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The Naranjo algorithm, Naranjo Scale, or Naranjo Nomogram is a questionnaire designed by Naranjo et al. for determining the likelihood of whether an adverse drug reaction (ADR) is actually due to the drug rather than the result of other factors. Probability is assigned via a score termed definite, probable, possible or doubtful. Values obtained from this algorithm are often used in peer reviews to verify the validity of author's conclusions regarding ADRs.
It is often compared to the WHO-UMC system for standardized causality assessment for suspected ADRs.
Empirical approaches to identifying ADRs have fallen short because of the complexity of the set of variables involved in their detection. Computer decision programs have helped in this analysis. Electronic medical record systems can be programmed to fire alerts when a potential adverse drug event is about to occur or has already occurred.[3,4] Automated adverse drug event monitors can search for keywords or phrases throughout the patient's medical record to identify drug therapies, laboratory results, or problem lists that may indicate that a patient has already been treated for an ADR. This detection method uncovers significantly more adverse events, including medication errors, than relying only on empirical methods or incident reports.[1,2]
Empirical methods to assess the likelihood that an ADR has taken place have been lacking. More formal, logical analysis can help differentiate between events that are attributable to a drug from those associated with underlying diseases or other factors, underlying the complexity of detection.[5]
Several investigators, among them researchers at the FDA, have developed such logical evaluation methods, or algorithms, for evaluating the probability of an ADR.[2, 20-24] Almost all of these methods employ critical causation variables identified by Sir Austin Bradford Hill in 1965.[6] The most widely accepted of these instruments is the Naranjo algorithm[22] (Table). This method has been tested for internal validity with between-rater reliability testing, and its probability scale has consensual, content, and concurrent validity as well as ease of use in clinical settings and controlled studies.
1. Are there previous conclusive reports on this reaction?
Yes (+1) No (0) Do not know or not done (0)
2. Did the adverse events appear after the suspected drug was given?
Yes (+2) No (-1) Do not know or not done (0)
3. Did the adverse reaction improve when the drug was discontinued or a specific antagonist was given?
Yes (+1) No (0) Do not know or not done (0)
4. Did the adverse reaction appear when the drug was re administered?
Yes (+2) No (-1) Do not know or not done (0)
5. Are there alternative causes that could have caused the reaction?
Yes (-1) No (+2) Do not know or not done (0)
6. Did the reaction reappear when a placebo was given?
Yes (-1) No (+1) Do not know or not done (0)
7. Was the drug detected in any body fluid in toxic concentrations?
Yes (+1) No (0) Do not know or not done (0)
8. Was the reaction more severe when the dose was increased, or less severe when the dose was decreased?
Yes (+1) No (0) Do not know or not done (0)
9. Did the patient have a similar reaction to the same or similar drugs in any previous exposure?
Yes (+1) No (0) Do not know or not done (0)
10. Was the adverse event confirmed by any objective evidence?
Yes (+1) No (0) Do not know or not done (0)
Scoring
Supervised learning (SL) is a paradigm in machine learning where input objects and a desired output value train a model. The training data is processed, building a function that maps new data on expected output values. An optimal scenario will allow for the algorithm to correctly determine output values for unseen instances. This requires the learning algorithm to generalize from the training data to unseen situations in a "reasonable" way. This statistical quality of an algorithm is measured through the so-called generalization error.
Non-steroidal anti-inflammatory drugs (NSAID) are members of a therapeutic drug class which reduces pain, decreases inflammation, decreases fever, and prevents blood clots. Side effects depend on the specific drug, its dose and duration of use, but largely include an increased risk of gastrointestinal ulcers and bleeds, heart attack, and kidney disease.
Anecdotal evidence is evidence based only on personal observation, collected in a casual or non-systematic manner.
Levofloxacin, sold under the brand name Levaquin among others, is an antibiotic medication. It is used to treat a number of bacterial infections including acute bacterial sinusitis, pneumonia, H. pylori, urinary tract infections, chronic prostatitis, and some types of gastroenteritis. Along with other antibiotics it may be used to treat tuberculosis, meningitis, or pelvic inflammatory disease. Use is generally recommended only when other options are not available. It is available by mouth, intravenously, and in eye drop form.
Pharmacovigilance, also known as drug safety, is the pharmaceutical science relating to the "collection, detection, assessment, monitoring, and prevention" of adverse effects with pharmaceutical products. The etymological roots for the word "pharmacovigilance" are: pharmakon and vigilare. As such, pharmacovigilance heavily focuses on adverse drug reactions (ADR), which are defined as any response to a drug which is noxious and unintended, including lack of efficacy. Medication errors such as overdose, and misuse and abuse of a drug as well as drug exposure during pregnancy and breastfeeding, are also of interest, even without an adverse event, because they may result in an adverse drug reaction.
An adverse drug reaction (ADR) is a harmful, unintended result caused by taking medication. ADRs may occur following a single dose or prolonged administration of a drug or may result from the combination of two or more drugs. The meaning of this term differs from the term "side effect" because side effects can be beneficial as well as detrimental. The study of ADRs is the concern of the field known as pharmacovigilance. An adverse event (AE) refers to any unexpected and inappropriate occurrence at the time a drug is used, whether or not the event is associated with the administration of the drug. An ADR is a special type of AE in which a causative relationship can be shown. ADRs are only one type of medication-related harm. Another type of medication-related harm type includes not taking prescribed medications, known as non-adherence. Non-adherence to medications can lead to death and other negative outcomes. Adverse drug reactions require the use of a medication.
An adverse effect is an undesired harmful effect resulting from a medication or other intervention, such as surgery. An adverse effect may be termed a "side effect", when judged to be secondary to a main or therapeutic effect. The term complication is similar to adverse effect, but the latter is typically used in pharmacological contexts, or when the negative effect is expected or common. If the negative effect results from an unsuitable or incorrect dosage or procedure, this is called a medical error and not an adverse effect. Adverse effects are sometimes referred to as "iatrogenic" because they are generated by a physician/treatment. Some adverse effects occur only when starting, increasing or discontinuing a treatment. Using a drug or other medical intervention which is contraindicated may increase the risk of adverse effects. Adverse effects may cause complications of a disease or procedure and negatively affect its prognosis. They may also lead to non-compliance with a treatment regimen. Adverse effects of medical treatment resulted in 142,000 deaths in 2013 up from 94,000 deaths in 1990 globally.
The number needed to treat (NNT) or number needed to treat for an additional beneficial outcome (NNTB) is an epidemiological measure used in communicating the effectiveness of a health-care intervention, typically a treatment with medication. The NNT is the average number of patients who need to be treated to prevent one additional bad outcome. It is defined as the inverse of the absolute risk reduction, and computed as , where is the incidence in the control (unexposed) group, and is the incidence in the treated (exposed) group. This calculation implicitly assumes monotonicity, that is, no individual can be harmed by treatment. The modern approach, based on counterfactual conditionals, relaxes this assumption and yields bounds on NNT.
An adverse event (AE) is any untoward medical occurrence in a patient or clinical investigation subject administered a pharmaceutical product and which does not necessarily have a causal relationship with this treatment. An adverse event can therefore be any unfavourable and unintended sign, symptom, or disease temporally associated with the use of a medicinal (investigational) product, whether or not related to the medicinal (investigational) product.
Predictive modelling uses statistics to predict outcomes. Most often the event one wants to predict is in the future, but predictive modelling can be applied to any type of unknown event, regardless of when it occurred. For example, predictive models are often used to detect crimes and identify suspects, after the crime has taken place.
In causal inference, a confounder is a variable that influences both the dependent variable and independent variable, causing a spurious association. Confounding is a causal concept, and as such, cannot be described in terms of correlations or associations. The existence of confounders is an important quantitative explanation why correlation does not imply causation. Some notations are explicitly designed to identify the existence, possible existence, or non-existence of confounders in causal relationships between elements of a system.
Uppsala Monitoring Centre (UMC), located in Uppsala, Sweden, is the field name for the World Health Organization Collaborating Centre for International Drug Monitoring. UMC works by collecting, assessing and communicating information from member countries' national pharmacovigilance centres in regard to the benefits, harm, effectiveness and risks of drugs.
Research on Adverse Drug Events and Reports (RADAR) is a pharmacovigilance team of 25 doctors who receive calls about possible adverse drug reactions (ADR) and investigate. RADAR is based at Northwestern's Feinberg School of Medicine. RADAR is led by Dennis West. Though it was without funding for its first four years, RADAR has raised about $12 million through grants from the National Institutes of Health, the American Cancer Society and other such institutions. Its work has identified safety problems with 33 drugs. Adverse drug events are a serious health problem.
Challenge–dechallenge–rechallenge (CDR) is a medical testing protocol in which a medicine or drug is administered, withdrawn, then re-administered, while being monitored for adverse effects at each stage. The protocol is used when statistical testing is inappropriate due to an idiosyncratic reaction by a specific individual, or a lack of sufficient test subjects and unit of analysis is the individual. During the dechallenge (withdrawal) phase, the medication is allowed to wash out of the system in order to determine what effect the medication is having on an individual.
A glossary of terms used in clinical research.
Iatrogenesis is the causation of a disease, a harmful complication, or other ill effect by any medical activity, including diagnosis, intervention, error, or negligence. First used in this sense in 1924, the term was introduced to sociology in 1976 by Ivan Illich, alleging that industrialized societies impair quality of life by overmedicalizing life. Iatrogenesis may thus include mental suffering via medical beliefs or a practitioner's statements. Some iatrogenic events are obvious, like amputation of the wrong limb, whereas others, like drug interactions, can evade recognition. In a 2013 estimate, about 20 million negative effects from treatment had occurred globally. In 2013, an estimated 142,000 persons died from adverse effects of medical treatment, up from an estimated 94,000 in 1990.
Drug therapy problems (DTPs) represent the categorization and definition of clinical problems related to the use of medications or "drugs" in the field of pharmaceutical care. In the course of clinical practice, DTPs are often identified, prevented, and/or resolved by pharmacists in the course of medication therapy management, as experts on the safety and efficacy of medications, but other healthcare professionals may also manage DTPs.
The proportional reporting ratio (PRR) is a statistic that is used to summarize the extent to which a particular adverse event is reported for individuals taking a specific drug, compared to the frequency at which the same adverse event is reported for patients taking some other drug (or who are taking any drug in a specified class of drugs). The PRR will typically be calculated using a surveillance database in which reports of adverse events from a variety of drugs are recorded.
The PageRank algorithm has several applications in biochemistry.
The discipline of forensic epidemiology (FE) is a hybrid of principles and practices common to both forensic medicine and epidemiology. FE is directed at filling the gap between clinical judgment and epidemiologic data for determinations of causality in civil lawsuits and criminal prosecution and defense.
A*l-Tajir GK, Kelly WN. Epidemiology, comparative methods of detection, and preventability of adverse drug events. Ann Pharmacother. 2005;39:1169-1174. Abstract