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Accuracy and trending of non-invasive hemoglobin measurement during different volume and perfusion statuses

Overview of attention for article published in Journal of Clinical Monitoring and Computing, January 2018
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About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • One of the highest-scoring outputs from this source (#6 of 700)
  • High Attention Score compared to outputs of the same age (98th percentile)
  • High Attention Score compared to outputs of the same age and source (90th percentile)

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16 news outlets

Citations

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32 Dimensions

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57 Mendeley
Title
Accuracy and trending of non-invasive hemoglobin measurement during different volume and perfusion statuses
Published in
Journal of Clinical Monitoring and Computing, January 2018
DOI 10.1007/s10877-018-0101-z
Pubmed ID
Authors

Abdelmoneim Adel, Wael Awada, Bassant Abdelhamid, Heba Omar, Omnia Abd El Dayem, Ahmed Hasanin, Ashraf Rady

Abstract

The evolution of non-invasive hemoglobin measuring technology would save time and improve transfusion practice. The validity of pulse co-oximetry hemoglobin (SpHb) measurement in the perioperative setting was previously evaluated; however, the accuracy of SpHb in different volume statuses as well as in different perfusion states was not well investigated. The aim of this work is to evaluate the accuracy and trending of SpHb in comparison to laboratory hemoglobin (Lab-Hb) during acute bleeding and after resuscitation. Seventy patients scheduled for major orthopedic procedures with anticipated major blood loss were included. Radical-7 device was used for continuous assessment of SpHb, volume status [via pleth variability index (PVI)] and perfusion status [via perfusion index (PI)]. Lab-Hb and SpHb were measured at three time-points, a baseline reading, after major bleeding, and after resuscitation. Samples were divided into fluid-responsive and fluid non-responsive samples, and were also divided into high-PI and low-PI samples. Accuracy of SpHb was determined using Bland-Altman analysis. Trending of SpHb was evaluated using polar plot analysis. We obtained 210 time-matched readings. Fluid non-responsive samples were 106 (50.5%) whereas fluid responsive samples were 104 (49.5%). Excellent correlation was reported between Lab-Hb and SpHb (r = 0.938). Excellent accuracy with moderate levels of agreement was also reported between both measures among all samples, fluid non-responsive samples, fluid-responsive samples, high-PI samples, and low-PI samples [Mean bias (limits of agreement): 0.01 (- 1.33 and 1.34) g/dL, - 0.08 (- 1.27 and 1.11) g/dL, 0.09 (- 1.36 and 1.54) g/dL, 0.01 (- 1.34 to 1.31) g/dL, and 0.04 (- 1.31 to 1.39) g/dL respectively]. Polar plot analysis showed good trending ability for SpHb as a follow up monitor. In conclusion, SpHb showed excellent correlation with Lab-Hb in fluid responders, fluid non-responders, low-PI, and high PI states. Despite a favorable mean bias of 0.01 g/dL for SpHb, the relatively wide levels of agreement (- 1.3 to 1.3 g/dL) might limit its accuracy. SpHb showed good performance as a trend monitor.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 57 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 57 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 5 9%
Other 4 7%
Student > Postgraduate 4 7%
Student > Master 4 7%
Student > Doctoral Student 4 7%
Other 13 23%
Unknown 23 40%
Readers by discipline Count As %
Medicine and Dentistry 20 35%
Nursing and Health Professions 4 7%
Engineering 4 7%
Agricultural and Biological Sciences 1 2%
Materials Science 1 2%
Other 1 2%
Unknown 26 46%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 121. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 14 March 2018.
All research outputs
#291,962
of 23,026,672 outputs
Outputs from Journal of Clinical Monitoring and Computing
#6
of 700 outputs
Outputs of similar age
#8,120
of 473,661 outputs
Outputs of similar age from Journal of Clinical Monitoring and Computing
#1
of 10 outputs
Altmetric has tracked 23,026,672 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 98th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 700 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.2. This one has done particularly well, scoring higher than 99% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 473,661 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 98% of its contemporaries.
We're also able to compare this research output to 10 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them