Litt's Drug Eruption & Reaction Manual
Bibliographic record
Abstract
Internationally relied upon by medical practitioners for its unparalleled focus on adverse effects and cutaneous reactions, Litt’s Drug Eruption & Reaction Manual is a succinct clinical reference and essential drug-safety tool for patient care. This 27th edition is a comprehensively revised and updated quick reference, and each entry includes:* Quantitative summaries of reports and incidence for reactions* Drug–drug interactions* Categories of adverse drug reactions, eruptions, and cutaneous reaction patterns* Essential reference information on prescription and over-the-counter drugs as well as herbals and supplements The book contains... * A to Z listing of the 1500 most consulted drug and herbal profiles, including generic name and trade names; pharmaceutical company; indications; half-life; and pregnancy category* Over 31,000 adverse reactions and drug-eruption listings * Includes supplements, vaccines, and botanicals* Clinical definitions of common and severe adverse reactions* List of drugs that cause severe adverse reactions* List of main classes of drugs as a quick clinical reference guide* 27 tables of members of a class of drugs (such as statins or monoclonal antibodies), enabling clinicians to see at a glance whether a reaction is common to all drugs included in that class, or to a majority of them, or is known in only a handful—information that is critical for an informed decision to change drugs within the same class* 2 extensive tables showing reported genetic associations with cutaneous adverse drug reactions and recommendations regarding genetic screening to prevent cutaneous adverse drug reactions* A concordance of synonyms and trade names for ease of cross-reference Markets: Dermatologists, Neurologists, Oncologists, Psychiatrists, Pharmacists, Family Physicians, and those caring for patients on multiple medications, such as Geriatricians and Hospital Generalist Physicians. Litt’s Drug Eruption & Reaction Manual is a succinct clinical reference derived from Litt’s Drug Eruption & Reaction Database, located at www.drugeruptiondata.com, which currently holds over 1750 drug profiles with almost 70,000 documented drug reactions, as evidenced by well over 145,000 references on PubMed. Quick and easy access via the Litt app provides real time access to the most up-to-date drug safety information to a busy practitioner on-the-go. Subscribers to the database benefit from:* Easy access via the Litt app, ideal for working across a number of work-places* Full drug profiles with a wealth of information including category, half-life, indications, drug-drug interactions, and known adverse reactions* Links to PubMed abstracts * Searching a class of drugs for a specific reaction* Searching by adverse reaction pattern* Searching by indication for a drug* Searching by drug name (generic name/brand name) as well as by pharmaceutical company or drug class* Searching herbal medicines and supplements* Diagnosing the cause of reactions in patients on multiple drugs by selecting the adverse reaction(s) experienced and the drug(s) the patient is taking* Comparing reaction profiles for up to four drugs in a customized chart that can be saved for future reference* Descriptions of reaction patterns* Photographs of adverse reactions* Access via a computer, tablet, or smartphone* Regular updates To learn more, and to subscribe to the database, visit www.drugeruptiondata.com.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.322 | 0.237 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".