Mimedx (MDXG) Total Non-Current Liabilities (2010 - 2026)
Mimedx (MDXG) reported Total Non-Current Liabilities of $54.2 million for Q2 2026, down 19.7% from $67.5 million a year earlier and down 10.6% from the prior quarter.
Mimedx (MDXG) Total Non-Current Liabilities (2010 - 2026) Analysis & Trends
At the end of FY2025, Mimedx posted Total Non-Current Liabilities of $80.73 million, up 27.3% from FY2024.
- Total Non-Current Liabilities has a five-year compound annual growth rate of -16.5% (FY2020 to FY2025).
- By year, Total Non-Current Liabilities came in at $63.43 million in FY2024 (-32.6%), $94.11 million in FY2023 (-49.0%), $184.65 million in FY2022 (+0.9%) and $182.98 million in FY2021 (-7.8%).
- The Q2 2026 figure ranks as the lowest quarterly Total Non-Current Liabilities since Q4 2017.
- Year over year, Total Non-Current Liabilities gained in four of the last eight quarters, with an average decline of 6.6%.
- The high point for year-over-year Total Non-Current Liabilities in five years was Q4 2025 (growth of 27.3%); the low point was Q2 2024 (a decline of 68.6%).
- Per Business Quant data, the three quarters before Q2 2026 came in at $60.64 million (Q1 2026), $80.73 million (Q4 2025) and $74.52 million (Q3 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Total Non-Current Liabilities (Qtr) |
|---|---|---|---|---|---|
| 1 | Thermo Fisher Scientific | 249.71 Bn | 228.86 Bn | 4.88 Bn | 55.95 Bn |
| 2 | Abbott Laboratories | 171.00 Bn | 142.08 Bn | 7.27 Bn | - |
| 3 | Danaher | 155.79 Bn | 139.61 Bn | 3.61 Bn | 33.25 Bn |
| 4 | Intuitive Surgical | 143.91 Bn | 123.46 Bn | 1.96 Bn | - |
| 5 | Medtronic | 110.42 Bn | 76.29 Bn | 6.34 Bn | 40.46 Bn |
| 6 | Stryker | 105.71 Bn | 91.82 Bn | 4.50 Bn | 21.28 Bn |
| 7 | Boston Scientific | 63.26 Bn | 58.27 Bn | 3.85 Bn | 17.56 Bn |
| 8 | Edwards Lifesciences | 49.80 Bn | 33.91 Bn | 1.35 Bn | 2.57 Bn |
| 9 | Becton Dickinson | 48.78 Bn | 45.93 Bn | 2.32 Bn | 23.92 Bn |
| 10 | Mimedx | 679.08 Mn | 75.26 Mn | 44.38 Mn | 54.20 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 54.20 Mn |
| Mar 31, 2026 | 60.64 Mn |
| Dec 31, 2025 | 80.73 Mn |
| Sep 30, 2025 | 74.52 Mn |
| Jun 30, 2025 | 67.50 Mn |
| Mar 31, 2025 | 60.15 Mn |
| Dec 31, 2024 | 63.43 Mn |
| Sep 30, 2024 | 59.96 Mn |
| Jun 30, 2024 | 58.26 Mn |
| Mar 31, 2024 | 60.67 Mn |
| Dec 31, 2023 | 94.11 Mn |
| Sep 30, 2023 | 185.09 Mn |
| Jun 30, 2023 | 185.79 Mn |
| Mar 31, 2023 | 182.08 Mn |
| Dec 31, 2022 | 184.65 Mn |
| Sep 30, 2022 | 186.83 Mn |
| Jun 30, 2022 | 177.99 Mn |
| Mar 31, 2022 | 177.32 Mn |
| Dec 31, 2021 | 182.98 Mn |
| Sep 30, 2021 | 182.26 Mn |
Mimedx Total Non-Current Liabilities API
Pull this series into your own models, spreadsheets and apps with the Business Quant
Historical Metrics API. The request below matches the chart above — change the
frequency, period or values and it follows. Swap YOUR_API_KEY for your own key.
https://data.businessquant.com/historic?slug=total-non-current-liabilities&ticker=MDXG&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "total-non-current-liabilities", "ticker": "MDXG", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()
const res = await fetch("https://data.businessquant.com/historic?slug=total-non-current-liabilities&ticker=MDXG&period=max&api_key=YOUR_API_KEY");
const data = await res.json();