Internal Evaluation Research Articles

Internal Piping Erosion Evaluation of Embankment Dam Considering the Spatial Variability of Soil Properties

Internal Piping Erosion Evaluation of Embankment Dam Considering the Spatial Variability of Soil Properties

Comparative Symbolic Analysis of the Ethno-Fusion Genre: Insights and Perspectives

Abstract This study explores the integration of music and technology, illustrating their potential to collaboratively push the boundaries of musical exploration. Despite traditionally being viewed as unrelated, the combination of these two fields can significantly contribute to the progress of musical development. This study uses advanced computational methods to build a dataset filled with symbolic musical sequences that belong to a specific genre. This dataset is shown to be highly accurate and provides a detailed analysis of frequencies when examined closely, highlighting its quality and depth. We subject our dataset to comparative analysis with the renowned MAESTRO dataset, employing chromagrams to examine audio signals, rhythms, chords, solos, and note patterns in MIDI format through a variety of methods. This comparison underscores the superior quality of our sequences relative to those in the MAESTRO dataset, emphasizing the meticulousness of our sequence creation process. Moreover, we conduct internal evaluations of our dataset using both three-dimensional and two-dimensional approaches to melody representation, confirming its viability for future scholarly work. This effort seeks to enhance the music field by integrating computer science insights and methodologies, expanding the scope for future music technology research. It highlights the collaborative potential between musical creativity and technological advances in ongoing studies.

An Analysis of Goldfish Hatchtery Business in the Situjaya Group of Situraja Village, Sumedang Regency, West Java

The purposes of this study were (1) To analyze the prospect of goldfish hatchery business in Situ Jaya Group, judged from the financial aspect. (2) To formulate any goldfish hatchery alternative strategy in Situjaya Group. The eligibility analysis criteria that is applied to analyze the business feasibility are Net Benefit Cost Ratio (Net B / C), and Payback Period (PP). Furthermore, the methods which are applied to identify the factors that influenced the business development using Internal Factor Evaluation (IFE) matrix, the EFE matrix, the Strategic Matrix, and the Matrix Strengths, Weaknesses, Opportunities and Threats (SWOT), on the final phase resulted in creating alternative development strategies. Data collection method was conducted by using census method. The number of respondents were 8 people in all members of the Situ Jaya Group. Based on the non-financial feasibility analysis, the hatchery business is still weak on all non-financial aspects. Based on the results of financial analysis, it yields worth 100%. The entire value of Net B / C that obtained is greater than 1, i.e. 1.67. All PP value that obtained is 6 years 11 months 27 days. Based on the Matrix Strategy analysis that can be applied is market penetration and product development. Based on the SWOT analysis, the strategy that needs to be done is aggressive strategy which means that the business is in steady and excellent condition so it is possible to continue to expand, enlarge the growth and achieve maximum progress. While the Alternative Strategy for business development is the application of Weaknesses-Opportunities Strategy.

A Company Analysis of XPENG Based on the Internal and External Environment

This paper examines the strategic evolution of XPENG Automobile within the burgeoning new energy vehicle sector. Through a SWOT analysis, it identifies the company's robust market momentum juxtaposed with pressing challenges in product upgrading and differentiation. Leveraging internal and external environmental evaluations, the study emphasizes the necessity for XPENG Automobile to bolster capital profitability, innovate core technologies, and diversify market strategies to enhance its competitive positioning. Furthermore, the paper delves into the multifaceted development risks facing XPENG Automobile, encompassing internal limitations in financing and after-sales services, necessitating a drive towards operational efficiency optimization. It advocates for proactive risk mitigation and the exploitation of emerging opportunities to reduce reliance on mainstream market trends and foster pioneering innovations. The paper sheds light on industry-wide dynamics by drawing insights from XPENG Automobile's journey as a trailblazer in China's new energy vehicle landscape. It underscores the company's resilience in navigating policy shifts and venturing into new markets, serving as a guiding example for the broader advancement of new energy vehicles in China.

Projections of the start of the airborne pollen season in Barcelona (NE Iberian Peninsula) over the 21st century

The effects of global warming are numerous and recent studies reveal that they can affect the timing of pollination. Temperature is the meteorological variable that presents a clearer relationship with the start of the pollination season of most of the observed airborne pollen taxa. In Catalonia, in the last fifty years, the average annual air temperature has increased by +0.23 °C/decade, and the local warming has been slightly higher than the one on a global scale. Projections point to an increase in temperature in the coming decades, which would be more marked towards the middle of the century.To analyse the effect of the increase in temperature due to global warming on the starting date of pollen season in Barcelona, a forecasting model has been applied to a set of projected future temperatures estimated by the European RESCCUE project. This model, largely used in the literature, is based on determining the thermal needs of the plant for the pollen season to begin. The model calibration to obtain the initial parameters has been made by using 20 years of pollen data (2000–2019), and the model effectiveness has subsequently been tested through an internal evaluation over the period of the calibration and an external evaluation on 4 years not included in the calibration (2020−2023). The mean bias error in the internal calibration ranged between −0.4 and − 0.6 days, and between +0.5 and − 8.3 in the external one, depending on the taxon. The results of the application of the model to the temperature projections over the 21st century point to a progressive advancement in the pollination dates of several pollen types abundant in the city, allergenic most of them. These advances ranged, at the end of the century, between 15 and 27 days, depending on the climate model, for the scenario of the highest concentrations (RCP8.5) and between 7 and 12 days for the emissions stabilization scenario (RCP4.5).

Disclosure of internal control evaluation reports of Chinese enterprises: History, problems and strategies

In the realm of corporate finance, the transparency of internal control evaluations significantly impacts investor trust, market efficiency, and governance. This study examines the evolution of internal control report disclosures among Chinese listed firms, tracing their shift from voluntary to mandatory within two decades, aiming for international alignment. Utilizing descriptive analytics, data trend analysis, and visualization, we identify critical flaws in current disclosure practices, including reporting delays, incompleteness, inconsistencies, and non-standardized evaluation criteria. These shortcomings undermine the reports' quality and reliability, emphasizing the need for a unified conceptual framework and standardized reporting protocols to improve disclosure quality. Our findings highlight the essential role of enhanced internal control disclosures in advancing corporate governance and market integrity. The paper suggests that addressing these issues could significantly benefit the investment landscape. It calls for further research, possibly through quantitative analysis and case studies, to develop more effective disclosure strategies.

Population Pharmacokinetics of Dasatinib in Healthy Subjects.

Dasatinib is one of the tyrosine kinase inhibitors. The main use of these agents is inhibition of cancerous cell proliferation. The therapeutic importance of tyrosine kinase inhibitors raises the necessity of many types of investigations, especially the pharmacokinetic analysis of these drugs in humans. This analysis, along with other investigations and clinical research, will contribute to the overall knowledge of the drug. This study focused on the population pharmacokinetics of dasatinib. The objective of the study was to investigate the sources of the variability of dasatinib in a population pharmacokinetics study in healthy participants. We utilized 4180 plasma observations from 110 subjects who were administered SPRYCEL® on two separate occasions under fasting conditions; data from 20% of the subjects (22 subjects) were extracted for the purpose of internal model evaluation and data from 88 subjects were used in modeling. The model was evaluated by visual predictive check of three different datasets. A two-compartmental model with first order absorption and transit compartment was considered the simplest base model to describe the data based on the corrected Bayesian information criterion evaluation. Covariates were tested through conditional sampling for the stepwise approach-screening procedure in Monolix 2020R1 version. Conditional sampling for the stepwise approach was used to include the correlated covariates within the base model in the forward inclusion step and then to eliminate them backwardly to ensure that the key covariates were kept in the model at the final stage. The effect of body mass index on the absorption rate constant was considered as significant covariate in the final established model. Visual predictive check for simulations, 20% of the original dataset (internal dataset) and an external dataset demonstrated the appropriateness of the final model. Population pharmacokinetic modeling was performed to describe dasatinib pharmacokinetics in healthy subjects. Body mass index was considered as a factor that might be used in the future along with studies on patients to adjust the dosing regimens. Dasatinib is classified as a highly variable drug; this variability was demonstrated in the study by the effect of body mass index on the absorption rate constant.

A pilot acceptability evaluation of MomMind: A digital health intervention for Peripartum Depression prevention and management focused on health disparities.

Health disparities cause significant strain on the wellbeing of individuals and society. In this study, we focus on the health disparities present in the condition of Peripartum Depression (PPD), a significant public health issue. While PPD can be managed through therapy and medication, many women do not receive adequate PPD treatment due to issues of social stigma and limited access to healthcare resources. Digital health technologies can offer practical tools for PPD management. However, current solutions do not integrate behavior theory and are rarely responsive to the transient information needs stemming from women's unique sociodemographic, clinical and psychosocial profiles. We describe a pilot acceptability evaluation of MomMind, a health-disparities focused digital health intervention for the prevention and management of PPD. A crucial MomMind advantage is its basis on behavior change theory and patient engagement as enabled by the Digilego digital health framework. Following an internal usability evaluation, MomMind was evaluated by patients through cross-sectional acceptability surveys, pre-and-post PPD health literacy surveys, and interviews. Survey respondents included n = 30 peripartum women, of whom n = 16 (53.3%) were Hispanic and n = 17 (56.7%) of low-income. Survey results show that 96.6% of participants (n = 29) approved and welcomed MomMind, and 90% (n = 27) found MomMind to be an appealing intervention. Additionally, significant improvements (p< = 0.05) were observed in participants' PPD health literacy, specifically their ability to recognize PPD symptoms and knowledge of how to seek PPD information. Interview main themes include MomMind's straightforward design and influence of others (family members, providers) on use of technology. Results suggest that enhancement of a digital health framework with health literacy theory can support production of digital health solutions acceptable to vulnerable populations. This study incorporates existing theories from different disciplines into a unified approach for mitigating health disparities, and produced a novel solution for promotion of health in a vulnerable population.

A taxonomy for advancing systematic error analysis in multi-site electronic health record-based clinical concept extraction.

Error analysis plays a crucial role in clinical concept extraction, a fundamental subtask within clinical natural language processing (NLP). The process typically involves a manual review of error types, such as contextual and linguistic factors contributing to their occurrence, and the identification of underlying causes to refine the NLP model and improve its performance. Conducting error analysis can be complex, requiring a combination of NLP expertise and domain-specific knowledge. Due to the high heterogeneity of electronic health record (EHR) settings across different institutions, challenges may arise when attempting to standardize and reproduce the error analysis process. This study aims to facilitate a collaborative effort to establish common definitions and taxonomies for capturing diverse error types, fostering community consensus on error analysis for clinical concept extraction tasks. We iteratively developed and evaluated an error taxonomy based on existing literature, standards, real-world data, multisite case evaluations, and community feedback. The finalized taxonomy was released in both .dtd and .owl formats at the Open Health Natural Language Processing Consortium. The taxonomy is compatible with several different open-source annotation tools, including MAE, Brat, and MedTator. The resulting error taxonomy comprises 43 distinct error classes, organized into 6 error dimensions and 4 properties, including model type (symbolic and statistical machine learning), evaluation subject (model and human), evaluation level (patient, document, sentence, and concept), and annotation examples. Internal and external evaluations revealed strong variations in error types across methodological approaches, tasks, and EHR settings. Key points emerged from community feedback, including the need to enhancing clarity, generalizability, and usability of the taxonomy, along with dissemination strategies. The proposed taxonomy can facilitate the acceleration and standardization of the error analysis process in multi-site settings, thus improving the provenance, interpretability, and portability of NLP models. Future researchers could explore the potential direction of developing automated or semi-automated methods to assist in the classification and standardization of error analysis.

Development and validation of an early mortality risk model for pediatric hemophagocytic lymphohistiocytosis: a comparison with HScore, PELOD-2, P-MODS, and pSOFA.

There has been no severity evaluation model for pediatric patients with hemophagocytic lymphohistiocytosis (HLH) that uses readily available parameters. This study aimed to develop a novel model for predicting the early mortality risk in pediatric patients with HLH using easily obtained parameters whatever etiologic subtype. Patients from one center were divided into training and validation sets for model derivation. The developed model was validated using an independent validation cohort from the second center. The prediction model with nomogram was developed based on logistic regression. The model performance underwent internal and external evaluation and validation using the area under the receiver operating characteristic curve (AUC), calibration curve with 1000 bootstrap resampling, and decision curve analysis (DCA). Model performance was compared with the most prevalent severity evaluation scores, including the PELOD-2, P-MODS, and pSOFA scores. The prediction model included nine variables: glutamic-pyruvic transaminase, albumin, globulin, myohemoglobin, creatine kinase, serum potassium, procalcitonin, serum ferritin, and interval between onset and diagnosis. The AUC of the model for predicting the 28-day mortality was 0.933 and 0.932 in the training and validation sets, respectively. The AUC values of the HScore, PELOD-2, P-MODS and pSOFA were 0.815, 0.745, 0.659 and 0.788, respectively. The DCA of the 28-day mortality prediction exhibited a greater net benefit than the HScore, PELOD-2, P-MODS and pSOFA. Subgroup analyses demonstrated good model performance across HLH subtypes. The novel mortality prediction model in this study can contribute to the rapid assessment of early mortality risk after diagnosis with readily available parameters.

Profile, reasons for hospitalization and nursing diagnoses of refugee-native patients admitted to internal medicine clinic-an evaluation from nursing perspective

PurposeThe study aims to evaluate the hospitalization diagnoses and nursing diagnoses of the refugee and local population hospitalized in internal medicine clinics, which are especially important in the early diagnosis, treatment, and rehabilitation of chronic diseases, and to emphasize their importance in nursing care.MethodsThe study was carried out in a descriptive retrospective design. The files of 3563 patients admitted to the internal medicine clinic of a training and research hospital in Türkiye in 2022 were evaluated. SPSS 26.0 program was used for data analysis.ResultsIn the study, 95.3% of hospitalizations were native and 4.7% were refugee patients. It was determined that refugee patients admitted to the internal medicine service had a lower mean age compared to the native population (p < 0.05), but there was no difference in the duration of hospitalization (p > 0.05). When the medical diagnoses of hospitalization were examined, it was determined that the highest number of hospitalizations in the native and refugee populations were for bacterial infections in both genders. In nursing diagnoses, it was determined that both populations and genders were diagnosed with infection risk by the medical diagnoses of the patients.ConclusionAs a result of the study, it was observed that the duration of hospitalization, reasons for hospitalization, and nursing diagnoses of local and refugee patients were similar. In addition, it was determined that the patients’ medical hospitalization diagnoses and nursing diagnoses were compatible.

Measurement and evaluation methods in corporate communications through the prism of Lasswell’s model

PurposeThis study aims to conceptualize, rethink and systematize methods used for measurement and evaluation (M&E) corporate communication.Design/methodology/approachThe reflection is based on 462 key English-language books and papers devoted to M&E in the fields of corporate communication and public relations from the 1970th to 2023. Keywords in the titles and abstracts found the necessary materials. A critical analysis of the central concepts, models and methods described in the literature was conducted. As a result, a new model that unifies and structures the M&E toolkit is proposed for discussion.FindingsDespite the significant contribution to developing a wide range of M&E models, they are still not perfect and universal. In addition, this system of approaches is continuously self-evolving and changing under the influence of digital innovations, so it requires steady rethinking and updating. On the other hand, most previous studies focused on communication management processes, losing focus on communication aspects. This led to the need for an alternative view based on proven theories to fill this gap. The proposed model combines quantitative and qualitative M&E methods for the five main components of corporate communication (communicator, audience, content, channels and result), covering a wide range of tools, from statistical and sociological research to big data analysis and neuro research.Originality/valueThis work contributes to developing the M&E theory of corporate communication, systematizing existing methods and opening new research perspectives. From a practical point of view, companies can use the presented approach for a more accurate and objective internal evaluation of the main components of corporate communication.

Improving the Prognostic Evaluation Precision of Hospital Outcomes for Heart Failure Using Admission Notes and Clinical Tabular Data: Multimodal Deep Learning Model.

Clinical notes contain contextualized information beyond structured data related to patients' past and current health status. This study aimed to design a multimodal deep learning approach to improve the evaluation precision of hospital outcomes for heart failure (HF) using admission clinical notes and easily collected tabular data. Data for the development and validation of the multimodal model were retrospectively derived from 3 open-access US databases, including the Medical Information Mart for Intensive Care III v1.4 (MIMIC-III) and MIMIC-IV v1.0, collected from a teaching hospital from 2001 to 2019, and the eICU Collaborative Research Database v1.2, collected from 208 hospitals from 2014 to 2015. The study cohorts consisted of all patients with critical HF. The clinical notes, including chief complaint, history of present illness, physical examination, medical history, and admission medication, as well as clinical variables recorded in electronic health records, were analyzed. We developed a deep learning mortality prediction model for in-hospital patients, which underwent complete internal, prospective, and external evaluation. The Integrated Gradients and SHapley Additive exPlanations (SHAP) methods were used to analyze the importance of risk factors. The study included 9989 (16.4%) patients in the development set, 2497 (14.1%) patients in the internal validation set, 1896 (18.3%) in the prospective validation set, and 7432 (15%) patients in the external validation set. The area under the receiver operating characteristic curve of the models was 0.838 (95% CI 0.827-0.851), 0.849 (95% CI 0.841-0.856), and 0.767 (95% CI 0.762-0.772), for the internal, prospective, and external validation sets, respectively. The area under the receiver operating characteristic curve of the multimodal model outperformed that of the unimodal models in all test sets, and tabular data contributed to higher discrimination. The medical history and physical examination were more useful than other factors in early assessments. The multimodal deep learning model for combining admission notes and clinical tabular data showed promising efficacy as a potentially novel method in evaluating the risk of mortality in patients with HF, providing more accurate and timely decision support.

Internal quality evaluation of ‘Fuji’ apples during storage based on bulk optical properties or diffuse reflection and transmission spectra

The purpose of this study is to compare the performance of prediction models based either on the bulk optical properties (BOP) or with models based on the diffuse reflection and transmission spectra to assess the soluble solids content (SSC) or fruit firmness (FF) of ‘Fuji’ apples. Diffuse reflection and transmission spectra of 240 apples in 500–1000 nm were acquired using a self-constructed single integrating sphere system, from which the absorption coefficient (μa) and reduced scattering coefficient (μ′s) were determined. The relationships of μa, μ′s, and the reflection and transmission spectra with the SSC and FF were analyzed, and detection models were established using partial least squares regression coupled with characteristic wavelength selection. Results showed that neither the SSC nor the FF changed obviously during 80-days storage, and the μa and μ′s showed no monotonic increase or decrease pattern. The SSC prediction model based on μa spectra combined with the baseline correction method performed the best (R2p = 0.79, RMSEP = 0.62), while the model based on μ′s spectra was the best for FF (R2p = 0.67, RMSEP = 0.35 N). Overall, the accuracy of the model based on BOP in predicting internal quality was better than that based on reflection and transmission spectra from the same measurement.

Analysis of Service Quality PT Pos Indonesia to Improve Market Share

In Indonesia's postal and logistics business, PT Pos Indonesia faces increased competition. Despite logistics' annual growth, the company's market share has declined. To be competitive in the courier and logistics market, PT Pos Indonesia must design a business strategy to improve its service quality and complement its good operational performance. This requires recognizing customer priorities and improving the company's performance in these areas. PT Pos Indonesia can use Importance-Performance Analysis (IPA) to identify customer-important service quality dimensions and underperforming areas by conducting internal and external evaluations. This complete strategy will allow PT Pos Indonesia to prioritize its efforts, strategically allocate resources, and focus on service quality that will most effect customer satisfaction. Based on the investigation, integrated logistic cooperation and solutions were presented to fill service shortages. These efforts used integrated logistical partnerships, staff advocacy, and an advanced marketing platform to improve coordination and delivery speed, employee competencies, and consumer insights. These measures were meant to bridge the gap between customer expectations and service level agreements, delivery speed, personnel competence, and customer needs. These techniques can help PT Pos Indonesia boost customer satisfaction and market share.

Coffee Business Development Strategy (Case Study at PT XYZ)

The coffee business especially in the coffee shop sector to be superior to the competition is something that must be carried out in a sustainable manner by PT XYZ. Realizing this goal, PT XYZ must formulate its business development strategy. This study aims to determine internal factors (strengths and weaknesses) and external factors (opportunities and threats) which are used as the basis for formulating coffee shop business development strategies. The basic research method is descriptive with data collection techniques through in-depth interviews, focus group discussions (FGD), observation, documentation. Information was obtained through key informants who were determined purposively with the consideration of knowing the coffee shop business, namely directors, managers, supervisors, baristas, consumers, competitors, suppliers and coffee experts. Data analysis uses internal factor evaluation matrix, external factor evaluation, Grand Strategy matrix, SWOT matrix, and participatory prospective analysis. The results of the study show that the position of the grand strategy of PT XYZ is in quadrant I, which means that the strategy concentrates on market and product sustainability, product diversification, and aggressiveness. The main strategy prioritized based on the driving strategy is to increase the effectiveness and efficiency of departmental performance and improve the quality of human resources.

Research on the Internal Talent Training Path and Performance Evaluation Mechanism of New R&amp;D Institutions in Zhejiang Province

New research and development (R&amp;D) institutions are an important part of the national innovation system, playing an important role in promoting the transformation of scientific and technological achievements. In recent years, new R&amp;D institutions have gradually become the driving force of innovation-driven development in China. Taking new R&amp;D institutions in Zhejiang Province as the research object, this paper studies the internal talent training path and performance evaluation mechanism of new R&amp;D institutions in Zhejiang Province by using the literature research method, comparison method, case verification method, and other methods. The investigation results show that there are problems such as lack of material and spiritual support and neglect of the absorption of local talents in the internal talent training, and there are problems such as unclear standards, insufficient data, and opaque processes in the performance evaluation mechanism, which greatly affect the establishment and improvement of the performance evaluation mechanism. Given the above problems, this paper puts forward a forward-looking, oriented, flexible, and compatible talent training path and performance evaluation mechanism, hoping to optimize the effective internal talent training path of new R&amp;D institutions, improve the evaluation performance, and promote healthy development of new R&amp;D institutions in Zhejiang Province.

IFE EFE Analysis of A Social Enterprise Business Strategy

The problem with Kawoel’s MSMEs is the dominance of decreased income, therefore MSMEs need the right business strategy and are suitable for this social enterprise. The object of this research was carried out at a social enterprise company, namely Kawoel's MSMEs. Therefore, the objectives of this study are: 1) to find out an overview of the business strategy carried out by MSMEs at Kawoel's, 2) to find out the strengths, weaknesses, opportunities and threats of Kawoel's MSMEs, 3) to find out alternative business strategy formulations using SWOT Internal Factor Evaluation (IFE) matrix analysis and External Factor Evaluation (EFE) matrix for MSMEs in Kawoel's. This type of research was descriptive qualitative with data collection techniques using observation, interviews, and literature study. This study uses a single variable, namely business strategy, to analyse business strategy in Kawoel's MSMEs using the IFE and EFE matrix tools. The business strategy implemented by Kawoel's had not been maximised so that it had a negative impact on its business. The results of the IFE and IFE matrix for Kawoel's business strategy formulation are in quadrant V, which means that it can be done with a maintain and maintain strategy.

Underprediction of extirpation and colonisation following climate and land‐use change using species distribution models

AbstractAimTo evaluate the performance of species distribution models in predicting observed colonisations, persistences and extirpations in response to changes in climate and land use over a multi‐decadal period.LocationSweden.MethodsWe use historical (early 20th century) land use and climate data to build species distribution models for 84 plant species across three provinces of Sweden. Model performance was then evaluated internally using a subset of the historical data for cross‐validation, as well as by using the models to project occurrences to the modern day and validating them with observed occurrences from 1990 to 2020. We then analysed predicted and observed occurrences in the modern period in terms of persistence, extirpation (local extinction) and colonisation in relation to species' habitat and climate associations.ResultsWe found overall high agreement between evaluation methods, although internal evaluation gave consistently higher values for model performance (using true skill statistic, TSS). Overall, extirpations were worst predicted, with on average fewer than one‐third of each species' extirpations being foreseen by the models. Colonisations were better predicted, while persistences were relatively well‐predicted. Predictive accuracy of colonisations was higher for species with relatively warmer temperature associations (climate‐driven expansion), while extirpations were better predicted in cool‐related species (retractions at cool edges). Colonisations of forest‐associated species were more common than predicted (underpredicted), despite widespread patterns of afforestation. Assessing grid‐cell level turnover, we found that in grid cells that experienced the largest changes in terms of climate and land use, predicted extirpations were less likely to have happened.Main ConclusionsWe found that commonly applied modelling approaches have limited ability to predict observed changes in species occurrences, especially extirpations. This suggests that we should take predictions of future biodiversity loss very seriously. However, the ability for species to (at least temporarily) persist in unsuitable conditions could be an opportunity for biodiversity conservation.

A Case Report of Temporal Macular Thinning Associated with Alport Syndrome

Purpose: To report a case of severe of severe temporal macular thinning in a patient with Alport syndrome. Bilateral temporal thinning is rarely associated with any other systemic conditions, so it is important that ophthalmologists be aware of the significance of this finding and refer for further internal medicine evaluation appropriately. Methods: Clinical examination and multimodal imaging are provided from a clinic visit one month after inpatient treatment for a hypertensive crisis associated with renal failure. Results: The 19-year-old patient had resolving hypertensive retinopathy. High-resolution optical coherence tomography (OCT) confirmed that he had temporal thinning indices (TTIs) consistent with his underlying clinical diagnosis of Alport syndrome. Conclusion: This case report emphasizes the important role of OCT as a commonly available noninvasive retinal imaging modality that can readily demonstrate the temporal macular thinning that is characteristic of Alport syndrome and just a few other conditions. OCT can be an attractive alternative to the much more invasive renal biopsy testing for Alport syndrome when genetic testing is ambiguous or when renal biopsy is considered too risky for the patient.