Assessing the diagnostic precision of multispecies automated hematology analyzers for red blood cell counting in sheep: A method comparison study

Assessing the diagnostic precision of multispecies automated hematology analyzers for red blood cell counting in sheep: A method comparison study | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Assessing the diagnostic precision of multispecies automated hematology analyzers for red blood cell counting in sheep: A method comparison study Warda Amjad, Saba Sattar, Mushtaq Hussain Lashari, Sikander Abbas, and 8 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5444671/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background The RBCs of sheep are small, non-nucleated and normally round in shape, with marked variations in its shape which makes their counting bit tricky. The present method-comparison analysis aims to ascertain diagnostic precision of two multispecies automated veterinary hematology analyzers (RBC-R and RBC-B) in comparison to three manual hematological counting techniques (using hemocytometer with three different dilutions, RBC-1, RBC-2 and RBC-3) for RBC counting in apparently healthy Sipli breed of sheep (n = 60) from Pakistan. Results Results revealed lowest CV (15.4%) for RBC-R. The RBC-R for overall and group-wise data was significantly (P ≤ 0.05) higher (7.29 ± 0.14×10 12 /L) than other four methods, though within normal physiological range for sheep. However, the remaining four methods showed non-significant (P ≥ 0.05) difference between each other. But the values were not within the normal physiological range for sheep being far lower (4.0-5.6×10 12 /L). Moderate direct relationship was revealed only between RBC-R and RBC-B as ascertained through logilinear regression, Bland and Altman test, Cronbach’s alpha and Intraclass Correlation Coefficient. Conclusions It is concluded that manual methods of RBC counting in sheep using hemocytometers may not be reliable. Furthermore, the multispecies hematology analyzers catered data having higher skewness, kurtosis, CV% and accuracy/precision. We recommend a broader need within veterinary hematology for species-specific calibration and the establishment of custom RIs, particularly in regions where resource-limited settings may rely on imported multispecies hematology analyzers that are calibrated primarily for more widely studied animals. Hematology analyzers Red blood cell count Sipli sheep Figures Figure 1 Figure 2 Figure 3 Background Pakistan has a large livestock population which is well-adapted to the local environment. The main types of livestock in Pakistan include sheep, goats, camels, cattle, and buffaloes. The latest Economic Survey of Pakistan (2023–2024) has reported that more than 8 million rural families depend on livestock rearing as the primary source of 35–40% of their total income. The livestock sector has become the cornerstone of agriculture, contributing 60.84% to the agriculture sector and 14.63% to the GDP in Pakistan. The gross value of livestock has increased from Rs 5,587 billion in 2022-23 to Rs 5,804 billion in 2023-24, marking an annual growth rate of 3.89% [ 1 ]. According to the Livestock Census of Punjab, Pakistan, there are 26.49 million sheep in Pakistan. In this census, Balochistan had the largest distribution of sheep, making up over 48% of the total whereas Punjab, Sindh and KPK had 24%, 15% and 13%, respectively [ 2 ]. Sipli breed of sheep is a thin-tailed indigenous sheep breed from Pakistan with a relatively long tail. It is medium-sized, with males weighing around 32.8 kg and females around 29.2 kg. It produces 0.2–0.4 liters of milk daily. It has a white body coat, and its head and ears are either white or light brown. The head is medium-sized with a flat nose, and the ears are about 15 cm long. This breed is primarily raised for mutton and wool by nomadic herders in the Bahawalpur, Bahawalnagar, and Rahim-Yar-Khan regions of the Cholistan desert in Southern Punjab, Pakistan [ 3 ]. Very lately, research work regarding its hematochemical profile has been reported from Pakistan [ 3 – 5 ]. However, data on its RBC counting with a reliable, accurate and precise methodology is yet scarce. The RBCs of sheep are small, non-nucleated and normally round in shape, with marked variations in its shape [ 6 ]. They have a width of 3.2-5µm, diameter of 4.5 µm and a lifespan of about 70–150 days, with a normal number of 10–15 m/dL [ 7 ]. Hemocytometer is considered as the most commonly used instrument for manual counting of blood cells. It comprises a dense glass microscopic slide containing the rectangular depression that makes chamber for counting the number of cells [ 8 ]. However, with the advent of veterinary hematology, various automated multispecies hematology analyzers are now being used as a precise and accurate tool for cell counting [ 9 , 10 ]. Being very small in size, and having extensive shape variations, the sheep RBCs are often mistakenly analyzed by hematology instruments designed for other species [ 11 ]. This method-comparison analysis is the first of its kind being reported for Sipli breed of sheep from Pakistan which aims to ascertain diagnostic precision of two multispecies automated veterinary hematology analyzers (RBC-R and RBC-B) in comparison to three manual hematological counting techniques using hemocytometer with three different dilutions, (RBC-1, RBC-2 and RBC-3), for RBC counting in apparently healthy Sipli breed of sheep (n = 60) from Pakistan. Results Regarding the normality of the attained data, the Shapiro-Wilk’s test revealed that the data for RBC-1 (attained through hemocytometer) and RBC-R (attained through Rayto RT-7600Vet, China, hematology analyzer) was distributed normally, with skewness and kurtosis being weak positive and platykurtic (having less outliers), respectively. Lowest CV (15.4%) was noticed for RBC-R as compared to that for RBC-1, RBC-2, RBC-3 (attained through hemocytometer using three different dilutions) and RBC-B (attained through Biobase BK-5000Vet, China, hematology analyzer) as given in Fig 1. The results of overall comparison for RBC count between manual methods (RBC-1, RBC-2 and RBC-3) and through two hematology analyzers (RBC-R and RBC-B) are given in Table 1. The results revealed that the RBC-R was significantly (P≤0.05) higher (7.29±0.14×10 12 /L) than other four studied methods, though within normal physiological range for sheep. However, the RBC-1 (attained manually) showed non-significant (P≥0.05) difference between each other and the values were not within the normal physiological range for RBC count in sheep being lower (4.0-5.6×10 12 /L). Similar results were attained for gender-based and age-based groups as well as shown in Table 2 and 3, respectively. In the present study, as the data for RBC-R (attained through hematology analyzer) was only found to be within the normal physiological range for sheep, hence the logilinear regression was implied between the data of RBC-R and the data of RBC-1, RBC-2 and RBC-3 (attained through manual methods) (Fig 2). A weak relationship was noticed between the RBC-R and RBC-1, RBC-2 and RBC-3 as indicated by weak r-values and adjusted r-square values. Moderate direct relation was revealed only between RBC-R and RBC-B (r-value= 0.54; r-square value= 0.299; 29.9% probability). As the automated, multispecies hematology analyzers are considered as gold-standard for deducing blood attributes, hence in the present study, the tests for ascertaining level of agreement (B&A, Cronbach Alpha and ICC) were implied between the data of the two hematology analyzers (RBC-R and RBC-B) utilized in this study. The B&A chart between RBC-R and RBC-B is given in Fig 3. A weak level of agreement was noticed between two methods of analysis (Mean=3.49; 95% CI=6.43 to 0.55) with S.D. of biasness being 1.50. Similarly, the results for Cronbach’s alpha and ICC are given in Table 4. The ICC estimates and their 95% CI were computed on the basis of mean-rating (k=2), two-way random effect model and consistency type. The obtained ICC value (0.65) indicated a moderate level of reliability. Discussion The technological advancement in veterinary hematology and launch of current products have led to a substantial growth in automated, multispecies hematology analyzers and their reagents. Sysmex Corporation, Japan (with its facilities and centers throughout the world) is considered to be the leading global firm for devising hematology analyzers. However, other countries such as USA, France, Germany and China have also initiated their production of hematology analyzers both for human and veterinary medical sciences. The Chinese machines are the cheapest and are widely being purchased by developing/underdeveloped countries [ 12 ]. Various leading firms from China such as (Rayto Co. and Biobase Group) have resultantly made a strong foothold in Pakistan and are marketing hematology analyzers both for human and veterinary medical practice [ 13 , 14 ]. These firms have recently given their sole dealerships to companies in Pakistan dealing in science equipment. And sale of both human and veterinary hematology analyzers by these companies has substantially escalated in the last 5 years or so (Ahmad, S., personal communication 2023). The present work is the first of its king which reports diagnostic precision of two different multispecies automated hematology analyzers (Rayto RT-7600Vet and Biobase BK5000Vet, China) against three manual methods of cell counting (using hemocytometer and three different dilutions) for Sipli breed of sheep from Pakistan. The results underscore the limitations of manual RBC counting methods in Sipli sheep from Pakistan, highlighting the subjectivity and variability inherent in hemocytometric methods, which can be compounded by operator expertise and dilution discrepancies. The data of RBC count attained through manual method (RBC-1) and through multispecies hematology analyzer (RBC-R) was distributed normally in the present study, with skewness and kurtosis being weak positive and platykurtic (having less outlier), respectively. Literature is rife with studies indicating least skewness and kurtosis in the data attained both from human and veterinary hematology analyzers, as compared to manual hematological methods [ 15 , 16 ]. Higher skewness and kurtosis in our results for RBC-B could be an inherent/manufacturing characteristic of the machine. On the other hand, a non-Gaussian result for data obtained through manual methods in the present study is due to the fact that counting through hemocytometry is a subjective test and is vulnerable to subjective interpretation owing to varied operator’s skills and dilutions. Our results are in line with various studies which have endorsed that the results attained through automated hematology analyzers have higher sensitivity, reliability and predictive values as compared to manual hematological methods such as hemocytometry [ 17 – 19 ]. Only RBC-R in the present study had a lowest CV (15.4%), whereas the RBC-1, RBC-2, RBC-3 and RBC-B had a higher CV% ranging from 31.6 to 55.9%. The RBC-B attained from the hematology analyzer had a CV% of 53.3% which is way higher than the value reported in instructions manual of the Biobase 5500Vet provided along with the analyzer (2.0%), and also higher than results reported for hematology analyzers elsewhere. A lower CV (1–9%) has been reported for human blood using Sysmex® HA [ 16 ] Similarly, while assessing performance evaluation of an Austrian HA (V Sight HA, Menarini Pharma, Austria) for bovine blood, it was elucidated that the CV% verified for all erythrocytic attributes should not be ≤ 5% [ 20 ] Even lower range of 1–3% has been reported while assessing a Coulter HA (Coulter Diff hematology analyzer, USA) [ 21 ]. On similar pattern, yet another study conducted on performance evaluation of a Coulter HA (Coulter Electronics, UK) for bovine and equine blood, a lower CV% of 0.7-3% has been reported with 5–7% for erythrocytic attributes [ 22 ]. A study conducted on assessing the clinical efficacy of a Swedish HA (CA530, Boule Medical, Stockholm, Sweden), it was reported that the CV for all hematological attributes attained through this machine were within acceptable range except for PLT of dogs, cats and horses [ 23 ]. Considering the fact that higher CV% indicates lesser equipment precision, the efficacy of the HA used in this study seems questionable. As per the CLSI and ASVCP guidelines, the manufacturers must present within-batch and within-run precision in terms of CV% [ 24 , 25 ]. However, the Rayto RT-7600Vet used in the present study did not have any information regarding CV% on its instruction’s manual. The inherent differences in the accuracy/precision of machines developed by different manufacturers, and potentially, variations specific to the unique cellular properties of sheep RBCs could be plausible justification for such high CV% in the present study. Regarding the overall and group-wise comparison for RBC count between three manual methods (RBC-1, RBC-2 and RBC-3) and through two hematology analyzers (RBC-R and RBC-B) of the present study, the overall mean value as well as the RIs of RBC count attained through hematology analyzer (RBC-R) were significantly higher (7.29 ± 0.14×10 12 /L, RI = 6.5–8.8) than other four methods, though they were within normal physiological range for sheep. Literature has reported RIs of 8.0-13.5×10 12 /L for sheep RBCs as counted through hematology analyzers [ 26 – 28 ]. On the contrary, the remaining four methods showed non-significant difference for overall mean values and RIs for RBC count between each other but the values were far lower (4.0-5.6×10 12 /L) than the normal physiological range for RBC count in sheep. The lower-than-normal physiological RBC count attained through three manual methods of the present study could plausibly be attributed to subjectivity of hemocytometry technique. Furthermore, for the results of hematology analyzer (RBC-B) of present study being lower-than-normal could be due to inherent functionality of the equipment which concords with the high CV% (53.3%) in the present study for this machine. In the present study, a weak relationship was noticed between the RBC count attained through hematology analyzer (RBC-R) and those through manual methods (RBC-1, RBC-2 and RBC-3) as indicated by weak r-values and adjusted r-square values. Moderate direct relation was revealed only between RBC-R and RBC-B (r-value = 0.54; adjusted r-square value = 0.299; 29.9% probability). This correlation is endorsed by the B&A chart between RBC-R and RBC-B which showed a weak level of agreement between two methods of analysis (Mean = 3.49; 95% CI = 6.43 to 0.55) with S.D. of biasness being 1.50. Similarly, the results for Cronbach’s alpha and ICC also indicated a moderate level of reliability. These results are not in line with previous work which have extensively reported (while comparing diagnostic efficacy) a strong correlation between results attained through various hematology analyzers [ 29 – 31 ]. The moderate reliability found between the results of two automated analyzers in this study (RBC-R and RBC-B) raises questions about the comparability of analyzer performance for animals with distinct RBC profiles. Cross-species studies have shown that animal blood cells, which vary considerably in size, shape, and morphology across species, can influence the accuracy of machine-based counts. Conclusion Keeping the results of the present study in perspective, it seems inevitable to conclude that manual methods of RBC counting in sheep using hemocytometers may not be reliable. Furthermore, the two multispecies automated hematology analyzers used in this study (Rayto RT-7600 and Biobas BK5000Vet, China) delivered data having higher skewness, kurtosis, and CV% with lower accuracy/precision. The results of this study could be a benchmark for laboratories/clinical settings (especially of resource-poor settings) which are using multispecies hematology analyzers for sheep blood assessments. Because these machines may present accurate results for common species such as cattle, buffaloes, dogs and cats, adaptations are essential for ensuring accuracy in sheep and other species with smaller, more variable RBCs. These findings suggest a broader need within veterinary hematology for species-specific calibration and the establishment of custom RIs, particularly in regions where resource-limited settings may rely on imported multispecies hematology analyzers that are calibrated primarily for more widely studied animals. Methods Geo-location of the study The present study was conducted simultaneously at Livestock Farm of the Faculty of Veterinary and Animal Sciences (FV&AS), Islamia University of Bahawalpur (IUB) and the Post-Graduate Lab, Department of Physiology, IUB, Pakistan. These facilities are situated in the periphery of Cholistan Desert (locally known as Rohi) of Bahawalpur, Punjab, Pakistan. It is located at latitudes 27°42′ and 29°45′ North and longitudes 69°52′ and 75°24′ East at height of 112 meters above sea level. The climate of this region is arid, hot subtropical and monsoonal with an average annual rainfall of 180mm. The mean annual temperature is 28.33°C, with June being the hottest month when maximum day temperature reaches 45°C [32, 33]. Study animals and blood sampling Apparently healthy Sipli sheep (n=60) being reared at the farm of the university were included in the study. The animals were being managed under intensive farming system. They were stall fed and the feeding included freshly-cut and chopped seasonal forage mixed with concentrate ration containing roughly 15% crude protein. Moreover, wheat straw and maize silage were also provided depending upon the demand. The fresh and clean drinking water remained available all the time. The routine veterinary inspection allied with regular vaccination and deworming was being maintained at the farm. Keeping the physical examination of each study animal and the data provided by the farm personnel, it was made sure that all the animals were healthy with no signs and symptoms of any diseases later confirmed through routine blood analysis. The study animals were restrained by the trained personnel and 5 mL of blood was aseptically drawn from jugular vein of each animal. Blood was transferred into purple-topped vacutainer tubes containing 0.5 mL of 1% EDTA solution (TUBER ® Vac EDTA K2, Australia). Blood samples were transported to the lab where the RBC counting was performed within 8 hours. Red blood cell counting The RBC counting was carried out as per following methods: Manual method: The RBC counting was performed with a Neubauer counting chamber/ hemocytometer (MARIENFELD, Germany) as per prescribed protocol [34] with minor modifications. Hayem's solution (SDL Scientific Enterprise, Pakistan) was used as a diluent and counting was carried out with three different dilutions viz . 1:200, 1:400 and 1:600 and were dubbed as RBC-1, RBC-2 and RBC-3, respectively. Automated method: The automated counting of RBCs was carried out using two different multispecies automated hematology analyzers (Rayto RT-7600Vet and Biobase BK-5000Vet, China), and dubbed as RBC-R and RBC-B, respectively. Both these analyzers are 3-part (lymphocytes, intermediate cells and granulocytes), multispecies analyzers meant for the blood analysis of cats, dogs, rabbits, pigs, horses, goats, monkeys, and four other self-defined animals. They use the principle of impedance for counting and differentiating blood cells and principle of colorimetry for Hb determination. They provide 23 test items/blood analysis attributes including three histograms each for WBCs, RBCs and PLT. The technical characteristics of the analyzers include a minimum whole blood volume of 10.0µL, pre-diluted blood volume of 20µL, test rate of about 1 minute/essay, and a working environment of 15-35ºC with humidity of 10-90%. They uses lyse solution, cleanser and a diluent for measurements and maintenance. As per their instructions manuals, accuracy of test results is attained by using the reagents provided along with the instruments. The settings for reference intervals of each species can be set manually. Values in the complete blood count report which are outside the normal range are marked automatically in the report. The quality control (QC) of the analyzer includes two methods namely L-J QC and R-X QC [35]. Statistical analysis Statistical analysis was performed using Statistical Package for Social Sciences (IBM SPSS, version 20) and Prism (GraphPad Prim 8.0.1). Normality of the data was tested visually as well as through Shapiro-wilk test. For the purpose of analyses, data was grouped as per sex (females, n=43; males, n=17) and age (up till 1year, n=10; from 1 to 2 years, n=35; above 2 years, n=15). The mean (±SE), median, range and reference intervals (RIs) (25 th to 90 th percentile) were deduced for the attained data keeping in view the guidelines provided by the American Society for Veterinary Clinical Pathology [36] using the Reference Value Advisor (freeware v.2.1: http://www.biostat.envt.fr/reference-value-advisor). Difference between analytical methods i.e. through manual methods and hematology analyzers for overall as well as for group-wise data was attained through ANOVA followed by Bonferroni post-hoc test. The results were considered significant when p≤0.05.Pearson’s correlation coefficient and linear regression were implied to assess the level of relation between the RBC count attained through different methods of the study, and to deduce the regression prediction equations, respectively. Three tests were implied to check the level of agreement between the results of two automated hematology analyzers viz. Bland and Altman (B&A), Cronbach’s Alpha and Intraclass Correlation Coefficient (ICC). Abbreviations RBC1: RBC count attained through hemocytometer using dilution of 1:200 with Hayem’s solution RBC2: RBC count attained through hemocytometer using dilution of 1:400 with Hayem’s solution RBC3: RBC count attained through hemocytometer using dilution of 1:600 with Hayem’s solution RBC-R: RBC count attained Rayto RT-7600Vet, China, hematology analyzer RBC-B: RBC count attained Biobase BK-5000Vet, China, hematology analyzer Declarations Ethics approval and consent to participate The study is a part of a collaborative research project carried out by the Department of Zoology and Department of Physiology, IUB vide approval No. PHYSIO-92/2024-52 dated 06-05-2024. Consent for publication Consent for publishing this article has been attained from all co-authors. Availability of data and materials All the relevant data has been incorporated within the article. Competing interests The authors have no conflict of interest regarding this manuscript. Funding Research funding was provided through Researchers Supporting Project No. (RSPD2025R470), King Saud University, Riyadh, Saudi Arabia. Authors' contributions The present study was designed and proposed by Z.U.R., U.F., M.H.L., and H.R. The lab protocol was carried out by W.A., S.S., S.Q., and M.I. Data was analyzed by U.F., S.A., K.A.S., and S.N. The manuscript was written and reviewed by U.F., H.R., S.M.A., and S.A. Funding and resources were managed by K.A.S., and S.M.A. References Pakistan Economic Survey. 2018-19 [ http://www.finance.gov.pk/survey/chapters_19/2-Agriculture.pdf] Livestock & Dairy Development Department P: First Real Time (Door to Door) Livestock Census. In. Edited by Livestock & Dairy Development Department P. Lahore, Pakistan: Lⅅ, Punjab. 2018: 30. Sharif M, Lashari MH, Farooq U, Idris M, Afzal MA. Diagnostic efficacy of hand-held digital refractometer for determining total serum protein in indigenous sheep of Pakistan. PLoS ONE. 2024;19(3):e0295107. 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Tables Table 1 Overall mean (±SE), median, interquartile range (IQR), minimum, maximum, 25 th to 90 th percentile of reference interval (RI) and 95% confidence interval (CI) for RBC count attained through manual methods (RBC-1, RBC-2 and RBC-3) and hematology analyzers (RBC-R and RBC-B) in apparently healthy Sipli sheep (n=60) Methods Mean (±SE) Median (IQR) Range (Min-Max) RI (25 th to 90 th ) 95% CI RBC-1 3.96±0.16 a 3.95 (1.62) 5.54 (1.72-7.26) 3.09-5.68 3.64-4.29 RBC-2 3.86±0.24 a 3.48 (1.36) 10.7 (1.62-12.4) 2.73-7.06 3.37-4.36 RBC-3 4.11±0.16 a 4.02 (1.46) 6.51 (2.10-8.61) 3.21-5.82 3.78­-4.44 RBC-R 7.29±0.14 b 7.23 (1.54) 4.90 (4.96-9.86) 6.50-8.86 7.01-7.58 RBC-B 3.80±0.23 a 3.42 (1.79) 9.57 (1.66-11.2) 2.57-5.69 3.34-4.26 a, b Superscripts indicate the significance at (P≤0.05) for different methods of RBC counting Table 2 Gender-wise RBC count as deduced through manual methods (RBC-1, RBC-2 and RBC-3) and hematology analyzers (RBC-R and RBC-B) for apparently healthy Sipli sheep (n=60) Methods Mean (±SE) Median (IQR) Range (Min-Max) RI (25 th to 90 th ) 95% CI Females (n=43) RBC 1 4.06±0.20 a 4.01 (1.70) 5.54 (1.72-7.26) 3.20-6.01 3.65-4.46 RBC 2 4.02±0.31 a 3.50 (1.94) 10.7 (1.62-12.4) 2.78-7.15 3.38-4.66 RBC 3 4.16±0.17 a 4.02 (1.26) 4.95 (2.22-7.17) 3.42-5.98 3.82-4.51 RBC-R 7.08±0.13 b 7.03 (1.23) 3.84 (5.51-9.35) 6.44-8.32 6.81-7.36 RBC-B 3.33±0.16 a 3.08 (1.26) 6.39 (1.66-8.05) 2.56-4.56 3.00-3.67 Males (n=17) RBC 1 3.73±0.25 a 3.46 (1.64) 4.36 (2.10-6.46) 2.88-5.07 3.19-4.27 RBC 2 3.47±0.31 a 3.46 (1.42) 5.58 (1.88-7.46) 2.50-5.39 2.80-4.14 RBC 3 3.98±0.39 a 3.69 (2.07) 6.51 (2.10-8.61) 2.82-6.37 3.14-4.83 RBC-R 7.82±0.34 c 8.15 (2.05) 4.90 (4.96-9.86) 6.73-9.81 7.10-8.54 RBC-B 4.97±0.62 a 4.77 (2.84) 9.47 (1.76-11.2) 3.09-9.63 3.65-6.29 SE=Standard Error; IQR=Interquartile Range; RI=Reference Interval; CI=Confidence Interval a, b, c Superscripts indicate the significance at (P≤0.05) for different methods of RBC counting within gender-based groups Table 3 Age-wise RBC count as deduced through manual methods (RBC-1, RBC-2 and RBC-3) and hematology analyzers (RBC-R and RBC-B) for apparently healthy Sipli sheep (n=60) Methods Mean±SE Median (IQR) Range (Min-Max) RI (25 th to 90 th ) 95% CI G1 (n=10) RBC 1 4.34±0.36 a 4.24 (1.69) 4.05 (2.25-6.30) 3.46-6.23 3.51-5.17 RBC 2 3.59±0.36 a 3.36 (2.24) 3.32 (2.12-5.44) 2.55-5.39 2.76-4.41 RBC 3 4.44±0.35 a 4.21 (0.75) 3.96 (3.21-7.17) 3.89-6.98 3.64-5.23 RBC-R 7.32±0.25 b 7.35 (1.36) 2.53 (5.92-8.45) 6.70-8.44 6.74-7.90 RBC-B 3.72±0.52 a 3.24 (1.32) 5.82 (2.23-8.05) 2.76-7.68 2.54-5.91 G2 (n=35) RBC 1 4.00±0.20 a 3.71 (1.51) 5.19 (2.07-7.26) 3.20-5.87 3.59-4.42 RBC 2 4.19±0.39 a 3.50 (2.04) 10.7 (1.62-12.4) 2.84-7.32 3.38-4.99 RBC 3 4.14±0.23 a 3.78 (2.04) 6.51 (2.10-8.61) 2.50-6.15 3.65-4.62 RBC-R 7.31±0.18 b 7.14 (1.76) 4.24 (5.62-9.86) 6.44-8.89 6.93-7.70 RBC-B 3.74±0.22 a 3.44 (2.20) 6.23 (1.98-8.21) 2.57-5.35 3.28-4.20 G3 (n=15) RBC 1 3.62±0.35 a 3.70 (2.45) 4.74 (1.72-6.46) 2.22-5.95 2.86-4.38 RBC 2 3.30±0.17 a 3.46 (1.30) 2.00 (2.16-4.16) 2.68-4.11 2.92-3.68 RBC 3 3.84±0.26 a 3.78 (1.71) 3.57 (2.25-5.82) 2.88 – 5.46 3.27-4.40 RBC-R 7.22±0.33 b 7.55 (1.71) 4.84 (4.96-9.80) 6.35 – 9.33 6.50-7.95 RBC-B 3.99±0.69 a 3.41 (1.53) 9.57 (1.66-11.2) 2.55 – 10.0 2.50-5.49 SE=Standard Error; IQR=Interquartile Range; RI=Reference Interval; CI=Confidence Interval; G1= up till 1 year; G2= from 1 to 2 years, G3= above 2 years a, b, Superscripts indicate the significance at (P≤0.05) for different methods of RBC counting within age-based groups Table 4 Cronbach’s alpha and intraclass correlation between RBC-R and RBC-B (attained through two hematology analyzers) in apparently healthy Sipli sheep (n=60) RBC-R versus RBC-B Intraclass Correlation Coefficient 95% CI Cronbach’s Alpha Single measure 0.49 0.27 – 0.66 0.65 Average measures 0.65 0.42 – 0.79 CI= Confidence Interval Additional Declarations No competing interests reported. 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Bahawalpur","correspondingAuthor":false,"prefix":"","firstName":"Saba","middleName":"","lastName":"Sattar","suffix":""},{"id":379337313,"identity":"0c8b72bd-37d9-423c-9dab-d3f26a27931d","order_by":2,"name":"Mushtaq Hussain Lashari","email":"","orcid":"","institution":"The Islamia University of Bahawalpur","correspondingAuthor":false,"prefix":"","firstName":"Mushtaq","middleName":"Hussain","lastName":"Lashari","suffix":""},{"id":379337314,"identity":"2e4c728a-899b-443e-a343-2a3c1987e253","order_by":3,"name":"Sikander Abbas","email":"","orcid":"","institution":"The Islamia University of Bahawalpur","correspondingAuthor":false,"prefix":"","firstName":"Sikander","middleName":"","lastName":"Abbas","suffix":""},{"id":379337315,"identity":"78094bbf-59b4-4a01-b66b-ee5370b6872a","order_by":4,"name":"Umer Farooq","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA60lEQVRIiWNgGAWjYNACGzDJ+CCB4QCQTgDiA4S0pIFJZgOStbBJMBCjxeDa4WMfGBLs8vnZm7dVPGy7w8DPnmPAXHAGj5bbackzGBKSLWf2HCu7kdj2jEGy540B84wb+LTkGDMw/mA2MLiRYwbUcpgByDBg5vmAT0v+Z6Dr68FaCkBa7AlryWEGajkM1sIAtkUCpAWPwyRvpxkzJCQcN5DsOVYskXDuGY/EmWcFh2fg8T7f7eTHDB8Sqg2AIbbx44+yO3L87ckbHxccw60FDBKgjgQRPCDiMAENCH/BWczEahkFo2AUjIIRAQB2eVQkcxn2+QAAAABJRU5ErkJggg==","orcid":"","institution":"The Islamia University of Bahawalpur","correspondingAuthor":true,"prefix":"","firstName":"Umer","middleName":"","lastName":"Farooq","suffix":""},{"id":379337316,"identity":"2990a94a-cd1c-42d8-bac4-3e68ea6ba8ee","order_by":5,"name":"Zia Ur-Rehman","email":"","orcid":"","institution":"The Islamia University of 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Bahawalpur","correspondingAuthor":false,"prefix":"","firstName":"Sumama","middleName":"","lastName":"Qayyum","suffix":""},{"id":379337320,"identity":"c1ecc049-b817-4bc6-b230-b9ec94c30bf3","order_by":9,"name":"Khawar Ali Shahzad","email":"","orcid":"","institution":"Tongji University","correspondingAuthor":false,"prefix":"","firstName":"Khawar","middleName":"Ali","lastName":"Shahzad","suffix":""},{"id":379337321,"identity":"5346c153-b4d4-4dd1-9d42-64f09ca159b5","order_by":10,"name":"Saeedah Musaed Almutairi","email":"","orcid":"","institution":"King Saud University","correspondingAuthor":false,"prefix":"","firstName":"Saeedah","middleName":"Musaed","lastName":"Almutairi","suffix":""},{"id":379337322,"identity":"e12099eb-c529-4d53-ae14-e815556bde63","order_by":11,"name":"Shagufta Nasreen","email":"","orcid":"","institution":"The Islamia University of Bahawalpur","correspondingAuthor":false,"prefix":"","firstName":"Shagufta","middleName":"","lastName":"Nasreen","suffix":""}],"badges":[],"createdAt":"2024-11-13 07:23:20","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-5444671/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-5444671/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":71303817,"identity":"504d5340-cc76-47a9-af5e-fdcfa3d370aa","added_by":"auto","created_at":"2024-12-13 06:02:22","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":173302,"visible":true,"origin":"","legend":"\u003cp\u003eHistograms for RBC count attained through manual methods (RBC-1, RBC-2 and RBC-3) and through two automated hematology analyzers (RBC-R and RBC-B) in Sipli sheep (n= 60)\u003c/p\u003e","description":"","filename":"Fig1.png","url":"https://assets-eu.researchsquare.com/files/rs-5444671/v1/008a252b9ec33d6411a1142a.png"},{"id":71303815,"identity":"d1132003-5ae2-4822-887c-08c87fc15463","added_by":"auto","created_at":"2024-12-13 06:02:22","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":131829,"visible":true,"origin":"","legend":"\u003cp\u003eScatterplots for logilinear regression between RBC-R and a) RBC-1 b) RBC-2 c) RBC-3 d) RBC-B for apparently healthy Sipli sheep blood (n= 60)\u003c/p\u003e","description":"","filename":"Fig2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-5444671/v1/75ea981be9c47de054bbfe0a.jpg"},{"id":71303818,"identity":"5df6a762-2f42-4456-96eb-58bb96535d24","added_by":"auto","created_at":"2024-12-13 06:02:22","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":13495,"visible":true,"origin":"","legend":"\u003cp\u003eScatterplot of Bland and Altman test between difference and mean of RBC-R and RBC-B attained through two hematology analyzers in Sipli sheep (n=60). Central line indicates mean difference (3.49) whereas the upper and lower lines indicate upper (6.43) and lower (0.55) values respectively (SD of Bias 1.50)\u003c/p\u003e","description":"","filename":"Fig3.png","url":"https://assets-eu.researchsquare.com/files/rs-5444671/v1/8867fa85fafa190f3e1b2123.png"},{"id":76425558,"identity":"58a83756-dfea-49b6-b253-c1d1d5a075a0","added_by":"auto","created_at":"2025-02-17 05:32:59","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1533350,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5444671/v1/28ac1d29-18db-488d-aee9-a6ebef15e408.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Assessing the diagnostic precision of multispecies automated hematology analyzers for red blood cell counting in sheep: A method comparison study","fulltext":[{"header":"Background","content":"\u003cp\u003ePakistan has a large livestock population which is well-adapted to the local environment. The main types of livestock in Pakistan include sheep, goats, camels, cattle, and buffaloes. The latest Economic Survey of Pakistan (2023\u0026ndash;2024) has reported that more than 8\u0026nbsp;million rural families depend on livestock rearing as the primary source of 35\u0026ndash;40% of their total income. The livestock sector has become the cornerstone of agriculture, contributing 60.84% to the agriculture sector and 14.63% to the GDP in Pakistan. The gross value of livestock has increased from Rs 5,587\u0026nbsp;billion in 2022-23 to Rs 5,804\u0026nbsp;billion in 2023-24, marking an annual growth rate of 3.89% [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. According to the Livestock Census of Punjab, Pakistan, there are 26.49\u0026nbsp;million sheep in Pakistan. In this census, Balochistan had the largest distribution of sheep, making up over 48% of the total whereas Punjab, Sindh and KPK had 24%, 15% and 13%, respectively [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eSipli breed of sheep is a thin-tailed indigenous sheep breed from Pakistan with a relatively long tail. It is medium-sized, with males weighing around 32.8 kg and females around 29.2 kg. It produces 0.2\u0026ndash;0.4 liters of milk daily. It has a white body coat, and its head and ears are either white or light brown. The head is medium-sized with a flat nose, and the ears are about 15 cm long. This breed is primarily raised for mutton and wool by nomadic herders in the Bahawalpur, Bahawalnagar, and Rahim-Yar-Khan regions of the Cholistan desert in Southern Punjab, Pakistan [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Very lately, research work regarding its hematochemical profile has been reported from Pakistan [\u003cspan additionalcitationids=\"CR4\" citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. However, data on its RBC counting with a reliable, accurate and precise methodology is yet scarce.\u003c/p\u003e \u003cp\u003eThe RBCs of sheep are small, non-nucleated and normally round in shape, with marked variations in its shape [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. They have a width of 3.2-5\u0026micro;m, diameter of 4.5 \u0026micro;m and a lifespan of about 70\u0026ndash;150 days, with a normal number of 10\u0026ndash;15 m/dL [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Hemocytometer is considered as the most commonly used instrument for manual counting of blood cells. It comprises a dense glass microscopic slide containing the rectangular depression that makes chamber for counting the number of cells [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. However, with the advent of veterinary hematology, various automated multispecies hematology analyzers are now being used as a precise and accurate tool for cell counting [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. Being very small in size, and having extensive shape variations, the sheep RBCs are often mistakenly analyzed by hematology instruments designed for other species [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. This method-comparison analysis is the first of its kind being reported for Sipli breed of sheep from Pakistan which aims to ascertain diagnostic precision of two multispecies automated veterinary hematology analyzers (RBC-R and RBC-B) in comparison to three manual hematological counting techniques using hemocytometer with three different dilutions, (RBC-1, RBC-2 and RBC-3), for RBC counting in apparently healthy Sipli breed of sheep (n\u0026thinsp;=\u0026thinsp;60) from Pakistan.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eRegarding the normality of the attained data, the Shapiro-Wilk\u0026rsquo;s test revealed that the data for RBC-1 (attained through hemocytometer) and RBC-R (attained through Rayto RT-7600Vet, China, hematology analyzer) was distributed normally, with skewness and kurtosis being weak positive and platykurtic (having less outliers), respectively. Lowest CV (15.4%) was noticed for RBC-R as compared to that for RBC-1, RBC-2, RBC-3 (attained through hemocytometer using three different dilutions) and RBC-B (attained through Biobase BK-5000Vet, China, hematology analyzer) as given in Fig 1.\u003c/p\u003e\n\u003cp\u003eThe results of overall comparison for RBC count between manual methods (RBC-1, RBC-2 and RBC-3) and through two hematology analyzers (RBC-R and RBC-B) are given in Table 1. The results revealed that the RBC-R was significantly (P\u0026le;0.05) higher (7.29\u0026plusmn;0.14\u0026times;10\u003csup\u003e12\u003c/sup\u003e/L) than other four studied methods, though within normal physiological range for sheep. However, the RBC-1 (attained manually) showed non-significant (P\u0026ge;0.05) difference between each other and the values were not within the normal physiological range for RBC count in sheep being lower (4.0-5.6\u0026times;10\u003csup\u003e12\u003c/sup\u003e/L). Similar results were attained for gender-based and age-based groups as well as shown in Table 2 and 3, respectively.\u003c/p\u003e\n\u003cp\u003eIn the present study, as the data for RBC-R (attained through hematology analyzer) was only found to be within the normal physiological range for sheep, hence the logilinear regression was implied between the data of RBC-R and the data of RBC-1, RBC-2 and RBC-3 (attained through manual methods) (Fig 2). A weak relationship was noticed between the RBC-R and RBC-1, RBC-2 and RBC-3 as indicated by weak r-values and adjusted r-square values. Moderate direct relation was revealed only between RBC-R and RBC-B (r-value= 0.54; r-square value= 0.299; 29.9% probability).\u003c/p\u003e\n\u003cp\u003eAs the automated, multispecies hematology analyzers are considered as gold-standard for deducing blood attributes, hence in the present study, the tests for ascertaining level of agreement (B\u0026amp;A, Cronbach Alpha and ICC) were implied between the data of the two hematology analyzers (RBC-R and RBC-B) utilized in this study. The B\u0026amp;A chart between RBC-R and RBC-B is given in Fig 3. A weak level of agreement was noticed between two methods of analysis (Mean=3.49; 95% CI=6.43 to 0.55) with S.D. of biasness being 1.50. Similarly, the results for Cronbach\u0026rsquo;s alpha and ICC are given in Table 4. The ICC estimates and their 95% CI were computed on the basis of mean-rating (k=2), two-way random effect model and consistency type. The obtained ICC value (0.65) indicated a moderate level of reliability.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe technological advancement in veterinary hematology and launch of current products have led to a substantial growth in automated, multispecies hematology analyzers and their reagents. Sysmex Corporation, Japan (with its facilities and centers throughout the world) is considered to be the leading global firm for devising hematology analyzers. However, other countries such as USA, France, Germany and China have also initiated their production of hematology analyzers both for human and veterinary medical sciences. The Chinese machines are the cheapest and are widely being purchased by developing/underdeveloped countries [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. Various leading firms from China such as (Rayto Co. and Biobase Group) have resultantly made a strong foothold in Pakistan and are marketing hematology analyzers both for human and veterinary medical practice [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. These firms have recently given their sole dealerships to companies in Pakistan dealing in science equipment. And sale of both human and veterinary hematology analyzers by these companies has substantially escalated in the last 5 years or so (Ahmad, S., personal communication 2023). The present work is the first of its king which reports diagnostic precision of two different multispecies automated hematology analyzers (Rayto RT-7600Vet and Biobase BK5000Vet, China) against three manual methods of cell counting (using hemocytometer and three different dilutions) for Sipli breed of sheep from Pakistan. The results underscore the limitations of manual RBC counting methods in Sipli sheep from Pakistan, highlighting the subjectivity and variability inherent in hemocytometric methods, which can be compounded by operator expertise and dilution discrepancies.\u003c/p\u003e \u003cp\u003eThe data of RBC count attained through manual method (RBC-1) and through multispecies hematology analyzer (RBC-R) was distributed normally in the present study, with skewness and kurtosis being weak positive and platykurtic (having less outlier), respectively. Literature is rife with studies indicating least skewness and kurtosis in the data attained both from human and veterinary hematology analyzers, as compared to manual hematological methods [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. Higher skewness and kurtosis in our results for RBC-B could be an inherent/manufacturing characteristic of the machine. On the other hand, a non-Gaussian result for data obtained through manual methods in the present study is due to the fact that counting through hemocytometry is a subjective test and is vulnerable to subjective interpretation owing to varied operator\u0026rsquo;s skills and dilutions. Our results are in line with various studies which have endorsed that the results attained through automated hematology analyzers have higher sensitivity, reliability and predictive values as compared to manual hematological methods such as hemocytometry [\u003cspan additionalcitationids=\"CR18\" citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eOnly RBC-R in the present study had a lowest CV (15.4%), whereas the RBC-1, RBC-2, RBC-3 and RBC-B had a higher CV% ranging from 31.6 to 55.9%. The RBC-B attained from the hematology analyzer had a CV% of 53.3% which is way higher than the value reported in instructions manual of the Biobase 5500Vet provided along with the analyzer (2.0%), and also higher than results reported for hematology analyzers elsewhere. A lower CV (1\u0026ndash;9%) has been reported for human blood using Sysmex\u0026reg; HA [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e] Similarly, while assessing performance evaluation of an Austrian HA (V Sight HA, Menarini Pharma, Austria) for bovine blood, it was elucidated that the CV% verified for all erythrocytic attributes should not be \u0026le;\u0026thinsp;5% [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e] Even lower range of 1\u0026ndash;3% has been reported while assessing a Coulter HA (Coulter Diff hematology analyzer, USA) [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. On similar pattern, yet another study conducted on performance evaluation of a Coulter HA (Coulter Electronics, UK) for bovine and equine blood, a lower CV% of 0.7-3% has been reported with 5\u0026ndash;7% for erythrocytic attributes [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. A study conducted on assessing the clinical efficacy of a Swedish HA (CA530, Boule Medical, Stockholm, Sweden), it was reported that the CV for all hematological attributes attained through this machine were within acceptable range except for PLT of dogs, cats and horses [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. Considering the fact that higher CV% indicates lesser equipment precision, the efficacy of the HA used in this study seems questionable. As per the CLSI and ASVCP guidelines, the manufacturers must present within-batch and within-run precision in terms of CV% [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. However, the Rayto RT-7600Vet used in the present study did not have any information regarding CV% on its instruction\u0026rsquo;s manual. The inherent differences in the accuracy/precision of machines developed by different manufacturers, and potentially, variations specific to the unique cellular properties of sheep RBCs could be plausible justification for such high CV% in the present study.\u003c/p\u003e \u003cp\u003eRegarding the overall and group-wise comparison for RBC count between three manual methods (RBC-1, RBC-2 and RBC-3) and through two hematology analyzers (RBC-R and RBC-B) of the present study, the overall mean value as well as the RIs of RBC count attained through hematology analyzer (RBC-R) were significantly higher (7.29\u0026thinsp;\u0026plusmn;\u0026thinsp;0.14\u0026times;10\u003csup\u003e12\u003c/sup\u003e/L, RI\u0026thinsp;=\u0026thinsp;6.5\u0026ndash;8.8) than other four methods, though they were within normal physiological range for sheep. Literature has reported RIs of 8.0-13.5\u0026times;10\u003csup\u003e12\u003c/sup\u003e/L for sheep RBCs as counted through hematology analyzers [\u003cspan additionalcitationids=\"CR27\" citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. On the contrary, the remaining four methods showed non-significant difference for overall mean values and RIs for RBC count between each other but the values were far lower (4.0-5.6\u0026times;10\u003csup\u003e12\u003c/sup\u003e/L) than the normal physiological range for RBC count in sheep. The lower-than-normal physiological RBC count attained through three manual methods of the present study could plausibly be attributed to subjectivity of hemocytometry technique. Furthermore, for the results of hematology analyzer (RBC-B) of present study being lower-than-normal could be due to inherent functionality of the equipment which concords with the high CV% (53.3%) in the present study for this machine.\u003c/p\u003e \u003cp\u003eIn the present study, a weak relationship was noticed between the RBC count attained through hematology analyzer (RBC-R) and those through manual methods (RBC-1, RBC-2 and RBC-3) as indicated by weak r-values and adjusted r-square values. Moderate direct relation was revealed only between RBC-R and RBC-B (r-value\u0026thinsp;=\u0026thinsp;0.54; adjusted r-square value\u0026thinsp;=\u0026thinsp;0.299; 29.9% probability). This correlation is endorsed by the B\u0026amp;A chart between RBC-R and RBC-B which showed a weak level of agreement between two methods of analysis (Mean\u0026thinsp;=\u0026thinsp;3.49; 95% CI\u0026thinsp;=\u0026thinsp;6.43 to 0.55) with S.D. of biasness being 1.50. Similarly, the results for Cronbach\u0026rsquo;s alpha and ICC also indicated a moderate level of reliability. These results are not in line with previous work which have extensively reported (while comparing diagnostic efficacy) a strong correlation between results attained through various hematology analyzers [\u003cspan additionalcitationids=\"CR30\" citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. The moderate reliability found between the results of two automated analyzers in this study (RBC-R and RBC-B) raises questions about the comparability of analyzer performance for animals with distinct RBC profiles. Cross-species studies have shown that animal blood cells, which vary considerably in size, shape, and morphology across species, can influence the accuracy of machine-based counts.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eKeeping the results of the present study in perspective, it seems inevitable to conclude that manual methods of RBC counting in sheep using hemocytometers may not be reliable. Furthermore, the two multispecies automated hematology analyzers used in this study (Rayto RT-7600 and Biobas BK5000Vet, China) delivered data having higher skewness, kurtosis, and CV% with lower accuracy/precision. The results of this study could be a benchmark for laboratories/clinical settings (especially of resource-poor settings) which are using multispecies hematology analyzers for sheep blood assessments. Because these machines may present accurate results for common species such as cattle, buffaloes, dogs and cats, adaptations are essential for ensuring accuracy in sheep and other species with smaller, more variable RBCs. These findings suggest a broader need within veterinary hematology for species-specific calibration and the establishment of custom RIs, particularly in regions where resource-limited settings may rely on imported multispecies hematology analyzers that are calibrated primarily for more widely studied animals.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003e\u003cstrong\u003eGeo-location of the study\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe present study was conducted simultaneously at Livestock Farm of the Faculty of Veterinary and Animal Sciences (FV\u0026amp;AS), Islamia University of Bahawalpur (IUB) and the Post-Graduate Lab, Department of Physiology, IUB, Pakistan. These facilities are situated in the periphery of Cholistan Desert (locally known as Rohi) of Bahawalpur, Punjab, Pakistan. It is located at latitudes 27\u0026deg;42\u0026prime; and 29\u0026deg;45\u0026prime; North and longitudes 69\u0026deg;52\u0026prime; and 75\u0026deg;24\u0026prime; East at height of 112 meters above sea level. The climate of this region is arid, hot subtropical and monsoonal with an average annual rainfall of 180mm. The mean annual temperature is 28.33\u0026deg;C, with June being the hottest month when maximum day temperature reaches 45\u0026deg;C [32, 33].\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStudy animals and blood sampling\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eApparently healthy Sipli sheep (n=60) being reared at the farm of the university were included in the study. The animals were being managed under intensive farming system. They were stall fed and the feeding included freshly-cut and chopped seasonal forage mixed with concentrate ration containing roughly 15% crude protein. Moreover, wheat straw and maize silage were also provided depending upon the demand. The fresh and clean drinking water remained available all the time. The routine veterinary inspection allied with regular vaccination and deworming was being maintained at the farm. Keeping the physical examination of each study animal and the data provided by the farm personnel, it was made sure that all the animals were healthy with no signs and symptoms of any diseases later confirmed through routine blood analysis.\u003c/p\u003e\n\u003cp\u003eThe study animals were restrained by the trained personnel and 5 mL of blood was aseptically drawn from jugular vein of each animal. Blood was transferred into purple-topped vacutainer tubes containing 0.5 mL of 1% EDTA solution (TUBER\u003csup\u003e\u0026reg;\u003c/sup\u003e Vac EDTA K2, Australia). Blood samples were transported to the lab where the RBC counting was performed within 8 hours.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eRed blood cell counting\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe RBC counting was carried out as per following methods:\u003c/p\u003e\n\u003col style=\"list-style-type: lower-alpha;\"\u003e\n \u003cli\u003e\u003cstrong\u003eManual method:\u0026nbsp;\u003c/strong\u003eThe RBC counting was performed with a Neubauer counting chamber/ hemocytometer (MARIENFELD, Germany) as per prescribed protocol [34] with minor modifications. Hayem\u0026apos;s solution (SDL Scientific Enterprise, Pakistan) was used as a diluent and counting was carried out with three different dilutions \u003cem\u003eviz\u003c/em\u003e. 1:200, 1:400 and 1:600 and were dubbed as RBC-1, RBC-2 and RBC-3, respectively.\u003c/li\u003e\n \u003cli\u003e\u003cstrong\u003eAutomated method:\u0026nbsp;\u003c/strong\u003eThe automated counting of RBCs was carried out using two different multispecies automated hematology analyzers (Rayto RT-7600Vet and Biobase BK-5000Vet, China), and dubbed as RBC-R and RBC-B, respectively. Both these analyzers are 3-part (lymphocytes, intermediate cells and granulocytes), multispecies analyzers meant for the blood analysis of cats, dogs, rabbits, pigs, horses, goats, monkeys, and four other self-defined animals. They use the principle of impedance for counting and differentiating blood cells and principle of colorimetry for Hb determination. They provide 23 test items/blood analysis attributes including three histograms each for WBCs, RBCs and PLT. The technical characteristics of the analyzers include a minimum whole blood volume of 10.0\u0026micro;L, pre-diluted blood volume of 20\u0026micro;L, test rate of about 1 minute/essay, and a working environment of 15-35\u0026ordm;C with humidity of 10-90%. They uses lyse solution, cleanser and a diluent for measurements and maintenance. As per their instructions manuals, accuracy of test results is attained by using the reagents provided along with the instruments. The settings for reference intervals of each species can be set manually. Values in the complete blood count report which are outside the normal range are marked automatically in the report. The quality control (QC) of the analyzer includes two methods namely L-J QC and R-X QC [35].\u003c/li\u003e\n\u003c/ol\u003e\n\u003cp\u003e\u003cstrong\u003eStatistical analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eStatistical analysis was performed using Statistical Package for Social Sciences (IBM SPSS, version 20) and Prism (GraphPad Prim 8.0.1). Normality of the data was tested visually as well as through Shapiro-wilk test. For the purpose of analyses, data was grouped as per sex (females, n=43; males, n=17) and age (up till 1year, n=10; from 1 to 2 years, n=35; above 2 years, n=15). The mean (\u0026plusmn;SE), median, range and reference intervals (RIs) (25\u003csup\u003eth\u003c/sup\u003e to 90\u003csup\u003eth\u003c/sup\u003e percentile) were deduced for the attained data keeping in view the guidelines provided by the American Society for Veterinary Clinical Pathology [36] using the Reference Value Advisor (freeware v.2.1: http://www.biostat.envt.fr/reference-value-advisor). Difference between analytical methods \u003cem\u003ei.e.\u003c/em\u003e through manual methods and hematology analyzers for overall as well as for group-wise data was attained through ANOVA followed by Bonferroni post-hoc test. The results were considered significant when p\u0026le;0.05.Pearson\u0026rsquo;s correlation coefficient and linear regression were implied to assess the level of relation between the RBC count attained through different methods of the study, and to deduce the regression prediction equations, respectively. Three tests were implied to check the level of agreement between the results of two automated hematology analyzers \u003cem\u003eviz.\u003c/em\u003e Bland and Altman (B\u0026amp;A), Cronbach\u0026rsquo;s Alpha and Intraclass Correlation Coefficient (ICC).\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003e\u003cstrong\u003eRBC1:\u0026nbsp;\u003c/strong\u003eRBC count attained through hemocytometer using dilution of 1:200 with Hayem\u0026rsquo;s solution\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eRBC2:\u0026nbsp;\u003c/strong\u003eRBC count attained through hemocytometer using dilution of 1:400 with Hayem\u0026rsquo;s solution\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eRBC3:\u0026nbsp;\u003c/strong\u003eRBC count attained through hemocytometer using dilution of 1:600 with Hayem\u0026rsquo;s solution\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eRBC-R:\u0026nbsp;\u003c/strong\u003eRBC count attained Rayto RT-7600Vet, China, hematology analyzer\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eRBC-B:\u0026nbsp;\u003c/strong\u003eRBC count attained Biobase BK-5000Vet, China, hematology analyzer\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study is a part of a collaborative research project carried out by the Department of Zoology and Department of Physiology, IUB vide approval No. PHYSIO-92/2024-52 dated 06-05-2024.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eConsent for publishing this article has been attained from all co-authors.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll the relevant data has been incorporated within the article.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors have no conflict of interest regarding this manuscript.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eResearch funding was provided through Researchers Supporting Project No. (RSPD2025R470), King Saud University, Riyadh, Saudi Arabia.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026apos; contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe present study was designed and proposed by Z.U.R., U.F., M.H.L., and H.R. The lab protocol was carried out by W.A., S.S., S.Q., and M.I. Data was analyzed by U.F., S.A., K.A.S., and S.N. The manuscript was written and reviewed by U.F., H.R., S.M.A., and S.A. Funding and resources were managed by K.A.S., and S.M.A.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003ePakistan Economic Survey. 2018-19 [\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://www.finance.gov.pk/survey/chapters_19/2-Agriculture.pdf]\u003c/span\u003e\u003cspan address=\"http://www.finance.gov.pk/survey/chapters_19/2-Agriculture.pdf]\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLivestock \u0026amp; Dairy Development Department P: First Real Time (Door to Door) Livestock Census. In. Edited by Livestock \u0026amp; Dairy Development Department P. 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Clinical evaluation of the CA530-VET hematology analyzer for use in veterinary practice. Vet Clin Pathol. 2007;36(2):155\u0026ndash;66.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBull B, Fujimoto K, Houwen B, Klee G, Van Hove L, Van Assendelft O, Bunyaratvej A, Buttarello M, Davis B, Koepke J. International Council for Standardization in Haematology (ICSH) recommendations for surrogate reference method for the packed cell volume. Lab Hematol. 2003;9:1\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eVis J, Huisman A. Verification and quality control of routine hematology analyzers. Int J Lab Hematol. 2016;38:100\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBarsila SR, Bhatt K, Devkota B, Devkota NR. Haematological changes in transhumant Baruwal sheep (Ovis aries) grazing in the western Himalayan mountains in Nepal. Pastoralism. 2020;10(1):4.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFrye EA, Behling-Kelly EL, Lejuene M, Webb JL. Complete blood count and biochemistry reference intervals for healthy adult sheep in the northeastern United States. Vet Clin Pathol. 2022;51(1):119\u0026ndash;25.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRiond B, Weissenbacher S, Hofmann-Lehmann R, Lutz H. Performance evaluation of the S ysmex poc H‐100i VD iff hematology analyzer for analysis of canine, feline, equine, and bovine blood. Vet Clin Pathol. 2011;40(4):484\u0026ndash;95.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGrebert M, Granat F, Braun JP, Leroy Q, Bourg\u0026egrave;s-Abella N, Trumel C. Validation of the Sysmex XN‐V hematology analyzer for canine specimens. Vet Clin Pathol. 2021;50(2):184\u0026ndash;97.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLee S-J, Chen P-Y, Lin J-W. Complete blood cell detection and counting based on deep neural networks. Appl Sci. 2022;12(16):8140.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMichael HT, Nabity MB, Couto CG, Moritz A, Harvey JW, DeNicola DB, Hammond JM. Improving quality control for in-clinic hematology analyzers: Common myths and opportunities. Vet Clin Pathol. 2022;51(3):302.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFarooq U, Samad H, Sher F, Asim M, Khan MA. Cholistan and Cholistani Breed of Cattle. Pakistan Veterinary J. 2010;30(2):2074\u0026ndash;7764.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFarooq U, Idris M, Rashid H. Conservation and upgradation of indigenous Cholistani cattle breed of Pakistan: a pathway to sustainable livestock. Trop Anim Health Prod. 2024;56(4):157.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBerkson J, Magath TB, Hurn M. Laboratory standards in relation to chance fluctuations of the erythrocyte count as estimated with the hemocytometer. J Am Stat Assoc. 1935;30(190):414\u0026ndash;26.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRayto RT-. 7600 Auto-hematology Analyzer Service Manual [\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://dokumen.tips/documents/rt-7600-service-manualpdf.html?page=1]\u003c/span\u003e\u003cspan address=\"https://dokumen.tips/documents/rt-7600-service-manualpdf.html?page=1]\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFriedrichs KR, Harr KE, Freeman KP, Szladovits B, Walton RM, Barnhart KF, Blanco-Chavez J. ASVCP reference interval guidelines: determination of de novo reference intervals in veterinary species and other related topics. Vet Clin Pathol. 2012;41(4):441\u0026ndash;53.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003e\u003cstrong\u003eTable 1 Overall mean (\u0026plusmn;SE), median, interquartile range (IQR), minimum, maximum, 25\u003csup\u003eth\u003c/sup\u003e to 90\u003csup\u003eth\u003c/sup\u003e percentile of reference interval (RI) and 95% confidence interval (CI) for RBC count attained through manual methods (RBC-1, RBC-2 and RBC-3) and hematology analyzers (RBC-R and RBC-B) in apparently healthy Sipli sheep (n=60)\u003c/strong\u003e\u003c/p\u003e\n\u003cdiv align=\"\"\u003e\n \u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eMethods\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eMean (\u0026plusmn;SE)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eMedian (IQR)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eRange\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(Min-Max)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eRI\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(25\u003csup\u003eth\u003c/sup\u003e to 90\u003csup\u003eth\u003c/sup\u003e)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003e95% CI\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eRBC-1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e3.96\u0026plusmn;0.16\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e3.95 (1.62)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e5.54\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e(1.72-7.26)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e3.09-5.68\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e3.64-4.29\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eRBC-2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e3.86\u0026plusmn;0.24\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e3.48 (1.36)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e10.7\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e(1.62-12.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e2.73-7.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e3.37-4.36\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eRBC-3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e4.11\u0026plusmn;0.16\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e4.02 (1.46)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e6.51\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e(2.10-8.61)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e3.21-5.82\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e3.78\u0026shy;-4.44\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eRBC-R\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e7.29\u0026plusmn;0.14\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e7.23 (1.54)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e4.90\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e(4.96-9.86)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e6.50-8.86\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e7.01-7.58\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eRBC-B\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e3.80\u0026plusmn;0.23\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e3.42 (1.79)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e9.57\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e(1.66-11.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e2.57-5.69\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e3.34-4.26\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u0026nbsp;\u003csup\u003ea, b\u0026nbsp;\u003c/sup\u003eSuperscripts indicate the significance at (P\u0026le;0.05) for different methods of RBC counting\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2 Gender-wise RBC count as deduced through manual methods (RBC-1, RBC-2 and RBC-3) and hematology analyzers (RBC-R and RBC-B) for apparently healthy Sipli sheep (n=60)\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cdiv align=\"\"\u003e\n \u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eMethods\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eMean (\u0026plusmn;SE)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eMedian (IQR)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eRange\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(Min-Max)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eRI\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(25\u003csup\u003eth\u003c/sup\u003e to 90\u003csup\u003eth\u003c/sup\u003e)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e95% CI\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"6\" valign=\"top\"\u003e\n \u003cp\u003eFemales (n=43)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eRBC 1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e4.06\u0026plusmn;0.20\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e4.01 (1.70)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e5.54\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e(1.72-7.26)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e3.20-6.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e3.65-4.46\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eRBC 2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e4.02\u0026plusmn;0.31\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e3.50 (1.94)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e10.7\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e(1.62-12.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e2.78-7.15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e3.38-4.66\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eRBC 3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e4.16\u0026plusmn;0.17\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e4.02 (1.26)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e4.95\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e(2.22-7.17)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e3.42-5.98\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e3.82-4.51\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eRBC-R\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e7.08\u0026plusmn;0.13\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e7.03 (1.23)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e3.84\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e(5.51-9.35)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e6.44-8.32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e6.81-7.36\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eRBC-B\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e3.33\u0026plusmn;0.16\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e3.08 (1.26)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e6.39\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e(1.66-8.05)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e2.56-4.56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e3.00-3.67\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"6\" valign=\"top\"\u003e\n \u003cp\u003eMales (n=17)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eRBC 1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e3.73\u0026plusmn;0.25\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e3.46 (1.64)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e4.36\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e(2.10-6.46)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e2.88-5.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e3.19-4.27\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eRBC 2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e3.47\u0026plusmn;0.31\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e3.46 (1.42)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e5.58\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e(1.88-7.46)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e2.50-5.39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e2.80-4.14\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eRBC 3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e3.98\u0026plusmn;0.39\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e3.69 (2.07)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e6.51\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e(2.10-8.61)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e2.82-6.37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e3.14-4.83\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eRBC-R\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e7.82\u0026plusmn;0.34\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e8.15 (2.05)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e4.90\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e(4.96-9.86)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e6.73-9.81\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e7.10-8.54\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eRBC-B\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e4.97\u0026plusmn;0.62\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e4.77 (2.84)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e9.47\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e(1.76-11.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e3.09-9.63\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e3.65-6.29\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003eSE=Standard Error; IQR=Interquartile Range; RI=Reference Interval; CI=Confidence Interval\u003c/p\u003e\n\u003cp\u003e\u003csup\u003ea, b, c\u003c/sup\u003e Superscripts indicate the significance at (P\u0026le;0.05) for different methods of RBC counting within gender-based groups\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 3 Age-wise RBC count as deduced through manual methods (RBC-1, RBC-2 and RBC-3) and hematology analyzers (RBC-R and RBC-B) for apparently healthy Sipli sheep (n=60)\u003c/strong\u003e\u003c/p\u003e\n\u003cdiv align=\"\"\u003e\n \u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"560\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eMethods\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eMean\u0026plusmn;SE\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eMedian (IQR)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 126px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eRange\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;(Min-Max)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eRI\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(25\u003csup\u003eth\u003c/sup\u003e to 90\u003csup\u003eth\u003c/sup\u003e)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e95% CI\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"6\" valign=\"top\" style=\"width: 560px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eG1 (n=10)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eRBC 1\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e4.34\u0026plusmn;0.36\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e4.24 (1.69)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 126px;\"\u003e\n \u003cp\u003e4.05\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e(2.25-6.30)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e3.46-6.23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003e3.51-5.17\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eRBC 2\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e3.59\u0026plusmn;0.36\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e3.36 (2.24)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 126px;\"\u003e\n \u003cp\u003e3.32\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e(2.12-5.44)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e2.55-5.39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003e2.76-4.41\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eRBC 3\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e4.44\u0026plusmn;0.35\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e4.21 (0.75)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 126px;\"\u003e\n \u003cp\u003e3.96\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e(3.21-7.17)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e3.89-6.98\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003e3.64-5.23\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eRBC-R\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e7.32\u0026plusmn;0.25\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e7.35 (1.36)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 126px;\"\u003e\n \u003cp\u003e2.53\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e(5.92-8.45)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e6.70-8.44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003e6.74-7.90\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eRBC-B\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e3.72\u0026plusmn;0.52\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e3.24 (1.32)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 126px;\"\u003e\n \u003cp\u003e5.82\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e(2.23-8.05)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e2.76-7.68\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003e2.54-5.91\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"6\" valign=\"top\" style=\"width: 560px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eG2 (n=35)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eRBC 1\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e4.00\u0026plusmn;0.20\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e3.71 (1.51)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 126px;\"\u003e\n \u003cp\u003e5.19\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e(2.07-7.26)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e3.20-5.87\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003e3.59-4.42\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eRBC 2\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e4.19\u0026plusmn;0.39\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e3.50 (2.04)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 126px;\"\u003e\n \u003cp\u003e10.7\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e(1.62-12.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e2.84-7.32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003e3.38-4.99\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eRBC 3\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e4.14\u0026plusmn;0.23\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e3.78 (2.04)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 126px;\"\u003e\n \u003cp\u003e6.51\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e(2.10-8.61)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e2.50-6.15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003e3.65-4.62\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eRBC-R\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e7.31\u0026plusmn;0.18\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e7.14 (1.76)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 126px;\"\u003e\n \u003cp\u003e4.24\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e(5.62-9.86)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e6.44-8.89\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003e6.93-7.70\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eRBC-B\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e3.74\u0026plusmn;0.22\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e3.44 (2.20)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 126px;\"\u003e\n \u003cp\u003e6.23\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e(1.98-8.21)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e2.57-5.35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003e3.28-4.20\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"6\" valign=\"top\" style=\"width: 560px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eG3 (n=15)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eRBC 1\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e3.62\u0026plusmn;0.35\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e3.70 (2.45)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 126px;\"\u003e\n \u003cp\u003e4.74\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e(1.72-6.46)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e2.22-5.95\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003e2.86-4.38\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eRBC 2\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e3.30\u0026plusmn;0.17\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e3.46 (1.30)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 126px;\"\u003e\n \u003cp\u003e2.00\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e(2.16-4.16)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e2.68-4.11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003e2.92-3.68\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eRBC 3\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e3.84\u0026plusmn;0.26\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e3.78 (1.71)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 126px;\"\u003e\n \u003cp\u003e3.57\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e(2.25-5.82)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e2.88 \u0026ndash; 5.46\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003e3.27-4.40\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eRBC-R\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e7.22\u0026plusmn;0.33\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e7.55 (1.71)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 126px;\"\u003e\n \u003cp\u003e4.84\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e(4.96-9.80)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e6.35 \u0026ndash; 9.33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003e6.50-7.95\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eRBC-B\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e3.99\u0026plusmn;0.69\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e3.41 (1.53)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 126px;\"\u003e\n \u003cp\u003e9.57\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e(1.66-11.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e2.55 \u0026ndash; 10.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003e2.50-5.49\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003eSE=Standard Error; IQR=Interquartile Range; RI=Reference Interval; CI=Confidence Interval; G1= up till 1 year; G2= from 1 to 2 years, G3= above 2 years\u003c/p\u003e\n\u003cp\u003e\u003csup\u003ea, b,\u003c/sup\u003e Superscripts indicate the significance at (P\u0026le;0.05) for different methods of RBC counting within age-based groups \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 4 Cronbach\u0026rsquo;s alpha and intraclass correlation between RBC-R and RBC-B (attained through two hematology analyzers) in apparently healthy Sipli sheep (n=60)\u003c/strong\u003e\u003c/p\u003e\n\u003cdiv align=\"\"\u003e\n \u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"4\" valign=\"top\" style=\"width: 557px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eRBC-R versus RBC-B\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 278px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eIntraclass Correlation Coefficient\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 131px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e95% CI\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 147px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCronbach\u0026rsquo;s Alpha\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 176px;\"\u003e\n \u003cp\u003eSingle measure\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 102px;\"\u003e\n \u003cp\u003e0.49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 131px;\"\u003e\n \u003cp\u003e0.27 \u0026ndash; 0.66\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 147px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.65\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 176px;\"\u003e\n \u003cp\u003eAverage measures\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 102px;\"\u003e\n \u003cp\u003e0.65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 131px;\"\u003e\n \u003cp\u003e0.42 \u0026ndash; 0.79\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u0026nbsp; \u0026nbsp; CI= Confidence Interval\u0026nbsp;\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Hematology analyzers, Red blood cell count, Sipli sheep","lastPublishedDoi":"10.21203/rs.3.rs-5444671/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5444671/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eThe RBCs of sheep are small, non-nucleated and normally round in shape, with marked variations in its shape which makes their counting bit tricky. The present method-comparison analysis aims to ascertain diagnostic precision of two multispecies automated veterinary hematology analyzers (RBC-R and RBC-B) in comparison to three manual hematological counting techniques (using hemocytometer with three different dilutions, RBC-1, RBC-2 and RBC-3) for RBC counting in apparently healthy Sipli breed of sheep (n\u0026thinsp;=\u0026thinsp;60) from Pakistan.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eResults revealed lowest CV (15.4%) for RBC-R. The RBC-R for overall and group-wise data was significantly (P\u0026thinsp;\u0026le;\u0026thinsp;0.05) higher (7.29\u0026thinsp;\u0026plusmn;\u0026thinsp;0.14\u0026times;10\u003csup\u003e12\u003c/sup\u003e/L) than other four methods, though within normal physiological range for sheep. However, the remaining four methods showed non-significant (P\u0026thinsp;\u0026ge;\u0026thinsp;0.05) difference between each other. But the values were not within the normal physiological range for sheep being far lower (4.0-5.6\u0026times;10\u003csup\u003e12\u003c/sup\u003e/L). Moderate direct relationship was revealed only between RBC-R and RBC-B as ascertained through logilinear regression, Bland and Altman test, Cronbach\u0026rsquo;s alpha and Intraclass Correlation Coefficient.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e \u003cp\u003eIt is concluded that manual methods of RBC counting in sheep using hemocytometers may not be reliable. Furthermore, the multispecies hematology analyzers catered data having higher skewness, kurtosis, CV% and accuracy/precision. We recommend a broader need within veterinary hematology for species-specific calibration and the establishment of custom RIs, particularly in regions where resource-limited settings may rely on imported multispecies hematology analyzers that are calibrated primarily for more widely studied animals.\u003c/p\u003e","manuscriptTitle":"Assessing the diagnostic precision of multispecies automated hematology analyzers for red blood cell counting in sheep: A method comparison study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-12-13 06:02:16","doi":"10.21203/rs.3.rs-5444671/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"6684959a-8a9f-43e0-8a35-dfa00080aded","owner":[],"postedDate":"December 13th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-02-17T05:23:26+00:00","versionOfRecord":[],"versionCreatedAt":"2024-12-13 06:02:16","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-5444671","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5444671","identity":"rs-5444671","version":["v1"]},"buildId":"_2-kVJe1T_tPrBINL-cwx","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}