Evidence map›Paper›PMID 35161482›Full record

ReviewSensors (Basel, Switzerland)2022

Advances in Therapeutic Monitoring of Lithium in the Management of Bipolar Disorder.

Mahsa Sheikh, Meha Qassem, Iasonas F Triantis, Panicos A Kyriacou

Open access · goldAbstract readReview
In one paragraph

Review in Sensors (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed
5.8field-weighted citation impact, top 3% of its field
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

15 citing papers in PubMed, 41 citations in OpenAlex.

  1. Early health economic assessment of eLiActa neuropsychiatrica · 2026
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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

4 authors at 1 institution in 1 country.

Mahsa SheikhResearch Centre for Biomedical Engineering, City University of London, London EC1V 0HB, UK.
Meha QassemResearch Centre for Biomedical Engineering, City University of London, London EC1V 0HB, UK.
Iasonas F TriantisResearch Centre for Biomedical Engineering, City University of London, London EC1V 0HB, UK.
Panicos A KyriacouResearch Centre for Biomedical Engineering, City University of London, London EC1V 0HB, UK.ORCID 0000-0002-2868-485X
City, University of London · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Since the mid-20th century, lithium continues to be prescribed as a first-line mood stabilizer for the management of bipolar disorder (BD). However, lithium has a very narrow therapeutic index, and it is crucial to carefully monitor lithium plasma levels as concentrations greater than 1.2 mmol/L are potentially toxic and can be fatal. The quantification of lithium in clinical laboratories is performed by atomic absorption spectrometry, flame emission photometry, or conventional ion-selective electrodes. All these techniques are cumbersome and require frequent blood tests with consequent discomfort which results in patients evading treatment. Furthermore, the current techniques for lithium monitoring require highly qualified personnel and expensive equipment; hence, it is crucial to develop low-cost and easy-to-use devices for decentralized monitoring of lithium. The current paper seeks to review the pertinent literature rigorously and critically with a focus on different lithium-monitoring techniques which could lead towards the development of automatic and point-of-care analytical devices for lithium determination.

Indexed as

Bipolar DisorderLithiumHumansIon-Selective ElectrodesPhotometrySpectrum AnalysisLithiumbipolar disorderlithium monitoringlithium sensorstherapeutic drug monitoring

Identifiers

PMID35161482
PMCPMC8838674
OpenAlexW4206686119

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.