Arnold : Point-Of-Care Assessment of Microvascular Flow

Arnold : Point-Of-Care Assessment of Microvascular Flow

Arnold: Point-of-care assessment of microvascular flow

Electronic Supplemental Material

Point-of-Care Assessment of Microvascular Blood Flow in

Critically Ill Patients

ELECTRONIC SUPPLEMENTAL MATERIAL

Ryan C. Arnold, MD; Joseph E. Parrillo, MD; R. Phillip Dellinger, MD;

Michael E. Chansky, MD; Nathan I. Shapiro MD, MPH, David J. Lundy MD,

Stephen Trzeciak MD, MPH; and Steven M. Hollenberg, MD on behalf of the

Microcirculatory Alterations in Resuscitation and Shock (MARS) Investigators

Submitted as a Brief Report to Intensive Care Medicine

Address for Correspondence:

Ryan Arnold, MD

Department of Emergency Medicine

UMDNJ-Robert Wood Johnson Medical School at Camden

Cooper University Hospital

One Cooper Plaza

Camden, NJ 08103

Phone: 856-340-0582

FAX: 856-968-8306

Email:

Electronic Supplemental Material

Figure 3: Microcirculatory flow image

CDday1

Figure 3: Please see the Intensive Care Medicine website for an example of sublingual microcirculatory images using Sidestream Darkfield (SDF) videomicroscopy in both high and low flow states.

Figure 4: Within-subject standard deviation against subject mean

Figure 5: Within-subject standard deviation against subject mean for each method of microcirculatory flow analysis. Data is grouped per subject and mean and standard deviation are calculated. According to Bland and Altman[1], plotting each subject’s standard deviation against subject means for each method separately allows for visual inspection to verify the assumption that variances within the study are independent of subject means. The assumption of independence is reasonable for these data.

Figure 5: Histogram of the observed differences in POC-MFI from the Offline-MFI.

POC

Figure 5: Histogram illustrating the number of observed differences between the POC and Offline-MFI methods. Data is presented as percent (%) of the sample size. A score of “0” is complete agreement between the two methods. The smallest measurable increment of disagreement in the POC method is 0.25. 94% of our POC assessments fall within ± 0.25 from the (Offline) reference standard.

Figure 6: ∆Offline-MFI compared to ∆POC-MFI

POC Delta Offline vs POC

Figure 6: A comparison of the change in Offline-MFI (∆Offline-MFI) to the change in POC-MFI (∆POC-MFI). The ∆MFI for each method was calculated as the difference between the average MFI measured at each time point. Each set of bars represents the average MFI assessed by each method in a single patient at a specific time interval. The data is presented based on an increasing ∆Offline-MFI from negative to positive. Data was limited to the presence of a previous MFI measurement to enable a ∆MFI calculation (36 paired measruements). [MFI = Microcirucaltory Flow Index]

References

1.Bland JM, Altman DG, (1999) Measuring agreement in method comparison studies. Stat Methods Med Res 8: 135-160

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