Impacts of Skin Color and Hypoxemia on Noninvasive Assessment of Peripheral Blood Oxygen Saturation: A Scoping Review.

Standard pulse oximeters estimate arterial blood saturation (SaO2) non-invasively by emitting and detecting light of a specific wavelength through a cutaneous vascular bed, such as a digit or the ear lobe. The quantity measured at these peripheral sites is designated as oxygen saturation (SpO2). Most reliable pulse oximeters are calibrated from measurements of healthy volunteers using some form of oxygen desaturation method. As the degree of inducible hypoxemia is limited, the calibration below achievable desaturation levels is usually extrapolated, leading to potential measurement error at low SaO2 values, especially in highly pigmented skin. Such skin color-related errors (SCRE) are the topic of this scoping review. Specifically, this study aimed to identify the combined impact of skin color and reduced SaO2 on the non-invasive assessment of SpO2 and report the consequences of potential inaccuracies. Three databases were searched (Cumulated Index to Nursing and Allied Health Literature (CINAHL), PubMed, and Web of Science) for peer-reviewed prospective and retrospective studies published in English between 2000 and 2022 involving human patients with hypoxemia that included a measure of skin color (Fitzpatrick scale or race/ethnicity). Ten studies met the criteria and were included in the final review. Eight of these studies reported statistically significant higher pulse oximeter readings in darker-skinned patients with hypoxia compared to their arterial blood gas measurements. Occult hypoxia was more prevalent in Black and Hispanic patients than in White patients. Minority patients overall (Black, Asian, and American Indian) were more likely to have a SaO2 < 88% that was not detected by pulse oximetry (occult hypoxemia) during hospitalization. With greater levels of hypoxemia, the differences between SpO2 and SaO2 were greater. If SaO2 was < 90%, then SpO2 was overestimated in all ethnicities but worse in minorities. In conclusion, the bias found in pulse oximeter readings in the skin of color broadly impacts patients with hypoxemia. The failure of SpO2 measuring devices to detect occult hypoxemia can delay the delivery of life-saving treatment to critically ill patients requiring respiratory rehabilitation and supplemental oxygen therapy. This may lead to adverse health outcomes, increased in-hospital mortality, and complications such as organ dysfunction. An improvement in pulse oximeter detection mechanisms that would include all skin pigmentations is therefore much desired to optimize individual healthcare status and minimize disparities in treatment.

Chronic Venous Insufficiency With Emphasis on the Geriatric Population.

The underpinning of Chronic Venous Insufficiency (CVI) is valvular dysfunction, which manifests on a spectrum depending on the severity of insufficiency and duration of the disease. The mainstay of treatment relies on compression therapy of a proper type and intensity. In older adults, special consideration must be taken during the patient encounter to account for age-related factors. This review discusses the clinical presentation, diagnosis, and mimicking of CVI, focusing mainly on older adults. The epidemiology, risk factors, disease burden, and grave complications -- such as thrombosis and ulceration, are reviewed. The physiological impacts of CVI are described, providing the background for treatment strategies, including non-invasive, medical, and surgical therapies. The findings show advanced age to be an important risk factor contributing to CVI and that other age-related factors add to the risk of severe complications. Clinical assessments combined with objective measurements that assess localized skin water using tissue dielectric constant values or whole limb assessments may aid in the differential diagnosis. Furthermore, understanding the mechanism of action of compression therapy, the mainstay of CVI treatment, and its physiological impacts, allows for its informed use in geriatric patients with increased risks of potential compression-related side effects.

Utility of a Body Shape Index Parameter in Predicting Cardiovascular Disease Risks.

BACKGROUND: Anthropometric indices are used as predictors of cardiovascular disease (CVD). The most used indices are body mass index (BMI) and waist circumference (WC); however, there are limitations regarding their validity to address different body shapes, fat and lean mass distribution. A body shape index (ABSI) has been proposed as an alternative parameter to reflect differences in body shape and potentially be more useful for predicting CVD. ABSI is calculated by ABSI = WC / (BMI2/3 • Height1/2). The purpose of this cross-sectional study was to determine the utility of ABSI as a predictor or modifiable risk factor of CVD compared to other commonly used measures in clinical practice. METHODS: The sample population was from the baseline interview and health examination included in the National Health and Nutrition Examination Survey (NHANES) 2013-2014. Patients (n=5,924, 52% female) were aged 18-80 years (47.4 ± 18.4 years) who completed a series of questionnaires on a spectrum of health-related risks. After the interview, health technicians performed a standardized examination of the participants to collect data on weight, height, BMI, WC, and sagittal abdominal diameter (SAD). Statistical analysis was done using R Studio, version 0.99.903 (RStudio, Inc. Boston, MA). Using logistic regression, the correlation between each predictor (ABSI, BMI, WC, SAD) as a continuous variable, and CVD outcomes was evaluated with two models: a univariable model and a multivariable model. In a secondary analysis, ABSI was reclassified into categorical values based on quartiles of the NHANES dataset. Logistic regressions were again run for overall CVD and all CVD sub-categories, followed by chi-square tests for significance. For comparison, BMI categories of normal, overweight, obese, and severely obese were tested with overall CVD and all CVD subcategories as outcome measures, followed by chi-square tests for significance. RESULTS: Approximately 10% of the sample population had at least one prior manifestation of CVD, the most common being myocardial infarction (MI) (4.0%). ABSI showed little correlation with weight, BMI, WC, and SAD (r<0.3), while BMI had a strong correlation with weight, BMI, WC, and SAD (r ≈ 0.9). In univariable logistic regression, ABSI showed the most robust associations of all predictors with overall CVD and all CVD subcategories. ABSI demonstrated stronger correlations than BMI for all CVD outcomes (except CHF in the multivariable model). This study attempted to create classifications of ABSI and compare them to the normative classifications of BMI. In this categorical analysis, ABSI was also stronger than BMI in all logistic regression analyses for CVD outcomes, except for CHF in the multivariable model. Severe obesity (BMI ≥40 kg/m2) almost doubled the odds of having CVD, while being categorized in Q2, Q3, and Q4 for ABSI increased odds by double, triple, and eight-fold, respectively. CONCLUSION: An ABSI parameter in the upper three quartiles increases the risk of CVD manifestations more significantly than an elevated BMI per category of overweight, obese, and severely obese, respectively. Since the categories for ABSI were created based on quartiles of a large sample size reflecting the US population, this suggests that the increased risk from an elevated ABSI is more widespread than previously understood. Thus, ABSI should be monitored more closely and managed in preventative medical care than BMI alone.