OBJECTIVE: To evaluate the effect and safety of Chinese medicine (CM) Fuzheng Huazhuo Decoction (FHD) in treating patients with coronavirus disease 2019 (COVID-19) who persistently tested positive for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). METHODS: This retrospective cohort study was conducted at Shanghai New International Expo Center shelter hospital in China between April 1 and May 30, 2022. Patients diagnosed as COVID-19 with persistently positive SARS-CoV-2 reverse transcription-polymerase chain reaction (RT-PCR) test results for ⩾8 days after diagnosis were enrolled. Patients in the control group received conventional Western medicine (WM) treatment, while those in the FHD group received conventional WM plus FHD for at least 3 days. The primary outcome was viral clearance time. Secondary outcomes included negative conversion rate within 14 days, length of hospital stay, cycle threshold (Ct) values of the open reading frame 1ab (ORF1ab) and nucleocapsid protein (N) genes, and incidence of new-onset symptoms during hospitalization. Adverse events (AEs) that occurred during the study period were recorded. RESULTS: A total of 1,765 eligible patients were enrolled in this study (546 in the FHD group and 1,219 in the control group). Compared with the control group, patients receiving FHD treatment showed shorter viral clearance time for nucleic acids [hazard ratio (HR): 1.500, 95% confidence interval (CI): 1.353-1.664, P<0.001] and hospital stays (HR: 1.371, 95% CI: 1.238-1.519, P<0.001), and a higher negative conversion rate within 14 days (96.2% vs. 82.6%, P<0.001). The incidence of new-onset symptoms was 59.5% in the FHD group, similar to 57.8% in the control group (P>0.05). The Ct values of ORF1ab and N genes increased more rapidly over time in the FHD group than those in the control group post-randomization (ORF1ab gene: β =0.436±0.053, P<0.001; N gene: β =0.415 ±0.053, P<0.001). The incidence of AEs in the FHD group was lower than that in the control group (24.2% vs. 35.4%, P<0.001). No serious AEs were observed. CONCLUSION FHD was effective and safe for patients with persistently positive SARS-CoV-2 PCR tests. (Registration No. ChiCTR2200063956).
Humans ; Drugs, Chinese Herbal/adverse effects* ; Retrospective Studies ; Male ; Female ; Middle Aged ; COVID-19 Drug Treatment ; SARS-CoV-2/drug effects* ; COVID-19/virology* ; Adult ; Aged ; Treatment Outcome

Objective:To screen the evidence related to perioperative pain management in thoracic surgery and summarize the best evidence, so as to provide evidence-based basis for clinical nursing practice.Methods:Databases such as Cochrane Library, International Association for the Study of Pain, American Pain Society, Wanfang Database, and China National Knowledge Infrastructure were systematically searched for guidelines, clinical decisions, evidence summaries, best practices, systematic reviews, and expert consensus related to perioperative pain management in thoracic surgery patients. The retrieval time limit was from the establishment of the database to December 31, 2023. Two researchers conducted quality evaluation and evidence extraction.Results:A total of 12 articles were included, including 6 guidelines, 4 systematic reviews, and 2 expert consensuses. Thirty pieces of evidence covering six aspects including organizational management, planning, education, assessment, implementation, and evaluation were summarized.Conclusions:The best evidence summarized in this study can provide evidence-based basis for standardizing the perioperative pain management of thoracic surgery patients.

Objective:To develop and validate a combined model integrating radiomics, dosiomics, and clinical parameters based on CT simulation and dosimetric images in order to predict the occurrence of radiation pneumonitis (RP) in patients with non-small cell lung cancer (NSCLC).Methods:A retrospective study was conducted on the clinic data of 143 NSCLC patients who received radiotherapy at the Affiliated Hospital of Jining Medical University from January 2016 to December 2022. Patients were randomly stratified into a training group ( n = 100) and an internal validation group ( n = 43) at a 7∶3 ratio. Moreover, clinic data were collected from 34 NSCLC patients who received radiotherapy at the Jining Cancer Hospital between January 2019 and December 2022 as an external validation group. All three groups (the training group, internal validation, and external validation groups) were further categorized into two groups based on the RP severity (i.e., RP ≥ grade 2 and RP < grade 2). Their radiotherapy dose, CT simulation, and 3D dose distribution images were collected. Then, the total lung minus planning target volume (TL-PTV) was defined as the region of interest (ROI) for radiomics and dosiomic feature extraction, followed by feature dimensionality reduction. Consequently, key features associated with RP were determined. Four predictive models were developed using machine learning approaches (especially multilayer perceptron, MLP): a clinical model (CM), a radiomics model (RM), a dosiomics model (DM), and a radiomics and dosiomics nomogram (RDN), with a nomogram subsequently constructed. Ultimately, the performance and clinical feasibility of these models were assessed using receiver operating characteristic (ROC), area under the curve (AUC), and decision curve analysis (DCA). Results:A total of 1 834 radiomic features and 1 834 dosiomic features were extracted. Using the occurrence of RP ≥ grade 2 as the marker variable, 14 radiomic features, 15 dosiomic features, and three clinical features were selected from the training group to construct the prediction models (CM, RM, DM, and RDN). The performance and generalizability of these models were subsequently validated in both the internal validation and external validation groups. Specifically, the RDN exhibited AUCs of 0.915 (95% CI: 0.852-0.978), 0.879 (95% CI: 0.777-0.982), and 0.838 (95% CI: 0.701-0.975) in the three groups, respectively. A nomogram was established for RDN by integrating the radiomics score (R-score), dosiomics score (D-score), mean lung dose (MLD), V20, and V30. This nomogram allowed for individualized risk estimation of RP and facilitated personalized radiotherapy planning. Conclusions:The RDN model that is developed based on CT simulation and 3D dose distribution images and integrates radiomics, dosiomics, and clinical features can effectively predict the RP risk of NSCLC patients. The integration of multidimensional data contributes to the formation of the optimal predictive model, offering guidance for clinicians.

Objective:To screen the evidence related to perioperative pain management in thoracic surgery and summarize the best evidence, so as to provide evidence-based basis for clinical nursing practice.Methods:Databases such as Cochrane Library, International Association for the Study of Pain, American Pain Society, Wanfang Database, and China National Knowledge Infrastructure were systematically searched for guidelines, clinical decisions, evidence summaries, best practices, systematic reviews, and expert consensus related to perioperative pain management in thoracic surgery patients. The retrieval time limit was from the establishment of the database to December 31, 2023. Two researchers conducted quality evaluation and evidence extraction.Results:A total of 12 articles were included, including 6 guidelines, 4 systematic reviews, and 2 expert consensuses. Thirty pieces of evidence covering six aspects including organizational management, planning, education, assessment, implementation, and evaluation were summarized.Conclusions:The best evidence summarized in this study can provide evidence-based basis for standardizing the perioperative pain management of thoracic surgery patients.

Objective:To explore the mediating role of self-perceived aging in the relationship between perceived social support and self-efficacy for exercise in aged patients undergoing surgery for lung cancer and provide a basis for formulating relevant clinical intervention strategies.Methods:Totally 220 aged lung cancer patients who underwent surgery and were hospitalized at the Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, from April to June 2024 were recruited by convenience sampling. Patients completed a demographic questionnaire, the Self-Efficacy for Exercise (SEE) , the Ageing Perceptions Questionnaire (B-APQ) , and the Perceived Social Support Scale (PSSS) . The mediation effect of self-perceived aging between perceived social support and self-efficacy for exercise was analyzed using Model 4 in the SPSS Process macro.Results:A total of 220 questionnaires were distributed, and 207 valid questionnaires were returned, with an effective recovery rate of 94.09%. The total score for B-APQ was (46.93±11.35) , the SEE score was (44.12±12.83) , and the PSSS score was (53.18±13.53) . Perceived social support had a direct effect on self-efficacy for exercise (effect value: 0.278; P<0.01) . Self-perceived aging played a partial mediating role between perceived social support and self-efficacy for exercise, with a mediation effect value of 0.138 ( P<0.01) , accounting for 33.17% of the total effect (0.138/0.416) . Conclusions:Perceived social support directly influences self-efficacy for exercise in aged patients undergoing surgery for lung cancer and also exerts an indirect effect through self-perceived aging. It is recommended that healthcare providers guide these patients to establish a positive perception of aging while focusing on enhancing their social support levels to improve their self-efficacy for exercise and promote recovery.

Objective:To explore the mediating role of self-perceived aging in the relationship between perceived social support and self-efficacy for exercise in aged patients undergoing surgery for lung cancer and provide a basis for formulating relevant clinical intervention strategies.Methods:Totally 220 aged lung cancer patients who underwent surgery and were hospitalized at the Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, from April to June 2024 were recruited by convenience sampling. Patients completed a demographic questionnaire, the Self-Efficacy for Exercise (SEE) , the Ageing Perceptions Questionnaire (B-APQ) , and the Perceived Social Support Scale (PSSS) . The mediation effect of self-perceived aging between perceived social support and self-efficacy for exercise was analyzed using Model 4 in the SPSS Process macro.Results:A total of 220 questionnaires were distributed, and 207 valid questionnaires were returned, with an effective recovery rate of 94.09%. The total score for B-APQ was (46.93±11.35) , the SEE score was (44.12±12.83) , and the PSSS score was (53.18±13.53) . Perceived social support had a direct effect on self-efficacy for exercise (effect value: 0.278; P<0.01) . Self-perceived aging played a partial mediating role between perceived social support and self-efficacy for exercise, with a mediation effect value of 0.138 ( P<0.01) , accounting for 33.17% of the total effect (0.138/0.416) . Conclusions:Perceived social support directly influences self-efficacy for exercise in aged patients undergoing surgery for lung cancer and also exerts an indirect effect through self-perceived aging. It is recommended that healthcare providers guide these patients to establish a positive perception of aging while focusing on enhancing their social support levels to improve their self-efficacy for exercise and promote recovery.

Objective:To develop and validate a combined model integrating radiomics, dosiomics, and clinical parameters based on CT simulation and dosimetric images in order to predict the occurrence of radiation pneumonitis (RP) in patients with non-small cell lung cancer (NSCLC).Methods:A retrospective study was conducted on the clinic data of 143 NSCLC patients who received radiotherapy at the Affiliated Hospital of Jining Medical University from January 2016 to December 2022. Patients were randomly stratified into a training group ( n = 100) and an internal validation group ( n = 43) at a 7∶3 ratio. Moreover, clinic data were collected from 34 NSCLC patients who received radiotherapy at the Jining Cancer Hospital between January 2019 and December 2022 as an external validation group. All three groups (the training group, internal validation, and external validation groups) were further categorized into two groups based on the RP severity (i.e., RP ≥ grade 2 and RP < grade 2). Their radiotherapy dose, CT simulation, and 3D dose distribution images were collected. Then, the total lung minus planning target volume (TL-PTV) was defined as the region of interest (ROI) for radiomics and dosiomic feature extraction, followed by feature dimensionality reduction. Consequently, key features associated with RP were determined. Four predictive models were developed using machine learning approaches (especially multilayer perceptron, MLP): a clinical model (CM), a radiomics model (RM), a dosiomics model (DM), and a radiomics and dosiomics nomogram (RDN), with a nomogram subsequently constructed. Ultimately, the performance and clinical feasibility of these models were assessed using receiver operating characteristic (ROC), area under the curve (AUC), and decision curve analysis (DCA). Results:A total of 1 834 radiomic features and 1 834 dosiomic features were extracted. Using the occurrence of RP ≥ grade 2 as the marker variable, 14 radiomic features, 15 dosiomic features, and three clinical features were selected from the training group to construct the prediction models (CM, RM, DM, and RDN). The performance and generalizability of these models were subsequently validated in both the internal validation and external validation groups. Specifically, the RDN exhibited AUCs of 0.915 (95% CI: 0.852-0.978), 0.879 (95% CI: 0.777-0.982), and 0.838 (95% CI: 0.701-0.975) in the three groups, respectively. A nomogram was established for RDN by integrating the radiomics score (R-score), dosiomics score (D-score), mean lung dose (MLD), V20, and V30. This nomogram allowed for individualized risk estimation of RP and facilitated personalized radiotherapy planning. Conclusions:The RDN model that is developed based on CT simulation and 3D dose distribution images and integrates radiomics, dosiomics, and clinical features can effectively predict the RP risk of NSCLC patients. The integration of multidimensional data contributes to the formation of the optimal predictive model, offering guidance for clinicians.

Objective:To provide references for the health management of thyroid nodules in naval flying personnel by analyzing the ultrasound characteristics of naval flying personnel with thyroid nodules.Methods:A total of 306 naval flying personnel, who were diagnosed as thyroid nodules in yearly health examination in the Third Sanatorium of Air Force Healthcare Center for Special Services Hangzhou from January of 2019 to December of 2021, were selected as the research subjects. They were divided into 3 groups by age (20-29 years, 30-39 years, ≥40 years), 2 groups by flying hours (<3 000 h, ≥3 000 h) and 3 groups by aircraft types (helicopter, transporter, fighter). The characteristics of thyroid nodule ultrasound images were retrospectively analyzed and the size, quantity and classification which defined in Chinese-thyroid imaging reporting and data system (C-TIRADS) of thyroid nodule were compared among the groups of different ages, flying hours, and aircraft types.Results:Among 306 naval flying personnel with thyroid noedules, 280 cases (91.50%) were small nodules (diameter <1 cm), 26 cases (8.50%) were large nodules (diameter ≥1 cm). One hundred and fifty-one cases (49.35%) were single nodules and 155 cases (50.65%) were multiple nodules. There were 135 cases (44.12%) with C-TIRADS grade 2 thyroid nodules, 158 cases (51.63%) with C-TIRADS grade 3 nodules, and 13 cases (4.25%) with C-TIRADS grade 4 nodules. There were significant differences in the size, number, classification of composition ratio of thyroid nodules among different age groups ( χ2=8.86, 5.94, 46.20, P=0.013, 0.051,<0.001). There were significant differences in the size and classification of composition ratio of thyroid nodules between different flying hours groups ( χ2=16.91, 24.35, both P<0.001). The proportion of C-TIRADS grade 4 nodules in the flying hours ≥3 000 h group was higher than that in the <3 000 h group, with a significant difference ( χ2=4.77, P=0.029).There were no significant differences in the size, number, classification of composition ratio of thyroid nodules among different aircraft types groups (all P>0.05). Conclusions:Age and flying hours have effects on size and classification of composition ratio of thyroid nodules in flying personnel, and age also has the effect on quantity. A scientific and systematic follow-up mechanism would be helpful to assess the risk of thyroid cancer and give early warning for the timely intervention.

Objective:To provide references for the health management of thyroid nodules in naval flying personnel by analyzing the ultrasound characteristics of naval flying personnel with thyroid nodules.Methods:A total of 306 naval flying personnel, who were diagnosed as thyroid nodules in yearly health examination in the Third Sanatorium of Air Force Healthcare Center for Special Services Hangzhou from January of 2019 to December of 2021, were selected as the research subjects. They were divided into 3 groups by age (20-29 years, 30-39 years, ≥40 years), 2 groups by flying hours (<3 000 h, ≥3 000 h) and 3 groups by aircraft types (helicopter, transporter, fighter). The characteristics of thyroid nodule ultrasound images were retrospectively analyzed and the size, quantity and classification which defined in Chinese-thyroid imaging reporting and data system (C-TIRADS) of thyroid nodule were compared among the groups of different ages, flying hours, and aircraft types.Results:Among 306 naval flying personnel with thyroid noedules, 280 cases (91.50%) were small nodules (diameter <1 cm), 26 cases (8.50%) were large nodules (diameter ≥1 cm). One hundred and fifty-one cases (49.35%) were single nodules and 155 cases (50.65%) were multiple nodules. There were 135 cases (44.12%) with C-TIRADS grade 2 thyroid nodules, 158 cases (51.63%) with C-TIRADS grade 3 nodules, and 13 cases (4.25%) with C-TIRADS grade 4 nodules. There were significant differences in the size, number, classification of composition ratio of thyroid nodules among different age groups ( χ2=8.86, 5.94, 46.20, P=0.013, 0.051,<0.001). There were significant differences in the size and classification of composition ratio of thyroid nodules between different flying hours groups ( χ2=16.91, 24.35, both P<0.001). The proportion of C-TIRADS grade 4 nodules in the flying hours ≥3 000 h group was higher than that in the <3 000 h group, with a significant difference ( χ2=4.77, P=0.029).There were no significant differences in the size, number, classification of composition ratio of thyroid nodules among different aircraft types groups (all P>0.05). Conclusions:Age and flying hours have effects on size and classification of composition ratio of thyroid nodules in flying personnel, and age also has the effect on quantity. A scientific and systematic follow-up mechanism would be helpful to assess the risk of thyroid cancer and give early warning for the timely intervention.

COVID-19 has been prevalent for three years. The virulence of SARS-CoV-2 is weaken as it mutates continuously. However, elderly patients, especially those with underlying diseases, are still at high risk of developing severe infections. With the continuous study of the molecular structure and pathogenic mechanism of SARS-CoV-2, antiviral drugs for COVID-19 have been successively marketed, and these anti-SARS-CoV-2 drugs can effectively reduce the severe rate and mortality of elderly patients. This article reviews the mechanism, clinical medication regimens, drug interactions and adverse reactions of five small molecule antiviral drugs currently approved for marketing in China, so as to provide advice for the clinical rational use of anti-SARS-CoV-2 in the elderly.