Gastroenterological conditions span a wide spectrum of disorders that affect the digestive system (see Figure 8-1), including the gastrointestinal (GI) tract, liver, stomach, small and large intestines, gallbladder, appendix, and pancreas, and can range from mild to severe. Some digestive diseases and conditions are acute, lasting only a short time, while others are chronic, or long-lasting. Depending on the disorder’s severity, digestive system disorders may affect a person’s ability to work and function. Examples of these conditions include inflammatory bowel disease (IBD), which can include Crohn’s disease and ulcerative colitis, as well as short bowel syndrome, malabsorptive syndrome/malabsorption, achalasia and other chronic gastrointestinal motility disorders, chronic anemia, liver disease, cirrhosis, chronic pancreatitis, uncontrolled diarrhea, and fecal incontinence.
Common techniques for diagnosing digestive disorders include clinical assessments, imaging techniques, scoring systems for measuring the severity of the disease process and quality-of-life measures, colonoscopy, upper GI endoscopy, capsule endoscopy, endoscopic retrograde cholangiopancreatography, endoscopic ultrasound, and, in some cases, laparoscopy or open surgery. Gastroenterologists, nurse practitioners, physician assistants, nutritionists, dietitians, primary care doctors, radiologists, and surgeons may all be involved in diagnosing a digestive disorder.
Multiple advances in electronics, nanotechnology, and imaging have significantly affected the practice of diagnostic and therapeutic gastroenterology. For example, the use of computed tomography (CT) and magnetic resonance imaging (MRI) in GI and abdominal imaging are becoming common practices and continue to evolve. In the use of non-surgical techniques
for examining the digestive tract, such as endoscopy, advances in wireless technologies have allowed a deeper and improved visualization of the GI tract and greater measurement of the physiologic parameters. The improved ability to identify digestive disease, including cancerous lesions, in the early stages can have a positive effect on prognosis and health outcomes.
This chapter provides information about select new and improved diagnostic and evaluative techniques in gastroenterology that have been introduced since 1990. It highlights major advances in testing that have generally resulted in better information about impairments that may affect patient functioning. Lastly, it identifies emerging digestive system techniques disabling conditions in the future.
The committee reviewed advances in the diagnostic and evaluative techniques for digestive disorders, as shown in Box 8-1 (see inclusion criteria in Chapter 1). These techniques are categorized into those that assess anatomical or physiologic functions and those that assess functional performance or capacity at both the body function level and the activity
level. Some tests may measure one or the other. The chapter discusses the evidence and information about the selected techniques and responds to the requested items (a)–(j) of the statement of task for each technique. The focus is on disorders of the digestive system in Social Security Administration’s Listings of Impairments. These include “gastrointestinal hemorrhage, hepatic (liver) dysfunction, inflammatory bowel disease, short bowel syndrome, and malnutrition. They may also lead to complications, such as obstruction, or be accompanied by manifestations in other body systems.” The Cumulative List of Medical Diagnostic or Evaluative Techniques does not include any tests for gastroenterological conditions, presently. Following the descriptions of the selected techniques, the last section of the chapter outlines emerging techniques used in the assessment of individuals with serious digestive system disorders.
The section describes advances in the diagnostic techniques used for assessing potentially disabling impairments of the digestive system. They are organized by imaging tests, endoscopic tests, and additional procedures. Refer to Chapter 3, Overview of Diagnostic and Evaluative Techniques, for background information about several of the techniques included here.
Computed tomography imaging is playing an increasing role in the evaluation of digestive system disorders (Liu, 2014). CT enterography (discussed in the next section) is a type of CT imaging optimized to produce detailed images of the small intestine and structures within the abdomen and pelvis. Newer techniques such as multidetector CT (MDCT) have become an important new tool for imaging suspected gastrointestinal and abdominal pathologies and have allowed for revolutionary improvements in temporal and spatial resolution when compared with the previous generation of CT scanners (Raman and Fishman, 2012). CT imaging is typically the initial imaging technique of choice for the evaluation of numerous pathologies, such as: gastrointestinal and intra-abdominal malignancies, bowel obstruction and bowel perforation, intra-abdominal sepsis, and small bowel disorders.
The requested information on MDCT for diagnostic capability is as follows:
Magnetic resonance enterography (MRE) and computed tomography enterography (CTE) have become widely accepted methods for performing detailed evaluations of the small bowel in patients with Crohn’s disease (Guglielmo et al., 2020). Enterography refers to the oral administration of relatively large amounts of enteral contrast material to carry out the test, and in many places it has become the standard of care for evaluating patients with Crohn’s disease, small bowel malignancy, small bowel stricture, and other disorders of the small bowel.
The requested information for MRE and CTE related to diagnosis is as follows:
previously conducted for similar indications. Fluoroscopy can deliver a significant radiation dose to the patient, whereas CTE delivers less and MRE none (Baker et al., 2008).
As described in Chapter 3, positron emission tomography (PET) and computer tomography (CT) scan are types of molecular imaging tests within nuclear medicine often used to detect cancers. The techniques were also discussed in Chapter 4, as they have utility in understanding cardiac and coronary pathophysiology. In this context, PET–CT scans are highly sensitive and trace a form of radioactive sugar as its absorbed by the body. Because cancer cells grow quickly, they take up larger amounts of sugar than normal cells. By 2000 this technique had become an essential modality
in the management of digestive system cancers, being used for diagnosis, staging, evaluation of treatment response, and assessment of prognosis (Beyer et al., 2000).
The requested information related to PET–CT and diagnostic and prognostic ability is as follows:
general categories to differentiate benign from malignant processes: SUV max < 2.5 = low uptake; SUV max 2.5–5 = intermediate uptake; SUV max > 5 = high uptake; and SUV max >10 = intense uptake (Ramzan and Tafti, 2022). There can also be false positives, which can occur from patient movement, or inflammatory uptake at sites of surgery, or false negatives because the tumor is the type that does not have a high uptake of the radioactive material (Ramzan and Tafti, 2022).
Defecography is an X-ray of the anorectal area that evaluates the completeness of stool elimination, identifies anorectal abnormalities, and evaluates rectal muscle contractions and relaxation. The test assesses the
complex and dynamic anatomical and functional changes of the rectum, the anal canal, and the pelvic floor during a bowel movement.
The requested information related to magnetic resonance defecography (MRD) and diagnostic ability is as follows:
involves various maneuvers for proper imaging as well as defecation in a supine position, which can be difficult for the patient (Kumra et al., 2019).
Magnetic resonance cholangiopancreatography (MRCP) is a medical imaging technique that which uses magnetic resonance to visualize the biliary tree and pancreatic ducts by non-invasive means to evaluate a wide range of pancreatobiliary diseases.
The requested information related to MRCP and diagnostic ability is outlined below:
morbidity and mortality risk due to the potential for perforation, bleeding, and infection upon exam (Kaltenthaler et al., 2006).
Transient elastography is a non-invasive method proposed for the assessment of hepatic fibrosis in chronic liver disease. It can be performed easily at the bedside or in outpatient clinics with immediate results. It has also been validated for the diagnosis of significant fibrosis, cirrhosis in chronic hepatitis C, recurrence of hepatitis C after liver transplantation, and coinfections in certain patients (de Lédinghen and Vergniol, 2008).
The details related to diagnosis of liver conditions with transient elastography are as follows:
with portal hypertension and assess disease recurrence following liver transplantation.
Colonoscopy is an endoscopic method of imaging the mucosa (inner lining) of the lower digestive tract (colon and terminal ileum) used to detect malignancies or polyps, diagnose inflammatory disorders, and identify the source of GI bleeding and anemia. In addition to being a diagnostic test, colonoscopy is also a therapeutic technique for removing polyps, making biopsies of abnormal tissue, and managing sources of GI bleeding. Virtual colonoscopy (or computed tomographic colonography) is a radiological diagnostic method that “combines conventional spiral computed axial tomography with virtual reality computer technology to assess the colonic mucosa for malignancies and polyps. The two-dimensional images generated by helical computed tomography are reconstructed into three-dimensional images by software that simulates the interior of the colon as it would be viewed through an endoscope.” (Moayyedi and Ford, 2002, p. 1401). Virtual colonoscopy is commonly used in colon cancer screening in patients where colonoscopy with sedation is contraindicated, when the patient has severe lung or heart disease, or when colonoscopy could not be completed for anatomical, technical, or patient safety reasons. However, virtual colonoscopy does not detect other mucosal pathologies such as inflammatory bowel disease or mucosal vascular pathologies.
The requested information on virtual colonoscopy for diagnosis is below:
Diagnostic methods in gastroenterology are now increasingly characterized by direct visual inspection and tissue sampling (Mallery and Van Dam, 2000). Advances in endoscopic imaging are enabling clinicians to detect subtle, small mucosal variations that were previously undetected and indistinguishable from normal tissue (Graham and Banks, 2015). Endoscopy is an effective diagnostic technique for some GI disorders that previously
required more invasive techniques (Mallery and Van Dam, 2000). Additionally, many techniques also now have a digital component that augments the testing even further with supportive imaging.
Endoscopic ultrasound (EUS) is a noninvasive procedure that examines the walls of upper (esophagus, stomach, duodenum) and lower (rectum) gastrointestinal tract. It can also be used to look at nearby organs, such as the mediastinum, liver, gall bladder, and pancreas. In 2000 it was called the most clinically significant technological advancement in endoscopy in the past 10 years.
The requested information for use of EUS for diagnosis is as follows:
has also been limited in utility because of interference from the air-filled lungs (Mallery and Van Dam, 2000). While another technique, endoscopic retrograde cholangiopancreatography, is highly accurate for the diagnosis of common duct stones, EUS has been found to be equivalent in accuracy but more cost-effective and less invasive.
Esophagogastroduodenoscopy (also called EGD or upper GI endoscopy) is a procedure to examine the inside of the esophagus, stomach, and duodenum with an endoscope. EGD is important in the diagnosis and treatment of esophageal, gastric, and small-bowel disorders. The endoscope is guided into the mouth and throat, then into the esophagus, stomach, and duodenum. The endoscope allows the endoscopist to view the inside of this area of the body as well as to insert instruments through the scope for the removal of a sample of tissue for biopsy and for therapeutic intervention (e.g., the removal of a lesion or stenting to relieve obstruction).
The requested information for use of EGD for diagnosis is as follows:
problems such as tumors, Celiac disease, Crohn’s disease, or infections in the upper GI tract (Johns Hopkins Medicine, 2022b).
In addition to imaging tests and types of endoscopies, there are other techniques, such as high-resolution manometry, prognostic scoring systems, and genetic testing, that clinicians use to evaluate a patient’s gastrointestinal tract and diagnose disorders of the digestive system.
Various manometry tests are used to measure the muscle movements and muscle tone of the gastrointestinal tract, most often to investigate disorders of the esophagus when patients complain of symptoms such as dysphagia, regurgitation, heartburn, or chest pain. Esophageal manometry can be done using conventional manometry or high-resolution manometry (HRM). HRM uses pressure sensors and is more accurate at assessing pressure changes than conventional manometry testing. Outcome studies have just begun to demonstrate how the increased knowledge generated by HRM has influenced patient care, including the introduction of novel therapies (Gilja et al., 2007).
The requested information on HRM as a diagnostic procedure is as follows:
Table 8-1 summarizes two new and improved instruments that are widely used by medical professionals for characterizing disease progression and determining prognosis the risk of death in the near future for patients with liver disease. The diagnostic evaluation of patients with liver cirrhosis is an important topic in the field of organ transplantation. Accurate prognosis of patients with cirrhosis can decrease the mortality of patients on
TABLE 8-1 Examples of Scoring Systems for Mortality Risk and Disability in Liver Disease
| Tool or Measure (Evidence) | Accepted Uses/Impairments Assessed | Advancement/Limitations of Previous Techniques | Estimated Date Available | Range of Outcomes | Limitations of Efficacy |
|---|---|---|---|---|---|
| Child-Turcotte-Pugh (CTP) Calculator (Abdalla et al., 2019; Kaplan et al., 2016; Tsoris and Marlar, 2022) |
A calculator using five lab values to predict severity of cirrhosis. Assesses severity and long-term survival with cirrhosis. | Modified in 2016 to improve ability to predict transplant-free survival | First developed in 1964, modified several times, most recently 2016 | Score of 5–6 points shows good hepatic function; 7–9 points moderately impaired; 10–15 points advanced deficits in hepatic function. Scores can predict mortality after transplant. | The test relies on two subjective assessments. It can also not be used to predict response to treatment using antivirals in “difficult to treat” patients. |
| Model for End-Stage Liver Disease (MELD) Score (Gotthardt et al., 2009; Kamath et al., 2001) |
Prognostic model to assess the severity of cirrhosis, organ allocation for liver transplant, etc. | Has a broad range of continuous variables, so was created to account for shortcomings of CTP calculator. Correlates significantly with the degree of liver functional impairment |
2001; updated for organ allocation use in 2016 | Scores range from 6 to 40 based on current condition. Larger increase in score can be due to infection or worsening of disease. The higher the score, the more often blood tests are needed. | MELD score has been criticized for variations in serum creatinine measurements and shown to be inferior to CTP score. Has been found to be limited in value for long-term prediction of mortality or removal of liver transplant patients from waiting list. MELD score can underestimate the severity of liver disease in women. |
waiting lists and improve posttransplant survival. While posttransplant survival can be predicted on the basis of the data-driven Model for End-Stage Liver Disease (MELD), the factors associated with posttransplant functioning are less well established (NASEM, 2021). Nonetheless, an advanced (>12) MELD score (which is associated with poor or limited function), or a score of C on the Child-Turcotte-Pugh (CTP) calculator (which is associated with a 55 percent mortality at 1 year), are likely associated with severe disability (Samoylova et al., 2017).
Genetic testing in digestive system diseases will typically be done for the diagnosis of a genetic syndrome, such as cystic fibrosis, a condition that cause chronic dysphagia and recurrent or chronic pancreatitis; to assess the risk of developing certain digestive disorders (e.g., cancer); to assess for a hereditary genetic syndrome in patients with a personal or family history of GI or non-GI malignancies; or to assess chances of responding to certain therapies (like cancer therapies and other), which can have implications for patient functioning and overall survival. Genetic testing in general is indicated when establishing a genetic diagnosis can have important implications for medical management and monitoring. Testing for germline mutations, which predispose individuals to syndrome-associated neoplastic manifestations, may be indicated in patients at increased risk for a hereditary cancer syndrome (Syngal et al., 2015). Genetic testing for a broad scope of applications is becoming increasingly available, but the analysis and interpretation of results remains complex, requiring specialized expertise, and it can be challenging to communicate the results to patients.
The requested information for genetic testing’s use as a diagnostic technique is as follows:
___________________
1 Details on the regulatory guidance are beyond the scope of this report, but more details can be found here: https://www.genome.gov/about-genomics/policy-issues/Regulation-of-Genetic-Tests.
Often, clinical judgments in digestive disorders are based on patient-reported symptoms in addition to data from objective diagnostic tests. Symptoms can lead to functional consequences that can prevent people from working. As discussed in chapters 2 and 3, the evaluation of symptoms can involve both patient-reported outcomes and clinical scales to assess severity of disease and how well a person can function. Patient-reported outcomes measure any aspect of patient-reported health (e.g., physical, emotional, or social symptoms) and can help to direct care and improve clinical outcomes. Table 8-2 provides examples of measures created to assess symptoms and functioning in patients with specific digestive disorders, including inflammatory bowel disease and other digestive system conditions. Such patient-reported outcomes capture the patients’ illness experience in a structured format. Using patient-reported outcomes can effectively aid in the detection and management of conditions, improve satisfaction with care, and enhance the patient–provider relationship (Spiegel, 2013).
This section reviews the major emerging breakthroughs in the field of gastroenterology that will likely influence how digestive disorders are diagnosed and evaluated in the coming years. Key techniques include artificial intelligence (AI), novel biomarkers, predictive algorithms, and portable sensors.
Together, AI and machine learning (ML) have the potential to bring major improvements to the diagnosis and evaluation of digestive system conditions. For example, the use of AI in GI endoscopy can reduce inter-operator variability, enhance diagnostic accuracy, and reduce the time and cost of endoscopic procedures (El Hajjar and Rey, 2020). Computer-assisted diagnosis for optical biopsy is one of the main systems of AI application. Studies have shown that this system has great promise for improving the detection and diagnosis of esophageal adenocarcinoma, which, when diagnosed early, can benefit from curative treatment. Many systems are also in development to assess various colon diseases. The use of AI during colonoscopies can assist in the diagnosis of polyps via “optical biopsy.” Diagnostic AI assistance can also be used in IBD patients to predict persistent histological inflammation in ulcerative colitis patients with 91 percent accuracy (Maeda et al., 2019). While some of these systems, such as those
for cancer diagnosis, will require more research and testing before they will be ready for clinical use, computer-assisted diagnosis for colon polyps is currently being introduced in clinical practice (Hajjar and Rey, 2020).
As discussed previously, the accurate diagnosis of IBD relies on a combination of clinical data, image and colonoscopy assessments, and inflammatory markers. Prognosis (assessing if a patient with IBD will develop IBD-related complications during the course of the disease) and monitoring the response to different therapies for IBD still require the identification of reliable biomarkers to understand which patients are at higher risk of disease progression and which therapeutic mechanism of action is best suited for each patient. The personalization of therapy and management will improve the outcomes of patients with IBD (Stankovic et al., 2021). Finally, identifying patients at risk of developing IBD before they develop symptoms will allow the development of proactive preventive strategies. AI can help integrate the data of the many environmental and socioeconomic factors as well as the genetic susceptibility genes to help detect patients at risk of developing IBD and to help risk-stratify patients with a diagnosis of IBD. It can also play a role in prognosis for chronic liver disease. For example, in a study by Segovia-Miranda and colleagues, ML was used to analyze bile canalicular features along with biliary flow dynamic simulations to effectively identify pathobiological processes in early nonalcoholic steatohepatitis (NASH) and characterize the transition from simple steatosis to NASH (Segovia-Miranda et al., 2019).
Since the mapping of the human genome, many new technologies have emerged that enable the measurement of biological molecules that are involved in the structure, function, and dynamics of a cell, tissue, or organism (IOM, 2012). These fields are often referred to as “omics” and can include proteomics, metabolomics, epigenomics, and many others. Several different types of tests related to “omics data” have been FDA-approved for clinical application, but the robust analysis of this type of big data will rely on AI and ML. Integrating all of the different types of data would likely improve the understanding of IBD pathology and management, and ML offers a way to handle the high dimensionality of these data with a goal of translating results into clinical practice. However, predictive models still need to be rigorously tested in various cohorts and settings to truly determine whether they can be beneficial.
In addition to numerous efforts using AI and ML, novel serum biomarkers for chronic liver disease are also being explored in various cohorts to spot the presence of early disease or identify patients with a high risk of disease progression. Researchers in the United Kingdom are specifically
TABLE 8-2 Examples of Patient-Reported Outcomes and Clinical Scales for Digestive Disorders
| Tool or Measure (Evidence) | Description | Impairments Assessed/Accepted Uses | Advancement/Limitations of Previous Techniques |
|---|---|---|---|
| GASTROINTESTINAL | |||
|
Inflammatory Bowel Disease Disability Index (IBD-DI) (Peyrin-Biroulet et al., 2012; Plebris and Lees, 2022) |
28-item questionnaire that measures disability in inflammatory bowel disease (e.g., ulcerative colitis, Crohn’s disease) | General health; environmental factors; sleep, energy, body image, pain, and other symptoms. | First tool to specifically assess IBD disability at a given time, including to follow changes in disease burden over time for monitoring treatment efficacy. |
|
IBD Disk (Ghosh et al., 2017; Le Berre et al., 2020; Paulides et al., 2019) |
10-item questionnaire that is an adaptation of IBD-DI. Includes domains of joint pain, abdominal pain, regulation of defecation, interpersonal interactions, education and work, sleep, energy, emotions, body image, and sexual functions. | Abdominal pain; regulating defecation; interpersonal interactions; education and work; sleep; energy, emotions; body image; sexual functions; joint pain | Designed for use during the clinical visit to give immediate visual representation of patient-reported IBD-related disability. Easier and faster to complete than the IBD-DI. |
| Est. Date Available | Range of Outcomes | Disparities In Access | How It Is Adminstered/Standard Requirements Governing Use | Limitations of Efficacy |
|---|---|---|---|---|
| 2012 | Based on 0–4 Likert scale. For the validated French version with 14 items, the mean score was 35. | Difficult to self-administer | Administered by a health care professional; mainly for use in the clinical trial setting. Studies have demonstrated its use as an outcome measure in clinical trials and prospective epidemiological studies. | Poor correlation with objective markers of endoscopic inflammation; can be cumbersome to calculate in clinical practice |
| 2017 | Overall score calculated as sum of 10 components, ranging from 0 to 100. Good correlation of IBD Disk score with daily life burden. | Unknown | Self-administered in clinical practice. Can be useful in remote monitoring. | The tool lacks assessment of clinical activity to confirm relationships with disease burden and QoL. |
| Tool or Measure (Evidence) | Description | Impairments Assessed/Accepted Uses | Advancement/Limitations of Previous Techniques |
|---|---|---|---|
| GASTROINTESTINAL | |||
|
GI-PROMIS (Almario et al., 2016; Kochar et al., 2018; Spiegel et al., 2014) |
The National Institutes of Health Patient-Reported Outcomes Measurement Information System (PROMIS) is a standardized set of patient-reported outcomes that cover physical, mental, and social health (Spiegel et al., 2014). GI symptom domains added as a 60-item questionnaire include gastroesophageal reflux (13 items), disrupted swallowing (7 items), diarrhea (5 items), bowel incontinence/soilage (4 items), nausea and vomiting (4 items), constipation (9 items), belly pain (6 items), and gas/bloat/flatulence (12 items). | Applicable across a range of GI diseases and conditions | The domains selected were strongly associated with disease activity and quality of life indices for IBD patients, providing a method of measuring quality of life and severity of disease more objectively |
|
SHORT HEALTH SCALE (SHS) (McDermott et al., 2013; Park et al., 2017) |
A four-part visual analogue scale questionnaire using open-ended questions that are designed to assess the impact of inflammatory bowel disease on health-related quality of life. The four dimensions include bowel symptoms, activities of daily life, worry, and general well-being. | IBD, including Crohn’s disease and ulcerative colitis | Previous measures did not take into account patient well-being and focused on biological burden of IBD. Previous scales also asked extensive questions about specific symptoms and activities. This one is shorter and easier to complete, also open-ended so patients can customize better to their context. |
| Est. Date Available | Range of Outcomes | Disparities In Access | How It Is Adminstered/Standard Requirements Governing Use | Limitations of Efficacy |
|---|---|---|---|---|
| 2014 | Mean score is 50, with SD of 10. Higher scores denote more symptoms, except social satisfaction, where a lower score indicates better satisfaction. | Uptake is not always equal across populations. In one study, African Americans were 56% less likely to complete the questionnaire prior to their visit. As these telehealth portals increase in use, the reasons driving these disparities need to be better understood. | Can be employed in clinical settings (in person or virtual) and research/clinical trials | A randomized controlled trial evaluating the impact in clinical practice found no differences in patient satisfaction or assessment of shared decision making. |
| 2006 | Has been validated across several populations/countries. Found a reliable measure of health related QoL. | Questions broadly applicable to diverse patients with varying demographics. | Quick and easy to administer, taking less than 1 minute. | Unknown |
| Tool or Measure (Evidence) | Description | Impairments Assessed/Accepted Uses | Advancement/Limitations of Previous Techniques |
|---|---|---|---|
| ESOPHAGEAL DISEASE | |||
|
Eckardt Symptom Score (ESS) (Botoman, 2019; Taft et al., 2018) |
Four-item self-report assessment tool for achalasia to drive clinical management decisions. Is most widely used tool as of 2018 | Assesses severity of symptoms of achalasia. | Simpler to use than other achalasia symptom scoring models |
|
Northwestern Esophageal Quality of Life Scale NEQOL (Bedell et al., 2016) |
14-item single scale measure of health related quality of life. Acts as a “hybrid” measure that can be broadly used but maintains sensitivity. | Applicable across several chronic esophageal conditions, e.g., GERD, EoE, achalasia, dysphagia. | Previous measures make it difficult to isolate true impact of disease on QoL; most also were not transportable across clinical and research settings. |
|
Adult Eosinophilic Oesophagitis Quality of Life (EoO-QOL-A) (Lucendoet al., 2018: Taft et al., 2011) |
37-item measure (later refined to 30) structured by 5 dimensions: eating/diet impact, social impact, emotional impact, disease anxiety, and choking anxiety. | Eosinophilic esophagitis (EoE) | Other generic health-related quality of life measures could not express multiple concerns about the condition people with EoE have. |
NOTE: EoE = eosinophilic esophagitis; GERD = gastroenterological reflux disease; GI = gastrointestinal; IBD = inflammatory bowel disease; QoL = quality of life; SD = standard deviation.
| Est. Date Available | Range of Outcomes | Disparities In Access | How It Is Adminstered/Standard Requirements Governing Use | Limitations of Efficacy |
|---|---|---|---|---|
| 1992 | Assigns 0–3 points for four symptoms of disease (dysphagia, regurgitation, chest pain, and weight loss). Scores of 0–1: clinical stage 0; 2–3: Stage I; 4–6: Stage II; and more than 6: Stage III. Final scores range from 0 to 12. | Achalasia is a rare disease, may require formal diagnosis to have access to this type of assessment. | Used in clinical and research settings to grade symptom severity; self reporting scale | The ESS has fair reliability and validity, but certain items in the tool may be decreasing it’s reliability, so further assessment warranted; the “weight loss” item has the weakest correlation with other measures. |
| 2016 | Each item rated on 5-point Likert scale (very true–not true at all). Each item is coded 0–4, with total score summing all items. | Unknown | Can be used as rapid assessment tool of health-related QoL in clinical settings. For research, other disease-specific measures are preferred over NEQOL until further evaluated across samples. | Additional validation needed. Samples in initial study were primarily Caucasian and highly educated, needs validation in more diverse patient populations. |
| 2011 | Scores for every item range from 0 (very good QoL) to 4 (very poor QoL). The final score is a weighted average of all dimensions. Recurrent food impaction affected most dimensions, and female gender exclusively affected diet dimension. | Many patients suffering from EoE have diagnosis delays of several years, so that could keep them from accessing this type of measure. | Can self administer; useful for clinical practice and research. | Multi-center studies with more diverse patient samples are needed. Test has only been validated for those with a formal diagnosis. |
examining serum biomarkers of fibrogenesis, genetic markers of fibrosis, and imaging and platform “omics” technologies (Bennett et al., 2022).
Advances have been made in developing diagnostic techniques and algorithms that can identify and risk-stratify individuals with nonalcoholic fatty liver disease (NAFLD) and its more progressive form, NASH. While diagnostic tests are available to accurately diagnose advanced liver disease, early diagnosis remains an ongoing challenge, and until recently no widely available non-invasive diagnostic test was able to distinguish between NAFLD and NASH. But there have been an extensive number of publications released recently and new therapeutic targets identified, with the common themes of a deeper understanding of disease pathogenesis, new and improved diagnostic and staging tools, and moving closer to FDA-approved therapies (Abdelmalek, 2021). Additionally, high-definition medicine has become an accepted approach to profiling and restoring a person’s health using analytical and therapeutic technologies, including geometric modeling.
For example, for the noninvasive identification of patients with significant NASH and liver fibrosis, a score using transient elastography was developed recently to identify those patients at increased risk of disease progression. A model using liver stiffness measurement by vibration-controlled transient elastography, controlled attenuation parameter, and aspartate aminotransferase had the best predictive properties for NAFLD and associated injury (Newsome et al., 2020). The score resulted in better discrimination than existing tests, but more research is needed to transition the use of the test to primary care. Approaches like these can enable other quantitative tools that could diagnose early disease or assess disease progression (Abdelmalek, 2021). This could also help to identify new biomarkers for diagnosis and prediction of which patients will progress to negative outcomes of disease.
Another novel method is the use of a portable magnetic resonance sensor with histological validation to stage steatosis and fibrosis in preclinical models. In one study such a portable sensor accurately predicted steatosis and fibrosis grade in ex vivo mouse livers and accurately quantified the fat fraction in human livers (Bashyam et al., 2021). While traditional MRI has clearly demonstrated its utility and accuracy for many conditions, its cost and requirements for facilities makes it a difficult tool to scale more widely or use as an ongoing longitudinal screening option. This type of
portable sensor offers similar abilities with the advantage of being used at point of care to monitor disease progression and potentially enable earlier diagnosis. See Chapter 3 for more information about the use of digital technologies in clinical medicine.
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