Loss of anti-spike antibodies following mRNA vaccination for COVID-19 among patients with multiple myeloma.

BACKGROUND: Multiple myeloma (MM) patients have variable responses to mRNA vaccination to COVID-19. Little is known regarding their vaccine-induced antibody levels over time. METHODS: We monitored spike IgG antibody levels over 24 weeks among a subset of 18 MM patients who showed a full response after two mRNA vaccinations. RESULTS: MM patients had a more rapid decline in antibody levels as compared to eight healthy controls, with power law half-lives of 72 days (vs. 107 days) and exponential half-lives of 37 days (vs. 51 days). The patients with longer SARS-CoV-2 antibody half-lives were more likely to have undetectable monoclonal protein than those with shorter half-lives, suggesting better disease control may correlate with longer duration of vaccine-induced antibodies. Regardless, by 16 weeks post-second dose of mRNA vaccination, the majority of patients had antibody levels below 250 binding arbitrary units per milliliter, which would be unlikely to contribute to preventing COVID-19. CONCLUSIONS: Thus, even MM patients who respond adequately to vaccination are likely to require more frequent booster doses than the general population.

Auxiliary signal-guided knowledge encoder-decoder for medical report generation.

Medical reports have significant clinical value to radiologists and specialists, especially during a pandemic like COVID. However, beyond the common difficulties faced in the natural image captioning, medical report generation specifically requires the model to describe a medical image with a fine-grained and semantic-coherence paragraph that should satisfy both medical commonsense and logic. Previous works generally extract the global image features and attempt to generate a paragraph that is similar to referenced reports; however, this approach has two limitations. Firstly, the regions of primary interest to radiologists are usually located in a small area of the global image, meaning that the remainder parts of the image could be considered as irrelevant noise in the training procedure. Secondly, there are many similar sentences used in each medical report to describe the normal regions of the image, which causes serious data bias. This deviation is likely to teach models to generate these inessential sentences on a regular basis. To address these problems, we propose an Auxiliary Signal-Guided Knowledge Encoder-Decoder (ASGK) to mimic radiologists' working patterns. Specifically, the auxiliary patches are explored to expand the widely used visual patch features before fed to the Transformer encoder, while the external linguistic signals help the decoder better master prior knowledge during the pre-training process. Our approach performs well on common benchmarks, including CX-CHR, IU X-Ray, and COVID-19 CT Report dataset (COV-CTR), demonstrating combining auxiliary signals with transformer architecture can bring a significant improvement in terms of medical report generation. The experimental results confirm that auxiliary signals driven Transformer-based models are with solid capabilities to outperform previous approaches on both medical terminology classification and paragraph generation metrics.

Self-managed weight loss by smart body fat scales ameliorates obesity-related body composition during the COVID-19 pandemic: A follow-up study in Chinese population

Background Since 2020, longer stay-at-home time in response to the coronavirus disease 2019 (COVID-19) pandemic has changed the weight-related behaviors of Chinese population. Objectives To explore the demographic and basic characteristics of body fat scale users and to investigate the changes in obesity-related body composition of overweight and obese users during COVID-19. Further, we analyzed the factors associated with successful weight loss and improved body composition changes in overweight and obese people. Methods The study included 107,419 Chinese adults registered in the smart app connecting to the body fat scale in 2020 to describe the demographic characteristics of body fat scale users by Unpaired Student’s t-test and Chi-Square test. Subsequently, overweight and obese participants with body mass index (BMI) of more than 24 kg/m2 were screened to investigate the independent factors associated with effective weight loss and improved body composition changes by multivariable logistic regression analyses. Results During the pandemic, the number of body fat scale users increased markedly compared with pre-pandemic. Over half of the participants were women and with normal baseline BMI. Based on BMI classification, multivariable logistic regressions showed that age, gender, measurement frequency classification, baseline BMI, visceral adipose index and skeletal muscle rate were associated with weight loss and fat loss in the overweight and obese population, with the high-frequency measurement being the most important factor for effective weight and fat loss. In the population with normal BMI obesity, younger age was the most significant factor for effective fat loss. Conclusion During the COVID-19 pandemic, participation in self-monitored weight loss increased markedly compared with pre-pandemic, and women accounted for the majority. We found that many overweight and obese participants achieved weight loss goals by smart body fat scales, and the effectiveness of weight and fat loss was greater in obese participants than in overweight participants, both based on BMI and PBF classification. In addition, promoting the usage of smart body fat scales could contribute to more effective weight and fat loss in the overweight and obese population based on BMI classification. However, in the population with normal BMI obesity, young subjects might be easier to successfully lose fat compared with the elder. Digital self-management by smart body fat scales could become a promising approach for the obese population with high BMI to lose weight and keep healthy.

Healthy Community-Life Circle Planning Combining Objective Measurement and Subjective Evaluation: Theoretical and Empirical Research

Background: The world faces vast health challenges, and urban residents living in high-density areas have even greater demand for healthy lifestyles. Methods: Based on the data of points of interest, a field survey, and an interview, we explored the healthy community-life circle in the downtown area of Chengdu, China from two perspectives: objective measurement and subjective perception of residents. We evaluated the coverage rate and convenience in accessing eight types of health service facilities within a 15-min walk using linear and logistics regression models to explore the degree of resident satisfaction with facilities and influencing factors. Results: Results showed significant differences in coverage rates between different districts. The overall convenience in accessing health service facilities decreased gradually from the city center to the outskirts. The social environment, the layout of health service facilities, and residents’ travel habits were related to health service facility satisfaction. Results also showed significant differences in various facilities’ accessibility satisfaction between objective measurement and residents’ perception measurement. Compared with subjective measurement, the objective measurements of accessibility for sports venues (objectively measured average minus perceived average: −1.310), sports zones (−0.740), and specialized hospitals (−1.081) were lower;those for community hospitals (0.095), clinics (1.025), and pharmacies (0.765) were higher;and facility accessibility measured by subjective perception had a more significant impact on health facility satisfaction. Pharmacies (OR: 1.932) and community hospitals (OR: 1.751) had the largest impact among the eight types of facilities. Conclusion: This study proposed to construct a healthy community-life circle with a category and hierarchy system.

Response to mRNA vaccination for COVID-19 among patients with multiple myeloma.

Multiple myeloma (MM) patients are at higher risk for severe COVID-19. Their mRNA vaccination response against SARS-CoV-2 is unknown. Thus, we analyzed responses to mRNA vaccination against COVID-19 among these patients. Using an ELISA-based assay that detects IgG antibodies to SARS-CoV-2 spike protein, we determined serum antibody levels prior to immunization and 12-21 and 14-21 days following the first and second vaccinations, respectively, with mRNA-1273 (Moderna) or BNT162b2 (Pfizer/BioNTech) among 103 MM patients (96 and 7 with active and smoldering disease, respectively). We stratified patients into clinically relevant responders (>250 IU/mL), partial responders (50-250 IU/mL, which was above pre-COVID-19 background), and nonresponders (<50 IU/mL). Smoldering MM patients responded better than those with active disease. Only 45% of active MM patients developed an adequate response, while 22% had a partial response. Lower spike antibody levels were associated with older age, impaired renal function, low lymphocyte counts, reduced uninvolved immunoglobulin levels, > second line of treatment, and among those not in complete remission. Patients who received mRNA-1273 vaccine had higher anti-spike antibody levels than those who were vaccinated with BNT162b2. Thus, most MM patients have impaired responses to mRNA vaccination against COVID-19, and specific clinical and myeloma-related characteristics predict vaccine responsiveness.