Evidence map›Paper›PMID 35592733›Full record

ArticleClinical, cosmetic and investigational dermatology2022

Comparison Between Trichoscopic and Histopathological Evaluations of Hair Parameters.

Danchen Hu, Ping Tu, Shuxia Yang

Open access · goldAbstract read
In one paragraph

Article in Clinical, cosmetic and investigational dermatology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
1.6field-weighted citation impact, top 19% 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

3 citing papers in PubMed, 7 citations in OpenAlex.

  1. Scalp Biopsies for Alopecia.Dermatopathology (Basel, Switzerland) · 2026
    Review
  2. Review
  3. Article
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

3 authors at 1 institution in 1 country.

Danchen HuDepartment of Dermatology, Peking University First Hospital, Beijing, 100034, People's Republic of China.ORCID 0000-0003-3062-4853
Ping TuDepartment of Dermatology, Peking University First Hospital, Beijing, 100034, People's Republic of China.
Shuxia YangDepartment of Dermatology, Peking University First Hospital, Beijing, 100034, People's Republic of China.
Peking University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Collecting data on hair counts helps dermatologists diagnose hair diseases more accurately. Quantitative trichoscopy analysis and pathologic examination are two common ways to evaluate hair parameters. Purpose: The study aims to compare the effect of quantitative trichoscopy analysis and pathologic examination in hair counting and quantify the hair density of average Chinese people. Methods: Trichoscopy was performed in four scalp regions with a total of twenty-three volunteers without alopecia: frontal, vertex, occipital, and parietal. Hair density parameters were recorded. A 4-mm punch biopsy was performed in the occipital area, and all specimens were transversely sectioned serially and observed to calculate the hair densities. Results: The average hair density, hairs per follicle unit, and vellus hair ratio from quantitative trichoscopy analysis in the occipital region were 163.07±28.17/cm Conclusion: Quantitative trichoscopy is a noninvasive, quick, and convenient way to evaluate hair density. Histopathologic examination is an invasive way but provides more accurate data. The data obtained from trichoscopy and pathological examination are different to some extent, which cannot be substituted entirely for each other. This study established the reference for hair density in the adult Chinese population.

Indexed as

hairhistopathologytrichoscopy

Identifiers

PMID35592733
PMCPMC9113037
OpenAlexW4229458573

What OpenQuestion holds

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LicenceCC BY-NC
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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.