.278/0.006/-0.001) + hb_poly(X=hemoglobin-14, -0.115/0.024/0.004) + fib4_poly(X, 0.205/-0.006) + egfr_poly(X=egfr-90, 0.071/0.036/0.002) + alb_poly(X=albumin-4, -0.405/0.326/0.156) + wbc_poly(X=WBC-4, -0.011/0.053/-0.008/0.000) + bmi_poly(X=BMI-25, -0.061/0.005/0.000) + hepatitis_c 0.273 + Table 2 Charlson condition coefficients + CCI-group x age-band interaction (CCI 0/1/2/3+ by <50, 50-64, 65-79, 80+; CCI 1 x 50-64 is reference 0); cci_group from caller-assigned condition weights (MI 1, CHF 1, PVD 1, CVD 1, dementia 1, pulmonary 1, rheumatic 1, PUD 1, DM without 1, DM with 2, hemiplegia 2, kidney mild-to-moderate 2, kidney severe 2, any malignancy 2, metastatic 6, liver mild 1, liver moderate-to-severe 3); McGinnis 2024 Table 2 Model 7; 1st/99th percentile winsorizing not published; 0-100 score uses unpublished development min/max Xbeta so magent does not scale; paper prints 0-100 score 30 → 1-year 1%, 2-year 3%, 5-year 8%, 10-year 18% and score 45 → 6%, 14%, 35%, 61%; no published S0; 2025 corrigendum PMID 39845833 does not change Table 2 coefficients; caller-assigned comorbidities, FIB-4, and eGFR",
      "hemiplegia_or_paraplegia": false,
      "hemoglobin_g_dl": 14,
      "hepatitis_c": false,
      "kidney_mild_to_moderate": false,
      "kidney_severe": false,
      "linear_predictor": 1.228,
      "liver_mild": false,
      "liver_moderate_to_severe": false,
      "metastatic_solid_tumor": false,
      "myocardial_infarction": false,
      "peptic_ulcer_disease": false,
      "peripheral_vascular_disease": false,
      "rheumatic_disease": false,
      "sex": "male",
      "wbc_10e9_l": 4
    },
    {
      "age": 55,
      "age_band": "50_64",
      "albumin_g_dl": 4,
      "any_malignancy": false,
      "bmi_kg_m2": 25,
      "cci_group": "0",
      "cci_score": 0,
      "cerebrovascular_disease": false,
      "chronic_pulmonary_disease": false,
      "citation": {
        "authors": "McGinnis KA, Justice AC, Marconi VC, et al.",
        "doi": "10.3389/fmed.2023.1342466",
        "id": "mcginnis-2024-vacs-cci",
        "pmid": "38356736",
        "source": "Front Med (Lausanne). 2024;10:1342466",
        "title": "Combining Charlson comorbidity and VACS indices improves prognostic accuracy for all-cause mortality for patients with and without HIV in the Veterans Health Administration"
      },
      "congestive_heart_failure": false,
      "dementia": false,
      "diabetes_with_complications": false,
      "diabetes_without_complications": 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.",
      "egfr_ml_min_1_73m2": 90,
      "fib4": 1,
      "formula": "vacs_cci",
      "formula_expression": "lp = sex_female -0.513 + age_poly(X=age-50, 0.278/0.006/-0.001) + hb_poly(X=hemoglobin-14, -0.115/0.024/0.004) + fib4_poly(X, 0.205/-0.006) + egfr_poly(X=egfr-90, 0.071/0.036/0.002) + alb_poly(X=albumin-4, -0.405/0.326/0.156) + wbc_poly(X=WBC-4, -0.011/0.053/-0.008/0.000) + bmi_poly(X=BMI-25, -0.061/0.005/0.000) + hepatitis_c 0.273 + Table 2 Charlson condition coefficients + CCI-group x age-band interaction (CCI 0/1/2/3+ by <50, 50-64, 65-79, 80+; CCI 1 x 50-64 is reference 0); cci_group from caller-assigned condition weights (MI 1, CHF 1, PVD 1, CVD 1, dementia 1, pulmonary 1, rheumatic 1, PUD 1, DM without 1, DM with 2, hemiplegia 2, kidney mild-to-moderate 2, kidney severe 2, any malignancy 2, metastatic 6, liver mild 1, liver moderate-to-severe 3); McGinnis 2024 Table 2 Model 7; 1st/99th percentile winsorizing not published; 0-100 score uses unpublished development min/max Xbeta so magent does not scale; paper prints 0-100 score 30 → 1-year 1%, 2-year 3%, 5-year 8%, 10-year 18% and score 45 → 6%, 14%, 35%, 61%; no published S0; 2025 corrigendum PMID 39845833 does not change Table 2 coefficients; caller-assigned comorbidities, FIB-4, and eGFR",
      "hemiplegia_or_paraplegia": false,
      "hemoglobin_g_dl": 14,
      "hepatitis_c": false,
      "kidney_mild_to_moderate": false,
      "kidney_severe": false,
      "linear_predictor": 1.228,
      "liver_mild": false,
      "liver_moderate_to_severe": false,
      "metastatic_solid_tumor": false,
      "myocardial_infarction": false,
      "peptic_ulcer_disease": false,
      "peripheral_vascular_disease": false,
      "rheumatic_disease": false,
      "sex": "male",
      "wbc_10e9_l": 4
    }
  ],
  "path": "/api/calc/vacs_cci"
}

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/39539.json for the price and payment options.
  3. Pay. Call GET https://api.magentlab.com/api/calc/vacs_cci. 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
3 calls · 1 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/vacs_cci"
# -> 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/vacs_cci");
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/vacs_cci")
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/vacs_cci
Machine-readable
/resources/39539.json