Lemaitre Vascular (LMAT) Total Liabilities (2010 - 2026)
Lemaitre Vascular's Total Liabilities was $220.21 million in Q2 2026, up 2.5% from $214.91 million a year earlier but down 1.2% from the prior quarter.
Lemaitre Vascular (LMAT) Total Liabilities (2010 - 2026) Analysis & Trends
At the end of FY2025, Total Liabilities at Lemaitre Vascular came in at $222.17 million, up 3.6% from FY2024.
- Total Liabilities has now increased for four consecutive years, with a five-year compound annual growth rate of 22.6% (FY2020 to FY2025).
- In earlier years, Total Liabilities was $214.53 million in FY2024 (+338.9%), $48.88 million in FY2023 (+15.6%), $42.28 million in FY2022 (+9.4%) and $38.65 million in FY2021 (-51.8%).
- Quarterly Total Liabilities has moved between $34.67 million (Q1 2022) and $222.9 million (Q1 2026) over five years.
- Compared with a year earlier, Total Liabilities has increased for 16 straight quarters, with growth averaging 185.3% over the last eight quarters.
- The best year-over-year quarter for Total Liabilities over five years was Q2 2025 (growth of 393.5%); the worst was Q3 2021 (a decline of 59.8%).
- Per Business Quant data, LMAT's Total Liabilities in the three quarters before Q2 2026 was $222.9 million (Q1 2026), $222.17 million (Q4 2025) and $219.15 million (Q3 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Total Liabilities (Qtr) |
|---|---|---|---|---|---|
| 1 | Thermo Fisher Scientific | 249.71 Bn | 228.86 Bn | 4.88 Bn | 60.49 Bn |
| 2 | Abbott Laboratories | 171.00 Bn | 142.08 Bn | 7.27 Bn | 57.45 Bn |
| 3 | Danaher | 155.79 Bn | 139.61 Bn | 3.61 Bn | 39.78 Bn |
| 4 | Intuitive Surgical | 143.91 Bn | 123.46 Bn | 1.96 Bn | 2.58 Bn |
| 5 | Medtronic | 110.42 Bn | 76.29 Bn | 6.34 Bn | 42.46 Bn |
| 6 | Stryker | 105.71 Bn | 91.82 Bn | 4.50 Bn | 23.94 Bn |
| 7 | Boston Scientific | 63.26 Bn | 58.27 Bn | 3.85 Bn | 20.04 Bn |
| 8 | Edwards Lifesciences | 49.80 Bn | 33.91 Bn | 1.35 Bn | 3.14 Bn |
| 9 | Becton Dickinson | 48.78 Bn | 45.93 Bn | 2.32 Bn | 26.32 Bn |
| 10 | Lemaitre Vascular | 1.89 Bn | 442.77 Mn | 50.76 Mn | 220.21 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 220.21 Mn |
| Mar 31, 2026 | 222.90 Mn |
| Dec 31, 2025 | 222.17 Mn |
| Sep 30, 2025 | 219.15 Mn |
| Jun 30, 2025 | 214.91 Mn |
| Mar 31, 2025 | 208.43 Mn |
| Dec 31, 2024 | 214.53 Mn |
| Sep 30, 2024 | 45.95 Mn |
| Jun 30, 2024 | 43.55 Mn |
| Mar 31, 2024 | 45.45 Mn |
| Dec 31, 2023 | 48.88 Mn |
| Sep 30, 2023 | 45.38 Mn |
| Jun 30, 2023 | 42.64 Mn |
| Mar 31, 2023 | 40.70 Mn |
| Dec 31, 2022 | 42.28 Mn |
| Sep 30, 2022 | 40.80 Mn |
| Jun 30, 2022 | 41.39 Mn |
| Mar 31, 2022 | 34.67 Mn |
| Dec 31, 2021 | 38.65 Mn |
| Sep 30, 2021 | 40.43 Mn |
Lemaitre Vascular Total 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-liabilities&ticker=LMAT&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "total-liabilities", "ticker": "LMAT", "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-liabilities&ticker=LMAT&period=max&api_key=YOUR_API_KEY");
const data = await res.json();