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Naranjo algorithm

Naranjo algorithm is a computer science topic covered in the lgStudy science library. This page brings together a partial reference excerpt, illustrations, worked examples, real-world applications and a short study plan, so you can understand Naranjo algorithm rather than just read about it. In short: 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.

Key takeaways

  • Naranjo algorithm belongs to computer science; place it in that map before memorising details.
  • Learn the definition first, then one example that makes the definition concrete.
  • Connect Naranjo algorithm to a quantity you can measure, compute or draw — that is where exam questions come from.
  • Reproduce the core statement of Naranjo algorithm from memory before moving on to harder problems.

Reference excerpt

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.

Questionnaire 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

≥ 9 = definite ADR 5-8 = probable ADR 1-4 = possible ADR 0 = doubtful ADR

References Naranjo, C A; Busto, U; Sellers, E M; Sandor, P; Ruiz, I; Roberts, E A; Janecek, E; Domecq, C; Greenblatt, D J (1981). "A method for estimating the probability of adverse drug reactions". Clinical Pharmacology and Therapeutics. 30 (2): 239–245. doi:10.1038/clpt.1981.154. ISSN 0009-9236. PMID 7249508. S2CID 29728085. A*l-Tajir GK, Kelly WN. Epidemiology, comparative methods of detection, and preventability of adverse drug events. Ann Pharmacother. 2005;39:1169-1174. Abstract

Brown S, Black K, Mrochek S, et al. RADARX: recognizing, assessing, and documenting adverse Rx events. Proc AMIA Symp. 2000:101-105. Classen DC, Pestotnik SL, Evans RS, et al. Description of a computerized adverse drug event monitor using a hospital information system. Hosp Pharm. 1992;27:774-783. Abstract Gandi TK, Bates DW. Computer adverse drug event detection and alerts. In: Making Healthcare Safer: A Critical Analysis of Patient Safety Practices. Rockville, Md: Agency for Healthcare Research and Quality; 2001. Jones JK. Adverse drug reactions in the community health setting: approaches to recognizing, counseling, and reporting. Fam Community Health. 1982;5:1982. Hill AB. The environment and disease association or causation. Proc R Soc Med. 1965;58:295-300. Abstract Naranjo CA, Busto U, Sellers EM, et al. A method for estimating the probability of adverse drug reactions. Clin Pharmacol Ther. 1981;30:239-245. Abstract

External links Naranjo algorithm Online calculator

Worked examples

Example 1 — a first encounter with Naranjo algorithm

Start with the simplest possible case. Write down what Naranjo algorithm claims or describes in one sentence, then invent the smallest concrete situation in which that sentence is true. In computer science, the smallest case is usually a single object, a single equation or a single measurement. Check that every symbol or term in your sentence has a meaning in that case.

Example 2 — changing one variable

Take the situation from Example 1 and change exactly one quantity: double it, halve it, or set it to zero. Predict what should happen to Naranjo algorithm before you calculate. Comparing your prediction with the result is the fastest way to find out whether you understand the idea or only the words.

Example 3 — an exam-style question

Typical questions about Naranjo algorithm ask you to (a) state it precisely, (b) apply it to given data, and (c) explain a limitation. Practise writing all three answers in under five minutes; the third part is what separates a full-mark answer from an average one.

Applications of Naranjo algorithm

In research
Naranjo algorithm appears in computer science research whenever the underlying quantities have to be modelled precisely. Papers usually cite it as a starting assumption and then explore where it breaks down.
In technology and industry
Engineering practice reuses Naranjo algorithm in design rules, simulations and safety margins. Knowing the idea lets you read a specification sheet and understand why the numbers look the way they do.
In the classroom
Naranjo algorithm is common in secondary-school and first-year university syllabi. It links to neighbouring topics Drug safety, so understanding it makes those chapters shorter.
In everyday life
Look for Naranjo algorithm outside the textbook — in sport, cooking, traffic, electronics or the sky above you. An example you found yourself is remembered far longer than one you were given.

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How to study Naranjo algorithm in 20 minutes

  1. Read the reference excerpt below once, without taking notes.
  2. Close the page and write down what Naranjo algorithm means in your own words.
  3. Compare your version with the excerpt and mark what you missed.
  4. Work through the three examples above with pen and paper.
  5. Explain Naranjo algorithm out loud to somebody else — or to Teacher Smith in the lgStudy chat.

Frequently asked questions

What is Naranjo algorithm in simple terms?

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…

Why does Naranjo algorithm matter?

Because it connects several computer science ideas at once: it gives you a definition you can apply, a quantity you can calculate, and a way to check whether a result is plausible.

How should I study Naranjo algorithm?

Read the excerpt, restate it from memory, then work through the examples and applications listed on this page. The five-step study plan above takes about twenty minutes.

What does this page cover?

It gives you a compact reference excerpt plus original lgStudy explanations, examples, applications and study material on Naranjo algorithm.

Tags

  • Drug safety

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