Si-Bone (SIBN) Change in Accrued Expenses (2017 - 2026)
Si-Bone's Change in Accrued Expenses came in at $3.98 million for Q3 2026, up 159.2% from $1.54 million a year earlier and up 221.3% from the prior quarter.
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Analysis
Si-Bone (SIBN) Change in Accrued Expenses (2017 - 2026) Analysis & Trends
Over the trailing twelve months to Sep 30, 2026, Si-Bone reported Change in Accrued Expenses of $1.69 million, up 22.1% year-over-year; for FY2025, it was $179,000, down 90.6% from FY2024.
- Going back by year, Change in Accrued Expenses was $1.91 million in FY2024 (-50.9%), $3.89 million in FY2023 (+222.1%), $1.21 million in FY2022 (-29.9%) and $1.72 million in FY2021.
- The Q3 2026 figure represents the highest quarterly Change in Accrued Expenses in data going back to Q4 2017.
- Year-over-year, Change in Accrued Expenses increased in two of the last six quarters, with growth averaging 9.0%.
- The fastest year-over-year change in Change in Accrued Expenses over five years came in Q3 2023 (growth of 189.0%), and the weakest in Q2 2025 (a decline of 43.8%).
- Business Quant data shows SIBN's Change in Accrued Expenses at $1.24 million (Q2 2026), -$5.64 million (Q1 2026) and $2.11 million (Q4 2025) in the three quarters before Q3 2026.
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Change Accrued Exp. (Qtr) |
|---|---|---|---|---|---|
| 1 | Thermo Fisher Scientific | 266.22 Bn | 242.86 Bn | 5.13 Bn | - |
| 2 | Abbott Laboratories | 191.31 Bn | 165.77 Bn | 7.39 Bn | - |
| 3 | Danaher | 166.16 Bn | 145.82 Bn | 3.84 Bn | 30.00 Mn |
| 4 | Intuitive Surgical | 155.98 Bn | 136.40 Bn | 2.08 Bn | 80.10 Mn |
| 5 | Medtronic | 130.05 Bn | 96.18 Bn | 6.34 Bn | -531.00 Mn |
| 6 | Stryker | 123.40 Bn | 109.59 Bn | 4.25 Bn | 77.00 Mn |
| 7 | Boston Scientific | 64.81 Bn | 60.48 Bn | 3.43 Bn | 89.00 Mn |
| 8 | Edwards Lifesciences | 59.87 Bn | 43.18 Bn | 1.35 Bn | 67.20 Mn |
| 9 | Medline | 53.84 Bn | 50.96 Bn | 1.93 Bn | 255.00 Mn |
| 10 | Si-Bone | 1.13 Bn | 544.91 Mn | 44.17 Mn | 3.98 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Sep 30, 2026 | 3.98 Mn |
| Jun 30, 2026 | 1.24 Mn |
| Mar 31, 2026 | -5.64 Mn |
| Dec 31, 2025 | 2.11 Mn |
| Sep 30, 2025 | 1.54 Mn |
| Jun 30, 2025 | 962,000.00 |
| Mar 31, 2025 | -4.43 Mn |
| Dec 31, 2024 | 3.31 Mn |
| Sep 30, 2024 | 2.55 Mn |
| Jun 30, 2024 | 1.71 Mn |
| Mar 31, 2024 | -5.66 Mn |
| Dec 31, 2023 | 3.86 Mn |
| Sep 30, 2023 | 2.93 Mn |
| Jun 30, 2023 | 732,000.00 |
| Mar 31, 2023 | -3.63 Mn |
| Dec 31, 2022 | 2.29 Mn |
| Sep 30, 2022 | 1.01 Mn |
| Jun 30, 2022 | 1.07 Mn |
| Mar 31, 2022 | -3.17 Mn |
| Dec 31, 2021 | 1.40 Mn |
API Access
Si-Bone Change in Accrued Expenses 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=change-in-accured-expenses&ticker=SIBN&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "change-in-accured-expenses", "ticker": "SIBN", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()const res = await fetch("https://data.businessquant.com/historic?slug=change-in-accured-expenses&ticker=SIBN&period=max&api_key=YOUR_API_KEY");
const data = await res.json();