Association between vaginal microecological alterations and high-risk human papillomavirus infection: a cross-sectional study by Nanqiu Peng, Nanqiu Peng, Jing Xiao, Li He, Li Xie, Li Xie

“…The ROC curve analysis yielded an AUC of 0.701, indicating moderate predictive value.ConclusionChanges in the vaginal microecological environment are significantly associated with HR-HPV infection. …”
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A feasibility study of a short lung ultrasound protocol as a screening method for fibrotic interstitial lung disease by Sara Braga, André Carvalho, Márcio Rodrigues, Pedro Madureira, Raquel Miriam Ferreira, André Terras Alexandre, Natália Melo, Patrícia Caetano Mota, António Morais, Hélder Novais Bastos

“…This protocol demonstrated high sensitivity and positive predictive value in identifying reticulation and honeycombing, as well as remarkable specificity and negative predictive value for the latter. …”
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XGBoost-SHAP-based interpretable diagnostic framework for knee osteoarthritis: a population-based retrospective cohort study by Zijuan Fan, Wenzhu Song, Yan Ke, Ligan Jia, Songyan Li, Jiao Jiao Li, Yuqing Zhang, Jianhao Lin, Bin Wang

“…Classifications were evaluated using sensitivity, specificity, positive predictive value, negative predictive value, accuracy, area under the curve(AUC), G-means, and F1 scores. …”
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Development and validation of a clinical prediction model for concurrent pulmonary infection in convalescent patients with intracerebral hemorrhage by Jixiang Xu, Xiaoxiao Han, Yinliang Qi, Xiaomei Zhou

“…Clinical utility was evaluated via decision curve analysis (DCA). Positive predictive value (PPV) and negative predictive value (NPV) were also calculated at the optimal threshold. …”
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Deep learning based screening model for hip diseases on plain radiographs. by Jung-Wee Park, Seung Min Ryu, Hong-Seok Kim, Young-Kyun Lee, Jeong Joon Yoo

“…The deep learning models were compared in terms of accuracy, sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), F1-score, and area under the receiver operating characteristic curve (AUROC).…”
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The use of contrast enhancement in the diagnosis of simple and complex cysts kidneys by Ya. A. Soloviev, L. A. Mitina, B. Ya. Alekseev, S. O. Stepanov, A. S. Kalpinskiy, O. V. Dimitrov, E. A. Nazoikin

“…The specificity of the method was 78.57%, the accuracy of the method was 85.71%, the predictive value of the positive result was 81.25%, and the predictive value of the negative result was 91.66%. …”
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Can artificial intelligence and contrast-enhanced mammography be of value in the assessment and characterization of breast lesions? by Lamiaa Mohamed Bassam Hashem, Heba Monir Azzam, Ghadeer Saad Abd El-Shakour El-Gamal, MennatAllah Mohamed Hanafy

“…In our study, CEM demonstrated a sensitivity of 98.33%, specificity of 92.86%, positive predictive value (PPV) of 98.34%, negative predictive value (NPP) of 92.85%, and accuracy of 97.3%. …”
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The relationship between the apnea-hypopnea index, oxygen desaturation index, average oxygen saturation, and body mass index in patients with obstructive sleep apnea by Novković Dobrivoje, Popović Nela, Novković Nikola, Lukić Jelena, Begović-Kuprešanin Vesna, Popević Martin

“…With its strong correlation with AHI, as well as predictive value for more severe forms of apnea, ODI has the same importance as AHI in diagnosing and assessing the severity of this disorder.…”
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IL-6 and CD4+/CD8+ are Important Indicators for Predicting Prognosis in Elderly AECOPD Patients: A Retrospective Study by Liu Q, Wang Y, Cao X, Zhang S, Xie J

“…Combining IL-6 with CD4+/CD8+ ratios significantly enhances the predictive value for adverse events.Keywords: elderly, acute exacerbation of chronic obstructive pulmonary disease, IL-6, CD4+/CD8+, prognosis…”
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Relationship between baseline dialysate to plasma ratio of creatinine at 4h and restless legs syndrome in peritoneal dialysis patients by Yan Qi-qi, Liu Gui-ling, Hao Li, Wang De-guang, Li Dan-dan

“…Objective To explore the relationship between the baseline dialysate to plasma creatinine ratio at 4 h and restless legs syndrome（RLS）in maintenance peritoneal dialysis（PD）patients.Methods From December 1,2019 to June 31,2020,92 hospitalized PD patients were recruited to assess peritoneal transport function and dialysis adequacy.Regular follow-ups were conducted.During hospitalization, RLS was screened according to the diagnostic criteria of International Restless Legs Syndrome Study Groupand the prevalence of RLS evaluated.They were divided into two groups of RLS（RLS+ group）and non-RLS（RLS-group）according to whether or not RLS occurred.All of them were evaluated for basic peritoneal transport function within 6 months after PD catheterization.To relationship was analyzed between baseline dialysate to plasma ratio of creatinine at 4 h（4 hD/Pcr）and RLS and the predictive value of baseline 4 hD/Pcrfor RLS examined.Results The prevalence rate of RLS was 33.7% and moderate-to-severe cases predominated（moderate 35.48%,severe 38.71%）.Age, dialysis age, baseline 4 hD/Pcr and ferritin of RLS+ group were significantly higher than those of RLS-group while urine output was significantly less than that of RLS-group（all P<0.05）.Multivariate Logistic regression analysis indicated that advanced age（OR=1.054,95%CI 1.010-1.100,P=0.015）,lower urine output（OR=0.998,95%CI 0.997-0.999,P=0.005）and higher baseline 4 hD/Pcr（OR=1.047,95%CI 1.009-1.086,P=0.014）were independent risk factors for RLS.Receiver operating characteristic（ROC）curve showed that the sensitivity of baseline 4 hD/Pcr for predicting the risk of RLS was 90.3% and the specificity 45.9% in PD patients.Conclusion Advanced age, lower urine output and higher baseline 4 hD/Pcrare independent risk factors for RLS in PD patients.And high baseline 4 hD/Pcr has some diagnostic and predictive value for RLS in PD patients.…”
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Ultrasound Characteristics of Myometrial Invasion in Endometrial Carcinoma: A Prospective Cohort Study by Anis Cerovac, Dubravko Habek, Zlatko Hrgović

“…Analysis of the diagnostic accuracy showed that the subjective TVS method compared to the gold standard in the diagnosis of MI >50% has a good diagnostic value: accuracy = 0.87; sensitivity = 0.77; specificity = 0.94; positive predictive value = 0.91; negative predictive value = 0.84; positive likelihood ratio = 13.08; negative likelihood ratio = 0.25. …”
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Effectiveness of a Community-Based Oral Cancer Screening Program Using Portable Fluorescence Spectroscopy in Rural Madhya Pradesh, India by Anuj Singh Parihar, Mahendrakumar A. Chaudhari, Hiren H. Patadiya, Jitender Kumar, Sanja Samir Sahu, Rashmi Laddha, Megha C Patel

“…For oral cancer detection, the sensitivity was 90.0%, and the specificity was 94.1%. The positive predictive value was 78.9% for OPMDs and 82.4% for oral cancer, while the negative predictive value was 96.3% and 97.5%, respectively. …”
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Prognostic role of levels of extracellular histones H3 for diagnosis of early dysfunction of transplant after hepatic transplantation by N. G. Novruzov

“…Neutrophils had a higher predictive value for liver dysfunction than any other parameter within 24 h (Odds ratio (OR) 16.3; 95% CI: 1.7-156.3, P = 0.016).   …”
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Predicting the efficacy of microwave ablation of benign thyroid nodules from ultrasound images using deep convolutional neural networks by Enock Adjei Agyekum, Yu-guo Wang, Eliasu Issaka, Yong-zhen Ren, Gongxun Tan, Xiangjun Shen, Xiao-qin Qian

“…Accuracy, sensitivity, specificity, positive predictive value, negative predictive value, and area under the curve (AUC) were all used to assess predictive performance. …”
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Enhanced prediction of ventilator-associated pneumonia in patients with traumatic brain injury using advanced machine learning techniques by Negin Ashrafi, Armin Abdollahi, Kamiar Alaei, Maryam Pishgar

“…Comprehensive evaluations were conducted based on multiple metrics, including Area Under the Curve (AUC), accuracy, F1 score, sensitivity, specificity, Positive Predictive Value, and Negative Predictive Value. XGBoost emerged as the top performing algorithm, achieving an AUC of 0.94 and an accuracy of 0.875 on the test set, marking substantial improvements over previously reported best results. …”
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Accuracy of Patient Self-Report of Stroke: A Systematic Review from the UK Biobank Stroke Outcomes Group. by Rebecca Woodfield, UK Biobank Stroke Outcomes Group, UK Biobank Follow-up and Outcomes Working Group, Cathie L M Sudlow

“…We extracted data on survey method(s), response rates, participant characteristics, the reference standard used, and the positive predictive value (PPV) of self-report. Where possible we also calculated sensitivity, specificity, negative predictive value (NPV), and stroke prevalence. …”
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Development and Validation of a Screening Equation for Obstructive Sleep Apnea by Antonio Fabozzi, Alessia Steffanina, Matteo Bonini, Paolo Palange

“…The results showed that AHIp had a sensitivity of 95%, a specificity of 28%, a positive predictive value (PPV) of 46%, and a negative predictive value (NPV) of 90%. …”
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Using radiomics model for predicting extraprostatic extension with PSMA PET/CT studies: a comparative study with the Mehralivand grading system by Linjie Bian, Fanxuan Liu, Yige Peng, Xinyu Liu, Panli Li, Qiufang Liu, Lei Bi, Shaoli Song

“…Key performance metrics, including the area under the curve (AUC), sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV), were reported. …”
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The Role of Urine Liver Fatty Acid Binding Protein in Early Detection of Acute Kidney Injury in Septic Patient by Adrian Hartomuljono, Andi Salahuddin, Hisbullah Amin, Syafruddin Gaus, Haizah Nurdin, Faisal Muchtar, Evan Kristiono

“…The sensitivity value of uL-FABP was 95.2% and the specificity was 54.5%, positive predictive value was 57.1% and negative predictive value was 94.7% and area under the curve was 0.92. …”
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Development of a Risk Score to Aid With the Diagnosis of Infections After Spinal Cord Injury: Protocol for a Retrospective Cohort Study by Felicia Skelton, Larissa Grigoryan, Joann Pan, Ashley Collazo, Barbara Trautner

“…For aim 2, we hypothesize that pyuria, heart rate, and temperature measurements will have a high positive predictive value for clinically meaningful UTI. …”
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