Pulmonx (LUNG) Change in Accrued Expenses (2019 - 2026)
Pulmonx's Change in Accrued Expenses came in at $528,000 for Q3 2025, down 27.9% from $732,000 a year earlier and down 79.1% from the prior quarter.
Pulmonx (LUNG) Change in Accrued Expenses (2019 - 2026) Analysis & Trends
Over the trailing twelve months to Sep 30, 2025, Pulmonx reported Change in Accrued Expenses of $2.14 million; for FY2024, it came in at $462,000, down 85.5% from FY2023.
- Change in Accrued Expenses carries a five-year compound annual growth rate of -32.8% (FY2019 to FY2024).
- Going back by year, Change in Accrued Expenses was $3.18 million in FY2023, $149,000 in FY2022 (-96.9%), $4.8 million in FY2021 (+371.1%) and $1.02 million in FY2020 (-69.8%).
- The five-year range for quarterly Change in Accrued Expenses is -$5.98 million (Q1 2024) to $3.98 million (Q4 2024).
- Year-over-year, Change in Accrued Expenses increased in three of the last six quarters, with growth averaging 20.1%.
- The fastest year-over-year change in Change in Accrued Expenses over five years came in Q2 2021 (growth of 237.3%), and the weakest in Q3 2021 (a decline of 81.8%).
- Business Quant data shows LUNG's Change in Accrued Expenses at $2.53 million (Q2 2025), -$4.89 million (Q1 2025) and $3.98 million (Q4 2024) in the three quarters before Q3 2025.
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 | Pulmonx | 121.94 Mn | -117.95 Mn | 17.40 Mn | 536,000.00 |
Historic Data
| Date | Value |
|---|---|
| Sep 30, 2026 | 536,000.00 |
| Jun 30, 2026 | 786,000.00 |
| Mar 31, 2026 | -1.17 Mn |
| Dec 31, 2025 | -443,000.00 |
| Sep 30, 2025 | 528,000.00 |
| Jun 30, 2025 | 2.53 Mn |
| Mar 31, 2025 | -4.89 Mn |
| Dec 31, 2024 | 3.98 Mn |
| Sep 30, 2024 | 732,000.00 |
| Jun 30, 2024 | 1.74 Mn |
| Mar 31, 2024 | -5.98 Mn |
| Dec 31, 2023 | 2.25 Mn |
| Sep 30, 2023 | 422,000.00 |
| Jun 30, 2023 | 2.98 Mn |
| Mar 31, 2023 | -2.48 Mn |
| Dec 31, 2022 | 2.39 Mn |
| Sep 30, 2022 | -940,000.00 |
| Jun 30, 2022 | 1.02 Mn |
| Mar 31, 2022 | -2.31 Mn |
| Dec 31, 2021 | 1.51 Mn |
Pulmonx 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=LUNG&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "change-in-accured-expenses", "ticker": "LUNG", "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=LUNG&period=max&api_key=YOUR_API_KEY");
const data = await res.json();