LogicMark (LGMK) Total Non-Current Liabilities (2012 - 2026)
Powered by 
Analysis
LogicMark (LGMK) Total Non-Current Liabilities (2012 - 2026) Analysis & Trends
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Total Non-Current Liabilities (Qtr) |
|---|---|---|---|---|---|
| 1 | Thermo Fisher Scientific | 241.25 Bn | 220.40 Bn | 4.88 Bn | 55.95 Bn |
| 2 | Abbott Laboratories | 167.33 Bn | 138.41 Bn | 7.27 Bn | - |
| 3 | Danaher | 148.83 Bn | 132.65 Bn | 3.61 Bn | 33.25 Bn |
| 4 | Intuitive Surgical | 142.00 Bn | 121.55 Bn | 1.96 Bn | - |
| 5 | Medtronic | 110.70 Bn | 76.57 Bn | 6.34 Bn | 40.46 Bn |
| 6 | Stryker | 104.72 Bn | 90.84 Bn | 4.50 Bn | 21.28 Bn |
| 7 | Boston Scientific | 62.66 Bn | 57.67 Bn | 3.85 Bn | 17.56 Bn |
| 8 | Edwards Lifesciences | 49.13 Bn | 33.24 Bn | 1.35 Bn | 2.57 Bn |
| 9 | Becton Dickinson | 48.51 Bn | 45.66 Bn | 2.32 Bn | 23.92 Bn |
| 10 | LogicMark | 989,734.92 | -26.70 Mn | 2.37 Mn | 3.59 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 3.59 Mn |
| Mar 31, 2026 | 3.40 Mn |
| Dec 31, 2025 | 3.74 Mn |
| Sep 30, 2025 | 4.22 Mn |
| Jun 30, 2025 | 3.73 Mn |
| Mar 31, 2025 | 3.99 Mn |
| Jun 30, 2024 | 3.40 Mn |
| Dec 31, 2023 | 3.86 Mn |
| Sep 30, 2021 | 5.77 Mn |
| Jun 30, 2021 | 7.96 Mn |
| Mar 31, 2021 | 11.09 Mn |
| Dec 31, 2020 | 16.46 Mn |
| Sep 30, 2020 | 16.04 Mn |
| Jun 30, 2020 | 16.14 Mn |
| Mar 31, 2020 | 16.02 Mn |
| Dec 31, 2019 | 17.22 Mn |
| Jun 30, 2019 | 22.33 Mn |
| Mar 31, 2019 | 22.37 Mn |
| Dec 31, 2018 | 20.97 Mn |
| Sep 30, 2018 | 22.49 Mn |
API Access
LogicMark 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=LGMK&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "total-non-current-liabilities", "ticker": "LGMK", "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=LGMK&period=max&api_key=YOUR_API_KEY");
const data = await res.json();