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The enteric form of B cereus food poisoning is characterized by watery diarrhea and occurs 8–16 hours after ingestion of contaminated food such as meat medications containing sulfa buy lamictal online pills, vegetables symptoms 0f heart attack cheap lamictal 50 mg otc, dried beans medicine 369 generic 100mg lamictal fast delivery, or cereals medicine lux order generic lamictal from india. The diagnosis can also be made by proximal to medicine runny nose generic 100mg lamictal overnight delivery distal “milking of the urethra” and showing evidence of a purulent or mucopurulent discharge and sending it for culture symptoms 3dp5dt purchase lamictal line. Other methods include examining a urethral swab or the sediment from the first 20–30 mL of voided urine (after the patient has not voided for several hours). Dysuria without inflammation may represent a functional problem and usually does not benefit from antibiotics. It presents with nonspecific symptoms such as poor school performance or mood and personality changes. It then progresses to intellectual decline, seizures, myoclonus, ataxia, and visual disturbances. The exact prevalence depends on the effectiveness of Chlamydial control programs in the population. It is usually the consequence of intraoperative contamination or postoperative bacteremia. Endocarditis occurring 12 months after surgery is usually due to the same organisms that cause native valve endocarditis. Although they can cause dysuria, it is of the “external” variety (ie, secondary to urine passing over the inflamed vulvar area). However, resistance to penicillin is too common to allow the routine use of this drug. Bacteremia is more common in certain groups (eg, Native Americans, Native Alaskans, African Americans), suggesting a genetic predisposition. Up to 40% of healthy children and 10% of healthy adults are asymptomatic carriers. Antibodies are not naturally occurring, but are the result of prior colonization, infection, or vaccination. Intact spleen, complement and macrophage function is important in clearance of pneumococci from sterile areas, but specific immunoglobulin G (IgG) antibody coating of a pneumococcal polysaccharide capsule is essential for macrophages to ingest and kill the bacteria. If candidal dermatitis of the penis is present, topical azole therapy would be appropriate. However, the only common predisposing factor in a young healthy population such as this would be a previous viral respiratory infection. However, not all pleural effusions in the setting of pneumococcal pneumonia represent pleural infection. Cough becomes more prominent if a lower respiratory tract infection ensues, but sputum production is not usually prominent. Tetracyclines and aminoglycosides inhibit protein synthesis by binding to the 30S ribosomal subunit. Some Gram-positive bacteria develop a mutation that allows them to actively pump the drug out. In contrast, erythromycin inhibits the enzyme involved in cyclosporine metabolism and can result in enhanced toxicity. Common findings include fever, weight loss, cough, lymphadenopathy, anemia, abnormal liver enzymes, and hepatosplenomegaly. The chronic pulmonary disease is characterized by cough, increasing sputum production, and apical infiltrates. One-third improve or stabilize spontaneously while the remainder progress slowly to develop cavitation of the upper lobes and altered pulmonary function. In histoplasmosis, oropharyn-geal ulcerations begin as solitary indurated plaques with no pain present at first, although eventually pain becomes deep-seated. However, only half of the patients with a thin-walled pulmonary cavity secondary to coccidioidomycosis will have symptoms. Although induration >10 mm is felt to be positive, interpretation is really dependent on the population being studied. When testing household contacts, >5 mm is probably enough to warrant prophylactic treatment. Transmission is by contact of Brucella organisms with abraded skin, through the conjunctiva, or by inhalation. A typical treatment course would be doxycycline plus an aminoglycoside for 4 weeks followed by a further 4 weeks of doxycycline and rifampin. The incubation period is 2–5 days, and the syndrome includes fevers, chills, headaches, myalgias, and tender hepatosplenomegaly. In addition, specific syndromes such as ulceroglandular or oculog-landular tularemia can accompany the nonspecific syndrome. When dark-field examination is not possible, direct fluorescent antibody tests are used. Infants may be asymptomatic at birth but later can present with a multitude of signs and symptoms, including chorioretinitis, strabismus, epilepsy, and psychomotor retardation. Salmonella gastroenteritis is not usually treated with antibiotics because the length of the illness is not shortened, but the length of time the organism is carried is increased. As humans are the only reservoir for smallpox, there is no longer any risk of infection from natural sources. The treatment of tetanus requires diazepam, muscle relaxants, antitoxin, respiratory care, and managing autonomic dysfunction. A 29-year-old woman presents to the clinic with symptoms of joints discomfort and hives 6 days after starting penicillin for a “strep throat” infection. She has also noticed some lumps in her neck, but no lip or tongue swelling, and no difficulty breathing. On physical examination, she has small mobile cervical lymph nodes, skin changes of urticaria, and no oral lesions. A 24-year-old man is diagnosed with disseminated histoplasmosis after developing symptoms of fever, lymphadenopathy, hepatosplenomegaly and pancytopenia. Which of the following is the body’s major immunologic defense against histoplasmosisfi Which of the following are large, granular lymphoid cells that are mediators of antibodydependent cellular cytotoxicityfi A 9-year-old boy presents to the clinic for assessment of sneezing, runny nose, and nasal congestion. A 19-year-old man presents to the emergency department with symptoms of recurrent attacks of gastrointestinal colic type discomfort and swelling of his face and legs. A 34-year-old woman is seen in the clinic for her annual assessment and has a routine complete blood count performed. She is not on any antiretroviral therapy currently, and is doing well with no symptoms. Which of the following changes is most likely seen on her peripheral blood cell countsfi In addition, she reports that her urine is very dark and “tea color” like, and today her partner commented that her eyes look yellow. Her past medical history is significant for myasthenia gravis for which she is taking azathioprine and pyridostigmine. Laboratory investigations reveal findings in keeping with autoimmune hemolytic anemia. A 19-year-old man presents to the emergency department complaining of coughing up blood and decreased urine output. On physical examination, there is normal air entry in the lungs, and the heart sounds are normal. A 25-year-old woman presents to the emergency room with new symptoms of decreased urine output, leg edema, and facial swelling. Laboratory investigations reveal acute kidney injury and a renal biopsy is performed. Immunofluorescence of the biopsy specimen reveals a granular pattern of immune complex-mediated glomerulonephritis. A 25-year-old woman is receiving desensitization shots for an allergy for the past 1 year. A 23-year-old man is receiving penicillin for the treatment of a group A strep throat infection. He now returns to the clinic with new symptoms of a rash and diffuse joint discomfort. A 22-year-old woman is seen in the clinic for assessment of recurrent fungal infections. She is suspected of having immunodeficiency secondary to impaired T-cell function. Which of the following is the most cost-effective screening test of cellular immunityfi A 19-year-old female university student unknowingly eats a noodle dish that has shrimp in it. Over the next 20 minutes she develops acute skin lesions consisting of erythematous wheals that are raised on the surface of the skin. A 27-year-old man presents to the clinic for assessment of an itchy rash that develops when he goes jogging, or while taking a hot shower. There is no rash at present to examine, but he does show you a digital picture of the rash. His past medical history is negative, he is not on any medications, and reports no known allergies. A 42-year-old man was seen in the clinic because of pain and redness in his finger. On physical examination, there is erythema, swelling, and tenderness of the second digit in the right hand. A few days later he presents to the emergency room complaining of difficulty breathing. A 47-year-old woman, with Type 1 diabetes of 30 years’ duration, is in the hospital for assessment of atypical chest pain. A 27-year-old woman presents to the clinic complaining of pain and discomfort on swallowing. A 34-year-old man presents to emergency room with headache and left-sided arm and leg weakness. On physical examination, he is alert and oriented; there is left-sided weakness rated 4–/5 in his arm and 4+/5 in his leg. A 23-year-old woman presents to the clinic for repeat assessment of wheezing symptoms and shortness of breath on exertion. She reports no “triggers” that bring on the symptoms, and they usually only occur in the spring and then resolve spontaneously. A 45-year-old man is admitted to the hospital because of increasing shortness of breath and cough due to an asthma exacerbation. He is interested in avoiding any potential agents that might trigger his asthma in the future. Which of the following foods is most likely to precipitate an asthmatic reaction in this manfi Questions 21 through 23: For each patient with symptoms after taking a new medication, select the most likely mechanism. A 23-year-old man has a reaction after being given oral penicillin for a sore throat. A 23-year-old man has an exacerbation of asthma when he takes aspirin for a headache. The pain is located in his lower back and gluteal area, and is associated with morning stiffness that improves after several hours. On examination, he has limited forward flexion and tenderness of the ischial tuberosities. A 24-year-old woman has a facial skin lesion, thrombocytopenia, arthralgia, and pericarditis. Her laboratory tests reveal hyperglycemia and a mildly increased anion gap metabolic acidosis. She notices 1 hour of morning stiffness and swelling with redness in her wrists and hand joints. A 33-year-old policeman develops acute asymmetric arthritis involving his left knee and ankle and right ankle. Questions 31 through 36: For each patient with a medical condition, select the most likely immune dysfunction. X-rays reveal multiple lytic lesions and his serum protein electrophoresis has an IgG spike of 12 g/dL. Common signs and symptoms include fever, skin rash (urticarial or morbilliform), arthralgias, lymphadenopathy, and albuminuria. Primary sensitization requires 1–3 weeks, but symptoms can occur rapidly on reexposure. Immediate-type hypersensitivity reactions depend on the release of inflammatory mediators from mast cells either directly or through IgE-specific antibodies. These reactions occur with minutes of exposure to the drug, which rules them out in this patient. This is a reaction of T cells, which have been stimulated by antigen to react against infectious agents, grafts, and tumors. A classic example is the response to the tuberculin skin test in a person previously exposed to Mycobacterium tuberculosis organisms which occurs between 48 and 72 hours after antigen exposure. It is dependent on an IgE response controlled by T and B lymphocytes and activated when antigens interact with mast cell-bound IgE molecules. These patients have B-lymphocyte deficiency and bacterial infections and diarrhea. The course of the hemoptysis is variable, but renal involvement is often progressive. Current therapy includes intensive plasma exchange, cytotoxic agents, and gluco-corticoids. Immune complexes with normal complement levels are found in IgA nephropathy and Henoch-Schonlein purpura.

Do not try to medications bladder infections buy lamictal 200 mg mastercard dazzle the public with the large number of records in your Big Data project medicine of the people buy generic lamictal 100 mg on line. Large studies are not necessarily good studies medicine z pack buy lamictal discount, and the honest data analyst will present the facts and the analysis without using the number of data records as a substitute for analytic rigor medicine descriptions purchase lamictal discount. You validate an assertion (which may appear in the form of a hypothesis treatment chlamydia order lamictal overnight, a statement about the value of a new laboratory test symptoms 7 days after implantation discount 25mg lamictal otc, or a therapeutic protocol) by showing that you draw the same conclusion repeatedly in comparable data sets. Pseudoscience is a pejorative term that applies to scientific conclusions that are consistent with some observations, but which cannot be confirmed or tested with additional data. For example, there is a large body of information that would suggest that the earth has been visited by flying saucers. The evidence comes in the form of eyewitness accounts, numerous photographs, and vociferous official denials of these events suggesting some form of cover-up. Our finest Big Data analyses are only valid to the extent that they have not been disproven. A good example of a tentative and clever conclusion drawn from data is the Titius–Bode law. Titius and Bode developed a simple formula that predicted the locations of planets orbiting a star. It was based on data collected on all of the planets known to Johann Daniel Titius and Johann Elert Bode, two 18th-century scientists. Its position fit almost perfectly into the Titius–Bode series, thus vindicating the predictive power of their formula. Though no fifth planet was found, astronomers found a very large solar-orbiting asteroid, Ceres, at the location predicted by Titius and Bode. Then came the discoveries of Neptune and Pluto, neither of which remotely obeyed the law. The Titius– Bode law was purely descriptive—not based on any universal physical principles. It was just one among many interesting theories aimed at explaining evolution and the origin of species. The Lamarckian theory of evolution preceded Darwin’s natural selection by nearly 60 years. The key difference between Darwin’s theory and Lamarck’s theory comes down to validation. Darwin’s theory has withstood every test posed by scientists in the fields of geology, paleontology, bacteriology, mycology, zoology, botany, medicine, and genetics. Predictions based on Darwinian evolution dovetail perfectly with observations from diverse fields. This theory was groundbreaking in its day, but subsequent findings failed to validate the theory. Darwin’s theory is correct, as far as we can know, because it was validated by scientific progress that occurred over the ensuing 150 years. The value of big data is not so much to make predictions, but to test predictions on a vast number of data objects. Scientists should not be afraid to create and test their prediction models in a Big Data environment. Sometimes a prediction is invalidated, but an important conclusion can be drawn from the data anyway. The Concorde was a supersonic transport jet, one of the most advanced and complex planes ever built. Some debris left on the runway had flipped up and torn a tire and some of the underside of the hull. Most failures occur when a Big Data resource is never completed or never attains an acceptable level of performance. Let us run down the reasons for failure that have been published in blogs, magazine articles, and books on the subject of Big Data disappointments: inappropriate selection and use of human resources (wrong leadership, wrong team, wrong people, wrong direction, wrong milestones, wrong deadlines), incorrect funding (too little funding, too much funding, 167 168 12. Generally, we see failure in terms of our own weaknesses: funders see failure as the result of improper funding, managers see failure as the result of poor management, programmers see deficiencies in programming methods, informaticians see deficiencies in metadata annotations, and so on. The field of Big Data is young; the most senior members of a Big Data team are little more than newbies, and there’s plenty of room for self-doubt. It may be useful to accept every imaginable defect in a Big Data project as a potential cause of failure. For convenience sake, these defects can be divided into two general categories: (1) failures due to design and operation flaws in Big Data resources and (2) failures due to improper analysis and interpretation of results. This chapter deals with the problems that arise when Big Data resources are poorly planned and operated. Nathaniel Borenstein Big Data resources are new arrivals to the information world. With rare exceptions, database managers are not trained to deal with the layers of complexity found in Big Data resources. It is hard to assemble a team with the composite skills necessary to build a really good Big Data resource. At this time, many data managers are reflexively acquiring new software applications designed to deal with Big Data collections. Far fewer data managers are coming to grips with the fundamental concepts discussed in earlier chapters. It may take several decades before these fundamental principles sink in and Big Data resources reach their highest potential. It is not unusual for large, academic medical centers to purchase information systems that cost in excess of $500 million. Successfully implemented electronic health record systems have not 164 been shown to improve patient outcomes. Based on a study of the kinds of failures that account for patient safety errors in hospitals, it has been suggested that hospital information 72 systems will not greatly reduce safety-related incidents. Clinical decision support systems, built into electronic health record systems, have not had much impact on physician 165 practice. These systems tend to be too complex for a hospital staff to master and are not well utilized. After investing $17 billion dollars, the project was ditched when members of Parliament 166–168 called the effort “unworkable. The 1992 crash of the London ambulance dispatch system was a setback to advanced computer control systems. Completed jobs were uncleared, resulting in ambulances that were unengaged yet unavailable. Four years later, after many investigative studies, a new 169 system was implemented; this one worked. There is no registry of Big Data projects that can be followed to determine which projects fail over time. There is no formal designation “Big Data project” that is bestowed on some projects and withheld from others. Would we require a project to be officially disbanded, with all funds withdrawn, before we say that it is defunctfi Or would we say that a Big Data project has failed if it did not meet its original set of goalsfi If a Big Data resource is built, and operates as planned, can we say that it has failed if nobody actually uses the resourcefi With these caveats in mind, it is believed that the majority of information technology projects fail, and that failure is positively correlated with the size and cost 170 of the projects. It is claimed that public projects costing hundreds of billions of dollars have 171 failed quietly, without raising much attention. Big Data projects are characterized by large size, high complexity, and novel technology, all of which aggravate any deficiencies in 170 management, personnel, or process practices. Open Systems Interconnection was a sevenlayer protocol intended as the Internet standard. It has been supplanted by the Transmission Control Protocol/ Internet Protocol, preferred by Unix. It is used throughout the world, and it is generally acknowledged as a vast improvement over every preceding measurement standard. Nonetheless, in the United States, our height is measured in feet and inches, not meters and centimeters, and our weight is measured in pounds, not kilograms. Here in the United States, it would be difficult to find a bathroom scale marked with metric graduations. The next time you look at your calendar, remember that about half the world uses a solar calendar. We may all agree that the world spins on its axis, but every assertion that follows is controversial and nonstandardized. Every new programming language is born with the hope that it will be popular and immortal. National Institute of Standards announced that Ada would be used by federal departments and agencies in software applications that involve control of real-time or parallel processes, very large systems, and 172 systems with requirements for very high reliability. Every Ada programmer knows that Ada is not an acronym; they bristle whenever Ada is spelled with all uppercase letters. On June 4, 1996, the maiden flight of the French Ariane 5 exploded 37 seconds after launch. A software exception occurred during a data conversion from a 64-bit floating point to 16-bit signed integer value. The data conversion instructions (in Ada code) were not protected from 173 causing an Operand Error. On September 23, 1999, the United States launched the Mars Climate Orbiter, which crashed on impact on the red planet. An official investigation by the Mars Climate Orbiter Mishap Investigation Board concluded that the crash occurred due to a software glitch that arose when English units of measurement were used in the software when metric units were 174 supplied as input. Ada is a fine programming language, but declaring it a government standard could not guarantee error-free implementations, nor could it guarantee its popularity among programmers. Following its ascension to standards status, the popularity of Ada declined rapidly. The most successful standards are specifications that achieved popularity before they achieved the status of “standard. The most unsuccessful standards are those prepared by a committee of special interests who create the standard ab initio. The altogether worst standards seem to be those that only serve the interests of the standards committee members. For small data projects and for software applications, the instability of data standards is not a major problem. Small data projects are finite in length and will seldom extend beyond the life span of the standards implemented within the project. For software designers, a standard implemented within an application can be replaced in the next upgrade. Instability in standards serves the interests of software developers by coercing customers to purchase upgrades that comply with the new versions of included standards. A failed standard may invalidate the data model for the resource—undoing years of work. Over 20 years ago, I was approached by a pathologist who was tasked with annotating his diagnostic reports with a standard vocabulary of diseases. His best bet, under the circumstances, was to write his reports in simple, declarative sentences, using canonical diagnostic terms. Simplified sentences could be easily parsed into constituent parts and accurately translated or mapped to any chosen vocabulary, 176 as needed. Consider the following sentence: “The patient has an scc, and we see invasion to the subcutaneous tissue, all the way to the deep margins, but the lateral margins are clear. Among other impediments, a computer would not know that the abbreviation “scc” corresponds to the diagnostic term “squamous cell carcinoma. The complex sentence could be rewritten as six declarative statements: Diagnosis: squamous cell carcinoma. Every surgical pathology case entered in the hospital information system could be coded again and again, using any new version of any nomenclature. We could go one step further, expressing every statement as a triple consisting of an identifier, a metadata term, and a data value. In a Big Data resource, an extremely simple data model might retain compatibility with any new data standard. If all of the data in the resource is available as simple triples, and if the model provides a method whereby data objects can be assigned to classes, then every data object can be fully specified. Specified data objects, expressed as a simple triples, can be ported into any old or new data standard, as needed. For example, consider the following triples: 2847302084 weight “25 pounds” 2847302084 instance of 8909851274 8909851274 class name “dog” 8909851274 subclass of 7590293847 7590293847 class name “canine” this tells us that the data object identified as 2847302084 weighs 25 pounds and is an instance of class 8909851274 of dogs. We can use triples to express any information we might ever collect, and we can relate every triple to other classes of triples, to produce a data model. Furthermore, our data can be ported into new standards created for specific types of data included in our resource. For example, if we needed to create a document for a veterinary department, in a standard format, we could collect our triples containing data on dogs, and we could produce a report, in a standard format, that lists everything we know about each dog. If you know the rules for standards, you can write a program that converts to the standard, as needed. In many instances, a simple, generic data model may free the Big Data manager from the problems that ensue when a data standard becomes obsolete. It is easy to write software that attains a level of complexity that exceeds anything encountered in the physical realm. Likewise, there is no limit to the complexity of operational methods, security standards, data models, and virtually every component of a Big Data resource.

Why isn’t this data deidentified using methods discussed earlier (Chapter 2) and distributed for public review and analysisfi None of the commercially available deidentification/scrubbing software does a perfect job treatment dynamics florham park buy cheap lamictal on-line. These software applications merely reduce the number of identifiers in records; they leave behind an irreducible number of identifying information bad medicine 1 buy generic lamictal 50 mg on line. If deidentification/scrubbing software actually performed as claimed hair treatment generic 50 mg lamictal free shipping, removing every identifier and every byte of unwanted data from electronic records medicine 8 discogs discount 25 mg lamictal amex, some records might be identified through the use of external database resources that establish identities through nonidentifying details contained in records (vida infra) medications qd 50mg lamictal with amex. Big Data managers are highly risk averse and would rather hoard their data than face the risk treatment zenkers diverticulum order 25mg lamictal amex, no matter how unlikely, of a possible tort suit from an aggrieved individual. Big Data managers are comfortable with restricted data sharing through legal instruments such as data use agreements (see Glossary item, Data sharing). Through such agreements, selected sets of data extracted from a Big Data resource are provided to one or a few entities who use the data for their own projects and who do not distribute the data to other entities. Data deidentification methods, like many of the useful methods in the information field, can be patented. Some of the methods for deidentification have fallen under patent restriction or have been incorporated into commercial software that is not freely available 45 to data managers. For some data managers, royalty and license costs are additional reasons for abandoning the deidentification process. Big Data managers are not fully convinced that deidentification is possible, even under ideal circumstances. It may seem impossible, but information that is not considered identifying may actually be used to discover the name of the person linked to deidentified records. Mischievous schemes to thwart the deidentification process all work through one simple trick: access to an external database that contains identified information linked to nonidentifying data. Here is an example whereby the trick works: suppose I have a data set composed of deidentified records that includes a field for gene variants and another field for criminal record. The data resource is being used for many analytic purposes, including efforts to determine whether there is an association between certain gene variants and certain types of criminal behavior. Let us imagine that there is a public database containing identified records that contain the same kinds of gene variant data (see Glossary item, Public data). All of the identified records in this database were obtained from volunteers who wished to participate in studies that might help identify their own ancestors. When he finds a match in gene variants, he acquires the name associated with the gene variant in the public database, and that name will correspond with the person whose criminal record is included in the deidentified database. Basically, deidentification is easy to break when deidentified data can be linked to a name in an identified database containing fields that are included in both databases. This is the common trick underlying virtually every method designed to associate a name with a deidentified record. In the example provided, it may be impossible to find an exact match between the gene variants in the deidentified database and the gene variants in the identified database. In this case, close matches to a group of records all identified with the same surname may provide all the information that is needed to establish a unique individual’s identity. Data managers who provide deidentified data sets to the public must worry whether there is, or ever will be, an available identified database that can be used to link fields, or combinations of fields, to their deidentified data, and thus linking their records to the names of individuals. This worry weighs so heavily on data managers and on legal consultants for Big Data resources that there are very few examples of publicly available deidentified databases. Everyone in the field of Big Data is afraid of the legal repercussions that will follow when the confidentiality of their data records is broken. These issues are often intractable because each side has a legitimate claim to their own preferences (businesses need to make profit and individuals need some level of privacy). At some point, every Big Data manager must create a privacy policy and abide by his or her own rules. It has been my experience that legal problems arise when companies have no privacy policy, have a privacy policy that is not well documented, have a privacy policy that is closed to scrutiny, have a fragmented privacy policy, or fail to follow their own policy. Companies are much more likely to get into trouble for ignoring their own policies than for following an imperfect policy. Every Big Data project should make the effort to produce a thoughtful set of policies to protect the confidentiality of its records and the privacy of data subjects. These policies should be studied by every member of a Big Data project, and should be modified as needed, and be reviewed at regular intervals. If you are a Big Data manager endowed with an overactive imagination, it is possible to envision all types of unlikely scenarios in which confidentiality can be breached. As an example, the privacy law that applies to hospitals and health care organi33 zations contains 390 occurrences of the string “reasonable. In addition to their use in diabetes research, the informed consent indicated the samples might be used for research on “behavioral and medical disorders,” not otherwise specified. The researchers tried but failed to make headway linking genes sampled from the Havasupai tribe with cases of diabetes. The gene samples were subsequently used for ancillary studies that included schizophrenia and for studies on the demographic trends among the Havasupai. In their opinion, these studies did not benefit the Havasupai and touched upon questions that were considered embarrassing and taboo, including the topic of consanguineous matings and the prevalence rates of mental illnesses within the tribe. In 2004, the Havasupai tribe filed a lawsuit indicating lapses in the informed consent process, violation of civil rights, violation of confidentiality, and unapproved use of the samples. The case was dismissed on procedural grounds, but was reinstated by the Arizona Court of 209 Appeals in 2008. Arizona State University agreed to pay individuals in the Havasupai tribe a total of $700,000. This award is considerably less than the legal costs already incurred by the university. If the Havasupai tribe won anything in this dispute, it must have been a Pyrrhic victory. Because the case was settled out of court, no legal decision was rendered and no clarifying precedent was established. Though I am not qualified to comment on the legal fine points, several of the general principles related to the acquisition and use of data are relevant and can be discussed as topics of general interest. Laypersons should not be put into a situation wherein they must judge the value of research goals. By signing consent, the signator indicates that he or she is aware of the potential harm from the research and agrees to accept the risk. In the case of samples or data records contributed to a Big Data resource, consenters must be warned, in writing, that the data will be used for purposes that cannot be specified in the consent form. Most consent is obtained to achieve one primary purpose, and this purpose is customarily described briefly in the consent form. The person who consents often wants to know that the risks that he or she is accepting will be compensated by some potential benefit to society. There is no ethical requirement that binds scientists to conduct their research for the sole benefit of one group of individuals. A good consent form will clearly state that research conducted cannot be expected to be of any direct value to the consenter. Finally, the consent form should include all of the potential harms that might befall the consenter as a consequence of his or her participation. It may be impossible to anticipate every possible adverse consequence to a research participant. In this case, the scientists at Arizona State University did not anticipate that the members of the Havasuapai tribe would be harmed if their gene data was used for ancillary research purposes. I would expect that the researchers at Arizona State University do not believe that their research produced any real harm. Had the original consent form listed all of the potential harms, as perceived by the Havasupai, then the incident could have been avoided. Had any members of the Havasupai tribe voiced concerns over the unspecified medical and behavioral disorders mentioned in the consent form, then the incident could have been avoided. The Havasupai did not understand how scientists use information to pursue new questions. The board of regents did not understand the harms that might occur when data is used for legitimate scientific purposes. The take-home lesson for data managers is the following: to the extent humanly possible, ensure that consent documents contain a complete listing of relevant adverse consequences. In some cases, this may involve writing the consent form with the assistance of members of the group whose consent is sought. The future directions of Big Data will be strongly influenced by social, political, and economic forces. Will scientists archive their experimental data in publicly accessible Big Data resourcesfi Will scientists adopt useful standards for their operational policies and their datafi How scientists use data over the next few years may provide the strongest argument for or against the proliferation of Big Data resources. The purpose of Big Data was rationalized under the following eight distinct hypotheses. Gumshoe hypothesis: Hoarding information about individuals for investigative purposes. In this hypothesis, Big Data exists for private investigators, police departments, and 201 202 14. The modern private eye has profited from Big Data, as have law enforcement officers. It is unsettling that savvy individuals have used Big Data to harass, stalk, and breach the privacy of other individuals. These activities have left some individuals dreading future sanctioned or unsanctioned uses of Big Data. The expectation that Big Data will serve to prevent crime, bring criminals to justice, and enhance the security of law-abiding citizens has not fully engaged the public consciousness. Big Brother hypothesis: Collecting information about a population of individuals to control every member of the population. Modern governments obtain data from surveillance cameras, arrest records, wiretaps and sophisticated eavesdropping techniques, census records, tax records, accounting records, driving records, public health records, and a wide variety of information collected in the normal course of official operations. When a government sponsors Big Data collections, there will always be some anxiety that the Big Data resource will be used to control the public, reducing our freedoms of movement, expression, and thought. On the plus side, such population-wide studies may eventually reduce the incidence of crime and disease, make driving safer, and improve society overall. Borg hypothesis: Collecting information about a population of individuals to learn everything about the population. I assume that if you are reading this book on Big Data, you most likely are a Star Trek devotee and understand that the Borg are a race of collectivist aliens who travel through galaxies, absorbing knowledge from civilizations encountered along the way. The conquered worlds are absorbed into the Borg “collective” while their scientific and cultural achievements are added to a Big Data resource. Big Data analysts predict and control the activities of populations: how crowds move through an airport, when and where traffic jams are likely to occur, when political uprisings will occur, how many people will buy tickets for the next 3D movie production, or how fast the next flu epidemic will expand. The late great comedian George Carlin famously chided us for wasting our time, money, and consciousness on one intractable problem: “Where do we put all our stufffi With cloud computing, search engines that encompass the Web, and protocols for retrieving our own information upon request, Big Data becomes an infinite storage attic. When the ancient Sumerians recorded buy–sell transactions, they used clay tablets. The safety, availability, and permanence of electronic “cloud” data is a hypothesis that will be tested over time. Find these: movies playing now at the local cineplex, Amtrak schedule for the northeast corridor of the United States, cost of tickets to a Broadway play, updated locations of spouse and children, average weight of male elephants, and in-air flight time to New Delhi. According to the scavenger hunt hypothesis, Big Data is everything you ever wanted to know about everything. Egghead hypothesis: Collecting information to draw generalized scientific conclusions. To fully understand the beauty of the egghead hypothesis, a preliminary explanation of the purpose of science is in order. Science is a method whereby we develop generalizations about the nature of our world and of the universe by observing individual objects in the universe under various naturally occurring or experimentally contrived conditions. For example, when an object such as an apple or a lead weight is dropped from a height, we can watch it fall, measure the time for the descent, determine that the apple and the lead weight dropped at the same rates throughout their respective descents, and develop a formula that relates the distance dropped to the square of the interval time for the drop. Once done, and confirmed on other objects, we know a great deal about how everything falls (not just one apple and one lead weight). When a scientist extracts Big Data collected on a large set of individuals, his or her purpose is to quickly move from the level of specificity. For example, if a scientist is studying the incubation period for West Nile virus, when humans are infected by a mosquito bite, the scientist will want to collect as many infection records as possible, with detailed information documenting the time that infection occurred and the time that symptoms emerged. The records will be identified, at some time in the data collection process, with information that links the record to a particular person. The last thing that the scientist is interested in is the identity of the patient. The scientist is marching in a path that leads to the most general statement possible: “The incubation period for West Nile virus is 2 to 15 days. It is important to understand that Big Data is focused on complex, and individual, identified data records, while responsible science is focused on simplifying information to yield nonpersonal generalizations. This last point is stressed because the public should not need to fear that scientists have any interest in any individual’s personal information. The new knowledge, tools, practices, and infrastructures produced will enable breakthrough discoveries and innovation in science, engineering, medicine, commerce, education, and national security—laying the foundations for U. The underlying assumption here is that people want to use their computers to interact with other people.

Syndromes

• Spleen
• Cranial CT scan to look for spread (metastasis) to the brain
• Deformity of the hand (rare)
• Burns of the esophagus (food pipe)
• Nausea and vomiting
• Have you come into contact with something you might be allergic to?

Progressive magnesium deficiency increases mortality from endotoxin challenge: protective effects of acute magnesium replacement therapy medicine interactions discount lamictal online american express. Intravenous magnesium sulfate for bronchial hyperreactivity: a randomized symptoms mononucleosis cheap lamictal 25mg without prescription, controlled treatment 20 lamictal 100mg overnight delivery, double-blind study medicine 0636 discount lamictal 25 mg without a prescription. Oral magnesium supplementation inhibits platelet-dependent thrombosis in patients with coronary heart disease medications that raise blood sugar trusted lamictal 100mg. Intravenous infusion of magnesium sulphate after acute myocardial infarction: effects on arrhythmias and mortality treatment question buy lamictal on line amex. Post-traumatic renal shutdown in humans: its prevention and treatment by the intravenous infusion of mannitol. 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Commonly used muscle relaxant therapies for acute low back pain: a review of carisoprodol, cyclobenzaprine hydrochloride, and metaxalone. Signi fi cantly impaired renal function Contraindicated Alternative adjustment: Data not available 439 Dosage Adjustment of Medications Eliminated by the Kidneys Metformin Selected References Abe M, Okada K, Soma M. Systematic review of current guidelines, and their evidence base, on risk of lactic acidosis after administration of contrast medium for patients receiving metformin. Metformin and antihypertensive therapy with drugs blocking the renin angiotensin system, a cause of concernfi Severe lactic acidosis treated with prolonged hemodialysis: recovery after massive overdoses of metformin. Management of metformin-associated lactic acidosis by continuous renal replacement therapy. Risk of fatal and nonfatal lactic acidosis with metformin use in type 2 diabetes mellitus (review). 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References:

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• https://www.cdc.gov/nchs/data/nhanes/nhanes3/hepatic_steatosis_ultrasound_procedures_manual.pdf
• https://www.oecd.org/health/health-systems/HWP-115-MEAs.pdf
• https://www.massgeneral.org/assets/MGH/pdf/news/coronavirus/mass-general-COVID-19-treatment-guidance.pdf
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