Pediatric cataract, a leading cause of blindness in children globally, imposing a significant financial burden on both families and society. The extensive phenotypic heterogeneity of this condition means that the underlying mechanisms remain poorly understood, limiting the development of precise and effective treatments. The advent of omics technologies has provided potent tools for unraveling the pathogenesis of pediatric cataract. By mapping expression profiles across various molecular levels, these omics approaches enhance our understanding of the disease’s etiological mechanisms, aid in the identification of novel biomarkers and key pathways, and offer researchers new insights for the innovative strategies in disease diagnosis and targeted therapies. In this review, we summarize the application of omics approaches in clinical and basic research on pediatric cataract over the past decade, encompassing genomics, transcriptomics, proteomics, and metabolomics. Furthermore, we discuss the current challenges and future prospects of omics analyses in pediatric cataract studies.

Pediatric cataract, a leading cause of blindness in children globally, imposing a significant financial burden on both families and society. The extensive phenotypic heterogeneity of this condition means that the underlying mechanisms remain poorly understood, limiting the development of precise and effective treatments. The advent of omics technologies has provided potent tools for unraveling the pathogenesis of pediatric cataract. By mapping expression profiles across various molecular levels, these omics approaches enhance our understanding of the disease’s etiological mechanisms, aid in the identification of novel biomarkers and key pathways, and offer researchers new insights for the innovative strategies in disease diagnosis and targeted therapies. In this review, we summarize the application of omics approaches in clinical and basic research on pediatric cataract over the past decade, encompassing genomics, transcriptomics, proteomics, and metabolomics. Furthermore, we discuss the current challenges and future prospects of omics analyses in pediatric cataract studies.

Purpose: The day surgery mode has significantly reduced preoperative waiting time for patients. However, this mode also led to brief and sometimes abrupt interactions between patients with vision loss and nursing staff during the preoperative visits. Additionally, patients may experience negative emotions. The aim of this study was to describe the preoperative experiences and identify related stressful factors among patients waiting vitreo-retinal day surgery. Methods: This study was guided by an interpretive approach. Semi-structured, face-to-face, in-depth interviews were conducted with patients from August 2021 to October 2024. Inductive content analysis and research software were used to analyze the data. Results: Twenty-seven patients agreed to participate the interviews. Their ages ranged from 19 to 70 years old. The waiting time before hospitalization varied from 7 to 90 days. Three main categories emerged from patients’ complaints: day surgery procedures, concerns about eye conditions and supports. Conclusions: The findings underscore the importance of preoperative care services. It is suggested that providing accurate preoperative information and effective support can significantly enhance the quality of preoperative care service.

Purpose: The day surgery mode has significantly reduced preoperative waiting time for patients. However, this mode also led to brief and sometimes abrupt interactions between patients with vision loss and nursing staff during the preoperative visits. Additionally, patients may experience negative emotions. The aim of this study was to describe the preoperative experiences and identify related stressful factors among patients waiting vitreo-retinal day surgery. Methods: This study was guided by an interpretive approach. Semi-structured, face-to-face, in-depth interviews were conducted with patients from August 2021 to October 2024. Inductive content analysis and research software were used to analyze the data. Results: Twenty-seven patients agreed to participate the interviews. Their ages ranged from 19 to 70 years old. The waiting time before hospitalization varied from 7 to 90 days. Three main categories emerged from patients’ complaints: day surgery procedures, concerns about eye conditions and supports. Conclusions: The findings underscore the importance of preoperative care services. It is suggested that providing accurate preoperative information and effective support can significantly enhance the quality of preoperative care service.

The choroid is a multifunctional, highly vascular, and dynamic tissue which contributes to ocular homeostasis and the regulation of eye growth in both animals and humans. Although challenging to reliably measure, recent advances in ocular imaging (particularly optical coherence tomography) has expanded the current understanding of the role of the choroid in ageing and refractive error development during childhood. This commentary considers recent advances in the field, particularly the impact of orthokeratology on choroidal thickness and contour in myopic children, and the potential use of choroidal metrics as a biomarker for future eye growth.

The choroid is a multifunctional, highly vascular, and dynamic tissue which contributes to ocular homeostasis and the regulation of eye growth in both animals and humans. Although challenging to reliably measure, recent advances in ocular imaging (particularly optical coherence tomography) has expanded the current understanding of the role of the choroid in ageing and refractive error development during childhood. This commentary considers recent advances in the field, particularly the impact of orthokeratology on choroidal thickness and contour in myopic children, and the potential use of choroidal metrics as a biomarker for future eye growth.

Aim: The objective of this study was to investigate the prognosis of massive vitreous hemorrhage(VH) secondary to polypoidal choroidal vasculopathy(PCV) after vitrectomy.  

Methods: Forty-nineeyes in 48 patients with PCV and breakthrough VH who underwent 23-gauge pars plana vitrectomy between January 2015 and December 2020 were enrolled. The main outcome parameters were best-corrected visual acuity, postoperative adverse events, and reoperation.

Results:The average follow-up time was 20.0±15.82 months. The average preoperative best-corrected visual acuity (BCVA) was 2.12±0.65 logarithm of the minimum angle of resolution (logMAR), the BCVA at six monthswas 1.65±0.64 logMAR, and the six-month follow-up BCVA was 1.67±0.76 logMAR. Compared to the average preoperative BCVA, the six-months and last follow-up BCVA after vitrectomy improved (P<0.05). The BCVAat the fnal follow-up was better than 1.3logMAR only in 14 eyes (28.6%). Postoperative complications were observed in 10 eyes (20.4%), including recurrent retinal detachment, recurrent vitreous hemorrhage, macular hole, hyphema and lens dislocation. Fourteen eyes(28.6%) underwent cataract surgery procedure an average of 10.16±5.14 months after vitrectomy. BCVAone week and three monthsafter cataract surgery improved compared toBCVAbefore cataract surgery (P<0.05). Hypertension was associated with BCVAsix months after vitrectomy (P=0.017). The BCVA at baseline and three months after PPV were worse in patients who underwent vitrectomy combined with silicone oil filling (P<0.05). Eyes with postoperative complications had worse BCVA at six months, 12 months, and at the final follow-up after PPV (P<0.05).The duration of VH is related to the BCVA12 months after PPV visual acuity after surgery. Patients who underwent vitrectomy within one month of the onset of vitreous hemorrhage had better BCVA 12 months after vitrectomy than those who underwent vitrectomy surgery one month later (P=0.015). 

Conclusions: Although the prognosis of vitrectomy varies greatly, cataract surgery could be considered to improve BCVAif polypoidal lesions are inactive six months after vitrectomy.

Aim: The objective of this study was to investigate the prognosis of massive vitreous hemorrhage(VH) secondary to polypoidal choroidal vasculopathy(PCV) after vitrectomy.

Methods: Forty-nineeyes in 48 patients with PCV and breakthrough VH who underwent 23-gauge pars plana vitrectomy between January 2015 and December 2020 were enrolled. The main outcome parameters were best-corrected visual acuity, postoperative adverse events, and reoperation.

Results:The average follow-up time was 20.0±15.82 months. The average preoperative best-corrected visual acuity (BCVA) was 2.12±0.65 logarithm of the minimum angle of resolution (logMAR), the BCVA at six monthswas 1.65±0.64 logMAR, and the six-month follow-up BCVA was 1.67±0.76 logMAR. Compared to the average preoperative BCVA, the six-months and last follow-up BCVA after vitrectomy improved (P<0.05). The BCVAat the fnal follow-up was better than 1.3logMAR only in 14 eyes (28.6%). Postoperative complications were observed in 10 eyes (20.4%), including recurrent retinal detachment, recurrent vitreous hemorrhage, macular hole, hyphema and lens dislocation. Fourteen eyes(28.6%) underwent cataract surgery procedure an average of 10.16±5.14 months after vitrectomy. BCVAone week and three monthsafter cataract surgery improved compared toBCVAbefore cataract surgery (P<0.05). Hypertension was associated with BCVAsix months after vitrectomy (P=0.017). The BCVA at baseline and three months after PPV were worse in patients who underwent vitrectomy combined with silicone oil filling (P<0.05). Eyes with postoperative complications had worse BCVA at six months, 12 months, and at the final follow-up after PPV (P<0.05).The duration of VH is related to the BCVA12 months after PPV visual acuity after surgery. Patients who underwent vitrectomy within one month of the onset of vitreous hemorrhage had better BCVA 12 months after vitrectomy than those who underwent vitrectomy surgery one month later (P=0.015). 

Conclusions: Although the prognosis of vitrectomy varies greatly, cataract surgery could be considered to improve BCVAif polypoidal lesions are inactive six months after vitrectomy.

Background: Diabetic retinopathy (DR) urgently needs novel and effective therapeutic targets. Integrated analyses of plasma proteomic and genetic markers can clarify the causal relevance of proteins and discover novel targets for diseases, but no systematic screening for DR has been performed.

Methods: Summary statistics of plasma protein quantitative trait loci (pQTL) were derived from two extensive genome-wide analysis study (GWAS) datasets and one systematic review, with over 100 thousand participants covering thousands of plasma proteins. DR data were sourced from the largest FinnGen study, comprising 10,413 DR cases and 308,633 European controls. Genetic instrumental variables were identified using multiple filters. In the two-sample MR analysis, Wald ratio and inverse variance-weighted (IVW) MR were utilized to investigate the

causality of plasma proteins with DR. Bidirectional MR, Bayesian Co-localization, and phenotype scanning were employed to test for potential reverse causality and confounding factors in the main MR analyses. By systemically searching druggable gene lists, the ChEMBL database, DrugBank, and Gene Ontology database, the druggability and relevant functional pathways of the identified proteins were systematically evaluated.

Results: Genetically predicted levels of 24 proteins were significantly associated with DR risk at a false discovery rate <0.05 including 11 with positive associations and 13 with negative associations. For each standard deviation increase in plasm protein levels, the odds ratios (ORs) for DR varied from 0.51 (95% CI: 0.36-0.73; P=2.22×10-5) for tubulin polymerization-promoting protein family member 3 (TPPP3) to 2.02 (95% CI: 1.44-2.83; P=5.01×10-5) for olfactomedin like 3 (OLFML3). Bidirectional MR indicated there was no reverse causality that interfered with the results of the main MR analyses. Four proteins exhibited strong co-localization evidence (PH4 ≥0.8): cytoplasmic tRNA synthetase (WARS), acrosin binding protein(ACRBP), and intercellular adhesion molecule 1 (ICAM1) were negatively associated with DR risk, while neurogenic locus notch homolog protein 2 (NOTCH2) showed a positive association. No confounding factors were detected between pQTLs and DR according to the phenotypic scan. Drugability assessments highlighted 6 proteins already in drug development endeavor and 18 novel drug targets, with metalloproteinase inhibitor 3 (TIMP) currently in phase I clinical trials for DR. GO analysis identified 18 of 24 plasma proteins enriching 22 pathways related to cell differentiation and proliferation regulation.

Conclusions:Twenty-four promising drug targets for DR were identified, including four plasma proteins with particular co-localization evidence. These findings offer new insights into DR's etiology and therapeutic targeting, exemplifying the value of genomic and proteomic data in drug target discovery.

Background: Diabetic retinopathy (DR) urgently needs novel and effective therapeutic targets. Integrated analyses of plasma proteomic and genetic markers can clarify the causal relevance of proteins and discover novel targets for diseases, but no systematic screening for DR has been performed.

Methods: Summary statistics of plasma protein quantitative trait loci (pQTL) were derived from two extensive genome-wide analysis study (GWAS) datasets and one systematic review, with over 100 thousand participants covering thousands of plasma proteins. DR data were sourced from the largest FinnGen study, comprising 10,413 DR cases and 308,633 European controls. Genetic instrumental variables were identified using multiple filters. In the two-sample MR analysis, Wald ratio and inverse variance-weighted (IVW) MR were utilized to investigate the

causality of plasma proteins with DR. Bidirectional MR, Bayesian Co-localization, and phenotype scanning were employed to test for potential reverse causality and confounding factors in the main MR analyses. By systemically searching druggable gene lists, the ChEMBL database, DrugBank, and Gene Ontology database, the druggability and relevant functional pathways of the identified proteins were systematically evaluated.

Results: Genetically predicted levels of 24 proteins were significantly associated with DR risk at a false discovery rate <0.05 including 11 with positive associations and 13 with negative associations. For each standard deviation increase in plasm protein levels, the odds ratios (ORs) for DR varied from 0.51 (95% CI: 0.36-0.73; P=2.22×10-5) for tubulin polymerization-promoting protein family member 3 (TPPP3) to 2.02 (95% CI: 1.44-2.83; P=5.01×10-5) for olfactomedin like 3 (OLFML3). Bidirectional MR indicated there was no reverse causality that interfered with the results of the main MR analyses. Four proteins exhibited strong co-localization evidence (PH4 ≥0.8): cytoplasmic tRNA synthetase (WARS), acrosin binding protein(ACRBP), and intercellular adhesion molecule 1 (ICAM1) were negatively associated with DR risk, while neurogenic locus notch homolog protein 2 (NOTCH2) showed a positive association. No confounding factors were detected between pQTLs and DR according to the phenotypic scan. Drugability assessments highlighted 6 proteins already in drug development endeavor and 18 novel drug targets, with metalloproteinase inhibitor 3 (TIMP) currently in phase I clinical trials for DR. GO analysis identified 18 of 24 plasma proteins enriching 22 pathways related to cell differentiation and proliferation regulation.

Conclusions:Twenty-four promising drug targets for DR were identified, including four plasma proteins with particular co-localization evidence. These findings offer new insights into DR's etiology and therapeutic targeting, exemplifying the value of genomic and proteomic data in drug target discovery.

Background: Research innovations inoculardisease screening, diagnosis, and management have been boosted by deep learning (DL) in the last decade. To assess historical research trends and current advances, we conducted an artifcial intelligence (AI)–human hybrid analysis of publications on DL in ophthalmology.

Methods: All DL-related articles in ophthalmology, which were published between 2012 and 2022 from Web of Science, were included. 500 high-impact articles annotated with key research information were used to fne-tune alarge language models (LLM) for reviewing medical literature and extracting information. After verifying the LLM's accuracy in extracting diseases and imaging modalities, we analyzed trend of DL in ophthalmology with 2 535 articles. 

Results: Researchers using LLM for literature analysis were 70% (p= 0.000 1) faster than those who did not, while achieving comparable accuracy (97% versus 98%, p = 0.768 1). The field of DL in ophthalmology has grown 116% annually, paralleling trends of the broader DL domain. The publications focused mainly on diabetic retinopathy (p = 0.000 3), glaucoma (p = 0.001 1), and age-related macular diseases (p = 0.000 1) using retinal fundus photographs (FP, p = 0.001 5) and optical coherence tomography (OCT, p = 0.000 1). DL studies utilizing multimodal images have been growing, with FP and OCT combined being the most frequent. Among the 500 high-impact articles, laboratory studies constituted the majority at 65.3%. Notably, a discernible decline in model accuracy was observed when categorizing by study design, notwithstanding its statistical insignificance. Furthermore, 43 publicly available ocular image datasets were summarized. 

Conclusion: This study has characterized the landscape of publications on DL in ophthalmology, by identifying the trends and breakthroughs among research topics and the fast-growing areas. This study provides an efcient framework for combined AI–human analysis to comprehensively assess the current status and future trends in the feld. 

Background: Research innovations inoculardisease screening, diagnosis, and management have been boosted by deep learning (DL) in the last decade. To assess historical research trends and current advances, we conducted an artifcial intelligence (AI)–human hybrid analysis of publications on DL in ophthalmology.

Methods: All DL-related articles in ophthalmology, which were published between 2012 and 2022 from Web of Science, were included. 500 high-impact articles annotated with key research information were used to fne-tune alarge language models (LLM) for reviewing medical literature and extracting information. After verifying the LLM's accuracy in extracting diseases and imaging modalities, we analyzed trend of DL in ophthalmology with 2 535 articles. 

Results: Researchers using LLM for literature analysis were 70% (p = 0.000 1) faster than those who did not, while achieving comparable accuracy (97% versus 98%, p = 0.768 1). The field of DL in ophthalmology has grown 116% annually, paralleling trends of the broader DL domain. The publications focused mainly on diabetic retinopathy (p = 0.000 3), glaucoma (p = 0.001 1), and age-related macular diseases (p = 0.000 1) using retinal fundus photographs (FP, p = 0.001 5) and optical coherence tomography (OCT, p = 0.000 1). DL studies utilizing multimodal images have been growing, with FP and OCT combined being the most frequent. Among the 500 high-impact articles, laboratory studies constituted the majority at 65.3%. Notably, a discernible decline in model accuracy was observed when categorizing by study design, notwithstanding its statistical insignificance. Furthermore, 43 publicly available ocular image datasets were summarized. 

Conclusion: This study has characterized the landscape of publications on DL in ophthalmology, by identifying the trends and breakthroughs among research topics and the fast-growing areas. This study provides an efcient framework for combined AI–human analysis to comprehensively assess the current status and future trends in the feld. 

The whole lacrimal passage intubation is widely used in lacrimal surgery. However, one of the most typical complications is the prolapse of the silicone tube from the medial canthus. In case, the bicanalicular silicone tube after whole lacrimal duct intubation has completely prolapsed from the medial canthus before extubation, then cannot be found in the opening of the nasolacrimal duct, and it would be a challenge to reposition or removal. A novel approach to employ a modified suture-probe and silk thread traction technique has been developed, and it is not only safe and effective, but also cost-effective.

The whole lacrimal passage intubation is widely used in lacrimal surgery. However, one of the most typical complications is the prolapse of the silicone tube from the medial canthus. In case, the bicanalicular silicone tube after whole lacrimal duct intubation has completely prolapsed from the medial canthus before extubation, then cannot be found in the opening of the nasolacrimal duct, and it would be a challenge to reposition or removal. A novel approach to employ a modified suture-probe and silk thread traction technique has been developed, and it is not only safe and effective, but also cost-effective.

Artificial intelligence (AI) is about simulating and expanding human intelligence. AI based on deep learning (DL) can analyze images well by using their inherent features, such as outlines, frames and so on. As researchers generally diagnoses ocular fundus diseases by images, it makes sense to apply AI to fundus examination. In ophthalmology, AI has achieved doctor-like performance in detecting multiple ocular fundus diseases through optical coherence tomography (OCT) images, fundus photographs, and ultra-wide-field (UWF) images. It has also been widely used in disease progression prediction. Nonetheless, there are also some potential challenges with AI application in ophthalmology, one of which is the black-box problem. Researchers are devoted to developing more interpretable deep learning systems (DLS) and confirming their clinical feasibility. This review describes a summary of the state-of-the-art AI application in the most popular ocular fundus diseases, potential challenges and the path forward.

Artificial intelligence (AI) is about simulating and expanding human intelligence. AI based on deep learning (DL) can analyze images well by using their inherent features, such as outlines, frames and so on. As researchers generally diagnoses ocular fundus diseases by images, it makes sense to apply AI to fundus examination. In ophthalmology, AI has achieved doctor-like performance in detecting multiple ocular fundus diseases through optical coherence tomography (OCT) images, fundus photographs, and ultra-wide-field (UWF) images. It has also been widely used in disease progression prediction. Nonetheless, there are also some potential challenges with AI application in ophthalmology, one of which is the black-box problem. Researchers are devoted to developing more interpretable deep learning systems (DLS) and confirming their clinical feasibility. This review describes a summary of the state-of-the-art AI application in the most popular ocular fundus diseases, potential challenges and the path forward.

Background: Previous studies have proposed an automated customized program named MATLAB used in the foveal avascular zone (FAZ) measurements in Triton optical coherence tomography angiography (OCTA) images. But it is not open-source and not easy to obtain, which will largely restrict its application in clinical practice and medical research. In this study, we aimed to investigate the feasibility of the Smooth Level Sets macro (SLSM), a free and open-source program, and compared with the manual measurements and MATLAB in the FAZ quantification in Triton OCTA.
Methods: Thirty-five eyes of 35 healthy subjects were scanned four times continuously using Triton OCTA. Manual and automated methods including the SLSM and MATLAB were used in the FAZ metrics (area, perimeter, and circularity) of the superficial capillary plexus. The accuracy, repeatability of all methods, and agreement between automated and manual methods were analyzed.
Results: The SLSM presented higher accuracy with a higher average Dice coefficient (0.9506) than MATLAB (0.9483), which was just second to the manual method (0.9568). Both the SLSM [intraclass correlation coefficient (ICC) =0.987; coefficient of variation (CoV) =3.935%] and MATLAB (ICC =0.983; CoV =4.165%) showed excellent repeatability for the FAZ area. They also had excellent agreement with manual measurement (SLSM, ICC =0.973; MATLAB, ICC =0.968).
Conclusion: The SLSM exhibits better accuracy than MATLAB in the automated FAZ measurement in Triton OCTA, the results of which were comparable to those obtained by manual measurement. This free and open-source program may be an accessible and feasible option for automated FAZ segmentation on Triton OCTA images.

Background: Previous studies have proposed an automated customized program named MATLAB used in the foveal avascular zone (FAZ) measurements in Triton optical coherence tomography angiography (OCTA) images. But it is not open-source and not easy to obtain, which will largely restrict its application in clinical practice and medical research. In this study, we aimed to investigate the feasibility of the Smooth Level Sets macro (SLSM), a free and open-source program, and compared with the manual measurements and MATLAB in the FAZ quantification in Triton OCTA.
Methods: Thirty-five eyes of 35 healthy subjects were scanned four times continuously using Triton OCTA. Manual and automated methods including the SLSM and MATLAB were used in the FAZ metrics (area, perimeter, and circularity) of the superficial capillary plexus. The accuracy, repeatability of all methods, and agreement between automated and manual methods were analyzed.
Results: The SLSM presented higher accuracy with a higher average Dice coefficient (0.9506) than MATLAB (0.9483), which was just second to the manual method (0.9568). Both the SLSM [intraclass correlation coefficient (ICC) =0.987; coefficient of variation (CoV) =3.935%] and MATLAB (ICC =0.983; CoV =4.165%) showed excellent repeatability for the FAZ area. They also had excellent agreement with manual measurement (SLSM, ICC =0.973; MATLAB, ICC =0.968).
Conclusion: The SLSM exhibits better accuracy than MATLAB in the automated FAZ measurement in Triton OCTA, the results of which were comparable to those obtained by manual measurement. This free and open-source program may be an accessible and feasible option for automated FAZ segmentation on Triton OCTA images.

Objective: To evaluate the effectiveness of music therapy on the anxiety level and physiological response of patients undergoing ophthalmic surgery.

Methods: Relevant randomized controlled trials that compared the combined effect of music therapy for patients undergoing ophthalmic surgery were included. Four English databases and three Chinese databases were searched from inception to Jan. 2022. Two reviewers independently performed data extraction and risk of bias assessments. The Cochrane Collaboration tool was used to assess the risk of bias. Meta-analysis was performed using Review Manager 5.3. The outcomes were overall anxiety, blood pressure, heart rate and pain.

Results: Atotal of 11 trials with 1,469 participants were included in the meta-analysis. Compared to standard care, music therapy had a good effect on reducing the anxiety levels of patients undergoing ophthalmic surgery (p<0.05). The results also suggested that music therapy  produced a signifcant improvement in blood pressure (p<0.05) and heart rate (p<0.05). The visual analogue scale (VAS) showed that music therapy signifcantly reduced pain compared to standard care (p<0.05).

Conclusions: This meta-analysis provided evidence that music therapy has an obvious effect on relieving anxiety levels, while it is also more effective in alleviating pain and improving physiological responses than standard care alone. Our fndings may provide accurate evidence-based guidance for the clinical implementation of music therapy. In the future, more high-quality studies are required for verifying these results. 

Objective: To evaluate the effectiveness of music therapy on the anxiety level and physiological response of patients undergoing ophthalmic surgery.

Methods: Relevant randomized controlled trials that compared the combined effect of music therapy for patients undergoing ophthalmic surgery were included. Four English databases and three Chinese databases were searched from inception to Jan. 2022. Two reviewers independently performed data extraction and risk of bias assessments. The Cochrane Collaboration tool was used to assess the risk of bias. Meta-analysis was performed using Review Manager 5.3. The outcomes were overall anxiety, blood pressure, heart rate and pain.

Results: Atotal of 11 trials with 1,469 participants were included in the meta-analysis. Compared to standard care, music therapy had a good effect on reducing the anxiety levels of patients undergoing ophthalmic surgery (p<0.05). The results also suggested that music therapy  produced a signifcant improvement in blood pressure (p<0.05) and heart rate (p<0.05). The visual analogue scale (VAS) showed that music therapy signifcantly reduced pain compared to standard care (p<0.05).

Conclusions: This meta-analysis provided evidence that music therapy has an obvious efect on relieving anxiety levels, while it is also more effective in alleviating pain and improving physiological responses than standard care alone. Our fndings may provide accurate evidence-based guidance for the clinical implementation of music therapy. In the future, more high-quality studies are required for verifying these results.