Accuracy of HemoCue301 portable hemoglobin analyzer for anemia screening in capillary blood from women of reproductive age in a deprived region of Northern Peru: An on-field study

Dulce E Alarcón-Yaquetto; Lenin Rueda-Torres; Nataly Bailon; Percy Vílchez Barreto; Germán Málaga

doi:10.1371/journal.pone.0293984

. 2023 Nov 14;18(11):e0293984. doi: 10.1371/journal.pone.0293984

Accuracy of HemoCue301 portable hemoglobin analyzer for anemia screening in capillary blood from women of reproductive age in a deprived region of Northern Peru: An on-field study

Dulce E Alarcón-Yaquetto ^1,^*,^#, Lenin Rueda-Torres ^1,^#, Nataly Bailon ¹, Percy Vílchez Barreto ², Germán Málaga ¹

Editor: Benedikt Ley³

PMCID: PMC10645325 PMID: 37963155

Abstract

Objective

We aim to assess the accuracy and effectiveness of the HemoCue 301, a point-of-care (POC) device for measuring hemoglobin levels, and detecting anemia among individuals living in Tumbes, a rural, underserved area in Northern Peru.

Methods

Baseline analysis of a clinical trial aimed at assessing the effect of multi-fortified bread (NCT05103709). Adult women with capillary blood HemoCue 301 readings below 12 g/dL were recruited in coastal city of Tumbes, Peru. A total of 306 women took part of the study, venous blood samples were taken and analyzed with an automated hematology analyzer. Serum samples were used to measure ferritin, serum iron and C reactive protein.

Results

Capillary blood measured by the Hemocue 301 has a bias of 0.36 ± 0.93 g/dL respect to the automated Hb. More than 50% of women with normal ferritin values were classified as anemics according to the HemoCue 301. Automated Hb cut-off of 10.8 g/dL [AUC 0.82 (0.77–0.88)] had a specificity of 0.817 and a sensitivity 0.711 while with the HemoCue 301 cut-off of 11.1 g/dL [AUC 0.71 (0.62–0.79)] had a specificity of 0.697 and a sensitivity 0.688. The performance of the automated Hb cut-off was significantly better than the HemoCue (p<0.001).

Conclusion

Caution must be taken when using POC devices, especially with values around the threshold. Cut-off values found in our study could be used as surrogate means when no confirmatory tests are available. Clinical outcomes should be prioritized when diagnosing iron deficiency anemia in women of reproductive age to ensure proper diagnosis.

Introduction

Despite major breakthroughs in health technology, iron deficiency anemia (IDA) remains a challenge worldwide. Its long-standing association with deprivation and impoverishment has made IDA’s eradication a universal goal to be achieved in the 2030 agenda [1]. A major hurdle to reach this objective is the inequity in its diagnosis with people from isolated communities being the more affected [2].

In Peru, anemia is considered a severe public health problem as shown by national statistics [3]. In some provinces, the rates of anemia greatly surpass the 40% cut-off value which is considered a critical threshold for public health concern, indicating a severe public health issue [4].

Still, research has questioned these figures due to several issues in the diagnosis. For instance, the sole measurement of hemoglobin (Hb) is not enough to diagnose IDA. It is widely known that Hb is only a proxy for IDA. Rationale behind its use is that ~70% of active bodily iron is contained in the protein [5]. However, it has even been showed to be poorly correlated to iron deficiency per se [6]. Despite this fact, the main strategy of health policies aimed to tackle anemia in Peru are based on iron supplementation [7]. IDA diagnosis needs the estimation of iron parameters and should not only rely on Hb measurement. This over simplification might be counterproductive [8].

The need for further confirmatory tests that properly give an account of iron homeostasis in the organism is warranted. These might be readily available in high-income countries and even in main cities from low-and-middle income countries (LMIC) but hardly ever offered to rural and remote populations.

Furthermore, automated hematology analyzers—the method suggested by the WHO [9]—cannot be properly used in remote communities due to resource constraints. Handheld devices have been routinely used to screen for anemia in LMIC countries such as the HemoCue system. In fact, this device is used by the Peruvian government as the main method for anemia surveillance, and public policy making [10].

The HemoCue 301 system is the newer version of the point of care device. The microcuvettes are not that sensitive to extreme weathers as the previous versions (201 and 201+) and the cost per sample is cheaper [11, 12]. While the manufacturer states the device’s discrepancy falls within 7% acceptable error compared to CLIA’88 regulations [13], Morris et al. (2007) found that 4% of samples were above the 7% limit and 1% above 10% error in blood-donor samples from the UK [12]; Rappaport et al. (2017) found a bias of 2 g/L compared to the 201 version in Cambodian women of reproductive age (WRA) [14] and Yadav et al. (2020) found a -0.25 (0.85) g/dL bias compared to automated analyzer in pregnant women from India [15].

Here, we compare the performance of HemoCue 301 to the reference method, automated hematology analyzer, while also assessing iron status in Tumbes, Peru. The main objective of this study is to assess the suitability and accuracy of this device as a method for anemia diagnosis in women of reproductive age in a coastal city with resource constraints.

Methods

Design and setting

Baseline analysis of a clinical trial aimed at assessing the effect of the consumption of multi-fortified bread in WRA with iron deficiency anemia. The study was carried out in Tumbes, a coastal city of Northern Peru with altitudes ranging from 6 to 124 meters above sea level. According to official statistics, Tumbes has between 9.2 to 12% of poverty and mean per capita earnings of 558 soles (~150 USD), 13.61% less than the national average [16].

Inclusion criteria and point of care Hb measurement

The study recruited apparently healthy, non-pregnant WRA, living permanently in the city. Inclusion criteria was adult WRA, living permanently in the city with capillary blood Hemocue301 readings below 12 g/dL. Women with amenorrhea non explained by pregnancy and those who were heavy smokers were excluded from the study. Due to ethical concerns raised by the IRB, all women with HemoCue values below 8 g/dL were also excluded and referred to primary care centers. Recruitment took place between August 5^th and September 17^th 2021.

HemoCue measurement was done by trained nurses following the manufacturers recommendations. Briefly, 301 cuvettes were filled with a drop of blood from the middle finger fingertip. The first 2 drops of blood were discarded. The microcuvette was put in the cuvette holder and a measurement was done immediately [11]. A trained phlebotomist took venous samples of each woman with the BD vacutainer system (one tube with EDTA and other without anticoagulant). Both HemoCue measurement and venous samples were taken the same day and time and at each participant’s house after informed consent was signed.

Laboratory analysis

Whole blood samples in EDTA tubes were transported to the Tumbes Regional Direction of Health in a temperature monitored cooler that remained at laboratory temperature (18°- 24° C). A complete blood count (CBC) was performed in venous blood samples within two hours of obtaining the sample. The CBC analyses followed the ISLH´s guidelines [17]. Briefly, slide review was performed to assess morphological changes of the red blood cell. No features suggestive of thalassemia or other type of hemoglobinopathies were found. An automated analyzer Prokan PE-6100 PLUS was used to measure hematological indices within the 4 hours after the sample was taken. A second tube with silica clot activator was transported in coolers at 4° - 8°C to the Tumbes Regional Direction where they were centrifuged, remaining serum was stored at -20°C and shipped to Lima where C-reactive protein (CRP), serum iron and ferritin were measured by spectrophotometric and turbidimetric assays (Wiener Lab CM250, Wiener Lab Switzerland) on an ISO 15189 compliant laboratory.

Statistical analysis

Anemia was defined using automated Hb values of 12 g/dL. Iron deficiency was assessed using ferritin values below 15 ug/dL [18] and IDA was defined when both conditions were satisfied (automated Hb values below 12 g/dL and ferritin below 15 ug/dL). Microcytosis was defined with mean corpuscular values (MCV) < 80 fl., hypochromia by mean corpuscular hemoglobin (MCH) values below 27. Descriptive statistics are provided as mean standard deviation or median and interquartile range for quantitative variables according to their distribution. Frequency and percentages are used for qualitative variables. The population was further divided into tertiles based both on automated Hb values and HemoCue values. Serum iron, ferritin and CRP were compared between tertiles, as well as other red blood markers and analysis of variance was used to assess differences.

Bland Altman plots are presented between automated Hb (aHb) and Hb values given by the HemoCue301. aHb is used as gold standard as it is the measure suggested by the WHO [9]. The plots were constructed using the B.A function [19] in RStudio. The normality of the differences was assessed through a Shapiro Wilk test.

Low ferritin values were defined as serum ferritin values below 15 ug/L [18]. The accuracy of the HemoCue Hb and automated Hb to identify low ferritin values was assessed using receiver-operating characteristic (ROC) curves. For this, a general linear model adjusted by age was plotted. ROC curves were constructed using the pROC package [20] using low ferritin (<15 ug/L) as gold standard. Ferritin shows the major diagnostic accuracy for iron deficiency in relation to bone marrow aspirate [21]. A sensitivity analysis was performed excluding all those participants with CRP values above 5 mg/L. Statistical test for ROC curves was the DeLong test. Optimal cut-off values were calculated using the Youden index. Sensitivity, specificity, positive and negative predictive values and their respective confidence intervals are provided for each cut-off point. Statistical significance was denoted by p values below 0.05. Analyses were performed with RStudio©1.1.45327(RStudio, Boston, MA).

Results

A total of 306 women participated in the study with an average age of 25.94±5.4 years. While according to our inclusion criteria, upon enrolment, all women had HemoCue readings below 12 g/dL, the median automated Hb values were 11.7 (10.6–12.3) g/dL. 123 women (40.2%) had automated Hb values below 12 g/dL, however, out of this group only 43 (23.6%) had also ferritin values below the threshold. While not the only reason of microcytic and hypochromic anemia, IDA is characterized by microcytosis and hypochromosis. Out of the sample, 53.95% had microcytosis while hypochromia based on MCH was found in 37.5%. Both conditions were found concomitantly in 34.21% of the sample. Table 1 features sociodemographic variables according to automated Hb status.

Table 1. Baseline characteristics of sample by automated Hb status.

Variable	Total (n = 306)	aHb> = 12 (n = 123)	aHb<12 (n = 183)	P value
Age (years)	25.5 (21–31)	26 (22–31)	25 (20–31)	0.302
Height (meters)	1.55±0.06	1.54±0.05	11.55±0.06	0.053
Weight (kilograms)	62.6 (54.55–76.15)	64.4 (54.4–75.1)	62.1 (54.7–76.5)	0.838
BMI (m/kg²)	26.66 (22.81–30.86)	27.58 (23.13–31.56)	26.37 (22.59–30.57)	0.333
HemoCue Hb (g/dL)	11.3 (10.8–11.6)	11.5 (11.2–11.7)	11.1 (10.4–11.5)	<0.001

Open in a new tab

Hb: Hemoglobin, aHb: Hb measured by automated analyzer. Values are mean ± SD or median and IQR. P values are from 2 tailed T tests or Wilcoxon Rank sum test.

We further classified participants based on tertiles of both capillary blood HemoCue 301 values and venous blood automated Hb values. The lowest Hemocue301 tertile had HemoCue values ranging from 8–11 g/dL (n = 111). In the second group HemoCue values ranged from 11.1 to 11.5 g/dL (n = 102), while the final group had values from 11.6 to 11.9 g/dL (n = 93).

In Fig 1, we show differences between red blood cell count indices of relevance for IDA diagnosis. The main difference resides between parameters from the first and second tertiles and with the first and third tertiles. No significant difference is seen between the second or the third tertile of any of the markers seen suggesting the main hurdle for the HemoCue 301 is distinguishing people with values close to the cut-off of 12 g/dL. Automated Hb values in the highest tertile were 12.15±0.89 g/dL (Fig 1A). In the case of red blood cell count, no difference is seen between any of the tertiles (Fig 1D).

Fig 2 shows the same red blood cell indices but according to automated Hb tertiles. Based on this measure, 104 participants were categorized on the lower tertile with aHb values ranging from 7–11.1 g/dL, 110 were categorized on the second tertile (11.2–12.1 g/dL) and the highest tertile was comprised by 92 participants (12.3–14.3 g/dL). Differences between the tertiles are more pronounced than when dividing the population in automated Hb tertiles. For instance, hematocrit, MCV and MCH had all significant difference between each group. RDW values were only different between the two lowest tertiles and between the lowest and the highest tertile. No difference was seen in RBC values (Fig 2).

In Table 2, we present the prevalence of anemia according to each method and the severity. Given our inclusion criteria, we did not recruit women with HemoCue values above 12 g/dl or below 8 g/dL. Therefore, these rates must be taken with caution.

Table 2. Prevalence and severity of anemia according to different methods.

	Capillary blood HemoCue 301	Venous blood Automated Analyzer
No anemia (> 12 g/dL)	--	41.47%
Mild anemia (11.-11.9 g/dL)	67.01%	30.77%
Moderate anemia (8–10.9 g/dL)	32.9%	26.76%
Severe anemia (< 8 g/dL)	--	1%

Open in a new tab

Iron status biomarkers were also assessed between tertiles as shown in Table 3. Ferritin is significantly different in all tertiles when using automated Hb to classify, but when HemoCue Hb values are used, there is no difference between the 2^nd and 3^rd tertiles. The same pattern is observed with serum iron. CRP levels are not significantly different in any classification.

Table 3. Iron status markers according to HemoCue and automated hemoglobin tertiles.

	HemoCue tertiles
Marker	I tertile (Hb 8–11.0)	II tertile (Hb 11.1–11.5)	III tertile (Hb 11.6–11.9)
Ferritin (ug/L)^a^, ^b^, ^c	20.53 (11.4–33.09)	32.57 (20.71–49.4)	29.51 (20.22–46.26)
Serum iron (ug/dL) ^c^, ^d^, ^e	49.55±33.95	62.88±32.59	72.08±31.73
CRP (mg/L) ^f	3.61±5.47	4.41±5.44	4.21±3.97
	Automated Hb tertiles
Marker	I tertile (Hb 7–11.1)	II tertile (Hb 11.2–12.1)	III tertile (Hb 12.3–14.3)
Ferritin (ug/L) ^g	18.73 (11.05–29.5)	25.62 (19.33–37.5)	43.3 (31.06–57.51)
Serum iron (ug/dL) ^g	38.63±27.23	62.21±27.69	84.21±31.60
CRP (mg/L) ^f	4.15±6.64	4.35±4.49	3.61±3.32

Open in a new tab

Values are mean ±SD. P values are from Tukey post hoc analysis ^a p = 0.002 I vs II tertile.

^b p = 0.008 I vs III

^c not significant II vs III tertile

^d p = 0.01 I vs II tertile

^e p<0.0001 I vs III tertile

^fnot significant between any groups

^g p<0.0001 between all groups. CRP: C-reactive protein.

In the whole sample, 182 women had venous blood—automated Hb values below 12 g/dL. However, out of this number, only 43 (23.63%) had also ferritin values under 15 ug/L. When excluding those with possible inflammation (n = 215, CRP> 5 mg/L), 129 women had anemia of which only 35 (27.13%) had also low ferritin values. On this group, 94 women (52.5%) with normal ferritin values are regarded as anemics.The degree of agreement between automated Hb values from venous blood samples and capillary blood HemoCue values is shown in a Bland Altman Plot (Fig 3). The bias between measurements is 0.36 ± 0.93 g/dL with the automated Hb yielding higher values. The 95% CI for the measurements was -1.47–2.19. The differences were normally distributed (Shapiro Wilk Z = 0.296, p = 0.3834).

Fig 3 — UL: Upper limit, LL: lower limit.

The ROC curve in Fig 4 shows the performance of both methods compared to ferritin measurements. We performed the analysis in the whole sample (Fig 4A) and excluding 90 subjects whose CRP values exceeded 5 mg/L. Automated Hb values are the ones showing better performance in the whole sample [AUC 0.82 (0.77–0.88) vs 0.71 (0.62–0.79), p<0.001] and in those with no suspected inflammation [AUC 0.83 (0.77–0.89) vs 0.70 (0.77–0.89), p<z0.001]. We calculated the best cut-off value for each measurement using the Youden Index. The cut-offs for each diagnostic test are provided in Table 4 alongside their specificity, sensitivity and predictive values. Using the Youden index, the optimal aHb cut-off is 10.8 which has a specificity of 0.711 and a sensitivity of 0.819, while the Hemocue reaches a specificity of 0.697 and a sensitivity of 0.688 with a cut-off of 11.1 g/dL. Positive and negative predictive values show that overall automated Hb with a cut-off of 10.8 g/dL accurately identifies 94% of patients that have low ferritin values. The cut-off values provided could be useful where no other means or confirmatory tests are available.

Table 4. Cut-off values for automated analyzer and Hemocue 301.

	Cut-off value (g/dL)	Sensitivity (95% CI)	Specificity (95% CI)	Positive predictive value (95% CI)	Negative Predictive Value (95% CI)
Venous Blood–Automated analyzer	10.8	0.82 (0.77–0.86)	0.71 (0.56–0.84)	0.94 (0.89–0.96)	0.41 (0.33–0.59)
Capillary blood Hemocue 301	11.1	0.69 (0.63–0.74)	0.67 (0.51–0.8)	0.92 (0.86–0.94)	0.27 (0.22–0.42)

Open in a new tab

Discussion

A right-based approach to health encompasses various characteristics, including accessibility, availability, quality, and equity. Ensuring that goods and services are of high quality and distributed equitably is essential, with no disparities based on geographic location or socio-economic status [22]. In this study we sought to determine whether anemia screening using the HemoCue 301 portable device was suitable in a high poverty area on the northern coast of Peru.

As we have seen, HemoCue 301 Hb values are significantly lower than those yielded by the automated method. The difference is of clinical relevance, 0.3 g/dL might determine if a woman is classified as anemic or not and misclassifying the severity of the condition.

HemoCue 301 is a screening device and it should be taken as such. Screening and diagnostic testing are two different procedures linked between each other. Screening is aimed at identifying those in high risk, and then, a diagnostic testing aims to provide a definite answer to whether or not the person has a given condition to start a treatment [19]. The analysis of other markers of IDA as CBC indices, ferritin, and serum iron allow us to see that using HemoCue 301 as a diagnostic device is not correct as it does not accurately classify subject with Hb values close to the threshold (12 g/dL). Women with ferritin values above 100 ug/L which generally excludes iron deficiency anemia [23] were regarded as anemics when using the POC device.

The cut-offs to define anemia have been a matter of debate since they were first proposed. Mainly because the basis of their original determination were statistics rather than health outcomes [24]. In a recent multi-country analysis, the pooled 5^th percentile of apparently healthy WRA was 10.81 (10.35–11.17) [25]. Furthermore, mild anemia in WRA (11–11.9 g/dL) was found not to be associated with small for gestational age in pregnant women in a systematic review [26]. The U-shaped association of hemoglobin values and adverse pregnancy outcomes has been established in several studies [27, 28] and a revision based on adverse outcomes has been suggested.

In our study, we find that 10.8 g/dL of venous blood samples analyzed with an automated hematological analyzer is the optimal cut-off value in terms of specificity, sensitivity and positive predictive value. Negative predictive value is around 40% which is acceptable for a screening test. Capillary blood Hemocue cut-off of 11.1 g/dL is a better predictor than the current cut-off of 12 g/dL and might be suitable in cases where measuring iron biomarkers is not possible.

Our results are in line with other studies. In Laotian children, Hemocue301 yielded lower Hb values than automated hematology analyzers [29]. The sensitivity found in this study for the HemoCue 301 is a little bit higher than that found in women in South Africa (0.72) [30] and Cameroon (0.62) [31]. As the authors of those papers state, it is a good performance for a screening device. Nevertheless, its use in Peru is not for the purpose of screening. These devices are used to quantify the total prevalence of anemia in the country; thus, inform public policies. Due to the high prevalence of anemia, preventive iron supplementation strategies are available in Peru [32, 33].

This approach would not signify further trouble if it were innocuous. Nevertheless, mounting evidence suggests it is not. Even mild iron overload is associated with an array of adverse outcomes including metabolic syndrome [34]. Furthermore, in deprived places where infections are endemic and sanitation is still an unmet need, iron supplementation might be counterproductive [35].

The benefits of the HemoCue cannot be denied. We support Sanchis-Gomar recommendations about when it is more needed. These circumstances include critical areas where a fast therapeutic decision is needed, or with patients in life-threatening conditions due to the low amount of blood needed as well as in natural disasters [36]. Our results suggest its use in population-based surveys is not appropriate.

Another argument used for the widespread deploy of HemoCue is the relative low-cost. Nevertheless, as far as we know, no proper health economic analysis has been performed to substantiate this claim. A CBC allows to screen for microcytosis, hypochromia and anisocytosis, which besides providing a better understanding as if the patient has IDA or not, is helpful to identify other possible causes of anemia such as inflammation. Knowing the underlying cause of the low Hb count is essential to provide the best treatment possible. According to global estimates, only half of the cases of anemia worldwide are due to IDA, while around a 40% are due to inflammation [37, 38]. The fact that accessibility to an automated analyzer is still a challenge in cities from an upper middle-income country such as Peru is a clear example of the inequities in health, which -we consider- is the main reason Peru has stagnated in its quest to diminish anemia prevalence.

This study has several limitations. The original sample size for the clinical trial was 351 participants. However, the prevalence of WRA with Hemocue readings below 12 g/dL was significantly below our expectations. The recruitment was stopped when over 300 women were recruited. However, the sample size gathered is sufficiently powered to detect statistically significant differences in iron status biomarkers. Also, due to nature of the condition and it being considered a major global health problem in Peru, we could not extract venous blood samples from women with Hemocue values below 8 g/dL. The prevalence of anemia and its severity must be interpreted in line of this recruitment considerations.

Furthermore, we compared capillary blood to venous blood which are not equivalent in terms of hemoglobin determination. Although some research has found the difference not to be clinically significative [39], it is important to see our results in light of the difference in sampling sites. Finally, even when a peripheral blood smear was performed on samples to identify features suggestive of hemoglobinopathies, this method cannot be used to definitively rule out thalassaemia or other haemoglobinopathies.

Our study shows that 52.2% of women with normal ferritin values are classified as anemics using HemoCue 301 in a coastal city in Peru. Our results urge for caution when using HemoCue 301 device to diagnose and treat IDA, mainly when cases of mild anemia are found. HemoCue 301 should only be used for screening. We call for the use of better methods to diagnose iron deficiency anemia in Peru, especially in areas where settings inherently represent a limitation to the correct functioning of these devices, such as extreme temperatures.

Acknowledgments

The authors would like to thank field workers at the Centro de Salud Global, that oversaw data collection in Tumbes. We also thank women who took part of the study.

Data Availability

Data is available at https://osf.io/4hrpx/.

Funding Statement

The study was funded by CONEVID, Universidad Peruana Cayetano Heredia. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

References

1.Daru J. Sustainable Development Goals for anaemia: 20 years later, where are we now? The Lancet Global Health. 2022;10: e586–e587. doi: 10.1016/S2214-109X(22)00127-9 [DOI] [PubMed] [Google Scholar]
2.Sinharoy SS, Fanzo J. Ethical and human rights considerations related to access to anemia diagnosis. Annals of the New York Academy of Sciences. 2019; nyas.14125. doi: 10.1111/nyas.14125 [DOI] [PubMed] [Google Scholar]
3.Instituto de Estadistica e Informática I. Encuesta Demográfica Y De Salud Familiar. In: 2019. 2018. [Google Scholar]
4.World Health Organization, WHO, World Health Organization. Haemoglobin concentrations for the diagnosis of anaemia and assessment of severity. WHO Geneva: World Health Organization;
5.Johnson-Wimbley TD, Graham DY. Diagnosis and management of iron deficiency anemia in the 21st century. Therapeutic Advances in Gastroenterology. 2011;4: 177–184. doi: 10.1177/1756283X11398736 [DOI] [PMC free article] [PubMed] [Google Scholar]
6.White KC. Anemia is a poor predictor of iron deficiency among toddlers in the United States: For heme the bell tolls. Pediatrics. Pediatrics; 2005. pp. 315–320. doi: 10.1542/peds.2004-1488 [DOI] [PubMed] [Google Scholar]
7.Gonzales GF, Rubín de Celis V, Begazo J, Del Rosario Hinojosa M, Yucra S, Zevallos-Concha A, et al. Correcting the cut-off point of hemoglobin at high altitude favors misclassification of anemia, erythrocytosis and excessive erythrocytosis. American journal of hematology. 2018;93: E12–E16. doi: 10.1002/ajh.24932 [DOI] [PMC free article] [PubMed] [Google Scholar]
8.Choque‐Quispe BM, Alarcón‐Yaquetto DE, Paredes‐Ugarte W, Zaira A, Ochoa A, Gonzales GF. Is the prevalence of anemia in children living at high altitudes real? An observational study in Peru. Annals of the New York Academy of Sciences. 2020; nyas.14356. doi: 10.1111/nyas.14356 [DOI] [PubMed] [Google Scholar]
9.World Health Organization (WHO). Assessing the iron status of populations: including literature reviews. 2007. [Google Scholar]
10.Instituto de Estadistica e Informática I. Metodología de la medición de la anemia. Encuesta Demográfica y de Salud Familiar. 2018. [Google Scholar]
11.HemoCue AB. HemoCue Hb 301 Microcuvettes—Product insert. Angelholm, Sweden; 2022. [Google Scholar]
12.Morris LD, Osei-Bimpong A, McKeown D, Roper D, Lewis SM. Evaluation of the utility of the HemoCue 301 haemoglobinometer for blood donor screening. Vox Sanguinis. 2007;93: 64–69. doi: 10.1111/j.1423-0410.2007.00919.x [DOI] [PubMed] [Google Scholar]
13.Ehrmeyer S. The New Poor Lab’s Guide To The Regulations (CLIA, The Joint Commission, CAP & COLA). 2021. [Google Scholar]
14.Rappaport AI, Karakochuk CD, Whitfield KC, Kheang KM, Green TJ. A method comparison study between two hemoglobinometer models (Hemocue Hb 301 and Hb 201+) to measure hemoglobin concentrations and estimate anemia prevalence among women in Preah Vihear, Cambodia. International Journal of Laboratory Hematology. 2017;39: 95–100. doi: 10.1111/ijlh.12583 [DOI] [PubMed] [Google Scholar]
15.Yadav K, Kant S, Ramaswamy G, Ahamed F, Jacob OM, Vyas H, et al. Validation of Point of Care Hemoglobin Estimation Among Pregnant Women Using Digital Hemoglobinometers (HemoCue 301 and HemoCue 201+) as Compared with Auto-Analyzer. Indian Journal of Hematology and Blood Transfusion. 2020;36: 342–348. doi: 10.1007/s12288-019-01196-5 [DOI] [PMC free article] [PubMed] [Google Scholar]
16.Instituto de Estadistica e Informática. Encuesta Demográfica y de Salud Familiar-ENDES 2014 Informe Principal. Tumbes. 2015. [Google Scholar]
17.International Society for Laboatory Hematology. Suggested Criteria for Action Following Automated CBC and WBC Differential Analysis. Available at: http://www.islh.org/web/consensus_rules.php [PubMed] [Google Scholar]
18.World Health Organization (WHO). WHO Guideline on use of Ferritin concentrations to assess iron status in individuals and populations. Geneva; 2020. [PubMed] [Google Scholar]
19.Karun KM, Puranik A. BA.plot: An R function for Bland-Altman analysis. Clinical Epidemiology and Global Health. 2021;12: 100831. doi: 10.1016/j.cegh.2021.100831 [DOI] [Google Scholar]
20.Robin X, Turck N, Hainard A, Tiberti N, Lisacek F, Sanchez J-C, et al. pROC: an open-source package for R and S+ to analyze and compare ROC curves. BMC Bioinformatics. 2011;12: 77. doi: 10.1186/1471-2105-12-77 [DOI] [PMC free article] [PubMed] [Google Scholar]
21.Parkin PC, Borkhoff CM. Practical tips for paediatricians: Assessment and management of young children with iron deficiency. Paediatrics & Child Health. 2018;23: 433–434. doi: 10.1093/pch/pxy045 [DOI] [PMC free article] [PubMed] [Google Scholar]
22.World Health Organization (WHO). Health and Human Rights. 2022. Available: https://www.who.int/en/news-room/fact-sheets/detail/human-rights-and-health [Google Scholar]
23.Galloway MJ, Smellie WSA. Investigating iron status in microcytic anaemia. BMJ. 2006;333: 791–793. doi: 10.1136/bmj.38979.358032.BE [DOI] [PMC free article] [PubMed] [Google Scholar]
24.WHO. Nutritional Anaemias: Report of a WHO Scientific Group. Geneva; 1968. [PubMed] [Google Scholar]
25.Addo OY, Yu EX, Williams AM, Young MF, Sharma AJ, Mei Z, et al. Evaluation of Hemoglobin Cutoff Levels to Define Anemia Among Healthy Individuals. JAMA Network Open. 2021;4: e2119123. doi: 10.1001/jamanetworkopen.2021.19123 [DOI] [PMC free article] [PubMed] [Google Scholar]
26.Kozuki N, Lee AC, Katz J. Moderate to Severe, but Not Mild, Maternal Anemia Is Associated with Increased Risk of Small-for-Gestational-Age Outcomes. Journal of Nutrition. 2012;142: 358–362. doi: 10.3945/jn.111.149237 [DOI] [PubMed] [Google Scholar]
27.Gonzales GF, Tapia V, Gasco M, Carrillo CE. Maternal hemoglobin concentration and adverse pregnancy outcomes at low and moderate altitudes in Peru. The Journal of Maternal-Fetal & Neonatal Medicine. 2012;25: 1105–1110. doi: 10.3109/14767058.2011.623200 [DOI] [PubMed] [Google Scholar]
28.Dewey KG, Oaks BM. U-shaped curve for risk associated with maternal hemoglobin, iron status, or iron supplementation. The American Journal of Clinical Nutrition. 2017;106: 1694S–1702S. doi: 10.3945/ajcn.117.156075 [DOI] [PMC free article] [PubMed] [Google Scholar]
29.Hinnouho G-M, Barffour MA, Wessells KR, Brown KH, Kounnavong S, Chanhthavong B, et al. Comparison of haemoglobin assessments by HemoCue and two automated haematology analysers in young Laotian children. Journal of Clinical Pathology. 2018;71: 532–538. doi: 10.1136/jclinpath-2017-204786 [DOI] [PMC free article] [PubMed] [Google Scholar]
30.Jaggernath M, Naicker R, Madurai S, Brockman MA, Ndung’u T, Gelderblom HC. Diagnostic Accuracy of the HemoCue Hb 301, STAT-Site MHgb and URIT-12 Point-of-Care Hemoglobin Meters in a Central Laboratory and a Community Based Clinic in Durban, South Africa. Szecsi PB, editor. PLOS ONE. 2016;11: e0152184. doi: 10.1371/journal.pone.0152184 [DOI] [PMC free article] [PubMed] [Google Scholar]
31.Tayou Tagny C, Kouam L, Mbanya D. [The new HemoCue system Hb 301 for the haemoglobin measurement in pregnant women]. Annales de biologie clinique. 2008;66: 90–4. doi: 10.1684/abc.2008.0195 [DOI] [PubMed] [Google Scholar]
32.Ministerio de Salud. Resolución Ministerial Nro. 069-2016/MINSA. Directiva sanitaria para el control y prevención de la anemia por deficiencia de hierro en gestantes y puérperas. El Peruano—Normas legales. 2016;577444. [Google Scholar]
33.Ministerio de Salud. Resolución Ministerial N° 706-2014-MINSA. Directiva sanitaria que establece la suplementación con multimicronutrientes y hierro para la prevención de anemia en niñas y niños menores de 36 meses. 2014. [Google Scholar]
34.Makker J, Hanif A, Bajantri B, Chilimuri S. Dysmetabolic Hyperferritinemia: All Iron Overload Is Not Hemochromatosis. Case Reports in Gastroenterology. 2015;9: 7–14. doi: 10.1159/000373883 [DOI] [PMC free article] [PubMed] [Google Scholar]
35.Fowkes FJI, Davidson E, Agius PA, Beeson JG. Understanding the interactions between iron supplementation, infectious disease and adverse birth outcomes is essential to guide public health recommendations. BMC Medicine. 2019;17: 153. doi: 10.1186/s12916-019-1376-8 [DOI] [PMC free article] [PubMed] [Google Scholar]
36.Sanchis-Gomar F, Cortell-Ballester J, Pareja-Galeano H, Banfi G, Lippi G. Hemoglobin Point-of-Care Testing: The HemoCue System. SLAS Technology. 2013;18: 198–205. doi: 10.1177/2211068212457560 [DOI] [PubMed] [Google Scholar]
37.Weiss G, Ganz T, Goodnough LT. Anemia of inflammation. Blood. 2019;133: 40–50. doi: 10.1182/blood-2018-06-856500 [DOI] [PMC free article] [PubMed] [Google Scholar]
38.Kassebaum NJ. The Global Burden of Anemia. Hematology/Oncology Clinics of North America. 2016;30: 247–308. doi: 10.1016/j.hoc.2015.11.002 [DOI] [PubMed] [Google Scholar]
39.Patel AJ, Wesley R, Leitman SF, Bryant BJ. Capillary versus venous haemoglobin determination in the assessment of healthy blood donors. Vox Sang. 2013. May;104(4):317–23. doi: 10.1111/vox.12006 Epub 2013 Jan 7. ; PMCID: PMC3633672. [DOI] [PMC free article] [PubMed] [Google Scholar]

PLoS One. doi: 10.1371/journal.pone.0293984.r001

Decision Letter 0

Benedikt Ley

14 Aug 2023

PONE-D-23-21513Accuracy of the Portable Hemoglobin Analyzer HemoCue301 in Women of Reproductive Age in a Deprived Region of Northern Peru: An On-Field StudyPLOS ONE

Dear Dr. Alarcón-Yaquetto,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

Please submit your revised manuscript by Sep 28 2023 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at plosone@plos.org. When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.

Please include the following items when submitting your revised manuscript:

A rebuttal letter that responds to each point raised by the academic editor and reviewer(s). You should upload this letter as a separate file labeled 'Response to Reviewers'.
A marked-up copy of your manuscript that highlights changes made to the original version. You should upload this as a separate file labeled 'Revised Manuscript with Track Changes'.
An unmarked version of your revised paper without tracked changes. You should upload this as a separate file labeled 'Manuscript'.

If you would like to make changes to your financial disclosure, please include your updated statement in your cover letter. Guidelines for resubmitting your figure files are available below the reviewer comments at the end of this letter.

If applicable, we recommend that you deposit your laboratory protocols in protocols.io to enhance the reproducibility of your results. Protocols.io assigns your protocol its own identifier (DOI) so that it can be cited independently in the future. For instructions see: https://journals.plos.org/plosone/s/submission-guidelines#loc-laboratory-protocols. Additionally, PLOS ONE offers an option for publishing peer-reviewed Lab Protocol articles, which describe protocols hosted on protocols.io. Read more information on sharing protocols at https://plos.org/protocols?utm_medium=editorial-email&utm_source=authorletters&utm_campaign=protocols.

We look forward to receiving your revised manuscript.

Kind regards,

Benedikt Ley, PhD

Academic Editor

PLOS ONE

Journal Requirements:

When submitting your revision, we need you to address these additional requirements.

1. Please ensure that your manuscript meets PLOS ONE's style requirements, including those for file naming. The PLOS ONE style templates can be found at

https://journals.plos.org/plosone/s/file?id=wjVg/PLOSOne_formatting_sample_main_body.pdf and

https://journals.plos.org/plosone/s/file?id=ba62/PLOSOne_formatting_sample_title_authors_affiliations.pdf

2. We note that you have stated that you will provide repository information for your data at acceptance. Should your manuscript be accepted for publication, we will hold it until you provide the relevant accession numbers or DOIs necessary to access your data. If you wish to make changes to your Data Availability statement, please describe these changes in your cover letter and we will update your Data Availability statement to reflect the information you provide.

3. Please include captions for your Supporting Information files at the end of your manuscript, and update any in-text citations to match accordingly. Please see our Supporting Information guidelines for more information: http://journals.plos.org/plosone/s/supporting-information.

[Note: HTML markup is below. Please do not edit.]

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #1: Partly

Reviewer #2: Yes

**********

2. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: No

Reviewer #2: Yes

**********

3. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #1: Yes

Reviewer #2: Yes

**********

4. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #1: Yes

Reviewer #2: Yes

**********

5. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: REVIEWER REPORT FOR MANUSCRIPT PONE-D-23-21513

General comment

Alarcón-Yaquetto et al have attempted to add data to the venous vrs capillary haemoglobin comparison study viz-a-viz different devices/instrument conundrum. However, the authors have not clearly defined basic concepts well to enable the reader to properly situate the findings. For example, the title is a bit misleading considering the study design employed. In line 86 – 88 (page 5), the authors write that “Briefly, 301 cuvettes were filled with a drop of blood from the middle finger fingertip. The first 2 drops of blood were discarded. The microcuvette was put in the cuvette holder and a measurement was done immediately”. In line 90 – 91 (page 5), the authors write that “Upon recruitment, a trained phlebotomist took venous samples of each woman with the BD vacutainer system”. The laboratory samples were venous blood samples. Therefore, the study compared venous haemoglobin (from automated analyser) to capillary haemoglobin (Haemocue 301). it is a known fact that venous haemoglobin and capillary haemoglobin are not equivalent (https://www.mdpi.com/2075-4418/12/12/3191; 10.1371/journal.pone.0278350). The title of the study is thus misleading and should be modified to reflect exactly what was done. Again, the distinction between iron deficiency anaemia and anaemia has not been made; the authors give the impression that the two terms are synonymous. However, that is not a scientific fact. This has confounded the write up and the data analyses as well as its interpretation. The manuscript should thus be revised holistically to address these.

Abstract

1. The abstract has been written on the basis of the assumptions that were used to analyse the data. As suggested above and below, the abstract need a re-work after taking the suggested revisions into consideration.

2. In the objective statement, indicate that the sampling site was different for the Haemocue and the automated haematology analyser.

Introduction

1. Line 40 – 41, authors seem to portray IDA as being equivalent to anaemia by the statement that “Peru is one of the countries where IDA is a severe public health problem as shown by national statistics.”

2. Line 56 – 57, authors write “Handheld devices have been routinely used to screen for IDA in LMIC countries such as the HemoCue system” to imply that Hemocue is a device for undertaking iron studies. This is misleading since the device estimates haemoglobin levels which is different from ferritin, iron, TIBC etc.

3. Authors again write that “The main objective of this study is to assess the suitability and accuracy of this device as a method for IDA diagnosis in women of reproductive age in a coastal city with resource constraints” Hemocue is not meant for iron studies.

Exclusion criteria

1. When authors write “Exclusion criterion was amenorrhea non explained by pregnancy and heavy smoking” does this mean that both conditions should be present before exclusion?

Statistical analyses

1. Authors defined Microcytosis using the CBC reported mean corpuscular values (MCV) < 80 fl.,

2. and hypochromia by mean corpuscular hemoglobin (MCH) values below 27. There are many causes of microcytic-hypochromic red blood cell picture. With the emphasis the authors are placing on iron deficiency anaemia, the authors should have at least undertaken peripheral blood morphology evaluation to assess whether there were unique red cell presentations such as pencil-shaped cells. This was not done.

3. Authors should clearly differentiate iron deficiency (ferritin less than 15 ng/dl) from iron deficiency anaemia (ferritin less than 15 ng/dl + Hb below threshold). This distinction has not been made. Since the authors make the erroneous assumption that IDA is equivalent to anaemia, it is not clear what the ROC analyses sought to predict.

4. Moreover, authors write that “Due to being an acute phase protein, ferritin is sensitive to inflammation. Values above 120 ug/L were excluded from the analysis.” The CRP cut-off of (5 mg/l) should be used to screen all the data but not only participants with ferritin levels >120 mcg/L. It is even possible that some with ferritin levels >120 mcg/L had haemochromatosis instead of inflammation-induced increased ferritin levels. Therefore, the assumption of excluding data only based on the ferritin levels >120 mcg/L is erroneous and should be corrected.

Results

1. The authors write that “123 women (40.2%) had ferritin values 125 above 15 g/dL using the automated analyzer”. What does this represent? ID or anaemia? The two are not equivalent and must be acknowledged as such. The haematotology anaelyser is not used to estimate ferritin.

2. Again, in line 125 – 127, the authors write “Iron deficiency anemia is characterized by microcytic and hypochromic red blood cells. Out of the sample, 53.95% had microcytosis while hypochromia based on MCH was found in 37.5%.” This is a faulty assumption that only iron deficiency causes hypochromic-microcytic picture. Please revise to correct this.

3. Figures 1 and 2 appear the same; can the authors clarifies the differences? All the figures in panel 1 are the same as that in panel 2.

4. Table 1, 2 and 3, as well as figure 1 should be re-labelled taking into consideration that the sampling sites were different i.e. capillary (Haemocue) vs venous (automated analyser). This different sampling sites definitely leads to differences in the values recorded.

5. The axis labelling on the figure 3 suggest that Haemocue Hb – aHb = 0.36; however, the authors write in line 170 – 171 that “The bias between measurements is 0.36 ± 0.93 g/dL with the automated Hb yielding higher values”. If the data actually represents what the authors have stated, then the y-axis labelling should be revised.

6. In line 175 – 180, what precisely is the ROC analyses seeking to achieve?

DISCUSSION

1. I am unable to objectively assess the discussion since the faulty assumptions used for the data analyses has been carried into the data interpretation.

2. For example, in line 193 – 194, the authors write “classifying those with Hb values close to the threshold (12 g/dL). Women with ferritin values above 100 ug/L which generally excludes iron deficiency anemia [24] were regarded as anemics when using the POC device.” And based this on the Haemocue Hb estimation.

Reviewer #2: Comments

Study Title: “Accuracy of the portable Hemoglobin Analyzer HemoCue301 in Women of Reproductive Age in a Deprived Region of Northern Peru: An On-Field study”

Summary/observation

The study is very significant as it addresses an important issue in public health. The study aimed to assess the suitability and accuracy of a portable device called HemoCue301 which is used to classify anemia. While the study appreciates the use of HemoCue301, it advised that, the used of the device for the classification of iron deficiency anemia (IDA) should be done with caution.

Introduction

1. Authors should kindly take note and proofread the writing. Example, authors may take a second look at line 56 and 57 of page 3

Method

2. No justification was provided for the exclusion of heavy smokers from the study, line 82 page 5.

3. How were the blood samples transported to the laboratory where automated analyzer was used? Line 90 to 96 of page 5

4. Quality control issues were not indicated

**********

6. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

If you choose “no”, your identity will remain anonymous but your review may still be made public.

Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #1: Yes: Patrick Adu

Reviewer #2: Yes: David Larbi Simpong

**********

[NOTE: If reviewer comments were submitted as an attachment file, they will be attached to this email and accessible via the submission site. Please log into your account, locate the manuscript record, and check for the action link "View Attachments". If this link does not appear, there are no attachment files.]

While revising your submission, please upload your figure files to the Preflight Analysis and Conversion Engine (PACE) digital diagnostic tool, https://pacev2.apexcovantage.com/. PACE helps ensure that figures meet PLOS requirements. To use PACE, you must first register as a user. Registration is free. Then, login and navigate to the UPLOAD tab, where you will find detailed instructions on how to use the tool. If you encounter any issues or have any questions when using PACE, please email PLOS at figures@plos.org. Please note that Supporting Information files do not need this step.

Attachment

Submitted filename: PONE-D-23-21513 REVIEWER REPORT.docx

Click here for additional data file.^{(17.8KB, docx)}

Attachment

Submitted filename: COMMENTS 2.pdf

Click here for additional data file.^{(100.6KB, pdf)}

PLoS One. 2023 Nov 14;18(11):e0293984. doi: 10.1371/journal.pone.0293984.r002

Author response to Decision Letter 0

28 Sep 2023

Thank you for your time and suggestions.

Below we provide a detailed answer to the concerns raised.

Answer to reviewers

Reviewer 1

General comment

Alarcón-Yaquetto et al have attempted to add data to the venous vrs capillary haemoglobin

comparison study viz-a-viz different devices/instrument conundrum. However, the authors have

not clearly defined basic concepts well to enable the reader to properly situate the findings. For

example, the title is a bit misleading considering the study design employed. In line 86 – 88

(page 5), the authors write that “Briefly, 301 cuvettes were filled with a drop of blood from the

middle finger fingertip. The first 2 drops of blood were discarded. The microcuvette was put in

the cuvette holder and a measurement was done immediately”. In line 90 – 91 (page 5), the

authors write that “Upon recruitment, a trained phlebotomist took venous samples of each

woman with the BD vacutainer system”. The laboratory samples were venous blood samples.

Therefore, the study compared venous haemoglobin (from automated analyser) to capillary

haemoglobin (Hemocue 301). it is a known fact that venous haemoglobin and capillary

haemoglobin are not equivalent (https://www.mdpi.com/2075-4418/12/12/3191;

10.1371/journal.pone.0278350). The title of the study is thus misleading and should be modified

to reflect exactly what was done. Again, the distinction between iron deficiency anaemia and

anaemia has not been made; the authors give the impression that the two terms are synonymous.

However, that is not a scientific fact. This has confounded the write up and the data analyses as

well as its interpretation. The manuscript should thus be revised holistically to address these.

Answer: Thank you for your comments. We have modified the title and we agree, one of the biggest problems in Peru is the generalisation of anaemia as IDA, we made changes throughout the document to reflect the distinction between anaemia and IDA.

Abstract

1. The abstract has been written on the basis of the assumptions that were used to analyse

the data. As suggested above and below, the abstract need a re-work after taking the

suggested revisions into consideration.

Answer: The abstract has been modified accordingly.

2. In the objective statement, indicate that the sampling site was different for the Haemocue

and the automated haematology analyser.

Answer: We apologise for the confusion. The sampling site was the same. Once a participant fitted eligibility criteria and had a fingerstick haemoglobin reading between 8 and 12 g/dL, a venous sample was taken from her at the same site. We transported the samples to the laboratory where further tests were analysed. We clarified this on the manuscript.

Introduction

1. Line 40 – 41, authors seem to portray IDA as being equivalent to anaemia by the

statement that “Peru is one of the countries where IDA is a severe public health problem

as shown by national statistics.”

Answer: We have rephrased the paragraph. This is how anaemia is treated in Peru. Even when only point of care devices such as the hemocue are used to diagnose the condition, iron supplementation is given. Confirmatory tests are hardly ever offered to patients living at remote areas.

2. Line 56 – 57, authors write “Handheld devices have been routinely used to screen for

IDA in LMIC countries such as the HemoCue system” to imply that Hemocue is a device

for undertaking iron studies. This is misleading since the device estimates haemoglobin

levels which is different from ferritin, iron, TIBC etc.

Answer: We have changed IDA for anaemia.

3. Authors again write that “The main objective of this study is to assess the suitability and

accuracy of this device as a method for IDA diagnosis in women of reproductive age in a

coastal city with resource constraints” Hemocue is not meant for iron studies.

Answer: We have changed IDA for anaemia and emphasise than even when hemocue is not meant for iron studies, it is used as such in Peru as it is the main device used in nation wide field studies to get national rates of anemia which in turn drive health policies.

Exclusion criteria

1. When authors write “Exclusion criterion was amenorrhea non explained by pregnancy

and heavy smoking” does this mean that both conditions should be present before

exclusion?

Answer: No. Both were different criteria to exclude. We have rephrased the paragraph.

Statistical analyses

1. Authors defined Microcytosis using the CBC reported mean corpuscular values (MCV) <

80 fl.,. and hypochromia by mean corpuscular hemoglobin (MCH) values below 27. There are

many causes of microcytic-hypochromic red blood cell picture. With the emphasis the

authors are placing on iron deficiency anaemia, the authors should have at least

undertaken peripheral blood morphology evaluation to assess whether there were unique

red cell presentations such as pencil-shaped cells. This was not done.

Answer: The CBC analyses followed the ISLH´s guidelines. Briefly, slide review was performed in to assess morphological changes of the red blood cell. No thalassemia nor other type of hemoglobinopathies were found. Historically, prevalence of these type of genetic disorders is very low in Peru. We took measures to exclude subjects with underlying conditions and excluded subjects with inflammation according to proxies. We have updated information in the manuscript to reflect this information.

3. Authors should clearly differentiate iron deficiency (ferritin less than 15 ng/dl) from iron

deficiency anaemia (ferritin less than 15 ng/dl + Hb below threshold). This distinction has

not been made. Since the authors make the erroneous assumption that IDA is equivalent

to anaemia, it is not clear what the ROC analyses sought to predict.

Answer: Thank you for your suggestion. We have rephrased the methods section accordingly.

4. Moreover, authors write that “Due to being an acute phase protein, ferritin is sensitive to

inflammation. Values above 120 ug/L were excluded from the analysis.” The CRP cut-off

of (5 mg/l) should be used to screen all the data but not only participants with ferritin

levels >120 mcg/L. It is even possible that some with ferritin levels >120 mcg/L had

haemochromatosis instead of inflammation-induced increased ferritin levels. Therefore,

the assumption of excluding data only based on the ferritin levels >120 mcg/L is

erroneous and should be corrected.

Answer: We have now included sensitivity analysis using CRP value of 5 mg/L as suggested.

Results

1. The authors write that “123 women (40.2%) had ferritin values 125 above 15 g/dL using

the automated analyzer”. What does this represent? ID or anaemia? The two are not

equivalent and must be acknowledged as such. The haematotology anaelyser is not used

to estimate ferritin.

Answer: Thank you for noticing the mistake. 123 women had automated hemoglobin values above 12 g/dL. We meant to provide how this number compared to low ferritin values. We have updated the paragraph and now provide correct percentages.

2. Again, in line 125 – 127, the authors write “Iron deficiency anemia is characterized by

microcytic and hypochromic red blood cells. Out of the sample, 53.95% had microcytosis

while hypochromia based on MCH was found in 37.5%.” This is a faulty assumption that

only iron deficiency causes hypochromic-microcytic picture. Please revise to correct this.

Answer: While its true that iron deficiency is not the sole cause of hypochromic and microcytic red blood cells, the other causes are not prevalent in Peru. As we have updated in the methods section, thalassemia was checked as per ISLH guidelines. We have rephrased the paragraph and added in the discussion a sentence noting that iron deficiency is not the sole cause of hypochromic and microcytic RBCs.

3. Figures 1 and 2 appear the same; can the authors clarifies the differences? All the figures

in panel 1 are the same as that in panel 2.

Answer: The figures have been updated.

4. Table 1, 2 and 3, as well as figure 1 should be re-labelled taking into consideration that

the sampling sites were different i.e. capillary (Haemocue) vs venous (automated

analyser). This different sampling sites definitely leads to differences in the values

recorded.

Answer: We have updated the labelling as suggested.

5. The axis labelling on the figure 3 suggest that Haemocue Hb – aHb = 0.36; however, the

authors write in line 170 – 171 that “The bias between measurements is 0.36 ± 0.93 g/dL

with the automated Hb yielding higher values”. If the data actually represents what the

authors have stated, then the y-axis labelling should be revised.

Answer: Thank you. We have corrected the y-axis label.

6. In line 175 – 180, what precisely is the ROC analyses seeking to achieve?

Answer We sought to analyse the accuracy of both methods in identifying a woman with ferritin values below 15 ng/dL. While the Hemocue is not meant for iron studies, that is the way it is used in Peru. This ROC analysis shows that the way the Peruvian government is tackling anemia by providing universal iron supplementation is an oversimplification of the condition. We run this analysis in the whole sample and in the sample excluding those with CRP values above 5 mg/l as suggested.

DISCUSSION

1. I am unable to objectively assess the discussion since the faulty assumptions used for the

data analyses has been carried into the data interpretation. For example, in line 193 – 194, the authors write “classifying those with Hb values close

to the threshold (12 g/dL). Women with ferritin values above 100 ug/L which generally

excludes iron deficiency anemia [24] were regarded as anemics when using the POC

device.” And based this on the Haemocue Hb estimation.

Answer: We have clarified the paragraph in the sense of noting Hemocue is a screening device and is not meant for iron deficiency diagnosis. However, that is the way it is being used in Peru.

Reviewer 2

Summary/observation

Answer: Thank you for your comments.

Introduction

1. Authors should kindly take note and proofread the writing. Example, authors may take a second

look at line 56 and 57 of page 3

Answer: The mentioned paragraph has been edited for clarity.

Method

2. No justification was provided for the exclusion of heavy smokers from the study, line 82 page 5.

Answer: Smoking is associated with decreased hemoglobin levels although the exact physiological mechanism is not fully understood. It might be due to the compound effect of inflammation, oxidative stress and the alteration of the antithrombotic system (Malenica et al 2017). The WHO has different cut-off values to define anemia in smokers. We have updated the information in the methods section.

Malenica M, Prnjavorac B, Bego T, Dujic T, Semiz S, Skrbo S, Gusic A, Hadzic A, Causevic A. Effect of Cigarette Smoking on Haematological Parameters in Healthy Population. Med Arch. 2017 Apr;71(2):132-136. doi: 10.5455/medarh.2017.71.132-136.

3. How were the blood samples transported to the laboratory where automated analyzer was

used? Line 90 to 96 of page 5

Answer: We have detailed how samples were transported.

4. Quality control issues were not indcated

Answer: We updated the information.

Attachment

Submitted filename: Answer to reviewers_1.docx

Click here for additional data file.^{(21KB, docx)}

PLoS One. doi: 10.1371/journal.pone.0293984.r003

Decision Letter 1

Benedikt Ley

19 Oct 2023

PONE-D-23-21513R1Accuracy of HemoCue301 Portable Hemoglobin Analyzer for Anemia Screening in Capillary Blood from Women of Reproductive age in a Deprived Region of Northern Peru: An On-Field StudyPLOS ONE

Dear Dr. Alarcón-Yaquetto,

Reviewer has made some very good additional points and I kindly ask the authors to address all of them. Please submit your revised manuscript by Dec 03 2023 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at plosone@plos.org. When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.

Please include the following items when submitting your revised manuscript:

A rebuttal letter that responds to each point raised by the academic editor and reviewer(s). You should upload this letter as a separate file labeled 'Response to Reviewers'.
A marked-up copy of your manuscript that highlights changes made to the original version. You should upload this as a separate file labeled 'Revised Manuscript with Track Changes'.
An unmarked version of your revised paper without tracked changes. You should upload this as a separate file labeled 'Manuscript'.

We look forward to receiving your revised manuscript.

Kind regards,

Benedikt Ley, PhD

Academic Editor

PLOS ONE

Journal Requirements:

Please review your reference list to ensure that it is complete and correct. If you have cited papers that have been retracted, please include the rationale for doing so in the manuscript text, or remove these references and replace them with relevant current references. Any changes to the reference list should be mentioned in the rebuttal letter that accompanies your revised manuscript. If you need to cite a retracted article, indicate the article’s retracted status in the References list and also include a citation and full reference for the retraction notice.

[Note: HTML markup is below. Please do not edit.]

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation.

Reviewer #1: (No Response)

Reviewer #2: All comments have been addressed

**********

2. Is the manuscript technically sound, and do the data support the conclusions?

Reviewer #1: Partly

Reviewer #2: Yes

**********

3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: Yes

Reviewer #2: Yes

**********

4. Have the authors made all data underlying the findings in their manuscript fully available?

Reviewer #1: Yes

Reviewer #2: Yes

**********

5. Is the manuscript presented in an intelligible fashion and written in standard English?

Reviewer #1: No

Reviewer #2: Yes

**********

6. Review Comments to the Author

Reviewer #1: Summary

The authors have made attempt to address the issues that were raised in the initial review process. While the effort is commended, there are still some issues that the authors need to address to make the manuscript technically sound. Authors still make it look like IDA is equivalent to anaemia. While this might be an accepted misconception in Peru (as the authors claim), the manuscript is written for the global audience and should therefore be approached as such. Additionally, the study design was such that fingertip blood (capillary blood) was used for the Hemocue Hb estimation; venous blood was used for the automated analyser Hb estimation. This should be consistently maintained throughout the manuscript to provide context for the data interpretation since the two blood samples are not equivalent.

ABSTRACT

Methods: in the sentence (line 22) “Adult women with HemoCue 301 readings below 12 g/dL were recruited”, authors should indicate that this was capillary blood.

In line 26 (Results), authors should specify that capillary blood was used for Hemocue Hb in the sentence “The Hemocue 301 has a bias of 0.36 ± 0.93 g/dL respect to the automated Hb.”

INTRODUCTION

Paragraph 2 of the introduction, authors correctly use the public health significance of anaemia in their classification (41 – 43). However, in paragraph 3 (line 44 – 45), the authors introduce a dimension that the severe anaemia challenge (prevalence of 40% in Peru) is questionable on the supposition that haemoglobin measurement is only a proxy for IDA. IDA classification is based on iron parameter estimates but not solely on haemoglobin measurement. Authors should decouple these in the write up.

The reference 9 cited in the statement “Furthermore, automated hematology analyzers —the method suggested by the WHO [9]” line 54 is not a WHO policy document; please correct this.

METHODS

under the inclusion criteria, authors should specify in line 80 – 81 that the Hemocue Hb was estimated from capillary blood.

Under laboratory analyses (line 95), authors should specify that CBC was undertaken using venous blood.

In line 96, the reference 18 as stated by the authors in the main reference list is not an ISLH guideline; please rectify this.

Under laboratory analyses (line 96 – 97), authors seem to make an erroneous claim that peripheral blood evaluation alone can be used rule out thalassaemia or other types of haemoglobinopathies. This is haematologically inaccurate. Thalassaemia trait could be silent and may present with few target cells only in peripheral smear. These same target cells are present in iron deficiency, haemoglobin C disease etc. authors should correct this as a peripheral blood morphology evaluation cannot be used to definitively rule out thalassaemia or other haemoglobinopathies.

Statistical analyses

In line 118 – 119, authors are not clear as to what the ROC sought to determine. The accuracy in detecting what exactly? is this ferritin <15? From the manuscript as a whole, one get the impression that the ROC was undertaken to provide a cut-off for Hemocue Hb or analyser Hb that could predict higher likelihood of IDA. If this is what was the target, the authors need to set out all the assumptions made under the statistical analyses.

RESULTS

In line 141, in writing “We further classified participants based on tertiles of both HemoCue 301 and automated Hb”, authors should specify that capillary blood was used for Hemocue Hb vs venous blood for analyser Hb.

In table 2, authors should include in the caption capillary blood (Hemocue Hb) and venous blood (analyser Hb).

In line 183, specify the venous vs capillary blood in the sentence

In line 189 – 196, the ROC & AUC should have a cut-off to guide clinical utility. In addition, there should be other parameters like PPV, NPV, sensitivity and specificity. These are better captured in a separate Table to inform the reader of the reliability of the estimates.

DISCUSSION

The discussion is silent on perhaps the key highlight of the study; the ROC and AUC data which sought to establish a cut-off for Hemocue Hb and analyser Hb that could be used as a surrogate means of diagnosing iDA in a resource poor setting. The rational for undertaking AUC and cut-off for analytes particularly in poor settings is to provide clinicians with surrogate estimates that provide high degree of suspicion so that treatment could be prescribed even in the absence of specific biochemical tests for diagnosing IDA. However, this important diagnostic dimension of the data is not explored in the discussion which leaves an obvious question as to why the authors employed the ROC in the first place.

Additionally, authors should not be silent on the fact that there are two dimensions on the results; 1) differences in methods [Hemocue vs automated analyser] and 2) different sampling sites of blood [capillary blood for Hemocue Hb vs venous blood for analyser Hb]. These two dimensions should be kept in focus as each affect the results. Should another lab repeat this study by maintain the two measurement techniques (Hemocue vs analyser) but use the same source of blood, the results will not be directly comparable to this study. Thus, it is important that authors stress these in the discussion.

MINOR

Line 95 “blood count (CBC) was performed withing two hours of the sample obtention” please correct “withing” and “obstention” and these do not exist.

Line 238 the deploy in “Another argument used for the widespread deploy of HemoCue” to deployment.

Reviewer #2: Authors have adequately addressed all comments raised in the previous round of review and that this manuscript is now acceptable for publication

**********

7. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

If you choose “no”, your identity will remain anonymous but your review may still be made public.

Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #1: Yes: Dr Patrick Adu

Reviewer #2: Yes: David Larbi Simpong

**********

Attachment

Submitted filename: Reviewer comment for PONE-D-23-21513R1.docx

Click here for additional data file.^{(14.9KB, docx)}

PLoS One. 2023 Nov 14;18(11):e0293984. doi: 10.1371/journal.pone.0293984.r004

Author response to Decision Letter 1

21 Oct 2023

Replies

Summary

ABSTRACT

Methods: in the sentence (line 22) “Adult women with HemoCue 301 readings below 12 g/dL were recruited”, authors should indicate that this was capillary blood.

Reply: Thank you. We have modified the sentence as suggested.

In line 26 (Results), authors should specify that capillary blood was used for Hemocue Hb in the sentence “The Hemocue 301 has a bias of 0.36 ± 0.93 g/dL respect to the automated Hb.”

Reply: We have modified the sentence as suggested.

INTRODUCTION

Reply: We have added a line stating that IDA diagnosis needs the estimation of iron parameters.

The reference 9 cited in the statement “Furthermore, automated hematology analyzers —the method suggested by the WHO [9]” line 54 is not a WHO policy document; please correct this.

Reply: Thank you for noticing the error. The correct reference is given in the updated version.

METHODS

The study design was such that fingertip blood (capillary blood) was used for the Hemocue Hb estimation; venous blood was used for the automated analyser Hb estimation. This should be consistently maintained throughout the manuscript to provide context for the data interpretation since the two blood samples are not equivalent. Therefore, under the inclusion criteria, authors should specify in line 80 – 81 that the Hemocue Hb was estimated from capillary blood. Under laboratory analyses (line 95), authors should specify that CBC was undertaken using venous blood. In line 96, the reference 18 as stated by the authors in the main reference list is not an ISLH guideline; please rectify this.

Reply: Line 80-81, 95 and the ISLH reference have been modified/added.

Reply: The paragraph has been rephrased and we added in the limitation section the fact that blood morphology evaluation cannot be used to rule out hemoglobinopathies.

Statistical analyses

Reply: The accuracy to detect values <15. We have updated this in the article. We updated methods about estimation of optimal cut-off value.

RESULTS

Reply: We have updated the line as suggested.

In table 2, authors should include in the caption capillary blood (Hemocue Hb) and venous blood (analyser Hb).

Reply: We have updated the table as suggested.

In line 183, specify the venous vs capillary blood in the sentence.

Reply: We have updated the line as suggested.

Reply: We have added table 4 which provides PPV, NPV, sensitivity and specificity. We updated the methods section respectively.

DISCUSSION

The discussion is silent on perhaps the key highlight of the study; the ROC and AUC data which sought to establish a cut-off for Hemocue Hb and analyser Hb that could be used as a surrogate means of diagnosing IDA in a resource poor setting. The rational for undertaking AUC and cut-off for analytes particularly in poor settings is to provide clinicians with surrogate estimates that provide high degree of suspicion so that treatment could be prescribed even in the absence of specific biochemical tests for diagnosing IDA. However, this important diagnostic dimension of the data is not explored in the discussion which leaves an obvious question as to why the authors employed the ROC in the first place.

Reply: We have added table 4 results in the discussion.

Reply: We have updated the discussion accordingly.

MINOR

Line 95 “blood count (CBC) was performed withing two hours of the sample obtention” please correct “withing” and “obstention” and these do not exist.

Line 238 the deploy in “Another argument used for the widespread deploy of HemoCue” to deployment.

Reply: We have amended the referenced lines.

Attachment

Submitted filename: Replies for PONE-D-23-21513R1.docx

Click here for additional data file.^{(16.9KB, docx)}

PLoS One. doi: 10.1371/journal.pone.0293984.r005

Decision Letter 2

Benedikt Ley

24 Oct 2023

Accuracy of HemoCue301 Portable Hemoglobin Analyzer for Anemia Screening in Capillary Blood from Women of Reproductive age in a Deprived Region of Northern Peru: An On-Field Study

PONE-D-23-21513R2

Dear Dr. Alarcón-Yaquetto,

We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements.

Within one week, you’ll receive an e-mail detailing the required amendments. When these have been addressed, you’ll receive a formal acceptance letter and your manuscript will be scheduled for publication.

An invoice for payment will follow shortly after the formal acceptance. To ensure an efficient process, please log into Editorial Manager at http://www.editorialmanager.com/pone/, click the 'Update My Information' link at the top of the page, and double check that your user information is up-to-date. If you have any billing related questions, please contact our Author Billing department directly at authorbilling@plos.org.

If your institution or institutions have a press office, please notify them about your upcoming paper to help maximize its impact. If they’ll be preparing press materials, please inform our press team as soon as possible -- no later than 48 hours after receiving the formal acceptance. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information, please contact onepress@plos.org.

Kind regards,

Benedikt Ley, PhD

Academic Editor

PLOS ONE

Additional Editor Comments (optional):

Reviewers' comments:

PLoS One. doi: 10.1371/journal.pone.0293984.r006

Acceptance letter

Benedikt Ley

5 Nov 2023

PONE-D-23-21513R2

Accuracy of HemoCue301 Portable Hemoglobin Analyzer for Anemia Screening in Capillary Blood from Women of Reproductive age in a Deprived Region of Northern Peru: An On-Field Study

Dear Dr. Alarcón-Yaquetto:

I'm pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now with our production department.

If your institution or institutions have a press office, please let them know about your upcoming paper now to help maximize its impact. If they'll be preparing press materials, please inform our press team within the next 48 hours. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information please contact onepress@plos.org.

If we can help with anything else, please email us at plosone@plos.org.

Thank you for submitting your work to PLOS ONE and supporting open access.

Kind regards,

PLOS ONE Editorial Office Staff

on behalf of

Dr Benedikt Ley

Academic Editor

PLOS ONE

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Attachment

Submitted filename: PONE-D-23-21513 REVIEWER REPORT.docx

Click here for additional data file.^{(17.8KB, docx)}

Attachment

Submitted filename: COMMENTS 2.pdf

Click here for additional data file.^{(100.6KB, pdf)}

Attachment

Submitted filename: Answer to reviewers_1.docx

Click here for additional data file.^{(21KB, docx)}

Attachment

Submitted filename: Reviewer comment for PONE-D-23-21513R1.docx

Click here for additional data file.^{(14.9KB, docx)}

Attachment

Submitted filename: Replies for PONE-D-23-21513R1.docx

Click here for additional data file.^{(16.9KB, docx)}

Data Availability Statement

Data is available at https://osf.io/4hrpx/.

[pone.0293984.ref001] 1.Daru J. Sustainable Development Goals for anaemia: 20 years later, where are we now? The Lancet Global Health. 2022;10: e586–e587. doi: 10.1016/S2214-109X(22)00127-9 [DOI] [PubMed] [Google Scholar]

[pone.0293984.ref002] 2.Sinharoy SS, Fanzo J. Ethical and human rights considerations related to access to anemia diagnosis. Annals of the New York Academy of Sciences. 2019; nyas.14125. doi: 10.1111/nyas.14125 [DOI] [PubMed] [Google Scholar]

[pone.0293984.ref003] 3.Instituto de Estadistica e Informática I. Encuesta Demográfica Y De Salud Familiar. In: 2019. 2018. [Google Scholar]

[pone.0293984.ref004] 4.World Health Organization, WHO, World Health Organization. Haemoglobin concentrations for the diagnosis of anaemia and assessment of severity. WHO Geneva: World Health Organization;

[pone.0293984.ref005] 5.Johnson-Wimbley TD, Graham DY. Diagnosis and management of iron deficiency anemia in the 21st century. Therapeutic Advances in Gastroenterology. 2011;4: 177–184. doi: 10.1177/1756283X11398736 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0293984.ref006] 6.White KC. Anemia is a poor predictor of iron deficiency among toddlers in the United States: For heme the bell tolls. Pediatrics. Pediatrics; 2005. pp. 315–320. doi: 10.1542/peds.2004-1488 [DOI] [PubMed] [Google Scholar]

[pone.0293984.ref007] 7.Gonzales GF, Rubín de Celis V, Begazo J, Del Rosario Hinojosa M, Yucra S, Zevallos-Concha A, et al. Correcting the cut-off point of hemoglobin at high altitude favors misclassification of anemia, erythrocytosis and excessive erythrocytosis. American journal of hematology. 2018;93: E12–E16. doi: 10.1002/ajh.24932 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0293984.ref008] 8.Choque‐Quispe BM, Alarcón‐Yaquetto DE, Paredes‐Ugarte W, Zaira A, Ochoa A, Gonzales GF. Is the prevalence of anemia in children living at high altitudes real? An observational study in Peru. Annals of the New York Academy of Sciences. 2020; nyas.14356. doi: 10.1111/nyas.14356 [DOI] [PubMed] [Google Scholar]

[pone.0293984.ref009] 9.World Health Organization (WHO). Assessing the iron status of populations: including literature reviews. 2007. [Google Scholar]

[pone.0293984.ref010] 10.Instituto de Estadistica e Informática I. Metodología de la medición de la anemia. Encuesta Demográfica y de Salud Familiar. 2018. [Google Scholar]

[pone.0293984.ref011] 11.HemoCue AB. HemoCue Hb 301 Microcuvettes—Product insert. Angelholm, Sweden; 2022. [Google Scholar]

[pone.0293984.ref012] 12.Morris LD, Osei-Bimpong A, McKeown D, Roper D, Lewis SM. Evaluation of the utility of the HemoCue 301 haemoglobinometer for blood donor screening. Vox Sanguinis. 2007;93: 64–69. doi: 10.1111/j.1423-0410.2007.00919.x [DOI] [PubMed] [Google Scholar]

[pone.0293984.ref013] 13.Ehrmeyer S. The New Poor Lab’s Guide To The Regulations (CLIA, The Joint Commission, CAP & COLA). 2021. [Google Scholar]

[pone.0293984.ref014] 14.Rappaport AI, Karakochuk CD, Whitfield KC, Kheang KM, Green TJ. A method comparison study between two hemoglobinometer models (Hemocue Hb 301 and Hb 201+) to measure hemoglobin concentrations and estimate anemia prevalence among women in Preah Vihear, Cambodia. International Journal of Laboratory Hematology. 2017;39: 95–100. doi: 10.1111/ijlh.12583 [DOI] [PubMed] [Google Scholar]

[pone.0293984.ref015] 15.Yadav K, Kant S, Ramaswamy G, Ahamed F, Jacob OM, Vyas H, et al. Validation of Point of Care Hemoglobin Estimation Among Pregnant Women Using Digital Hemoglobinometers (HemoCue 301 and HemoCue 201+) as Compared with Auto-Analyzer. Indian Journal of Hematology and Blood Transfusion. 2020;36: 342–348. doi: 10.1007/s12288-019-01196-5 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0293984.ref016] 16.Instituto de Estadistica e Informática. Encuesta Demográfica y de Salud Familiar-ENDES 2014 Informe Principal. Tumbes. 2015. [Google Scholar]

[pone.0293984.ref017] 17.International Society for Laboatory Hematology. Suggested Criteria for Action Following Automated CBC and WBC Differential Analysis. Available at: http://www.islh.org/web/consensus_rules.php [PubMed] [Google Scholar]

[pone.0293984.ref018] 18.World Health Organization (WHO). WHO Guideline on use of Ferritin concentrations to assess iron status in individuals and populations. Geneva; 2020. [PubMed] [Google Scholar]

[pone.0293984.ref019] 19.Karun KM, Puranik A. BA.plot: An R function for Bland-Altman analysis. Clinical Epidemiology and Global Health. 2021;12: 100831. doi: 10.1016/j.cegh.2021.100831 [DOI] [Google Scholar]

[pone.0293984.ref020] 20.Robin X, Turck N, Hainard A, Tiberti N, Lisacek F, Sanchez J-C, et al. pROC: an open-source package for R and S+ to analyze and compare ROC curves. BMC Bioinformatics. 2011;12: 77. doi: 10.1186/1471-2105-12-77 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0293984.ref021] 21.Parkin PC, Borkhoff CM. Practical tips for paediatricians: Assessment and management of young children with iron deficiency. Paediatrics & Child Health. 2018;23: 433–434. doi: 10.1093/pch/pxy045 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0293984.ref022] 22.World Health Organization (WHO). Health and Human Rights. 2022. Available: https://www.who.int/en/news-room/fact-sheets/detail/human-rights-and-health [Google Scholar]

[pone.0293984.ref023] 23.Galloway MJ, Smellie WSA. Investigating iron status in microcytic anaemia. BMJ. 2006;333: 791–793. doi: 10.1136/bmj.38979.358032.BE [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0293984.ref024] 24.WHO. Nutritional Anaemias: Report of a WHO Scientific Group. Geneva; 1968. [PubMed] [Google Scholar]

[pone.0293984.ref025] 25.Addo OY, Yu EX, Williams AM, Young MF, Sharma AJ, Mei Z, et al. Evaluation of Hemoglobin Cutoff Levels to Define Anemia Among Healthy Individuals. JAMA Network Open. 2021;4: e2119123. doi: 10.1001/jamanetworkopen.2021.19123 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0293984.ref026] 26.Kozuki N, Lee AC, Katz J. Moderate to Severe, but Not Mild, Maternal Anemia Is Associated with Increased Risk of Small-for-Gestational-Age Outcomes. Journal of Nutrition. 2012;142: 358–362. doi: 10.3945/jn.111.149237 [DOI] [PubMed] [Google Scholar]

[pone.0293984.ref027] 27.Gonzales GF, Tapia V, Gasco M, Carrillo CE. Maternal hemoglobin concentration and adverse pregnancy outcomes at low and moderate altitudes in Peru. The Journal of Maternal-Fetal & Neonatal Medicine. 2012;25: 1105–1110. doi: 10.3109/14767058.2011.623200 [DOI] [PubMed] [Google Scholar]

[pone.0293984.ref028] 28.Dewey KG, Oaks BM. U-shaped curve for risk associated with maternal hemoglobin, iron status, or iron supplementation. The American Journal of Clinical Nutrition. 2017;106: 1694S–1702S. doi: 10.3945/ajcn.117.156075 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0293984.ref029] 29.Hinnouho G-M, Barffour MA, Wessells KR, Brown KH, Kounnavong S, Chanhthavong B, et al. Comparison of haemoglobin assessments by HemoCue and two automated haematology analysers in young Laotian children. Journal of Clinical Pathology. 2018;71: 532–538. doi: 10.1136/jclinpath-2017-204786 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0293984.ref030] 30.Jaggernath M, Naicker R, Madurai S, Brockman MA, Ndung’u T, Gelderblom HC. Diagnostic Accuracy of the HemoCue Hb 301, STAT-Site MHgb and URIT-12 Point-of-Care Hemoglobin Meters in a Central Laboratory and a Community Based Clinic in Durban, South Africa. Szecsi PB, editor. PLOS ONE. 2016;11: e0152184. doi: 10.1371/journal.pone.0152184 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0293984.ref031] 31.Tayou Tagny C, Kouam L, Mbanya D. [The new HemoCue system Hb 301 for the haemoglobin measurement in pregnant women]. Annales de biologie clinique. 2008;66: 90–4. doi: 10.1684/abc.2008.0195 [DOI] [PubMed] [Google Scholar]

[pone.0293984.ref032] 32.Ministerio de Salud. Resolución Ministerial Nro. 069-2016/MINSA. Directiva sanitaria para el control y prevención de la anemia por deficiencia de hierro en gestantes y puérperas. El Peruano—Normas legales. 2016;577444. [Google Scholar]

[pone.0293984.ref033] 33.Ministerio de Salud. Resolución Ministerial N° 706-2014-MINSA. Directiva sanitaria que establece la suplementación con multimicronutrientes y hierro para la prevención de anemia en niñas y niños menores de 36 meses. 2014. [Google Scholar]

[pone.0293984.ref034] 34.Makker J, Hanif A, Bajantri B, Chilimuri S. Dysmetabolic Hyperferritinemia: All Iron Overload Is Not Hemochromatosis. Case Reports in Gastroenterology. 2015;9: 7–14. doi: 10.1159/000373883 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0293984.ref035] 35.Fowkes FJI, Davidson E, Agius PA, Beeson JG. Understanding the interactions between iron supplementation, infectious disease and adverse birth outcomes is essential to guide public health recommendations. BMC Medicine. 2019;17: 153. doi: 10.1186/s12916-019-1376-8 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0293984.ref036] 36.Sanchis-Gomar F, Cortell-Ballester J, Pareja-Galeano H, Banfi G, Lippi G. Hemoglobin Point-of-Care Testing: The HemoCue System. SLAS Technology. 2013;18: 198–205. doi: 10.1177/2211068212457560 [DOI] [PubMed] [Google Scholar]

[pone.0293984.ref037] 37.Weiss G, Ganz T, Goodnough LT. Anemia of inflammation. Blood. 2019;133: 40–50. doi: 10.1182/blood-2018-06-856500 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0293984.ref038] 38.Kassebaum NJ. The Global Burden of Anemia. Hematology/Oncology Clinics of North America. 2016;30: 247–308. doi: 10.1016/j.hoc.2015.11.002 [DOI] [PubMed] [Google Scholar]

[pone.0293984.ref039] 39.Patel AJ, Wesley R, Leitman SF, Bryant BJ. Capillary versus venous haemoglobin determination in the assessment of healthy blood donors. Vox Sang. 2013. May;104(4):317–23. doi: 10.1111/vox.12006 Epub 2013 Jan 7. ; PMCID: PMC3633672. [DOI] [PMC free article] [PubMed] [Google Scholar]

PERMALINK

Accuracy of HemoCue301 portable hemoglobin analyzer for anemia screening in capillary blood from women of reproductive age in a deprived region of Northern Peru: An on-field study

Dulce E Alarcón-Yaquetto

Lenin Rueda-Torres

Nataly Bailon

Percy Vílchez Barreto

Germán Málaga

Roles

Abstract

Objective

Methods

Results

Conclusion

Introduction

Methods

Design and setting

Inclusion criteria and point of care Hb measurement

Laboratory analysis

Statistical analysis

Results

Table 1. Baseline characteristics of sample by automated Hb status.

Fig 1. Red blood cell indices according to HemoCue hemoglobin tertiles.

Fig 2. Boxplots of red cell blood indices according to automated hemoglobin tertiles.

Table 2. Prevalence and severity of anemia according to different methods.

Table 3. Iron status markers according to HemoCue and automated hemoglobin tertiles.

Fig 3. Bland Altman limits of agreement plot between automated Hb and HemoCue 301.

Fig 4. Are under the ROC curve for hemoglobin measured with the Hemocue301 and the automated analyser (aHb).

Table 4. Cut-off values for automated analyzer and Hemocue 301.

Discussion

Acknowledgments

Data Availability

Funding Statement

References

Decision Letter 0

Benedikt Ley

Roles

Author response to Decision Letter 0

Decision Letter 1

Benedikt Ley

Roles

Author response to Decision Letter 1

Decision Letter 2

Benedikt Ley

Roles

Acceptance letter

Benedikt Ley

Roles

Associated Data

Supplementary Materials

Data Availability Statement

ACTIONS

PERMALINK

RESOURCES

Similar articles

Cited by other articles

Links to NCBI Databases