Medical Journal Armed Forces India最新文献_第3页

Q2 Medicine

Medical Journal Armed Forces India

Pub Date : 2025-11-01 DOI: 10.1016/j.mjafi.2025.09.001

Rakesh Datta

引用次数: 0

The spectrum of cytogenetics and clinical profile in Robertsonian translocations: An experience of two decades from tertiary referral center in India 罗伯逊易位的细胞遗传学和临床谱：印度三级转诊中心二十年的经验

Q2 Medicine

Medical Journal Armed Forces India

Pub Date : 2025-11-01 DOI: 10.1016/j.mjafi.2024.11.002

Krishna Kumar Maharjan , Paresh Singhal , Vandana Kamath , Samuel P. Oommen , Sarah Mathai , Jiji Mathews , Kurien Anil Kuruvila , Sumita Danda , Vivi M. Srivastava

Background

Robertsonian translocations (Rob-t) are the most common structural chromosomal abnormalities observed in humans. Cytogenetic analysis remains essential to identify these abnormalities which cannot be identified by currently used DNA-based tests. This study describes the cytogenetic profile and clinical presentations of Rob-t.

Methods

This was a retrospective observational study of patients with Rob-t who underwent cytogenetic analysis at a tertiary-care center in south India from 2001 to 2019.

Results

Rob-t were observed in 88/12,227(0.72%) patients tested including 4/1425 (0.28%) prenatal samples. There were 21 (0.09%) adults and 63 (0.58%) children (M:F = 1.27:1). With 10 types of Rob-t, eight (72.7%) heterologous and two homologous (27.3%). Thirty(34%) were balanced and 58(66%) unbalanced (associated with trisomy). All 21 adults had balanced Rob-t and had recurrent pregnancy loss, infertility/oligospermia, premature ovarian failure or were carrier parents. All unbalanced Rob-t were observed in children with trisomy 21(98.2%) or trisomy 13(1.8%). The der(14;21), der(21;21) and the der(13;14) accounted for 32(36.4%), 22(25%) and 17(19.3%), respectively and the other Rob-t for <6% each; 16(18.2%) der(13;14) were balanced.

One child had mosaicism for der(21;21) and a ring chromosome 21. Three more patients had additional abnormalities, namely, t(10;12) (p11.1;q22), 15q microdeletion consistent with Prader–Willi syndrome and mosaic X/XXX.

Conclusions

All adults had balanced Rob-t. Unbalanced Rob-t were seen only in children. The unbalanced der(14;21) was our most common Rob-t followed by der(21;21) because the majority were ascertained in children with Down syndrome. The der(13;14) was the most common balanced Rob-t.

罗伯逊易位（robt）是人类观察到的最常见的染色体结构异常。细胞遗传学分析对于识别目前使用的基于dna的测试无法识别的这些异常仍然至关重要。本研究描述了robt的细胞遗传学特征和临床表现。方法：这是一项回顾性观察性研究，研究对象是2001年至2019年在印度南部一家三级医疗中心接受细胞遗传学分析的robt患者。结果12227例患者中有88例（0.72%）存在罗布-t，其中产前样本中有4/1425例（0.28%）存在罗布-t。成人21例（0.09%），儿童63例（0.58%）（M:F = 1.27:1）。其中，异源8例（72.7%），同源2例（27.3%）。30例（34%）平衡，58例（66%）不平衡（与三体相关）。所有的21名成年人都有平衡的Rob-t，反复流产，不孕/少精症，卵巢早衰或携带父母。在21三体（98.2%）或13三体（1.8%）患儿中观察到所有不平衡的robt。der（14;21）、der（21;21）和der（13;14）分别占32（36.4%）、22（25%）和17(19.3%)，其他robt各占6%；16例（18.2%）例（13例；14例）平衡。一个孩子有der（21;21）嵌合和环状21号染色体。另外3例患者有额外的异常，即t(10;12) (p11.1;q22)， 15q微缺失与Prader-Willi综合征和马赛克X/XXX一致。结论所有成人均有平衡的robt。不平衡的罗伯特-t只在儿童中出现。不平衡的der（14;21）是我们最常见的robb -其次是der(21;21)，因为大多数是在患有唐氏综合症的儿童中确定的。der（13;14）是最常见的平衡robt。

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引用次数: 0

Adoption of artificial intelligence technologies in health care: A cross-sectional survey on insights and perspectives of healthcare professionals 在医疗保健中采用人工智能技术：对医疗保健专业人员的见解和观点的横断面调查

Q2 Medicine

Medical Journal Armed Forces India

Pub Date : 2025-11-01 DOI: 10.1016/j.mjafi.2025.04.012

Poonam Raj , Anubhav Singh , Kamal Preet Singh , Rakesh Datta

Background

The successful implementation of artificial intelligence (AI)–enabled technologies in health care requires a thorough understanding of the needs and expectations of healthcare professionals (HCPs). This study evaluated the acceptability, expectations, needs, and concerns of HCPs regarding the adoption of AI technologies.

Methods

A cross-sectional survey of 572 HCPs was conducted using an online survey questionnaire. The survey responses were aggregated, and proportions of agreement were computed to assess the familiarity, perception, expectations, and attitudes towards the adoption of AI technologies in health care. The data were further analysed as per the broad specialities of respondents. Thematic analysis was conducted to analyse the responses to open-ended questions.

Results

The survey found significant gaps in technical knowledge and expertise for implementation of AI-enabled healthcare technologies, with potential scope for improvement. Whilst 73.33% of respondents rated their knowledge of computers as mediocre, 42.31% were familiar with the concepts of AI, and only 36.89% were familiar with applications of AI in their speciality. Medicine and allied specialities had the least agreement regarding the adoption of AI. The respondents noted strong optimism regarding the potential of AI in improving efficiency and clinical outcomes. However, various technical, legal, and regulatory challenges remain to be addressed before full-scale implementation of AI technologies in health care.

Conclusion

The study provides valuable insights into the perspectives of HCPs regarding the integration of AI-assisted technologies, highlighting the importance of training in AI, development of robust technologies, and addressing the needs and concerns to ensure the optimal utilisation of AI in health care.

背景人工智能（AI）技术在医疗保健领域的成功实施需要对医疗保健专业人员（hcp）的需求和期望有透彻的了解。本研究评估了医护人员对采用人工智能技术的可接受性、期望、需求和关注。方法采用在线调查问卷对572名医护人员进行横断面调查。汇总调查回复，计算同意比例，以评估对在医疗保健中采用人工智能技术的熟悉程度、感知、期望和态度。根据受访者的广泛专业对数据进行了进一步分析。进行了专题分析，以分析对开放式问题的答复。结果调查发现，在实施人工智能医疗技术的技术知识和专业知识方面存在重大差距，存在潜在的改进空间。73.33%的受访者认为他们的计算机知识一般，42.31%的受访者熟悉人工智能的概念，只有36.89%的受访者熟悉人工智能在他们专业中的应用。医学和相关专业在采用人工智能方面的一致性最低。受访者对人工智能在提高效率和临床结果方面的潜力表示强烈乐观。然而，在卫生保健领域全面实施人工智能技术之前，仍需解决各种技术、法律和监管挑战。结论本研究为医护人员整合人工智能辅助技术的观点提供了有价值的见解，强调了人工智能培训的重要性，开发稳健的技术，并解决了人工智能在医疗保健中的最佳利用的需求和关注点。

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引用次数: 0

Significance of increased 18F-FDG uptake in determining pathological status in post-chemotherapy lymphoma cases involving head-neck region on PET-CT 18F-FDG摄取增加在PET-CT上判断头颈部化疗后淋巴瘤病理状态的意义

Q2 Medicine

Medical Journal Armed Forces India

Pub Date : 2025-11-01 DOI: 10.1016/j.mjafi.2024.09.009

D.K. Gupta , Sanjeeva Bharadwaja , M. Vigneshwaran , A.G. Pandit

Background

Currently, all follow-up cases of lymphoma showing fluorodeoxyglucose (FDG) avid uptake on positron emission tomography/computed tomography (PET-CT) in head-neck region undergo biopsy for tissue confirmation of diagnosis. There are no consensus or practice guidelines in literature pertaining, whether to biopsy all such FDG avid lesions post-chemotherapy. Hence, this study was conducted to determine the significance of PET-CT (SUVmax 5.0 or above) in determining remission or pathological status in these patients.

Methods

A retrospective cohort analysis conducted between July 2019 and May 2023 at our institute of 40 follow-up cases of lymphoma post-chemotherapy (Group A) showing FDG Uptake with SUVmax 5.0 or above on PET-CT in Waldeyer's Ring (WR) or neck, and 40 non- lymphoma cases (Group B) showing FDG Uptake with similar SUVmax in WR or neck. All cases in group A underwent tonsillectomy and results of histopathology were correlated with PET-CT findings. All cases in group B underwent thorough clinical correlation with respect to PET-CT findings. A Receiver Operating Characteristic (ROC) curve for SUVmax was plotted to statistically analyse this data.

Results

Statistical analysis of our observations by plotting a ROC curve for SUVmax revealed a sensitivity of 90% with 10% specificity and an insignificant p-value of 0.733.

Conclusion

We propose that unnecessary biopsy in all cases with FDG avid uptake must not be encouraged unless accompanied by a suspicious holistic clinical picture of asymmetry, significant lymph node involvement with FDG avid uptake and counterpart finding on CT. A tissue confirmation in all such cases may result in unnecessary risk and increase the cost of therapy.

目前，所有在头颈部正电子发射断层扫描/计算机断层扫描（PET-CT）上显示氟脱氧葡萄糖（FDG）摄取旺盛的淋巴瘤随访病例都需要进行活检以确认诊断。关于化疗后是否对所有此类FDG病变进行活检，文献中没有共识或实践指南。因此，本研究旨在确定PET-CT （SUVmax 5.0及以上）在确定这些患者的缓解或病理状态方面的意义。方法回顾性队列分析2019年7月至2023年5月在我所随访的40例化疗后淋巴瘤患者（A组）在Waldeyer's Ring （WR）或颈部PET-CT显示FDG摄取，SUVmax为5.0及以上，40例非淋巴瘤患者（B组）在WR或颈部显示FDG摄取，SUVmax相似。A组所有病例均行扁桃体切除术，组织病理学结果与PET-CT表现相关。B组所有病例均与PET-CT表现进行了全面的临床对照。绘制SUVmax的受试者工作特征（ROC）曲线对该数据进行统计分析。结果通过绘制SUVmax的ROC曲线对我们的观察结果进行统计分析，结果显示敏感性为90%，特异性为10%，p值为0.733，不显著。结论：我们建议不鼓励所有FDG摄取病例进行不必要的活检，除非伴有可疑的整体临床图像不对称，FDG摄取的明显淋巴结累及和CT上的相应发现。在所有这些病例中进行组织确认可能会导致不必要的风险并增加治疗费用。

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引用次数: 0

Development and validation of an artificial intelligence algorithm for cervical vertebral maturation staging using lateral cephalograms 开发和验证人工智能算法的颈椎成熟分期使用侧位脑电图

Q2 Medicine

Medical Journal Armed Forces India

Pub Date : 2025-11-01 DOI: 10.1016/j.mjafi.2025.08.012

Ramnarayan BK , Sindhu P , Preeti Patil , Arjun Krishnamurthy , Mahesh DR , Darshana S

Background

Cervical vertebral maturation (CVM) assessment using lateral cephalograms offers a reliable method for evaluating skeletal maturity without additional radiation exposure. However, traditional manual analysis is time-intensive and prone to variability. With the growing role of artificial intelligence in medical imaging, this study aimed to develop and validate a deep learning algorithm capable of automatically determining CVM stages from lateral cephalometric radiographs, improving diagnostic efficiency and accuracy.

Methods

In total, 525 lateral cephalograms from individuals aged 7–17 years (249 males and 276 females; mean age, 12.67 years) were analyzed. An artificial intelligence-powered annotation platform, developed using PLAINSIGHT, was employed to identify 19 anatomical landmarks and perform 20 linear measurements on the C2, C3, and C4 vertebrae. The VGG19 convolutional neural network model was trained using 1300 augmented images generated from 420 original cephalograms. Model validation was performed on an independent dataset comprising 105 cephalograms.

Results

The trained VGG19 model achieved an overall accuracy of 86% in CVM staging, with optimal performance observed between 80 and 100 training epochs. Confusion matrix analysis indicated the highest classification accuracy in CVS stages 4, 5, and 6. The model demonstrated an overall F1 score of 0.85, with the highest score in CVS6 (0.93) and the lowest in CVS1 (0.79), reflecting robust predictive capability across multiple maturation stages.

Conclusion

The VGG19-based deep learning model showed strong potential for automating CVM assessment using lateral cephalograms. Its high accuracy and reproducibility suggest its utility as a clinical decision-support tool for evaluating skeletal development in growing individuals.

背景：使用侧位头颅造影评估颈椎成熟度（CVM）为评估骨骼成熟度提供了一种可靠的方法，无需额外的辐射暴露。然而，传统的手工分析是费时的，而且容易发生变化。随着人工智能在医学成像中的作用越来越大，本研究旨在开发和验证一种深度学习算法，该算法能够从侧位头颅x线片自动确定CVM分期，提高诊断效率和准确性。方法收集7 ~ 17岁患者525张侧位脑片，其中男性249张，女性276张，平均年龄12.67岁。使用PLAINSIGHT开发的人工智能注释平台识别了19个解剖标志，并对C2、C3和C4椎体进行了20次线性测量。利用420张原始脑电图生成的1300张增强图像对VGG19卷积神经网络模型进行训练。模型验证在包含105张脑电图的独立数据集上进行。结果训练后的VGG19模型在CVM分期中的总体准确率为86%，在80 ~ 100个训练周期之间表现最佳。混淆矩阵分析表明，CVS阶段4、5和6的分类准确率最高。该模型的F1总得分为0.85，其中CVS6得分最高（0.93），CVS1得分最低（0.79），具有较强的跨成熟期预测能力。结论基于vgg19的深度学习模型在侧位脑电图CVM自动评估方面具有很强的潜力。它的高准确性和可重复性表明它作为临床决策支持工具的效用评估骨骼发育的个体。

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引用次数: 0

Role of artificial intelligence-enabled hand-held fundus camera for community-based diabetic retinopathy screening 人工智能手持式眼底相机在社区糖尿病视网膜病变筛查中的作用

Q2 Medicine

Medical Journal Armed Forces India

Pub Date : 2025-11-01 DOI: 10.1016/j.mjafi.2024.09.008

Vijay K. Sharma , Srishti Khullar , Prabhjot Singh , Vikas Ambiya , Ashok Kumar , Anuroop N , Gaurav Kapoor , Preeti RK

Background

This study aimed to assess the diagnostic accuracy of an artificial intelligence (AI) system integrated with a portable handheld fundus camera for the detection of diabetic retinopathy (DR) in a community-based screening program.

Methods

A DR screening camp was organized at a tertiary care hospital in India. A cohort of 261 patients with diabetes was screened using a nonmydriatic handheld fundus camera. Retinal images were graded by specialists and compared with the AI system's output. Sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and area under the receiver operating characteristic curve (AUC-ROC) were calculated. Subgroup analyses based on image quality was performed.

Results

Of the 261 patients screened, 253 had available retinal images, and 243 had gradable images. The AI system achieved a sensitivity of 85.29%, specificity of 99.04%, PPV of 93.55%, and NPV of 97.64% for detecting referable DR. The AUC-ROC was 0.93. The AI system's performance remained robust across all image-quality categories. The AI system showed strong agreement with human graders (κ = 0.86). However, it failed to identify certain non-DR pathologies detected by human graders.

Conclusions

The AI system integrated with a portable handheld fundus camera demonstrated high diagnostic accuracy for referable DR detection in a community-based screening setting. This technology shows promise for expanding DR-screening coverage in resource-limited settings.

本研究旨在评估人工智能（AI）系统与便携式手持式眼底相机在社区筛查项目中检测糖尿病视网膜病变（DR）的诊断准确性。方法在印度某三级医院组织开展DR筛查营活动。261例糖尿病患者使用无晶状体手持式眼底相机进行筛查。视网膜图像由专家评分，并与人工智能系统的输出进行比较。计算敏感性、特异性、阳性预测值（PPV）、阴性预测值（NPV）和受试者工作特征曲线下面积（AUC-ROC）。基于图像质量进行亚组分析。结果在261例患者中，253例有可用的视网膜图像，243例有可分级图像。人工智能系统检测可参考dr的灵敏度为85.29%，特异性为99.04%，PPV为93.55%，NPV为97.64%，AUC-ROC为0.93。人工智能系统的性能在所有图像质量类别中都保持强劲。AI系统与人类评分者表现出很强的一致性（κ = 0.86）。然而，它无法识别人类分级员检测到的某些非dr病理。结论与便携式手持式眼底相机集成的人工智能系统在社区筛查环境中可参考DR检测具有较高的诊断准确性。这项技术有望在资源有限的情况下扩大dr筛查的覆盖范围。

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引用次数: 0

Artificial intelligence in simulation-based training for Health Professions Education: Navigating the rabbit hole 人工智能在卫生专业教育模拟培训中的应用：探索兔子洞

Q2 Medicine

Medical Journal Armed Forces India

Pub Date : 2025-11-01 DOI: 10.1016/j.mjafi.2025.08.010

Rakhi Negi , Deepti Chopra , Komal Maheshwari , Anushi Mahajan , Dinesh Badyal , Padmini Venkataramani

Simulation-based training (SBT) for health professions education has seen an evolution from low-fidelity trainers to technology-integrated high-fidelity trainers, which has opened doors to newer and promising prospects of integration of artificial intelligence (AI) into SBT. This review provides insights into the use of AI to augment and transform various elements of SBT like complex scenario designing, realism, feedback, student engagement, etc. This is exemplified through the successful application of AI in various SBT platforms, which have increased the efficacy of simulations. However, several challenges and barriers have been perceived in the use of AI in SBT, which include bias in AI algorithms originating due to skewed training datasets leading to inaccurate decisions, errors due to black box, cost factors, need for constant update, and ethical, legal, and cultural issues. Despite these challenges, the railroads of AI are fast-tracking with increased interest and collaborative ventures between various stakeholders like healthcare professionals, educators, technological experts, and policymakers. This article attempts to provide a comprehensive overview of the role of AI in SBT, challenges, and the way forward to amalgamating it with SBT in an optimal manner.

卫生专业教育的模拟培训（SBT）经历了从低保真度培训师到技术集成高保真度培训师的演变，这为将人工智能（AI）融入模拟培训开辟了新的前景。这篇综述提供了使用人工智能来增强和转化SBT的各种元素的见解，如复杂的场景设计、真实感、反馈、学生参与等。人工智能在各种SBT平台上的成功应用证明了这一点，这提高了仿真的效率。然而，在SBT中使用人工智能存在一些挑战和障碍，其中包括由于训练数据集偏差导致决策不准确、黑箱错误、成本因素、需要不断更新以及道德、法律和文化问题而导致的人工智能算法偏差。尽管存在这些挑战，但随着医疗保健专业人员、教育工作者、技术专家和政策制定者等不同利益相关者之间的兴趣和合作企业的增加，人工智能的铁路正在快速发展。本文试图全面概述人工智能在SBT中的作用、挑战以及以最佳方式将其与SBT合并的方法。

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引用次数: 0

Artificial intelligence driven diagnostic model for detecting paranasal sinus opacification in computed tomography images: Development and evaluation 人工智能驱动的诊断模型用于检测计算机断层图像中的鼻窦混浊：开发和评估

Q2 Medicine

Medical Journal Armed Forces India

Pub Date : 2025-11-01 DOI: 10.1016/j.mjafi.2025.02.007

Anubhav Singh , Kamal Deep Joshi , Sachin Girdhar , Dharamendra Kumar Singh , Rakesh Datta , Abhipsa Hota , Poonam Raj , Suraj Thapa

Background

Visual analysis of paranasal sinuses (PNS) on computed tomography (CT) images requires interpretation and reporting of sinus involvement and other anatomical factors. This is time consuming, labour intensive and subjective. Artificial intelligence (AI)–based machine learning (ML) tools are under development for analysis of radiological images. The scope of this study was to develop and evaluate a coding–free ML model for automated identification of PNS on CT images.

Methods

A total of 19,119 anonymous coronal images retrieved from 90 CT studies were included. All images were annotated with locations, names and opacification status of the sinuses. The images were divided into training, validation and testing datasets. The ML model was trained for 2000 iterations using YOLOv2 algorithm, and its accuracy was evaluated using F1 score and Intersection over Union (IoU) metrics.

Results

An ML model was developed using “Create ML” application on an Apple MacBook computer. A mean F1 score of 0.89 and a mean IoU50 of 79% was achieved during evaluation of the model on the testing dataset. The highest accuracy was seen in the detection of normal sphenoid sinus, and the lowest in the detection of opacified frontal sinus.

Conclusion

The study demonstrates the utility of AI and ML in automating the interpretation of PNS CT images. From the results of our study, it can be concluded that a coding–free ML model can be developed and deployed for automated identification of PNS on CT images with accuracy similar to custom–coded ML models.

计算机断层扫描（CT）图像上鼻窦（PNS）的视觉分析需要解释和报告鼻窦受累和其他解剖学因素。这是耗时、劳动密集和主观的。基于人工智能（AI）的机器学习（ML）工具正在开发中，用于分析放射图像。本研究的范围是开发和评估一个无编码的ML模型，用于自动识别CT图像上的PNS。方法从90份CT研究中检索到19119张匿名冠状图像。所有图像都标注了鼻窦的位置、名称和混浊状态。将图像分为训练集、验证集和测试集。使用YOLOv2算法对ML模型进行2000次迭代训练，并使用F1分数和Intersection over Union （IoU）指标评估其准确性。结果在苹果MacBook电脑上使用“Create ML”应用程序开发了一个ML模型。在测试数据集上对模型进行评估时，平均F1得分为0.89，平均IoU50为79%。正常蝶窦的检测准确率最高，额窦混浊的检测准确率最低。结论人工智能和机器学习在PNS CT图像自动解译中的应用。从我们的研究结果可以得出结论，可以开发和部署一种无需编码的ML模型，用于CT图像上PNS的自动识别，其精度与自定义编码的ML模型相似。

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引用次数: 0

To study the efficacy of case based learning on prescription practices in post graduate students on geriatric patients attending medical OPD 目的：研究基于案例学习的研究生处方实践对老年门诊患者的影响

Q2 Medicine

Medical Journal Armed Forces India

Pub Date : 2025-11-01 DOI: 10.1016/j.mjafi.2024.04.005

Vivek Aggarwal , Pradeep Behal , Vishal Sharma , A.K. Yadav , Uday Yanamandra

Background

Rationalizing drugs and deprescribing potentially inappropriate medicines in elderly patients is a major challenge faced by doctors in today’s era due to the ever-increasing number of diseases, drugs, changing guidelines, and indications. The objective of this study was to study the efficacy of case-based learning on prescription practices in postgraduate students on geriatric patients attending medical outpatient department (OPD).

Methods

Observation cross-sectional study done on postgraduate medicine residents working in medicine/geriatric OPD. Prescriptions were analyzed for quality by prescription quality index (PQI) score. The baseline PQI score was generated. An interactive workshop and training session on case-based learning on appropriate prescribing for the elderly was conducted. The prescribing habits and PQI scores were reassessed and compared to assess the change in PQI scores along with satisfaction levels and faculty feedback.

Results

A total of 60 prescriptions from 24 medicine residents were initially assessed for baseline PQI. A total of 41 residents participated in the workshop. Sixty fresh prescriptions were reassessed after one month of the workshop. The mean baseline PQI was 27.15 (±3.70) which increased to 31.81 (±3.60) [p < 0.001. The majority of the faculty (10/12) felt improvement in prescribing practices. Two third of residents (28/41) had a very good and excellent level of satisfaction with the case-based learning.

Conclusion

Case-based learning is an effective tool for enhancing the prescribing skills of postgraduates, especially in geriatric patients. There was a significant improvement in PQI score after the case-based learning workshop in the prescriptions of the postgraduate students with a p-value of < 0.001.

由于疾病、药物、指南和适应症的不断变化，使老年患者的药物合理化和减少可能不适当的药物处方是当今时代医生面临的主要挑战。本研究的目的是研究案例学习对研究生处方实践的影响，以帮助老年患者在门诊就诊。方法对在医学/老年门诊工作的研究生住院医师进行观察性横断面研究。采用处方质量指数（PQI）对处方质量进行分析。生成基线PQI评分。举办了一个互动式讲习班和培训课程，以案例为基础学习老年人的适当处方。重新评估处方习惯和PQI评分，并比较PQI评分的变化以及满意度和教师反馈。结果对24名住院医师共60张处方进行了基线PQI评估。共有41位居民参加了工作坊。讲习班一个月后，对60个新处方进行了重新评估。平均基线PQI为27.15（±3.70），上升至31.81（±3.60）[p < 0.001]。大多数教师（10/12）认为处方实践有所改善。三分之二的住院医生（28/41）对基于案例的学习感到非常满意。结论基于案例的学习是提高研究生，尤其是老年患者处方技能的有效工具。在案例学习工作坊后，硕士生处方的PQI得分显著提高，p值为<； 0.001。

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引用次数: 0

Standardisation of 3D-laser whole body scanner protocol for anthropometric measurements in cockpit ergonomics 座舱人体工程学中用于人体测量的3d激光全身扫描仪协议的标准化

Q2 Medicine

Medical Journal Armed Forces India

Pub Date : 2025-11-01 DOI: 10.1016/j.mjafi.2025.05.014

M. Binu Sekhar , Punyashlok Biswal , V. Raghunandan , N.K. Tripathy

Background

Standardizing the measurement protocol for 3D-Laser whole body scanners is crucial to ensure accurate anthropometric measurements essential for designing cockpit workspaces. The aim of this study was to standardize the use of 3D laser anthropometric scanners for cockpit ergonomic studies.

Methods

Four hundred healthy male volunteers, aged 18 to 56 years (mean±SD: 32.9±10.2 years), participated in this study. Thirty-two anthropometric parameters relevant to the ergonomic design of aircraft cockpits were measured using both a standard manual method and a newly developed 3D-laser scanner protocol. Manual measurements were conducted with the IAM Portable Manual Anthropometer, while 3D-laser scanning was performed using the VITUS® 3D-Laser Whole Body Scanner and ANTHROSCAN software by Human Solutions GmbH. Statistical comparisons were made for each parameter to evaluate differences in means, correlations, and agreement between the two measurement methods.

Results

The percentage differences in means were up to 1% for 10 parameters, between 1% and 5% for 15 parameters, and exceeded 5% for 7 parameters. Seven parameters showed good correlation, 24 had moderate correlation, and one parameter had poor correlation. The agreement analysis revealed that the maximum bias for the 95% confidence interval, expressed as a percentage of the average of both means, was less than 5% for five parameters, between 5% and 10% for 14 parameters, and exceeded 10% for 13 parameters.

Conclusion

Analysis of differences in means, correlation strength, and agreement bias indicated that among the 32 anthropometric parameters, five were highly comparable, 14 were moderately comparable, and the remaining 13 were weakly comparable. Recommendations were made to refine and validate the 3D-scanner measurement protocol for better use in cockpit design ergonomics.

标准化3d激光全身扫描仪的测量协议对于确保精确的人体测量至关重要，这对于设计驾驶舱工作空间至关重要。本研究的目的是标准化使用3D激光人体测量扫描仪的驾驶舱人体工程学研究。方法400名健康男性志愿者，年龄18 ~ 56岁（mean±SD: 32.9±10.2岁）。采用标准的手工方法和新开发的3d激光扫描仪协议测量了32个与飞机驾驶舱人体工程学设计相关的人体测量参数。使用IAM便携式手动人体测量仪进行手动测量，而使用VITUS®3d激光全身扫描仪和Human Solutions GmbH的ANTHROSCAN软件进行3d激光扫描。对每个参数进行统计比较，以评估两种测量方法在平均值、相关性和一致性方面的差异。结果10个参数的平均值差异在1%以内，15个参数的平均值差异在1% ~ 5%之间，7个参数的平均值差异超过5%。7个参数相关性良好，24个参数相关性中等，1个参数相关性较差。一致性分析显示，95%置信区间的最大偏差（以两个平均值的平均值的百分比表示）在5个参数中小于5%，在14个参数中介于5%到10%之间，在13个参数中超过10%。结论通过均数、相关强度和一致性偏倚分析，32个人体测量参数中，5个具有高度可比性，14个具有中度可比性，其余13个具有弱可比性。提出了改进和验证3d扫描仪测量协议的建议，以便更好地在驾驶舱设计中使用人体工程学。

{"title":"Standardisation of 3D-laser whole body scanner protocol for anthropometric measurements in cockpit ergonomics","authors":"M. Binu Sekhar , Punyashlok Biswal , V. Raghunandan , N.K. Tripathy","doi":"10.1016/j.mjafi.2025.05.014","DOIUrl":"10.1016/j.mjafi.2025.05.014","url":null,"abstract":"<div><h3>Background</h3><div><span><span>Standardizing the measurement protocol for 3D-Laser whole body scanners is crucial to ensure accurate </span>anthropometric measurements essential for designing cockpit workspaces. The aim of this study was to standardize the use of 3D laser anthropometric scanners for cockpit </span>ergonomic studies.</div></div><div><h3>Methods</h3><div>Four hundred healthy male volunteers, aged 18 to 56 years (mean±SD: 32.9±10.2 years), participated in this study. Thirty-two anthropometric parameters relevant to the ergonomic design<span> of aircraft cockpits were measured using both a standard manual method and a newly developed 3D-laser scanner protocol. Manual measurements were conducted with the IAM Portable Manual Anthropometer, while 3D-laser scanning was performed using the VITUS® 3D-Laser Whole Body Scanner and ANTHROSCAN software by Human Solutions GmbH. Statistical comparisons were made for each parameter to evaluate differences in means, correlations, and agreement between the two measurement methods.</span></div></div><div><h3>Results</h3><div>The percentage differences in means were up to 1% for 10 parameters, between 1% and 5% for 15 parameters, and exceeded 5% for 7 parameters. Seven parameters showed good correlation, 24 had moderate correlation, and one parameter had poor correlation. The agreement analysis revealed that the maximum bias for the 95% confidence interval, expressed as a percentage of the average of both means, was less than 5% for five parameters, between 5% and 10% for 14 parameters, and exceeded 10% for 13 parameters.</div></div><div><h3>Conclusion</h3><div>Analysis of differences in means, correlation strength, and agreement bias indicated that among the 32 anthropometric parameters, five were highly comparable, 14 were moderately comparable, and the remaining 13 were weakly comparable. Recommendations were made to refine and validate the 3D-scanner measurement protocol for better use in cockpit design ergonomics.</div></div>","PeriodicalId":39387,"journal":{"name":"Medical Journal Armed Forces India","volume":"81 6","pages":"Pages 689-697"},"PeriodicalIF":0.0,"publicationDate":"2025-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145420579","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

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