Company: PFSA
Filing Date: 2025-04-03
Form Type: S-4/A
Source: 0001213900-25-028544
Chunk: 440

Company: Profusa, Inc.
Filing Date: 2025-04-03
Form: S-4/A
Chunk 440
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.7 | 18.2 |    19.3 |         |
| Max         |    40.2 |    40.1 |    40.3 | 31.1 |    34.9 |         |
| Therapy (%) | Insulin |     100 |     100 |   94 |       0 |      29 |
| Oral        |       0 |       0 |       0 |   71 |      29 |         |
| Both        |       0 |       0 |       6 |   29 |      42 |         |
| HbA1C (%)   |    Mean |     6.9 |     7.5 |    — |     9.6 |     8.6 |
| Min         |       6 |     6.3 |       — |  6.7 |     7.7 |         |
| Max         |     7.9 |     9.3 |       — | 14.8 |     9.4 |         |

Results The feasibility study at the four clinical sites provided data on sensor locatability, system performance (the ability to accurately estimate glucose), in addition to monitoring for adverse events. All the sensors were locatable. The feasibility study was not designed and powered to provide a robust estimate of the commercial performance of the system, however, data collected in the study enabled the refinement of the algorithm. Using the data, Profusa was able to show evidence of the system’s ability to track glucose. Data indicate that the sensors were responsive to glucose during the study period and provided a significant body of data for algorithm development and evaluation. Performance analysis of the data yielded an aggregate mean absolute relative difference (MARD) of 11.7% for sessions from 7 – 90 days post -injection. The consensus error grid and cumulative MARD distribution are presented below, representing 163 sessions from 37 patients that passed the data quality filters, resulting in 2406 paired blood

240 glucose reference points. Data quality filters that were developed and automated during the algorithm development exclude problematic traces including poorly placed readers over the sensor, unexpected fluorescence contamination of the skin surface over the sensor, and poor adhesion of the reader over the sensor yielding low signal to noise. The figure above shows a standard Consensus Error grid, which is a tool used to evaluate the accuracy of blood glucose meters. It visualizes the paired