Telogen Effluvium

Özlü, Emin; Karadağ, Ayşe Serap

doi:10.5772/66975

Cited by 3 publications

(2 citation statements)

References 32 publications

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“…Symptoms such as acne, hirsutism, or irregular menstrual cycles indicate excess androgen, whereas a strict vegetarian diet or heavy menses are suggestive of iron deficiency anemia. [7]…”

Section: Historymentioning

confidence: 99%

Expert consensus on the management of telogen effluvium in India

Mysore¹,

Parthasaradhi

Kharkar

et al. 2019

Int J Trichol

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Alopecia, a frequently reported problem, severely impacts the quality of life of patients and is often associated with loss of confidence and low self-esteem. Several conditions such as telogen effluvium (TE), anagen effluvium, diffuse type of alopecia areata, female pattern hair loss, hair shaft abnormalities, loose anagen hair syndrome, and congenital atrichia or hypotrichosis are associated with hair loss. The actual prevalence rate of TE is not reported since most cases are subclinical in nature. Further, since women get more distressed by hair fall and promptly seek treatment, they tend to be over-represented. However, both genders can suffer from this condition if triggering factors are present. This consensus paper was developed by taking into account opinions of renowned experts in the field and is hoped to serve as an evidence-based platform for selecting efficacious and safe therapy for patients with TE. This review presents a synopsis of the key opinions of experts on all aspects of treatment and effective management of this condition.

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“…Symptoms such as acne, hirsutism, or irregular menstrual cycles indicate excess androgen, whereas a strict vegetarian diet or heavy menses are suggestive of iron deficiency anemia. [7]…”

Section: Historymentioning

confidence: 99%

Expert consensus on the management of telogen effluvium in India

Mysore¹,

Parthasaradhi

Kharkar

et al. 2019

Int J Trichol

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“…Ozlu et al [14] performed some high-speed turning experiments using inserts with different rake angles. They calculated the friction coefficient, cutting forces, and total contact length, but they did not consider the optimization of cutting parameters.…”

Section: Introductionmentioning

confidence: 99%

Modeling Cutting Forces in High-Speed Turning using Artificial Neural Networks

Hernández-González

Curra-Sosa

Pérez‐Rodríguez

et al. 2021

TecnoL.

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Cutting forces are very important variables in machining performance because they affect surface roughness, cutting tool life, and energy consumption. Reducing electrical energy consumption in manufacturing processes not only provides economic benefits to manufacturers but also improves their environmental performance. Many factors, such as cutting tool material, cutting speed, and machining time, have an impact on cutting forces and energy consumption. Recently, many studies have investigated the energy consumption of machine tools; however, only a few have examined high-speed turning of plain carbon steel. This paper seeks to analyze the effects of cutting tool materials and cutting speed on cutting forces and Specific Energy Consumption (SEC) during dry high-speed turning of AISI 1045 steel. For this purpose, cutting forces were experimentally measured and compared with estimates of predictive models developed using polynomial regression and artificial neural networks. The resulting models were evaluated based on two performance metrics: coefficient of determination and root mean square error. According to the results, the polynomial models did not reach 70 % in the representation of the variability of the data. The cutting speed and machining time associated with the highest and lowest SEC of CT5015-P10 and GC4225-P25 inserts were calculated. The lowest SEC values of these cutting tools were obtained at a medium cutting speed. Also, the SEC of the GC4225 insert was found to be higher than that of the CT5015 tool.

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Dermatologic manifestations of patients with severe and non-severe COVID-19 infection: A cross-sectional study

Amirnia,

Haghdoost,

Raeisnia

et al. 2024

J Res Clin Med

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Introduction: Since the emergence of COVID-19 in late 2019, multiple concerns have been raised regarding the unknown nature of the disease, including dermatologic complications. In this study, we discussed dermatologic manifestations of patients with COVID-19 infection who visited our clinic. Methods: Eighty- six patients were involved based on our inclusion and exclusion criteria (50 female and 36 male). All patients with definite diagnosis of COVID-19 who were referred to our dermatologic clinic were enrolled in this cross-sectional study. Only lesions which occurred 1 week prior to or 3 months after first COVID-19 symptoms were included. The photographs of all lesions were independently reviewed by four experienced dermatologists and an infectious disease specialist to reach the objectives stated above. Qualitative data presented as frequency (%) and compared using chi-squared or Fisher’s exact test, and quantitative data presented as mean±SD or median (IQR) based on normality, with P value≤0.05 considered statistically significant. Results: Eighty- six patients were enrolled in the study (mean±SD age=36.95±17.78). Eighteen specific types of dermatologic complications were seen. The most common lesions included maculopapular rash and scalp hair loss. The only lesions with a statistically significant difference regarding COVID-19 symptom onset time were maculopapular rash, telogen effluvium, and papular urticaria. The only lesions with statistically significant difference regarding COVID-19 severity were maculopapular rash, telogen effluvium, and urticaria. Conclusion: Our study revealed that a wide range of skin lesions may occur in patients with COVID-19. We found a statistically significant relation between disease severity and certain dermatologic manifestations.

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Telogen Effluvium

Cited by 3 publications

References 32 publications

Expert consensus on the management of telogen effluvium in India

Expert consensus on the management of telogen effluvium in India

Modeling Cutting Forces in High-Speed Turning using Artificial Neural Networks

Dermatologic manifestations of patients with severe and non-severe COVID-19 infection: A cross-sectional study

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