Evaluation of multiwave pulse total-hemoglobinometer during general anesthesia

Comparison of invasive and noninvasive blood hemoglobin measurement in the operating room: a systematic review and meta-analysis

Noninvasive hemoglobin (Hb)-monitoring devices are new inventions in pulse oximeter systems that show hemoglobin levels continuously. The aim of this systematic review and meta-analysis was to evaluate the accuracy and precision of noninvasive versus standard central laboratory Hb measurements in the operating room. We systematically searched multiple databases. Then, for the quality assessment of studies, we modified QUADAS-2 in the Revman 5.3 software. The GRADE approach was used to measure the quality of evidence (Grading of Recommendations Assessment, Development, and Evaluation). Data were analyzed using the meta-analysis method (random effect model) using STATA 11 software. A total of 28 studies on 2000 participants were included in the meta-analysis. Meta-analysis results of mean differences between noninvasive and the central laboratory Hb measurements in overall pooled random effects were - 0.27 (95% LoA (0.44, - 0.10); P value < 0.05). According to this meta-analysis, noninvasive hemoglobin measurement has acceptable accuracy in comparison with the standard invasive method.

Meta-analytic estimation of measurement variability and assessment of its impact on decision-making: the case of perioperative haemoglobin concentration monitoring

Background

As a part of a larger Health Technology Assessment (HTA), the measurement error of a device used to monitor the hemoglobin concentration of a patient undergoing surgery, as well as its decision consequences, were to be estimated from published data.

Methods

A Bayesian hierarchical model of measurement error, allowing the meta-analytic estimation of both central and dispersion parameters (under the assumption of normality of measurement errors) is proposed and applied to published data; the resulting potential decision errors are deduced from this estimation. The same method is used to assess the impact of an initial calibration.

Results

The posterior distributions are summarized as mean ± sd (credible interval). The fitted model exhibits a modest mean expected error (0.24 ± 0.73 (−1.23 1.59) g/dL) and a large variability (mean absolute expected error 1.18 ± 0.92 (0.05 3.36) g/dL). The initial calibration modifies the bias (−0.20 ± 0.87 (−1.99 1.49) g/dL), but the variability remains almost as large (mean absolute expected error 1.05 ± 0.87 (0.04 3.21) g/dL). This entails a potential decision error (“false positive” or “false negative”) for about one patient out of seven.

Conclusions

The proposed hierarchical model allows the estimation of the variability from published aggregates, and allows the modeling of the consequences of this variability in terms of decision errors. For the device under assessment, these potential decision errors are clinically problematic.

Electronic supplementary material

The online version of this article (doi:10.1186/s12874-016-0107-5) contains supplementary material, which is available to authorized users.

Continuous noninvasive hemoglobin monitoring: ready for prime time?

PURPOSE OF REVIEW

Determination of hemoglobin (Hb) concentration is essential for the detection of anemia and hemorrhage and is widely used to evaluate a patient for a possible blood transfusion. Although commonly accepted as intrinsic to the process, traditional laboratory measurements of Hb are invasive, intermittent, and time-consuming. Noninvasive Hb (NIHb)-monitoring devices have recently become available and promise the potential for detecting sudden changes in a patient's Hb level. In addition to reduced delays in clinical intervention, these devices also allow for a reduction in patient discomfort, infection risk, required personnel, and long-term costs. Unfortunately, it has been shown that many clinical factors can influence their accuracy.

RECENT FINDINGS

Many studies have been published on the accuracy and precision of NIHb-monitoring devices in various clinical settings. A recent meta-analysis has shown a small mean difference but wide limits of agreement between NIHb and laboratory measurements, indicating that caution should be used by physicians when making clinical decisions based on this device.

SUMMARY

NIHb measurements may currently be considered to be a supplemental tool for monitoring trends in Hb concentration, but are not currently developed enough to replace an invasive approach. Moreover, further studies are still required before implementing NIHb in the clinical decision-making process. Specifically, no studies have demonstrated that this technology improves clinical outcomes or patient safety.