Chapter 1:Introduction
1.1.Role of Hematology
Hematology is becoming a more essential diagnostic and treatment tool in both human and veterinary medicine around the world. The blood picture of a subject allows for clinical investigation of the presence of various metabolites and other constituents in the body of the animal and it is critical in determining the body activities, nutritive wholesome and diseased position of the animal(Hewson, 2006).
Hematological studies are not only of ecological concern, but also of physiological importance in learning about the relationship between blood characteristics and environment, which may be useful in selecting breeds of animals that are genetically resistant to certain infections and different environmental situations(Ovuru and Ekweozor, 2004).According to Afolabi et al., 2011, alterations in hematological parameters are widely utilised to assess animal body state and to identify pressures caused by dietary, pathogenic or environmental variables (Zecchini et al., 2003;Farooq et al, 2017).
The status of the body and pressures brought on by environmental, dietary and/or pathological variables are frequently assessed using changes in the hematological parameters. Age, sex, breed, climate, geographic location, season, day length, time of day, nutritional status, species’ way of life, current state of the individual and their components all have an impact on the hematological values of chicken (Islam et al., 2004)
1.2.Red Blood Cells Indices
Red Blood Cells (RBCs) also known as erythrocytes, are biconcave discs that are essential for gas exchange (Kendall, 2001).Their main product is hemoglobin (Hb), which transports oxygen and carbon dioxide throughout the body. Hb is made up of four globin subunits, usually two and two chains in adults, each of which surrounds a core haem-moiety.Iron is found in the centre of the haem and is required for gaseous movement. The characteristic redness associated with erythrocytes is caused by Hb. According to hematological analysis, young animals typically have lower RBC characteristics, which rise with age. According to credible research (Onasanya et al., 2015) these alterations are the result of the destruction of fetal RBCs.However, due to their larger RBC count, several researches have shown that male cattle have higher RBC parameters than their female counterparts. Male cattle had significantly greater RBC indices than female cattle, according to a study on Iranian cattle (Mirzadeh et al., 2010).
RBCs’ biconcave shape and flexible cell membrane allow them to expand up to 150fL or fit into capillaries with a diameter significantly less than 8mm. Macrophages remove ageing red cells from circulation as a result of their hard and inflexible membranes. With the exception of bilirubin, nearly all of the components in the 6-7 g of daily catabolized hemoglobin are recycled (Klinken, 2002).
1.2.1. Mean Corpuscular Volume (MCV)
The mean size of a RBC is checked by MCV (Yokoyamaet al., 2016). High MCV is associated with folic acid and vitamin B12 insufficiency, which is sometimes seen in individuals with a history of gastrectomy; malnutrition due to heavy alcohol intake, hypothyroidism, blood illness, and so on. High MCV has also been linked to an increased risk of various cancers (Yokoyamaet al., 2016).Furthermore, new research has discovered a link between high MCV and the prognosis of colorectal and liver cancer(Lee et al., 2015). Both prior malnutrition and the occurrence of multiple primary cancers can have adverse effect on the prognosis of esophageal cancer (Yokota et al., 2017).If a high MCV is associated with malnutrition and an increased risk of numerous main diseases,it has the potential to be a powerful prognostic marker for cancer. However, to the best of our knowledge, few researches evaluating the relationship between MCV and esophageal cancer prognosis that have been done.
1.2.2. Mean Corpuscular Hemoglobin (MCH)
The amount of Hb in a RBC is referred to asMCH. A vitamin deficiency or certain types of anemia may be indicated by high or low values.The most often used markers for thalassemia screening isMCH levels, which are low in thalassemia carriers. Those with MCH 27pg are deemed low risk and do not require further DNA testing. However, because multiple forms of thalassemia carriers with MCH levels have been found. MCH is an important measure that can be used to evaluate differences, changes, or conservation of Hb content in RBCs. MCH is changed in various clinical situations, including blood disorders(Rappazet al., 2008).
1.2.3. Mean Corpuscular Hemoglobin Concentration (MCHC)
MCHC is a measure of the average quantity of Hb in a RBC in relation to the cell’s volume.The MCHC is calculated from the Hb and hematocrit readings and represents the concentration of Hb within RBCs. As a result, a low MCHC is thought to indicate functional iron shortage (Okonkoet al.,2011).MCHC is a measurement of Hb concentration in a given volume of packed RBCs. It is traditionally computed by dividing the amount of Hb by the hematocrit. MCHC is reduced (hypochromic) in some types of microcytic anemia, where Hb loss is greater than cell volume reduction, but normal (normochromic) in macrocytic anemia, where Hb is increased but cell size is also proportionally increased.In hereditary spherocytosis and sickle cell disease, MCHC levels are increased. This is called hyperchromic condition.
1.3. Packed Cell Volume(PCV)
PCV, commonly known as hematocrit (Hct) or erythrocyte volume fraction is percentage of RBCs in the blood of an animal. It is incharge of transportation of oxygen and nutrients absorbed. Amplified PCV not only improves transportation but also increases primary and secondary polycythemia. Furthermore, a high PCV measurement indicated either an increase in the number of RBCs or decrease in the volume of circulating blood.PCV is the most accurate method of calculating erythrocyte volume and can also be used to estimate total blood volume and Hb level. The manual, spun PCV (through microhematocrit technique) is a critical measurement that underpins most of hematology.Almost all Hematology Autoanalyzer calibration can be traced back to the PCV in some way(Bull and Fujimoto, 2003). The validity of this calibration affects the reference ranges for the hematocrit and red cell indices, as well as the assignment of predicted values to calibrators and controls, and the assignment of target values for statistical population-based quality control programmes.Any inaccuracies in PCV assignment have far-reaching consequences (Farooqet al.,2023).
1.4. Desert of Cholistan and Livestock of Cholistan
Cholistan Desert, which was once a lucrative, active and thriving woodland is now almost uninhabited. It is a modal desert that presents notably to the state’s production line for live animals and their products line for living animals and the goods they provide, such as milk and meat, but its potential for production is declining despitethe reality that more creatures are living in deserts, while bioresearch is declining. Under this deteriorating condition, the greatest preciousresources in the region, such as tamed animals, may perish if their escape is not handled quickly through far-off canal colonies or the Sutluj River’s bank for the river’s provision of water and feed (Ahmadet al., 2005).
The Cholistan Desert has historically known for cultivating diverse breeds of animal and producing high-excellence goods that contribute significantly to the country’s production of beef,production of milk and wool. The overall number of livestock approximated in 2008 was 1,547,000 heads of which, 80,000 were camels, accounting for only 5% of the total animal population, compared to 5.7% in prior years. Other animal species include 43% cattle, 29% sheep, and 23% goats (Khan et al., 2008).
1.5. Objectives of Study
- To verify whether a special relationship is present between PCV and RBC count in the blood samples of Cholistani cattle or not
- To evaluate the validity of formula for determining PCV as multiple of nine with RBCcount in Cholistani cattle
- To formulate these hematological relationship in the form of certain mathematical formulae
1.6. Hypothesis of Study
Various hematological attributes of livestock have a special relationship with each other especially between PCV and RBC. This relationship can be expressed in the form of a mathematical formula.
1.7. Statement of Novelty
The present study is the first of its type reporting association between PCV and RBC for Cholistani cattle. It shows novel mathematical expression for deduction of PCV from RBC under field conditions.
Chapter 2: Review of Literature
The chapter caters to the two major aims of a review, which are to summarise prior work on related areas and to provide research gaps in study. As a result, the following chapter discusses PCV as a reliable diagnostic tool, the interaction between PCV and red blood cells(RBCs) indices (primarily in humans because work in veterinary sciences is limited), and research on Cholistani cattle in Pakistan.
2.1. Cholistan Desert
Cholistan, formerly a lush and fertile territory with the old Hakra River as its water source was the birthplace of the legendary The Hakra Valley Civilization, sometimes referred to as the Indus Ghaggar-Hakra Civilization(Wojtill, 2011).Because of its unpredictable flow, the Hakra River dried up in 600 BC. For the most part, the same could be said. The Great Indian Desert, which includes the Thar Desert in Pakistan and the Rajhastan Desert in India, is actually expanded into the Cholistan Desert (“ROHI” in local dialect) (Farooqet al., 2010). The 26100 sq. km.-large Cholistan desert is located in South Punjab. Climate-wise, it is Pakistan’s driest and warmest desert, with June temperatures reaching 50°C or higher (Malik and Ali, 2017).
It is located between latitudes 27°-42 and 29°-45 North and longitudes 69°-52 and 75°-24 East Bahawalpur, Punjab, Pakistan’s largest city, is around 30 kilometres away.The climate of the Cholistan Desert is dry subtropical, with infrequent and little rainfall, high temperatures, significant evaporation, low relative wetness, and strong winds in the summer. It is 112m above sea level and has an average yearly temperature of 28.33o C. In this region of Pakistan, which is also the driest, the maximum temperature is regularly above 45°C on any given day and can occasionally reach 50°C in June (Ahmad et al., 2005). Throughout the months of July, August, and September, the Monsoon winds force the daily maximum temperature to drop, causing evenings to drastically cool (Farooqet al., 2010).
Although the annual rainfall average is 180mm, it can go as low as 2mm (Aliet al., 2009). From a geomorphological standpointaccording to current research, the Satluj and seven dumped Hakra Rivers were recently responsible for the deposition of the mixed calcareous material from the igneous and metamorphic rocks of the Himalayas that comprise alluvium. The principal origins of the identified Aeolian sands comprised Kutch’s Rann and to a lesser extent, the lower Indus Basin (Ahmadet al., 2005). The two geomorphic portions of this desert region are separated by terrain, plant life and soil type: the Lesser Cholistan (7,770 km2) in the north and the Greater Cholistan (18,130 km2) in the south.Low lying flat fields and flowing streams in the Lesser Cholistan have improved its suitability for farming, albeit at the expense of a one-third decline in free grazing areas. At the turn of the century, however, a substantial irrigation system based on canals was built along Lesser Cholistan’s Northern boundary.
The Greater Cholistan, on the other hand, is a windswept sandy desert with a variety of old Hakra Rivers terraces, sandy ridges, and inter ridge valleys of various landforms and soils of Bahawalpur division(Aliet al., 2009).Pakistan’s second largest desert, Cholistan, is home to a semi-nomadic way of life. The raising of animals remains to be an important root of earning because of the excessive heat, a lack of water, and sand dunes that are always shifting (Afzal and Naqvi, 2004).Cholistan is home to impoverished and severely poor households that are solely dependent on raising and selling animals due to its location in Southern Punjab, a region that is plagued by poverty. Two things that the Cholistani People and their cattle lack are food and water. These are primary causes of the country’s extreme poverty. In Cholistan, there are patches of arable ground, although farming is quite uncommon due to a lack of reliable irrigation water. Because it is salty and far below the earth’s surfaceground water cannot be used for irrigation or drinking (Afzal and Rizwan, 2017).
Cholistanis have no choice but to rear their animals on the region’s natural flora and grasslands because the soil is unfit for crop growth. They are compelled by this dependency to adopt a nomadic and semi-nomadic lifestyle and to move around in search of water and grazing areas for their animals (Khan and Khan, 2015).
2.2. Cholistan’s Pastoral and Livestock Production Systems
Transhumanie and nomadic pastoralisms exist in Cholistan for cattle production. Transhumanism refers to the huge mass movement of people and cattle herds. Because forages are plentiful during the rainy monsoon months of July and August, pastoralists settle near Tobas in the desert. This system is heavily reliant on rainfall quantity and timing, and droughts have the ability to substantially disrupt it. Migration to semi-permanent villages with wells (Khoo and Kund in the native tongue) begins in the post-monsoon season (October and November). During the spring months of March and April, pastoralists shift to the periphery of canal-irrigated areas (Khan, 2009).
The larger herds of cattle, camels, sheep and goats that remain in Cholistan all year are a part of the nomadic system. The size of these herds ranges from four to one hundred and fifty animals. One or two members of each family remain in the back to keep an eye on the herds in the desert. If the herd is particularly large, an additional herdsman may be hired to assist. The rest of the family exits the transhumanie system and returns to the irrigated area, accompanied by one or two camels (Ahmadet al., 2005). Livestock is critical to the nomadic herders’ way of life and financial stability, yet the fragile environment is suffering as a result of their proliferation.Cholistan raises a variety of animal species that contribute significantly to the country’s milk, meat and wool supply (Aliet al., 2009). According to figures provided by the Deputy Livestock Office and the Cholistan Development Authority, Bahawalpur, livestock population is increasing with time despite diminishing greenery and resources(Farooq et al., 2010).
2.3. Cholistani Cattle
The Zebu (Bos indicus) is a humped Cholistani breed native to India. Cattle from the species Zebu and Taurine (Bos Taurus) descended from the same parent (Bos primigenius). Cattle accounted for 47% of the overall livestock population. According to a number of untrustworthy sources, the Sahiwal breed descended from the Cholistani breed. A detailed phylogenetic investigation and gene mapping would disclose the breed’s precise origin. In terms of phenotypic features, Cholistani cattle are a large, chubby breed with short horns, long ears and a noticeable dewlap in both sexes, as well as a distinct hump in males. They have ten red, black, or brown dots on their body and a black switch on their tail. Cholistani cows, which are genetically superior, can produce between 15 and 18L of milk each day(Farooq et al., 2010).
The thermo-tolerance genes in the Zebu breed were gained via many generations of evolution and genetic adaptation, making them better at maintaining their body temperature than the temperate Taurine breed. As a result, Bos indicus suffers from the negative consequences of heat stress less frequently than Bos Taurus, notably in terms of milk and meat output. Similarly, Cholistani cows were discovered to have this feature (Farooqet al., 2010). The Cholistani breed of cattle was able to survive substantial heat stress with little influence on productive and reproductive performance due to its thermo-tolerance and tick resistance.Numerous researches have been conducted on the performance of the Sahiwal and Red Sindhi Cattle breeds in their native habitat (Aslamet al., 2002; Zafaret al., 2008). There was more work to be done in the Cholistani cattle’s environment, which was a tropical desert (Farooqet al., 2010).
Farooqet al.,(2010) discovered that Cholistani cattle are comparable to Sahiwal and Red Sindhi Cattle in terms of reproductive and productive features such as calving interval, age at maturity, gestation time, age at first calving, and age at first service. Lactation length, lactation yield, dry period, wet average, overall average and fat content in milk are all productive features. However, additional highly structured research within the local climate will necessitate concerted efforts. Furthermore, gene mapping and marker-based selection will open up new avenues for studying its performance features. It may improve the neighborhood’s socioeconomic condition as well as the scarcity of milk and meat.
Cholistan has a long history of cultivating a wide range of cattle, significantly boosting the nation’s production of milk, meat, and wool in spite of erratic rainfall, low humidity, and harsh weather. In total, 1,547,000 animals were expected to be lived here as livestock in 2008 (Khan et al., 2008). 43% of them were cattle.It is believed that the thermotolerant, tick-resistant Cholistani cow breed is the ancestor of the Sahiwal cattle.. Early data on numerous reproductive and productive features of Cholistani cows housed at the Jugait Peer Government Livestock Station, from 2005 to 2009, the average values for the productive traits lactation length, lactation yield, dry period, service time and fat content in milk in Bahawalpur were 165 days, 1235L, 155 days, 121 days and 4.8%, respectively. The average values for reproductive characteristics such as age at maturity, age at first calving, gestation period and calving interval were likewise equivalent to those of Sahiwal and red Sindhi cattle, which were 11,121,390,278, and 422 days, respectively (Farooqet al., 2010).
2.4.Hematological Formulae
A hematological rule of three has been verified in human medical practise for healthy human population. Estimating hemoglobin(Hb) levels as 1/3rd of PCV is one such formula. The link between PCV and Hb in indigenous cattle has been researched for veterinary medical sciences.Studies and pen-side hematological formulae for Hb estimation for goats and Cholistani breed of cattle have been reported by our laboratory. Astudy was devisedin order to assess the association between Hb concentration and PCV in camels raised under pastoralism and to develop a straightforward pen-side hematological formula for estimating Hb from PCV.In contrast to Hb estimation using the cyanmethemoglobin method (HbD), the PCV was calculated using the microhematocrit method.Additionally, the Hb was computed as 1/3 of PCV and was known as calculated Hb (HbC)(Farooq et al., 2023).Overall, there was a significant difference between HbD and HbC (P≤0.05). For all study groups, including males and females as well as juvenile and adult camels, similar results were obtained.
Through the use of the regression prediction equation obtained from the linear regression model, the corrected Hb (CHb) was calculated.Instead of calculating Hb concentration as one-third of PCV, a more straightforward pen-side haematological formula is advised: Hb concentration (g/dL)=0.18(PCV)+5.4 for all age and gender categories of camels(Farooq et al., 2023).Another investigation was made. The study’s major goals were to determine whether there is a clear and consistent correlation between total erythrocyte count (TEC) and Hb concentration in the blood of cholistani cattle and to explore the utility of TEC for calculating Hb levels in groups of cholistani cattle based on age and gender.The Veterinary Hematology Analyzer was used to estimate the TEC and Hb.
Additionally, the Hb was computed as TEC*3 and designated as HbC.HbD and HbC showed a difference that was statistically significant (P≤0.05).Between HbD and CHb, a non-significant (P≥0.05) difference was found.For Cholistani cattle, the rule of thumb that Hb concentration should be three times of TEC was incorrect.However, an alternative pen-side hematological equation, Hb(g/dL)=0.66(TEC)+6.1 yields a more accurate estimation of Hb from the TEC in cattle blood (Farooq et al., 2023).
Another study was designed to assess the connection between PCV and Hb levels in beetal goats raised under pastoralism. Additionally, it attempts to develop a hematological formula for PCV based Hb estimate.Both male and female goats were bled for the purpose of determining PCV using the microhematocrit method and estimating Hb using the Sahlis hemoglobinometer (HbD) and a computation that is 1/3rd of PCV.Both the HbD and HbC for male and female beetal goats were not statistically significant (P≥ 0.05)(Ahmad et al., 2022).In response, they suggested using a more straightforward formula for calculating Hb concentration in beetal goats: Hb concentration=0.24(PCV)+1.5 rather than calculating it as one-third of PCV.
In the Cholistan Desert, Pakistan, a study was conducted to develop a haematological formula for the calculation of Hb from PCV in Cholistani breed cattle. It also attempts to confirm the validity of the in human medicine used rule of calculating Hb concentration as one-third of PCV and vice versa.Cholistani cattle were bled for the purpose of determining PCV using the microhematocrit method, estimating Hb using the Hematology Analyzer (HbD) and calculating PCV as one-third of HbC. For all research groups, the independent-sample t-test was assumed to determine the difference between HbD and HbC as well as between HbD and corrected Hb (CHb).In conclusion, it cannot be assumed that Cholistani cattle follow the rule of human clinical medicine that Hb concentration is a third of PCV and vice versa. For accurate Hb estimation from the PCV in cattle, an alternative equation, i.e. Hb(g/dL)=0.13(PCV)+6.3, may be used (Ahmad et al., 2022).
In Africa, studies were conducted to see if there was a proportional link between PCV and Hb concentration in blood samples from cattle and to evaluate the reliability of the conventional wisdom that Hb concentration should be taken as a third of PCV.Specifically, PCV was measured using the microhematocrit technique and haemoglobin concentration was determined using the cyanmethemoglobin method in Ghana utilising cattle from four different breeds (Ndama, 110; West African Short Horn, 110; Zebu, 110; and Sanga, 110).Scatterplots were used in trend line analyses to produce linear regression equations. A substantial and persistent correlation between Hb concentration and PCV (%) was discovered for all the animals.As a result, a simplified formula for estimating Hb concentration from cattle PCV can be Hb (g/dL)=(0.3 PCV)+3 (Turkson and Ganyo, 2015).
In order to determine whether there is a proportional relationship between Hb concentration and PCV in avian blood samples, blood samples from 128 birds representing 13 avian orders were collected. Hb concentration was measured using a point-of-care portable hemoglobinometer, and the corresponding PCV was determined. A significant and persistent association between Hb concentration and PCV, defined as Hb= (0.304* PCV)+0.461 was discovered for all birds studied and aggregated across orders.Nine bird orders with an average of n > 8 samples each were subjected to a linear regression analysis to ascertain whether the association between PCV and Hb differs. According to a single slope that can be used to predict the link between avian Hb and PCV for these taxonomic orders, the individual slopes for the 9 orders did not differ substantially from one another (P≥0.44). Except for order Phoenicopterif ormes, which was the only intercept that was substantially different from 0 (P≤0.01), a single intercept can also be employed. These findings show that a condensed relationship of Hb (g/dL)=0.30* PCV yields an accurate estimate of Hb concentration from the PCV of birds belonging to the orders Anseriformes, Columbiformes, Falconiformes, Galliformes, Passeriformes, Psittaciformes, Sphenisciformes, and Strigiformes, but a different relationship is also (Velguth et al., 2010).
Hb concentrations determined by the hemoglobinometer in horses for samples from clinic patients were lower than those determined by the cyanmethemoglobin method; however, there was a linear relationship between concentrations determined by the 2 methods. Breed, sex, body weight and the length of sample storage had no discernible impact on the variance in Hb concentrations between the two procedures. PCV=[2.83*Hb]- 0.62] shown a significant linear association between PCV and hemoglobinometer Hb concentration. When the Hbconcentration exceeded 16 g/dL, a significant negative bias with the hemoglobinometer was visible for samples from the healthy horses (Chevaliar et al., 2003).
Table 2.1:Research Work Conducted on Hematological Formulae in Various Spp.
| Sr No. | Species(n) | Formula to Validate | Formula Devised | References |
| 1 | Cholistani Camel (n=215) | Hb = PCV/3 | Hb= 0.18(PCV)*5.4 | Farooq et al., 2023 |
| 2 | Cholistani Cattle (n=264) | Hb =TEC*3.3 | Hb= 0.66(TEC)*6.1 | Farooq et al., 2023 |
| 3 | Beetle Goat (n=100) | Hb = PCV/3 | Hb=0.24(PCV)+1.5 | Ahmadet al., 2022 |
| 4 | Cholistani Cattle (n=364) | Hb = PCV/3 | Hb= 0.1(PCV) + 6.3 | Ahmadet al., 2022 |
| 5 | African Cattle (n=440) | Hb = PCV/3 | Hb=0.3(PCV) + 3 | Turkson and Ganyo, 2015 |
| 6 | Birds (n=128) | Hb = PCV/3 | Hb=0.30(PCV)+0.461 | Velguth et al., 2010 |
| 7 | Horse (n=55) | Hb = PCV/3 | PCV =2.83(Hb)– 0.62 | Chevalieret al., 2003 |
2.5. Role of Hematology in Diagnostics
In order to analyse the physical and health conditions of animals and birds, the evaluation of hematological and serum biochemical indicators, as well as the detection, prediction, management and prophylaxis of various livestock illnesses have all been thoroughly published (Zvorc et al., 2006).
Hematological testing is useful not just for diagnosing blood and bone marrow disorders in cattle, but also for detecting other organ and system issues. Although a person’s total blood count is rarely used to diagnose illness a hemogram can provide significant information for analysis, examination and making projections about how an infection will evolve over time in a specific person. It is well accepted that automated cell counts are used in veterinary surgeries. As a result, anomalies in blood volume, Hb content and cell count that can be identified by automated cell counters have been observed in a number of studies.
If aberrant results or blood cell dysfunction are discovered, a microscopic inspection of the blood smear is strongly indicated. A point-of-care tool capable of providing quick and accurate Hb concentrations and PCVs would be beneficial in animal medicine. In a previous investigation, the gold standard (GS) method and a human instrument called Mission Plus (MP) were used to measure the levels of Hb and PCVs in cattle blood. Clinically healthy bovine blood samples were obtained for this purpose, either with or without the anticoagulant (K2EDTA). To help with field diagnostics, the MP gadget can be used to measure the PCVs and Hb concentrations in cow blood (Baueret al., 2021).
Given the details about the inflammatory process, blood tests are crucial in the early diagnosis of the condition. Leukocyte count, traits like neutrophil or lymphocyte dominance, inflammation, collateral organ damage (acute renal failure, acute liver failure) and illness severity are all included in this data. Additionally, biomarkers reveal the type of pneumonia, allowing doctors to analyse blood test data to establish whether a condition is caused by bacteria or another cause (Bekdas et al., 2014). Stress causes circulating leukocytes to produce more neutrophils and fewer lymphocytes; the ratio of these two measures is also used as an indicator of inflammation (Xianget al., 2013).The fundamental benefit of hematological indicators is their low cost, making them widely and conveniently accessible in routine clinical use. Additionally, they have demonstrated their diagnostic and prognostic utility in a number of cardiovascular conditions (Budzianowskiet al., 2017)
Due to their impact on the instability of atherosclerotic plaques, leukocytes are essential in the pathogenesis of acute coronary syndrome. Leukocytes first penetrate endothelial cells and then become activated when they reach the tunica intima. They cause the development of micro vascularity there, increasing the susceptibility of plaques to rupture (Madjidet al, 2004).By dividing the neutrophil count by the lymphocyte count in a differential white blood cells (WBC) sample, NLR can be calculated with ease. One of the most highly regarded hematological biomarkers; it offers predictive and diagnostic data in ACS. In the recent years, a great deal of research has been done on its function in cardiovascular illnesses (Gurmet al., 2003).
2.6. Packed Cell Volume: Estimation and Vitality
PCV which is measured using the microhematocrit technique can be used to estimate a variety of other blood parameters (Yasiniet al., 2012).Calculating PCV, crucial component of a complete blood count profile, helps one to estimate an animal’s health. Anemia, (a harmful condition) develops in people when their PCV concentrations are found to be below particular defined thresholds. Variations in the traditional linkages between PCV and RBC size are commonly used as calculated erythrocyte indices to better precisely describe hematopathology in mammalian species (Thrall et al., 2012).
PCV, a widely used clinical examination, is commonly utilised in anemia surveys due to its simplicity and universal accessibility of its essential components. A PCV result below the normal range indicates anemia, whereas a value over the reference interval indicates polycythemia (Bainet al., 2006).The handy microhematocrit centrifuge is excellent for usage in the field. To function, it requires a steady power source and a quick easy training period. A drop of blood (0.5mL) is placed in a capillary tube, which is closed at one end and centrifuged for a brief length of time (WHO, 2007).
According to published studies, the microhematocrit centrifuge technique has a high level of precision and accuracy for clinical use. Furthermore, it is a less harmful approach that workers with less training can use. As a result, when automated techniques for measuring PCVare unavailable, approximated PCV is determined based on observed RBC values. In large-scale population studies, computing PCV is more cost effective because hematocrit operating costs are generally cheap in rural areas (WHO, 2000).
Centrifuged PCV has an integrated bias that results in a considerable shift in PCV levels due to the confined plasma that may have been increased by aberrant RBC morphology. The PCV tested with a centrifuge was found to be 1-3% higher. When dealing with certain settings, however, the spun PCV often yields up to 6% fudged results that are superior to those produced under regular conditions. High spun PCV readings can also be caused by poor centrifugation.Abnormal PCV readings may be caused by variables such as a high white blood cell count, agglutinated RBCs and a high platelets count, which result in an incorrect RBC count and MCV result from an Automated Analyzer.
In contrast to transportable hemoglobinometers, the manual estimation of PCV using microhematocrit technique does not involve the transfer of blood samples and the findings are also provided in a relatively short amount of time. The need for a sufficient centrifugal force to prevent a large volume of plasma from becoming caught between the erythrocytes is one fault in manual PCV estimation. This restriction, however, can be lifted by using a secure power supply (WHO, 2007).
In an automated system, the PCV is an approximated value. The volume of each red cell is measured as it is counted to calculate the mean red cell volume (Prihirunkit, 2008). PCV can also be calculated by multiplying MCV by RBC count. The two methods are not fundamentally equivalent. As a result, anything that changes the red cell count or red cell volume measurement will have an effect on the PCV calculation. In addition to PCV, Automated Hematology Analyzers, which are now commonly used in veterinary services and are based on Coulter’s impedance idea, can be used to obtain a range of additional unique blood parameters (Bleulet al., 2002).
When evaluating the Automated (Cell-Dyn 3500) Hematology Analyzer for cattle,(Bleul, 2002) observed strong positive connections between PCV, erythrocytes, leukocytes, neutrophils, eosinophils and lymphocytes. While acceptable correlations were revealed between platelets, monocytes, and basophilic granulocytes, no substantial link between these two cell types was discovered.
In a study on canine and feline blood Prihirunkitet al., (2008) compared the manual (microhematocrit) approach to the Automated (Cell Dyn 3500) Hematology Analyzer for detection of Hb. The outcomes of the study also demonstrated that, while the PCV values acquired using both processes were accurate and exact, those obtained using an Automated Hematological Analyzer could not be substituted for those obtained using a manual procedure.
In a study conducted in Nigeria, Ikeet al., (2010) compared the measured PCV acquired using a manual approach to that obtained using an Automated Analyzer (Sysmex KX-21N) and they discovered a statistically significant difference in the PCV levels obtained using the two methods. A significant positive correlation coefficient was discovered between manual and automated approaches for estimating PCV.Borgeset al., (2014) found a high association between PCV, RBC and WBC, similar to Bleulet al., (2002).
Gebretsadkanet al., 2015 conducted a comparative cross-sectional study in Southern Ethiopia to compare and contrast the analytical capabilities of a microhematocrit and Hematology (Mindray BC-3000 plus) Analyzer, which compute PCV indirectly by counting and measuring the size of RBCs. The PCV of the original sample was calculated using the following formula: PCV = the numbers of RBCs multiply by 9.
There was a disparity between the PCV values acquired using a manual approach and an Automated Analyzer (Sysmex XP 300TM), according to (Karemet al., 2016).In a study, (Kakel, 2013)found higher PCV level than (Karem, 2016) who used a manual technique. Kakel’s research employed an automated method. A correlation coefficient was observed in the PCV values estimated using both methodologies but no meaningful association was established.Because the majority of automated equipment is designed for human blood, it is required to fine-tune these analyzers for the assessment of animal blood samples (Bull, 2001;Birhaneselassieet al., 2013).
PCV is a readily obtainable metric for detecting anemia or polycythemia and can be useful in evaluating changes in hemodilution or hemoconcentration. It is utilised and combined with the RBC count. It is, in reality, the volume of erythrocytes in a sample expressed as a percentage of the volume of whole blood. It is the most precise method of calculating RBC volume and can also be used to calculate total blood volume and Hb levels.
Centrifugation can be used to measure PCV directly. Some automated equipment make indirect measurements of the PCV; approaches include determining red cell volume and count on a cell-by-cell basis using electrical conductivity measurements or optical extinction measures (Verbrugge and Albert, 2015). These two readings are then used to calculate the PCV. These methods, while not considered correct in the technical sense of the term, are widely recognised alternatives as part of the “automated complete blood count;” the measured quantity is frequently referred to as the hematocrit.
The manual, spun PCV is a critical measurement that underpins most of hematology. Although manual, spun PCV is simple and inexpensive to perform, it is influenced by a number of factors, including trapped plasma (Verbrugge and Huisman, 2015), white blood cells and platelets contamination of the red cell layer (Grunwaldtet al., 2005), an indistinct margin between red and white cell layers (Bull, 2001), non-flat tube seals (Bullet al., 2003), red cell dehydration (Junioret al., 2020).
PCV levels are influenced by a number of variables. Higher Hb and PCV levels than the reference values could be attributable to the animals’ ages (Grunwaldtet al., 2005). (Ottoet al. et al.,2000), on the other hand, found no age influence on PCV values. There were no differences in PCV values between Aberdeen Angus and Criollo Argentino (Grunwaldtet al., 2005). (Ottoet al., 2000), on the other hand, discovered a PCV value of 32% in Mozambique Anguni cattle, which tended to be lower than Aberdeen Angus Cattle, indicating breed differences. The reference limits for PCV and Hb concentrations in indigenous cattle grown in rural production conditions in Southern Africa are mostly unknown.
Anemia, hemorrhage, bone marrow failure, erythrocyte destruction, leukaemia, malnutrition or particular nutritional insufficiency, multiple myeloma, and rheumatoid arthritis can all be caused by PCV (Bull and Hay, 2001; Ndlovuet al., 2007). PCV values that are greater than the standard values may suggest dehydration caused by diarrhoea, erythrosis or polycythermia. Low hematocrit can be caused by vitamin or mineral insufficiency, cirrhosis of the liver and cancer (Bull and Hay, 2001). A decrease in Hb implies a deficiency in amino acids, vitamins (particularly B12, E, folic acid, and niacin) and/or minerals (Bullet al., 2003).
Animal RBCs include the metalloprotein Hb, which transports oxygen and contains iron. Anemia symptoms are caused by a drop in Hb with or without a decrease in RBC. Anemia can be caused by a variety of factors, the most prevalent of which is iron deficiency. Because iron deficiency reduces heme synthesis, hypochromic RBC (those without the red Hb pigment) and microcytic RBC (those smaller than normal) are produced (Kneippet al., 2006).Blood-borne diseases such as trypanosomiasis, babesiosis, anaplasmosis and others have been shown to have significantly lower PCV than normalhealthy animals (Marcotty et al., 2008; Ozkanet al., 2015).(Tejedor-Juncoet al., 2011) concluded that, while PCV is a sensitive, reliable and specific molecular diagnostic test, a decrease in PCV in infected animals is also an important indicator of a blood-borne disorder in livestock.
A study was carried out to investigate the prevalence and importance of cow haemoparasites. According to usual protocol, the samples were processed for PCV and thin smear stained with Geimsa stain. PCV values are less than 20% in all animals positive for blood parasites. There was a significant difference (P≤0.05) in PCV between infected and non-infected animals, with infected animals having much lower levels. Similar findings were made for cattle in Pakistan when researching the frequency of tropical theileriosis in Cholistani cattle (Saeedet al., 2015).
Blood parameters changed in 18 crossbred dairy cows in northwest Iran were studied after short-term road travel stress (Ali-Gholiet al., 2007). On five different days, cows were moved in four groups of four cows and one group of two cows. Each group was transported for one hour by vehicle up to a distance of 40 km round trip. Before transit, blood was drawn in 5mL increments from each cow’s jugular vein and bleeding was repeated at 1.5 hourintervals up to 7.5 hours later. PCV was shown to be significantly lower in all cows due to travel stress, confirming PCV as a crucial stress indicator.
A prospective case control study of 125 horses with gastrointestinal tract induced colic was carried out to see if heart rate (HR) and PCV can predict surgical vs medical treatment and short-term survival (time of patient discharge) (Koset al., 2022). 64 horses were treated medically and 61 surgically (29 cases of small intestinal obstruction and 32 cases of big intestinal obstruction). Both PCV and HR were higher at admission in horses treated surgically than in horses managed medically; however, with a longer duration of colic before presentation, PCV was higher exclusively in the small intestinal surgery group. Furthermore, non-survivors had greater PCV and HR, as well as a longer duration of colic than survivors.Binary logistic regression revealed a significant (P≤0.05) relationship between HR and PCV.
In Turkey, a study was done to assess changes in serumnitric oxide (NO) levels in cattle with theileriosis in relation to PCV levels.For this reason, 10 healthy cattle and 42theileriosis-affected cattle were used. It was determined that NO levels increased and PCV levels fell considerably (P≤0.05) in theileriosis, and that further research into the significance of NO release, as well as measures for limiting its release, should be conducted in the future (Ozkanet al., 2015).
While researching PCV reference intervals, researchers in Europe and North America discovered that for non-iron-deficient adult Caucasian males, the normal mean PCV is 0.46 and the 2.5-97.5 percentile interval is 0.40-0.53 (Fairbanks and Tefferi, 2000). For adult Caucasian females, the corresponding values are: mean PCV 0.42; 2.5-97.5 percentile interval 0.36-0.48. Polycythemia studies in adult Caucasian males with PCV0.55 (Hb Conc. 180g/L) or adult Caucasian females with PCV0.50 (Hb Conc. 16.5g/L) are not typically appropriate.The application of this theory will reduce the amount of unnecessary and costly investigations that would otherwise be undertaken in patients whose PCV values are only in the top percentiles of the normal range,\ and will aid in the avoidance of misdiagnoses and therapeutic errors.
In Enugu, Nigeria, a study was undertaken to investigate the accuracy of capillary blood for the detection of true PCV and anemia among pregnant women (Dimet al., 2017). From May to June 2012, 200 consecutive pregnant women’s venous and capillary blood pairs were tested for PCV at the UNTH prenatal clinic in Enugu, Nigeria. Standard measurements were utilised to test the accuracy of capillary PCV (cPCV) using venous blood as the gold standard. Participants’ cPCV (median=34.0%, IQR=31.0-35.8) differed substantially from their venous PCV (median=34.0%, IQR=32.0-37.0), P 0.001. The average percentage error for cPCV was 34.44%.PCV has a sensitivity and specificity of 93.0% and 89.5% for determining anemia, respectively. In Enugu, Nigeria, the cPCV has a pretty high accuracy for determining anemia in pregnancy (Dimet al., 2017).
2.7. Work Conducted in Pakistan
A lot of study has been done on numerous indigenous livestock breeds in Cholistani regionaccording to the literature. Despite numerous research studies, using PCV to estimate Hb levels is one such formula in Cholistani camel (Farooq et al., 2023).Second, analyse the association between PCV and Hb levels in beetal goats (Farooq et al., 2023).An additional investigation was conducted to develop a pen-side hematological formula for estimating Hb from PCV in cattle of the Cholistani breed (Ahmad et al., 2022). However, to date, no study has examined the interactions between PCV and RBC in Cholistani cattle, which constitutes the primary goal of the current investigation.
Chapter 3:Material and Method
3.1. Geo-location of Study
The following locations hosted simultaneous research operations:
- a) Cholistan Desert (On field Herds of cattle at the TOBAS for blood collection) b) Physiology Post-graduate Lab, Department of Physiology, The Islamia University of Bahawalpur, Pakistan
The desert can be found at latitudes 27°42′ and 29°45′ North and longitudes 69°52′ and 75°24’East and an elevation of 112m above sea level. This region’s climate is desert, hot subtropical and monsoonal with an annual rainfall of 180mm.But the amount and length of rainfall varies greatly with notable droughts happening around every ten years. The hottest month is June, when daily maximum temperature surpasses 45°C. The average yearly temperature is 28.33°C (Farooqet al., 2012). In addition to sedge, herbs, shrubs, and trees, the Cholistan Desert’s common flora includes both annual and perennial grasses (Arshad and Akbar, 2002; Farooqet al., 2010).
3.2. Experimental Animals
The current study was conducted on Cholistani cattle raised in the Cholistan Desert of Pakistan under a transhumanie and nomadic pastoral livestock system.The health status of each research animal was ascertained by utilising anamnesis in conjunction with the history that was obtained from the livestock owner/herder. Only healthy and active animals were included in the study; animals that showed signs of listlessness, sadness, being off-feed or being isolated from the herd were not. Cattle ages were determined and confirmed using information provided by their owners.
3.3. Blood Collection
Research animals were confined in the field for blood collection, with the assistance of livestock owners, in accordance with the working and field situations. Cattle blood was collected aseptically using a disposable syringe from the upper neck jugular vein. Each animal had a blood sample obtained of about 5mL. The blood sample was transferred to apurple-topped container containing 0.5mL of 1% EDTA solution (Becton Dickinson, USA) as an anticoagulant.A total of 54 blood specimens were collected. Blood that was not in clotted form was stored and used for hematological studies.
With the same staff and timing, the same restraint method was applied to reduce animal discomfort. Take into consideration daily variations in blood samples and uphold standard blood collection procedures. The samples were carefully inverted and carried in an ice boxto the Physiology Post-graduate Laboratory, The Islamia University of Bahawalpur, Pakistan, wherethey were chilled and subjected to a 24-hour hematological study.
3.4. Hematological Analyses
Using an Automated Hematology Analyzer (Rayto, Modal: RT- 7600, China) blood samples were analysed for several hematological characteristics. Packed cell volume and red blood cells were two hematological characteristics studied. The blood vacutainers were placed on an electrical test tube roller mixer (DAIHAN Scientific, Modal: Mix R-40, Korea) for this purpose.The analyzer automatically issued the results receipt.
3.4.1. Packed Cell Volume
Microhematocrit centrifugation technique wasused to calculate PCV (Bull, 2001).To drain the blood sample, microhematocrit heparinized capillary tubes were employed. Blood was brushed away from the capillary tube’s tip. The capillary tube was kept in a microhematocrit centrifuge with the closed end facing out. The microhematocrit (Model: PRO ANALYTICAL.C1015, United Kingdom) was spun for five minutes at 3000-4000 rpm(figure 3.2).After that, the capillary tube was removed from the centrifuge machine, placed on a hematocrit reader, and the PCV was measured.
3.4.2. Red Blood Cell Count
A hemocytometer is a device used to count cells under a microscope, particularly RBCs. Neubauer’s slide, cover slip, diluting or thoma pipette, and cover glass make up this set. Because blood samples include a relatively large number of RBCs, manually counting them is exceedingly challenging. In order to accomplish this practically, a blood sample is diluted (often 1:200) using RBC diluting fluid, also known as Hayem’s fluid. RBCs do not suffer any harm from this solution because it is isotonic to them.
Blood is first diluted at a ratio of 1:200. Diluting fluid is drawn up to the 101 mark, and blood is drawn exactly up to the 0.5 mark on the Thoma pipette. Anticoagulated whole blood and fluid are combined. Two droplets of the mixture are thrown away. A cleaned hemocytometer was used to load the remainder. Positioned on a microscope stage, the hemocytometer was used to focus a 40X lens counting chamber on a big centre square that was divided into 25 smaller squares, each of which was further divided into 16 smaller squares. Out of 25 squares, 4 corners and 1 middle square had their RBCs counted.
Calculation
Total RBC Count = Average count *200*25*10
Where
200 = Diluting Factor
25 = Area Multiplication Factor
10 = Depth of Chamber
3.5. Statistical Analyses
The Statistical Package for Social Science (SPSS for Windows version 12, SPSS Inc., Chicago, IL, USA) was used to analyse the data. The means (±SE) and 95% CI for the hematological characteristics (PCV and RBC) of Cholistani cattle were calculated utilising the provided formulae. Using the Shapiro-Wilk test, the normality of every researched attribute was determined.The Mann Whitney-U test was assumed to be a non-parametric test for the purposes of analysis in order to determine the difference between PCV-GS and RBC and PCV-GS and RBC-Cfor each of the study groups (young = 140, adult = 124; females = 142, males = 122).As previously instructed, scatterplots were created between the following and linear regression analyses were performed (Bland and Altman, 1999).
- PCV-GS and RBC
- PCV-GS and PCV-C
As a result, regression prediction equations were generated. Using these calculations to get the maximum adjusted r-square value,C-PCV was computed.
Chapter 4: Results
4.1. Summary
The packed cell volume, which was manually estimated in this study as9th of red blood cells, was evaluated for statistical significance (P≤0.05). Moreover, the link between PCV and RBCs was examined using the microhematocrit technique of PCV. As a result, regression models were created to verify this formula across all research groups. The following outcomes are detailed. Table 4.2 displays the mean (±SE) and 95% confidence interval (CI) for the haematological characteristics (PCV and RBC) of Cholistani cattle (n = 264).
4.2. Normality Testing
When it came to the normalcy of the two analysed qualities (PCV and RBC), the results of the Shapiro-Wilk test showed that they were not both normally distributed, as shown in Table 4.1.
Table 4.1: Overall Results of Normality Testing (Shapiro-Wilk Test) for the Hematological Attributes of the Study in Cholistani Cattle (n= 264)
| Attributes | Statistic | Sig. | Skewness | Kurtosis |
| RBC Count | 0.991 | 0.130 | 0.205 | 0.311 |
| PCV | 0.846 | 0.00 | 2.203 | 9.595 |
RBC= Red Blood Cells; PCV= Packed Cell Volume
4.3. Difference in Hematological Attributes
Mean (±SE) values and 95% CI for hematological attributes (PCV and RBC) in Cholistani cattle (n= 264) are presented in Table 4.2.A substantial (P≤0.05) difference was found between PCV and RBC in the total data. Moreover, comparable outcomes were obtained across all study groups in this investigation (adults versus children, and females against men).
Table 4.2: Mean (±SE) Values and Confidence Intervals for Various Hematological Attributes in Cholistani Cattle (n=264)
| Groups | PCV-GS
(g/dL) |
PCV-C
(g/dL) |
Sig | RBC Count
(%) |
||||
| x±SE | CI | x±SE | CI | x±SE | CI | |||
| Gender | Females (n=142) | 35.1±0.89 | 33.3-36.9 | 64.7±1.13 | 62.5-66.9 | 0.00 | 7.19±0.13 | 6.94-7.44 |
| Males (n=122) | 36.6±0.77 | 35.1-38.2 | 70.8±1.27 | 68.36-37.4 | 0.00 | 70.8±014 | 7.59-8.15 | |
| Age | Young (n=140) | 36.6±0.95 | 34.7-38.5 | 72.3±1.12 | 70.17-74.59 | 0.00 | 8.04±0.12 | 7.79-8.28 |
| Adult (n=124) | 34.9±0.68 | 33.5-36.2 | 62.17±1.17 | 59.8-64.5 | 0.00 | 6.91±0.13 | 6.65-7.16 | |
|
Overall (n=264) |
35.8±0.59 |
34.6-37.02 |
67.5±0.86 |
65.8-69.3 |
0.00 |
70.51±0.96 |
7.32-7.69 |
|
*Significant at P≤0.05 within rows for each group between PCV-GS and PCV calculated.
PCV-GS= Packed Cell Volume-Gold Standard; RBC= Red Blood Cells; PCV-C= Packed Cell Volume calculated
4.4. Regressions and Prediction Equation
The results for linear regression for all study groups are presented in Table 4.3. For young calves, a significantly (P≤0.01) stronger positive correlation coefficient was observed between PCV-GS and RBC as well as between PCV-GS and RBC-C (r=0.506; adjusted r-square=0.251).For every research group, regression equations were created to verify the 9thcorrelation between PCV and RBC. In order to calculate PCV, also known as corrected PCV, the overall results regression equationi.e.PCV= 3.8(RBC)+6.8 was utilized to derive PCV. Between PCV and RBC, a non-significant (P≥0.05) difference was observed. Therefore, it is believed that this equation is reliable for estimating PCV from RBC in all age and gender categories of Cholistani cattle.
Table 4.3: Linear Regression between Various Hematological Attributes for Cholistani Cattle (n= 264)
| Groups | PCV-GS vs RBC Count | PCV-GS vs PCV-C | R | Adjusted r Square | |
| Gender | Females (n=142) | y=4.07; x+ 5.8 | y=0.45; x +5.8 | 0.575 | 0.326 |
| Males (n=122) | y=3.80; x + 6.63 | y= 0.42; x+6.63 | 0.702 | 0.489 | |
| Age | Young (n=124) | y=3.80; x+ 5.68 | y=0.42; x+5.68 | 0.506 | 0.251 |
| Adult (n=140) | y=4.64; x+ 2.85 | y=0.51; x+2.8 | 0.878 | 0.769 | |
| Overall (n=264) | y=3.8; x+ 6.8 | y=0.43; x+6.8 | 0.622 | 0.385 | |
*Significant correlation at P≤0.01.
PCV-GS= Packed Cell Volume-Gold Standard; RBC= Red Blood Cells; PCV-C= Packed Cell Volume calculated
4.5. Scatterplots
The scatterplots of manually determined PCV-GS and RBC and PCV-GS and RBC-C calculated as 9th of RBC have been given in Figure 4.2 and 4.3, respectively. Similarly, Figure 4.3 displays the scatterplots and the Bland and Altman Chart for the differences between PCV-GS and RBC and PCV-GS and RBC-C. The PCV-GS and RBC showed a good degree of agreement on the Bland Altman chart, and the data distribution around the mean difference line showed no proportional bias
The results of the Bland Altman test showed a good degree of agreement between the two PCV detection methods—the auto hematology analyzer and our calculated formula. The distribution of the data around the mean difference line showed no proportional bias.
Chapter 5: Discussion
5.1. Background
In both human and veterinary medicine, a thorough physical examination combined with an accurate medical history can reveal a patient’s state of health. One of the essential and accurate instruments that is being utilised extensively worldwide to obtain a conclusive diagnosis is blood analysis (Hippel, 2007; DeNicola, 2011).
Compared to veterinary medicine, human clinical haematology has advanced significantly in the medical sciences. Over the past ten or so years, there has been a noticeable trend in veterinary haematology and its use as a diagnostic tool for numerous blood-borne illnesses.As a result, the 3-part and 5-part automated veterinary haematology analyzers have replaced the manual haematology methods such as Packed Cell Volume through micro centrifugation (WHO, 2000), Total Erythrocyte Count, and Total White Blood Cell Count through hemocytometer (Sandhaus, 2016). Because they are still used for quality control and to validate haematology analyzers, manual haematology methods are still in use.
5.2. Rule of Three
In human medicine, a “rule of three” is inferred for PCV, TEC, and Hb in order to diagnose haematological characteristics and guarantee the accuracy of inferred haematological parameters (Doig and Zhang, 2017). According to the conventional rule of threethat PCV (%) = RBCs×9.Nevertheless, there is a dearth of research published and a dearth of literature addressing such haematological equations for veterinary medical sciences.For blood analyses, veterinarians, researchers, and academicians so employ manual haematology or veterinary haematology analyzers. The use of haematology analyzers is restricted in resource-poor environments like Pakistan because of their high cost, high maintenance requirements, requirement for frequent validation, and expensive chemical reagents.
As a result, a small number of the veterinary haematology analyzers that are housed at Pakistan’s numerous research and academic institutions are useless.This aims to create haematological formulas on the pen side for use in veterinary medicine. The prevalence of anaemia in populations can be tracked and evaluated using PCV and RBCs alone or in combination. To diagnose patients fast and track them in the field, clinicians and researchers typically have to select only one blood feature.
In these situations, PCV appears to be a sensible option, even when carried out alone.In actuality, the goal is to acknowledge that both strategies are dependable and, in the PCV’s opinion, have some value rather than to declare one superior to the other. While the PCV provides an indirect value, the RBCs provide a direct evaluation of the blood’s capacity to carry oxygen.When resources are limited and technical support is insufficient, a simple screening technique is probably going to work better than intricate processes that require careful dilutions and preparations/provisions of standards. Furthermore, PCV computation is less expensive in large-population study (WHO, 2000).
5.3. The Interrelationships
The clinical human convention that the PCV is the 9thof the RBC is validated by human medical practice. However, this formula is not applicable in the practice of veterinary medicine.This study represents the first of its kind to specifically report the association between PCV and RBC for cattle raised in Cholistani.It provides a new mathematical formula for field-specific PCV derivation from RBC. This paper provides a more recent method that researchers, academics, stakeholders, and veterinarians can utilize to determine PCV and in turn, estimate anaemia.For every study group (females vs males, and adults vs young), there was a significant difference between the PCV computed as the 9th of RBC and the PCV assessed manually.
The findings show that cattle blood cannot be considered to follow this established standard in human clinical medicine practice.Similar to this, certain research on human blood has also called into question the legitimacy of this convention.The current study found that the connection between PCV-GS and RBC and PCV-GS and RBC-C was much stronger for young cattle (R=0.506; adjusted r-square=0.251).In this work, a Corrected Packed Cell Volume was calculated using the formula PCV= 3.8(RBC)+6.8 , which was discovered by our regression equations.The manually determined PCV and the corrected PCV were comparable.
When comparing this to research done on other breeds, it becomes clear that no such relationship could be inferred for any of those breeds. As a result, we suggest the following mathematical conversion for Cholistani cattle:
Conclusions
In light of the current study’s findings, the following is determined:
- For cattle blood, there is a stable and particular link between the PCV and RBC
- For Cholistani cattle, the conversion formula (which is implicit in human medical practice) that determines PCV as the 9th of the RBC does not apply
- Given the blood of Cholistani cattle, a different formula of PCV (%)= 3.8(RBC)+6.8 might be inferred.
Recommendations
Considering the study’s findings and conclusions, the following is advised:
- To confirm the links between the hematological characteristics of different breeds of Cholistani livestock and larger populations, similar research might be carried out
- It is possible to validate more mathematical formulas about hematological interrelationship utilized in human medicine for different livestock species in Pakistan
- To enables an early detection of anaemia in Cholistani cattle in particular and Pakistani livestock in general, pen-side conversions or equations may be validated
- The Livestock and Dairy Development Department (L&DD) in Punjab, Pakistan as well as private practitioners and researchers may validate manual haematological techniques in their laboratories
- En masse awareness campaigns for academics and researchers in the public and private sectors might be held to emphasize the importance of hematological studies in the early detection of anaemia in livestock
- Staff members at L&DD, researchers, and academic institutions may receive practical instruction in blood collection, handling, preservation and manual hematological analysis
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