Th Uss f Bihmil Dtin linil Mdiin - Case Study Example

Name Task Disсuss thе usеs оf biосhеmiсаl dеtаin сliniсаl mеdiсinе, аnd thе асquisitiоn аnd intеrрrеtаtiоn оf thе Biосhеmiсаl dаtа. Date Introduction Biochemical data is an informational process that entails choice of weight logical options out of the possible alternatives in patient’s managements. In order to achieve suitable clinical medicine decisions decision making excellently, biochemical data collection framework adheres to analytical and biological models to ensure that outcomes of biochemical data acquisition and interpretation are the most appropriate. This investigative process is often referred to as a turning point since it proclaims to support objectives previously outlined in clinical medicine data usefulness success (Robinson, 2009). On similar accounts, it means that biochemical data involves concepts and tools application in livings organisms structural chemistry especially biomolecules structural and physical properties. Analysis presented in this document is helpful in understanding uses of biochemical data in screening, diagnosis, prognosis, and monitoring and disease treatment process (Marshall, 2004). It further illustrates how analytical and biological factor affects biological test results and lastly, provides relevant and accurate interpretation of normal and abnormal results with the use of relevance ranges to achieve clinical medicine decision-making in patient management process. Relationship of clinical biochemical results to other sources of information. Clinical, biochemical data results are mostly related to other significant results or sources of information especially those that explore pathological, biomolecule, nutritional analysis and biophysics. On the other hand, clinical biochemistry analysis involves mainly blood and urine laboratory investigative tests though; it also includes other body fluids specimen investigative tests such as cerebrospinal fluids, ascetic fluids and gastric aspirates (Swaminathan, 2011). Hence, hematological and electrochemical information is needed and followed that assists in determining optimal disease pattern characteristic recognitions. Biochemical investigative data is extensively useful in clinical medicine specifically in relation to disease pathology and metabolic related basis. It is worth noting that, conditions that affect metabolism mechanism such as diabetic disorders and diseases such as renal failure are consequences of biochemical changes. Conversely, this principal is applicable in biochemical investigation process based on diagnosis, screening, disease prognosis, monitoring and treatments (Gagne, 2014). Biochemical data diagnosis of disease uses. In diagnosis process, biochemical investigation data and others data investigations are used to conduct a differential diagnosis based on the patient history to refute or confirm a diagnosis. Acquisition and interpretation of biochemical data mark a confidential diagnosis is based on the patient history and examination findings for characterization and recognition of the kind of the disease present with reference to clinical signs (Robinson, 2009). Therefore, after providing usefulness in the diagnosis, biochemical data indicates the exposure and the presence of particular defects that cause a particular disease. Biochemical data uses in clinical medicine disease prognosis. Biochemical investigation data are used in conjunction with diagnosis requirements to provides relevant prognosis information through other biochemical information are used specifically for prognosis process as an indication of a likely disease outcome (Samour, 2012).. Plasma creatinine concentration serial measures for this case in renal disease prognosis are used critically to indicate dialysis requirement period. It further illustrates exposures risks in acquiring a particular disease. The increase in concentration of biochemical molecules indicates a related risk increase of developing related conditions, although these risks fails to provide a precise prediction of acquiring the disease condition as measurements are obtained from epidemiological investigative data (Swaminathan, 2011). Biochemical data importance in screening To find out the type of disease presence in a subclinical given population or individual? a biochemical investigation is carried out through mass screen of all individuals suspected with a particular disease, population screening, selective screening, individual screening and lastly opportunistic screening. Biochemical profile and battery of biochemical tests are used to provide an uncommon and unexpected disease finding that provides alarm in earlier management of disease. Biochemical data uses in monitoring disease progress and treatment. Illness course follow-ups and treatment effects monitoring use biochemical data to provide baseline guidelines for investigation (Swaminathan, 2011). To meet this objective, suitable and accurate analytical investigation of biochemical molecules results found based on specialized tests, dynamic function tests on body responses to external stimuli, and discretionary test for grouping of biochemical results ought to be conducted accurately (Samour, 2012). Thus, it produces relevant information on a specific disease progress monitoring and the response to treatments. Complication of disease is detected further during treatments of diseases and administering of drugs, thereby providing equivalent relevant information in drugs toxicity, drugs clinical trials and drug’s effectiveness test in the treatment of a particular condition. Preanalytical factors affecting data. For a biochemical data to be of a clinical value, the specimen samples used are maintained in a specified procedure in deal analytical method. 84% a preanalytical phases errors mainly cause clinical laboratory errors, these errors are closely related to biochemical data collection techniques especially through handling prior to testing (Samour, 2012). Preanalytical errors affect the quality and interpretation of the results in the affected samples that results from incorrect labeling, specimen contaminations and insufficient mixing of samples. To eliminate these errors out, preanalytical phase’s maintenance is critical with an appropriate personnel adhered to all standards and recommendation of sample collection and handling samples achieved through a significant training and education. Any deviation from the producer's recommendations should be clearly validated be being initiated for use. The significance use in clinical, biochemical test is to provide baseline along which an initial data is collected, thus, helpful in eliminating any possible effects that may affect the results at preanalytical stages and biases increasing reliability. Factors affecting data-pre-analytical, biological, endogenous Biological endogenous factors are factors that affect analytical, biochemical data variation during data collection that includes those biological factors that affect the patient’s fluids composition directly or indirectly. On the broad aspects, these are factors that discriminate between abnormal and normal findings caused by physiological factors (Marshall, 2004). These factors include species, breed type, age of a specified individual, stress, sex, exercise, drugs used by the organisms and fasting periods that affect diet. It also includes those factors that affect physiological body hormonal function thereby affecting analytical data. They may be gender related that that affects the endocrine system, pulsatile hormonal secretion and diurnal variation of hormonal secretion (Gagne, 2014). Biological endogenous factors cause variation of the analytical result as it varies from one individual to another. Therefore, significance is setting a standard ranges or measurements that will provided data collected with a more reliable results. Factors affecting data-pre-analytical, biological exogenous. Exogenous biological factors that affect cause propounding effects on biochemical variables concentrations thereby causing a major influences on a biochemical test even on a healthy population. These exogenous biological factors include the time of the day that the biological test was carried out, posture, stress, current health conditions and other related factors such as drugs (Samour, 2012). These factors are important in biological testing as they form part of the results. Thus; a predictive value is to estimate or prevented in the overall interpretation of the result. Pre-analytical, technical factors affecting data- Technical factors that affect biochemical results that have a significance clinical values in data collection includes; patient identification techniques that are that aids in eliminating both biological exogenous and endogenous factors. It also includes other factors such as correct collection container with an appropriate preservative agent (Gagne, 2014). Labeling is also part of technical factors followed by a timely and faster transport system to a relevant biochemical laboratory. Technical factors contribute in obtaining the most accurate and reliable results that contain minimum errors and deviations from the expected results. Analytical actors affecting data Analytical factors that cause analytical variations during biochemical test that also contains much significance in clinical, biochemical tests includes, those factors that either increases or reduces the possibility of errors during data evaluation and analysis (Samour, 2012). In the other words, it means that the tests methods and procedure selected in data analysis have to maintain performance standards that reduce mixed or inaccurate results. Various strategies with analytical goals are applied with considerate standards that meet reference range requirements and analytical impression goals, therefore, significantly important. Analytical factors include analytical range that provides a concentration measurement, accuracy and bias that reflects ability to obtain a true value, precision measurements that reflect reproducibility. On the same note, it also consists of specificity and interferences among other factors with the significant influences on analytical variations. Postanalytical factors affecting data. Postanalytical factors are those factors that cause effects on biochemical data after analysis of results. In other words, it means that these are errors caused calculations, estimations and measurements resulting to transmission or transcription errors (Robinson, 2009). Conversely, it's worth noting that errors that result from data interpretation, reporting results, clinical, biochemical data requirements and treatments are all classified under post-analytical factors. These factors are of significance in analytical variation of biochemical data as they intend to correct the findings obtained from the test conducted. Therefore, biochemical representation of data during post-analytical analysis and process will be effectively and significantly be corrected and recorded. Reference intervals and their interpretation. Reference intervals and interpretation of biochemical-collected data and other related useful information obtained are testified to be relevant, accurate, sensitive and specific if only they justify certain factors (Trefil, 2012). These factors satisfactorily justifies whether this biochemical data is to be relied upon or even considered as irrelevant. Therefore, these means that the distribution of variables should be considered whether they are normal or skewed in a Gaussian distribution curve. Conversely, it means that in a normal distribution data, 95% approximate prediction will be found within a specified range of ±2 SD regardless of data collection mechanisms used and the other remaining 5% falling within either on a half higher or lower than the limited range. Therefore, normal range biochemical data analytical analysis has a significant limitation in defining and calculating expected outcomes and associated risks. An appropriate reference interval is used with knowledge application of sensitivity, specificity predictive values and all other measurement techniques that are relevant in data interpretation to interpret the results after data analysis to correct normal range problems (Marshall, 2004). The reference interval then assesses the significance of a given biochemical results thereby indicating that presence of a pathological process is not always indicated by abnormal results. Reference intervals improvement measures. The collected data should positively indicate and defined to show that, and the findings are different from the previous collected result to produce an analytical significance that is found within expected analytical expectations (Swaminathan, 2011). Consistency of the clinical findings matters a lot in clinical explanation and interpretation of the results to confirm a clinical diagnosis or expected outcome. Consistency of the results ensures the data is accurate, quality and its significance to be relied upon during the application where possible. Conversely, the results found at the extreme areas specifically outside outsides the reference interval that other scholars will refer as critical area are considered as the most significance results but with an exceptional enzymes result (Tang, 2013). On the same aspect, the more abnormal the biochemical result is obtained, the higher the probability the pathological process is obtained with a significance difference in the reference interval. Thus, this feature is crucial in marking differential diagnosis for a specified disease. Conclusion Critical evaluation and data analysis through biochemical test results consideration can generate a positive change in the data reliability of both clinical diagnosis and treatments. These technical approaches applied reduce any chances of obtaining clinical medical errors and inaccurate results. If the biochemical tests fail to fit effectively with the clinical details obtained during the systematic biochemical methods and procedures, additional investigative techniques may be required to review the whole process. Considering these relevant facts and evidence-based argument, it is, therefore, corrects to say that a retest procedure maybe more appropriate to conduct a confirmative clinical finding from the previously obtained results. A laboratory testing conducted for this matter should aim at meeting the high standards of accurate results in terms of reliability and proficiency, but for some cases the results produced can be indicating either a false negative or false positive . Most of the errors that occur some significant number of laboratories are usually detected, identified by a common control measures that involve software data handling or personal results analysis, Evaluation of the obtained accurately reported and recorded effectively by laboratory staff. Most of biochemical results obtained is results obtained may be obvious to some individuals when they go in an expecting direction, but others remain undetected making their resultant errors eradication difficult. In the other words, analytical results are continuously improving with the change of modern technology that works entirely to improve precision, accuracy and reliability of biochemical data. References Gagne, F. (2014). Biochemical Ecotoxicology Principles and Methods. San Diego: Academic Press. print. Marshall, W. J., & Bangert, S. K. (2004).Clinical chemistry (5th ed.). Edinburgh: Mosby. Samour, P. Q., & King, K. (2012). Pediatric nutrition (4th ed.). Sudbury, MA: Jones & Bartlett Learning. Robinson, E.(2009). Current therapy in equine medicine. St. Louis, Mo, Saunders Elsevier. Trefil, M. (2012). The sciences: an integrated approach.Amazon Publishers. New York City Marshall, W. J., lapsley, M. (2014). Clinical Biochemistry Metabolic and Clinical Aspects. London, Elsevier Health Sciences UK Swaminathan, R (2011). Handbook of clinical biochemistry. Singapore, World Scientific Publishing Company. Tang, F, (2013). Use of an Indirect Sampling Method to Produce ReferenceIntervals for Hematologic and Biochemical Analyses in Psittaciform Species. Journal of Avian Medicine and Surgery. 27, 194-203 Read More