Background: Severe acute respiratory syndrome coronavirus 2 has caused a worldwide pandemic since late 2019. Strict policies for timely isolation and treatment can help reduce the spread of coronavirus disease 2019 (COVID-19).We aimed to investigate whether a shorter symptom onset to admission time could improve outcomes of COVID-19 patients and provide an effective strategy for COVID-19 control.Methods: A systematic review and meta-analysis were performed to identify studies published between December 1, 2019 and April 15, 2020. Additionally, clinical data of COVID-19 patients diagnosed between January 20 and February 20, 2020 at the First Affiliated Hospital of the University of Science and Technology of China were retrospectively analyzed. The symptom onset to admission time and severity of illness in patients with COVID-19 were used as effect measures. Propensity score matching was applied to adjust for confounding factors in the retrospective study. The random effects model was used to analyze the heterogeneity across studies. Categorical data were compared using the Fisher's exact test. We compared the differences in laboratory characteristic vary times using a two-way nonparametric, Scheirer-Ray-Hare test. P < 0·05 was considered statistically significant.Findings: Eleven studies including 2503 cases were finally enrolled in this meta-analysis. Among which, 500 cases were combined with adverse outcomes: 245 deaths, 36 intensive care unit admissions, and 219 with severe disease. Patients with adverse outcomes had a longer symptom onset to admission time (I 2 =39%, mean difference=0·88, 95% confidence interval=0·47–1·30).Interpretation: Shortening the symptom onset to admission time may help reduce the possibility of mild patients with COVID-19 progressing to severe illness.Funding Statement: The study was funded by the Natural Science Foundation Project of Guangdong Province, China, (No.2018A030313618), and the Postdoctoral Science Foundation of China (Grant No. 2019M663260 & 2020T130148ZX).Declaration of Interests: All authors declare that they have no conflicts of interest.Ethics Approval Statement: This study was approved by the Research Ethics Commission of the First Affiliated Hospital of the University of Science and Technology of China (approval no. 2020-P-018). The requirement for informed consent was waived because it was a retrospective study, and the patients could not be identified.
BACKGROUND Facial biometric data, despite commercial value, poses significant privacy and security concerns. OBJECTIVE To address these concerns and support auxiliary diagnoses, we developed Digital FaceDefender, an AI-driven solution. METHODS To ensure privacy protection, we generated a diverse set of virtual Asian-face avatars representing both genders, spanning ages from 5 to 85 years in 10-year increments, utilizing 70,000 facial images and 13,061 Asian faces images. Landmark data were separately extracted from both the preprocessed patient images and the avatar images to accurately delineate the eye region. Affine transformations were applied to align the eye regions for image fusion, followed by color correction and Gaussian blur to enhance the quality of the finally fused images. For auxiliary diagnosis, we established 95% confidence intervals (CIs) for pixel distances within the eye region on a cohort of 1,163 individuals, serving as diagnostic benchmarks. Reidentification risks were assessed using ArcFace on 2,500 Detailed Expression Capture and Animation (DECA)-reconstructed images. Finally, Cohen’s Kappa analyses, conducted on 114 individuals, were used to evaluate the agreement between these diagnostic benchmarks and ophthalmologists' assessments. RESULTS Compared to traditional method, Digital FaceDefender significantly enhances privacy protection while maintaining essential ocular diagnostic features. Similarity score and Rank-1 accuracy analyses further confirm its efficacy in minimiznig reidentification risks across various facial poses. The Cohen's Kappa results indicate excellent agreement between the developed diagnostic benchmarks and ophthalmologists' assessments. The convenient Digital FaceDefender platform is established and accessible. CONCLUSIONS In summary, Digital FaceDefender offers a robust solution for safeguarding privacy while supporting auxiliary diagnoses in ocular disease.
Biometric data extracted from facial images holds significant commercial value, yet raises substantial security concerns. Inspired by the discussions of Yang et al. and Meeus et al. in their respective publications in Nature Medicine (2023), which discuss the effectiveness of digital masks (DM) in preserving patients' privacy, we introduce Digital FaceDefender (Digital FD) as an innovative strategy aimed not only at safeguarding patient privacy but also at facilitating auxiliary diagnosis. Following the generation of Asian-face virtual avatars, 52 landmarks from bothvirtual avatars and patients were captured for subsequent image fusion using Google's MediaPipe library. Affine Transformation of the Eye Region between patients and avatars was performed to create preliminary fusion images, followed by color correction and Gaussian blur to enhance final fusion effects. Verification experiments employing ArcFace and DECA methodologies were conducted on a sample of 50 individuals, each represented by five images sourced from the CASIA-FaceV5 dataset. Furthermore, two auxiliary diagnostics models were constructed using a dataset comprising 1163 healthy individuals. Utilizing the Digital FD framework, the Digital FD platform was established and made accessible. In contrast to conventional digital masks characterized by extensive coverage, Digital FD offers a natural aesthetic that not only safeguards patients' privacy but also fosters empathy between healthcare providers and patients, concurrently facilitating auxiliary diagnoses. Additionally, the results of the similarity score and Rank-1 accuracy analysis indicated a reduced likelihood of reidentification when employing Digital FD. In summary, our findings exhibit the efficacy of Digital FD in preserving patients' privacy and facilitating auxiliary diagnoses.Funding: Our research was partially supported by National Natural Science Foundation of China grants No.12231017, 72171216, 71921001, and 71991474, and Innovative development funds of Anhui Province Federation of Social Sciences (No.2022CX081).Declaration of Interest: The authors declare no competing interests.Ethical Approval: The research protocol and ethical review process for this study received approval from the Institutional Review Board/Ethics Committee of the Fourth Affiliated Hospital of Harbin Medical University (2023-Ethics Review-54). Informed consent was obtained from all individuals participating in the study.
Patients with severe COVID-19 are more likely to develop adverse outcomes with a huge medical burden. We aimed to investigate whether a shorter symptom onset to admission time (SOAT) could improve outcomes of COVID-19 patients.
Treating patients with COVID-19 is expensive, thus it is essential to identify factors on admission associated with hospital length of stay (LOS) and provide a risk assessment for clinical treatment. To address this, we conduct a retrospective study, which involved patients with laboratory-confirmed COVID-19 infection in Hefei, China and being discharged between January 20 2020 and March 16 2020. Demographic information, clinical treatment, and laboratory data for the participants were extracted from medical records. A prolonged LOS was defined as equal to or greater than the median length of hospitable stay. The median LOS for the 75 patients was 17 days (IQR 13-22). We used univariable and multivariable logistic regressions to explore the risk factors associated with a prolonged hospital LOS. Adjusted odds ratios (aORs) and 95% confidence intervals (CIs) were estimated. The median age of the 75 patients was 47 years. Approximately 75% of the patients had mild or general disease. The univariate logistic regression model showed that female sex and having a fever on admission were significantly associated with longer duration of hospitalization. The multivariate logistic regression model enhances these associations. Odds of a prolonged LOS were associated with male sex (aOR 0.19, 95% CI 0.05-0.63, p = 0.01), having fever on admission (aOR 8.27, 95% CI 1.47-72.16, p = 0.028) and pre-existing chronic kidney or liver disease (aOR 13.73 95% CI 1.95-145.4, p = 0.015) as well as each 1-unit increase in creatinine level (aOR 0.94, 95% CI 0.9-0.98, p = 0.007). We also found that a prolonged LOS was associated with increased creatinine levels in patients with chronic kidney or liver disease (p < 0.001). In conclusion, female sex, fever, chronic kidney or liver disease before admission and increasing creatinine levels were associated with prolonged LOS in patients with COVID-19.
Abstract Background The sudden outbreaking of COVID-19 worldwide has brought into sharp increased burden of economic and treatment in worldwide. All confirmed patients with different severity not only share the limited healthcare systems simultaneously but increase the risk of cross-infection among patients and health care workers. Hence, effective separation of critical COVID-19 patients from the common COVID-19 will be the key to success for ensuring critical patients to obtain treatment priorities and avoiding cross-infections in the hospital. Methods: A total of 105 patients with complete medical records were collected, including 84 blood samples of patients who confirmed in the First Affiliated Hospital of the University of Science and Technology at Anhui and 25 blood samples of patients in two hospitals at Shantou. Series of machine learning tools were introduced to explore and validate the most significant laboratory characteristics. Meanwhile, we compared it to three current popular assessment systems for pneumonia by using three methods, including the AUC index, NRI index and the net benefit. Results: We identified four significant potential laboratory characteristics for the classification of critical patients, including C-reactive protein, albumin, globulin, and sodium levels. The results also suggested the accurate and prediction efficacy of these selected indicators are the highest. Conclusions In conclusion, four easily available and low-cost laboratory characteristics appear to be import predictors of classification in critical patients after hospital admission. They guide therapeutic options and help clinicians make clinical decisions. Hence, we believe that such classification is essential for a more rational allocation scarce medical resource.
Background: Epidemiological and clinical characteristics of patients with COVID-19 have been reported. Treating patients with COVID-19 is high cost, so investigating the risk factors for prolonged hospital length of stay (LOS) is useful. Knowing these risk factors could help identify COVID-19 patients with a poor prognosis early and thus improve outcomes for these patients. Methods: This retrospective study involved patients with COVID-19 laboratory-confirmed from the infectious Diseases Department of the First Affiliated Hospital of the University of Scienc and Technology of China, Hefei (discharged from January 20 to March 16, 2020). Demographic, clinical treatment, and laboratory data were extracted from medical records. Prolonged LOS was defined as equal to or greater than the median inhospitable stay time. We used univariable and multivariable logistic regression to explore risk factors associated with prolonged hospital LOS. Adjusted odds ratios (aORs) and 95% confidence intervals (CIs) were estimated. Results: The median age of the 75 patients was 47 (interquartile range 31-54) years (range 5 to 91), and 57% were male. About 75% of the patients had mild or general disease. Odds of prolonged LOS was associated with female sex (aOR 0.19, 95%CI 0.05-0.63, p =0.01), fever (aOR 8.27, 95%CI 1.47-72.16, p = 0.028), and chronic kidney or liver disease on admission (aOR 13.73, 95%CI 1.95-145.4, p =0.015) as well as each 1-unit increase in creatinine level (aOR 0.94, 95% CI 0.9-0.98, p =0.007). Conclusions: Female sex, fever, chronic kidney or liver disease before admission and increasing creatinine level were associated with prolonged LOS in patients with COVID-19. Future research should evaluate and support interventions and treatments to improve outcomes for these high-risk groups.Funding Statement: This study received the following funding: Natural Science Foundation of China (11801540), Natural Science Foundation of Guangdong (2017A030310572) and Fundamental Research Funds for the Central Universities (WK2040170015, WK2040000016), the Science and Technology Planning Project of Guangdong Province (2017A010101030), the third Medical technology projects of Shantou City in 2018.Declaration of Interests: The authors declare no competing interests.Ethics Approval Statement: The study was approved by the Research Ethics Commission of the First Affiliated Hospital of the University of Science and Technology of China (2020-P-018) and the requirement for informed consent was waived by the ethics commission.
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