Medical Diagnostic for Monitoring Alzheimer Disease - Essay Example

Medical Diagnostic for Monitoring Alzheimer Disease Name Date Abstract Medical diagnosis and clinical laboratory have existed since the ancient times. The evolution of medical diagnosis and research has been based on the examinations done by past physicians on the human body. The diagnostic criteria used for Alzheimer Disease is the use of biomarkers for the purpose of molecular and structural analysis. Ongoing preclinical diagnosis is used as a means of assisting researchers to come up with improved ways of treatment as well as medication for patients. An advanced medical approach is viewed as a way to come up with and implement preventive treatment techniques for patients and those at risk. The use of new diagnostic techniques is likely to introduce relevant objectives in diagnostic medical research and provide alternative and definitive cure for Alzheimer Disease. The study on this paper aims to explore past and present medical diagnostic approaches for the Alzheimer Disease. The discussion is going to focus on how these approaches have influenced the treatment of Alzheimer, patients and if there have been any effective or preventive cures. KEYWORDS: Medical Diagnostic, Alzheimer Disease, Clinical Diagnosis Introduction Alzheimer Disease (AD) is the main cause of dementia among older patients, whereby AD and dementia are commonly used interchangeably during diagnosis. According to McKhann et al. (1984), AD is characterized by the growth of plaques leading to neuron degradation which further contributes to the cognitive, memory and behavioral impairment of a person. Standard clinical diagnostic approaches are used as a medical technique to asses and evaluate the Alzheimer Disease. Various clinical approaches for Alzheimer disease are used depending of the setting (Jack et al., 2010). For instance, the clinical approach of demented patients vary in a medical facility among primary care givers, physicians, clinical neurologists in a neighborhood as well as among medical researchers in academic facilities (Jack et al., 2009). Nonetheless, over the years, researchers have been focused on establishing explicit and standardized care programs for demented patients. There have been increased efforts to have accurate diagnostic mechanisms for Alzheimer Disease in order to have diverse, accurate and viable treatment plans for patients. Clinical diagnosis performed in the past has been conducted during autopsy by examining the pathognomonic plaques neurofibrillary tangles in the brain (McKhann et al., 1984). A number of batteries of clinical assessment have been used as medical approaches for three decades as a mechanism to identify early stages of AD. Mayeux et al. (1998), argues that although these assessments have been used to identify cognitive symptoms of AD, medical practioners still have major reservations on its accuracy. This is because these assessment fail to give definitive results that will assist physicians to distinguish between dementia and other related cognitive disorder syndromes (Jobst et al., 1998; Mayeux et al., 1998). Advance medical diagnosis for Alzheimer Disease is aimed at providing accurate diagnosis which can be used in providing prognostic data for patients and their families. Significantly, these diagnostic methods assist in identifying possible ways to reverse or implement a cure for cognitive conditions and behavioral changes associated with Alzheimer Disease (Jack et al., 2011). Sperling et al., (2011) argues that AD lacks a standard medical diagnostic approach apart from that done during autopsy. Clinical researchers continue to battle with the idea of finding a standard diagnostic test that will aid in coming up with a treatment plan which allows physicians to implement preventive measures that will slow down the rapid progress of AD symptoms. However, clinical trials have led to the introduction of potential therapeutic monitoring tests which allow physicians to pay attention on early and mild symptoms of AD. This has resulted to the growing interest of implementing diagnostic biomarkers for AD. New and improved technologies such as imaging-based tests, retinal scans, cerebrospinal fluids (CSF) and markers detectable in the blood system are being used to detect and treat AD (Small et al., 2008). Physicians and clinical researchers have opted for provisional and standardized assessment criteria for AD to accurately monitor and asses the status and diagnosis of the symptoms related to AD. This is a strategy that is aimed at implementing coherent guidelines that can be used to effectively diagnose AD and reduce the growing numbers of dementia patients (Jack et al., 2011). In the 19th century neuropsychological testing, memory and cognitive impairment clinical diagnosis were used to detect any pathological symptoms of deficits in memory or cognitive functions. These were among the first clinical diagnostic tests done at the beginning and during the progression period of AD (McKhann et al., 1984). According to Jack et al., (2009), despite the effective nature of neuropsychological testing to identify and monitor who is developing dementia, they are still not successful to distinguish patients who have acquired symptoms due to AD pathology or other cognitive diseases. For instance, even though imaging and CSF clinical tests are able to detect AD pathology, it is important to note that cognitive symptoms and AD pathology are not consistent (Price at al., 1999). Thus, it is unable to provide physicians with accurate diagnosis for dementia. Moreover, cognitive symptoms are likely to be absent despite the detection of AD pathology in an examination (Davis et al., 1999; Knopman et al., 2003; Price et al., 1999). The new biomarkers currently used in the diagnosis of AD have been incorporated into the three stages of AD including: preclinical, mild cognitive impairment (MCI) and AD dementia. Sperling (2011), states that this is different as compared to the earlier methods of diagnostics used which mainly concentrated on conducting an autopsy on the brain of a patient. The new diagnostic guidelines provide physicians with the possibility of implementing presymptomatic or preclinical management of AD (Albert et al., 2011). Colburn (2000) defines a biomarker as a “a characteristic that is objectively measured and evaluated as an indicator of normal biological processes, pathogenic processes, or pharmacologic responses to a therapeutic intervention”. In medical diagnosis, biomarkers are used in various ways for instance: they are used as predictive tools to provide a prognostic test, to examine a patient’s anatomy for underlying pathology that could cause a disease, to analyze the outcome of a treatment and as a diagnostic tool for a disease (Hampel, 2010; Blennow, 2010). Oncologists use biomarkers to identify different types of tumors, thus physicians in the field of oncology have adopted the use of biomarkers as a predictive test. This way oncologists can easily monitor and asses the recovery process of a patient while identifying which patients are likely to have high chances of survival, minimize side effects of a treatment as well as slow the advancement of an illness (Mandrekar and Sargent, 2009). Some of the approved oncologic biomarkers and are commonly used include: “KRAS as a predictor in advanced colorectal cancer; HER-2 as a predictor of the efficacy in breast cancer; and epidermal growth factor receptor (EGFR) as a predictive marker of response to tyrosine kinase inhibitor treatment for non-small cell lung cancer” (Mandrekar and Sargent, 2009). However, the use of biomarkers in the treatment of AD differs greatly. Due to the rapid growth and evolution of AD, biomarkers continue to play an important role in the development of cures for AD symptoms. It is however important to note that there are no biomarkers in the treatment of AD that are used as prognostic tests, outcome tests or diagnostic test in clinical diagnosis (Mandrekar and Sargent, 2009). Amyloids and tau tests are examples of biomarkers that have been used at the beginning of clinical human trials to determine whether the intended drug performs its functions or alters the biochemical mechanism. The final stages of a drug test, biomarkers are commonly used as tools to enhance the effective nature of a drug and a clinical trial is conducted mainly on patients who have been identified to have the underlying pathology. Through this way researchers are able to document the accurate benefits and capabilities of a drug (Mandrekar and Sargent, 2009). According to Hampel (2010), there is a possibility of using biomarkers as surrogate outcomes in clinical diagnosis of AD therapeutics. Researchers argue that it is a challenge for regulators to accept the use of biomarkers as part of the surrogate outcome. This is because there is need to establish a relationship between the documented outcome induced by the biomarker as well as the expected clinical outcome (Hampel, 2010). In the treatment of AD, a biomarker can play the role of a surrogate outcome when it can be substituted for a clinically relatable outcome of the patient’s response to a drug. This requires the use of random clinical trials that must be improved in the surrogate outcome so as to meet the expected patient outcome (Katz, 2004; Temple, 1999). According to Blennow (2010), despite the fact that some CSF amyloid biomarkers continue to show significant outcomes among AD patients, researchers are yet to come up with evidence that supports that these biomarkers have actually resulted to the significant outcomes in clinical trials. Various neuropsychological tests have been used by a number of clinical researchers of dementia. Medical researchers argue that the diagnosis of AD and the symptoms of cognitive impairments stress on the importance of this medical diagnosis to register rate at which the cognitive functioning of a patient declines or improves (Albert et al. 2011; Gorelick et al. 2011). According to Gorelick et al. (2011), the clinical diagnosis of dementia “must be based on cognitive testing, and a minimum of 4 cognitive domains should be assessed: executive [functions]/attention, memory, language, and visuospatial functions.” Additionally, Albert et al. (2011) emphasize that neuropsychological assessment is best alternative for physicians to assess and have the actual extent of cognitive impairment in a patient. Imaging technologies have been widely used to monitor the development of AD. Imaging modalities in the treatment of AD are used for assessing the brain capacity, body metabolism, blood perfusion analytical of AD or otherwise to measure the amyloid-related biomarkers linked to the cognitive decline (Albert et al., 2011). Four imaging modalities have been implemented as advance secondary medical diagnostics for clinical trials on AD. These include; structural magnetic resonance imaging (sMRI), functional MRI (fMRI), magnetic resonance spectroscopy (MRS), and positron emission tomography (PET) (Gorelick et al, 2011). The purpose of these for technologies is to assist the physician with comprehensive data on the regional distribution of the microscopic or mesoscopic changes that are taking place in the human anatomy during treatment. They act as the MRI scale so as to give any significant changes between the intermediate changes that occur (Albert et al., 2011). In addition to these medical diagnostic and prognostic techniques for the treatment of AD, newer and advanced techniques continue to be explored. They include improved imaging and CSF-based technologies (Gorelick et al, 2011). These new medical diagnostic approaches are assumed to be convenient for both the patient and physician as well as reduce the treatment cost. Advanced medical diagnostic technology that is easily accessible and affordable will ensure that patients from all financial backgrounds are able to afford treatment (Albert et al., 2011). Moreover, reducing the cost of treatment will also ensure the family of a patient is not financially strained and can be able to comfortably care for the patient at home. Since dementia is a reversible disease, having an early diagnosis will ensure that doctors are able to implement the right treatment plan according to the symptoms exhibited by the patients. This will result in reduced number of patients suffering from dementia, reduced medical costs due to prolonged treatment as well as the emotional turmoil that patients and their families have to endure during treatment (Gorelick et al, 2011). Newer technologies will assist physicians to have accurate diagnostic tests and a comprehensive analytical framework. Advanced medical diagnostic approaches will ensure that doctors are able to solely focus on the symptoms of AD while testing as the equipment used does not provide ambiguous results. As previously discussed, some of the diagnostic approaches that are being are not able to narrow down the cognitive symptoms that are solely linked to dementia but tend to give general outcomes. Newer technologies will assist physicians in detecting the onset and gradual progress of the symptoms of AD while managing the disease (Albert et al., 2011). Previous research has revealed that neuropathological changes observed in AD earlier years before they are clinically detected. Therefore having advanced diagnostic technologies will ensure that during routine checkup, elderly patients that are likely to have dementia can be treated before the neuropsychiatric symptoms start showing. According to () cognitive healthy elderly people may live without any signs of cognitive decline but they possess neuropathological changes in the brain which are aligned with the diagnosis of AD. With the right diagnostic equipments physicians are in a better position to detect the whether a patient is in the preclinical stage of dementia disease. Conclusion Advance medical diagnostic approaches are likely to improve treatment of cognitive diseases as there is a possibility of early diagnosis. There is definitely need to put in place improved medical services that will aid in the administration of better and improved medical services to dementia patients. We are faced with the task of having new treatment plans that are tested for AD and can effectively cure dementia or delay the onset of the disease. This is an important aspect as some elderly patients start showing symptoms of AD as early as 60 years old, hence tend to lose years of their lives earlier on than anticipated. Biomarkers are relatively important in assisting physicians in confirming a diagnosis. This is especially important when there is a decline in cognitive functioning in a patient. Clinical tests and research need to be focused on ways that will assist in the treatment of AD. Past research works have revealed that there has not been intensive clinical test in the treatment of AD as required. In some preclinical diagnosis, the symptoms of AD can be detected but due to the lack of clarity if the symptoms are that of dementia, doctors do not have an advantage during treatment. Researchers need to be able to understand whether the clinical diagnostic tests for AD are relevant for a patient’s outcome before administering them. This will ensure that the physician is able to asses and monitor the progress of the patient as related to the test results. Baker (2003) affirms that the outcomes must me relevant to the patient, clinically significant and provide long term importance. Some of these outcomes include; mortality, quality of life led by a patient during and after treatment, ability of patient to perform daily activities as well as institutionalization. Baker (2003) and Fleming (1996), argue that biomarkers can be used as surrogate outcome measure, however in order for them to be accredited as relevant; they must be backed up with strong, independent and consistent clinical diagnostics by the biomarker and the changes registered by a patient during treatment. Despite this observation, there still lacks an AD biomarker that meets these specifications. Therefore, it imperative that research continues in order to come up with biomarkers that can be linked to clinical outcomes. References Albert, M. S., DeKosky, S. T., Dickson, D., Dubois, B., Feldman, H. H., Fox, N. C., ... and Snyder, P. J. 2011. 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