Evidence map›Paper›PMID 19270474›Full record

ReviewThe Korean journal of internal medicine2009

Overview of therapeutic drug monitoring.

Ju Seop Kang, Min Ho Lee

Abstract readReview
In one paragraph

Review in The Korean journal of internal medicine, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 235 papers, 5 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
235citing papers in PubMed, 5 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

235 citing papers in PubMed, 5 syntheses or guidelines pooled it.

  1. Pooled it
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  6. Trial
  7. Article
  8. Observational
  9. Review
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  14. Article
  15. Drug Critical Limits for Urgent Physician Notification.Clinical pharmacology and therapeutics · 2026
    Article
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  17. Review
  18. Article
  19. Review
  20. Article

175 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Ju Seop KangDepartment of Pharmacology and Clinical Pharmacology Laboratory, Hanyang University College of Medicine, Seoul, Korea. jskang@hanyang.ac.kr
Min Ho Lee

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Therapeutic drug monitoring (TDM) is the clinical practice of measuring specific drugs at designated intervals to maintain a constant concentration in a patient's bloodstream, thereby optimizing individual dosage regimens. It is unnecessary to employ TDM for the majority of medications, and it is used mainly for monitoring drugs with narrow therapeutic ranges, drugs with marked pharmacokinetic variability, medications for which target concentrations are difficult to monitor, and drugs known to cause therapeutic and adverse effects. The process of TDM is predicated on the assumption that there is a definable relationship between dose and plasma or blood drug concentration, and between concentration and therapeutic effects. TDM begins when the drug is first prescribed, and involves determining an initial dosage regimen appropriate for the clinical condition and such patient characteristics as age, weight, organ function, and concomitant drug therapy. When interpreting concentration measurements, factors that need to be considered include the sampling time in relation to drug dose, dosage history, patient response, and the desired medicinal targets. The goal of TDM is to use appropriate concentrations of difficult-to-manage medications to optimize clinical outcomes in patients in various clinical situations.

Indexed as

AlgorithmsDose-Response Relationship, DrugDrug MonitoringForecastingHumansPatient CompliancePharmacokinetics

Identifiers

PMID19270474
PMCPMC2687654

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.