American ginseng with different processing methods ameliorate immunosuppression induced by cyclophosphamide in mice via the MAPK signaling pathways.

This study aimed to clarify the effects of two processed forms of American ginseng (Panax quinquefolius L.) on immunosuppression caused by cyclophosphamide (CTX) in mice. In the CTX-induced immunosuppressive model, mice were given either steamed American ginseng (American ginseng red, AGR) or raw American ginseng (American ginseng soft branch, AGS) by intragastric administration. Serum and spleen tissues were collected, and the pathological changes in mice spleens were observed by conventional HE staining. The expression levels of cytokines were detected by ELISA, and the apoptosis of splenic cells was determined by western blotting. The results showed that AGR and AGS could relieve CTX-induced immunosuppression through the enhanced immune organ index, improved cell-mediated immune response, increased serum levels of cytokines (TNF-α, IFN-γ, and IL-2) and immunoglobulins (IgG, IgA, and IgM), as well as macrophage activities including carbon clearance and phagocytic index. AGR and AGS downregulated the expression of BAX and elevated the expression of Bcl-2, p-P38, p-JNK, and p-ERK in the spleens of CTX-injected animals. Compared to AGS, AGR significantly improved the number of CD4+CD8-T lymphocytes, the spleen index, and serum levels of IgA, IgG, TNF-α, and IFN-γ. The expression of the ERK/MAPK pathway was markedly increased. These findings support the hypothesis that AGR and AGS are effective immunomodulatory agents capable of preventing immune system hypofunction. Future research may investigate the exact mechanism to rule out any unforeseen effects of AGR and AGS.

Factors Influencing the Uptake of Seasonal Influenza Vaccination among Community-Dwelling Older Adults during COVID-19: A Mixed Methods Study.

Background: Despite making the influenza vaccine accessible and affordable, vaccination rates remained low among community-dwelling older adults. Therefore, this study aimed to explore the factors influencing vaccine uptake and the impact of COVID-19 on vaccine uptake among community-dwelling older adults in Singapore. Methods: A mixed methods study involving a survey and semi-structured interviews were conducted between September 2020 and July 2021. Community-dwelling older adults aged ≥ 65 years were recruited from 27 Community Nurse Posts. Data on participants' demographics, health condition(s), vaccination status, attitudes towards influenza infections and vaccinations, willingness to pay, intention for future vaccination and source of information were collected via the survey. Semi-structured interviews were conducted to understand vaccination experiences, key enablers and barriers, and the impact of COVID-19 on vaccine uptake. All interviews were analysed using Braun and Clarke's thematic analysis. Quantitative data were analysed using descriptive statistics, chi-square tests and multinomial logistic regressions. Results: A total of 235 participants completed the survey. Living arrangement was a statistically significant contributing factor for influenza vaccine uptake (ꭓ2= -0.139; p = 0.03). Participants who lived alone were 2.5 times more likely to be vaccinated than those living with others (OR = 2.504, 95% CI: 1.294-4.842, p = 0.006). Avoidance of getting infected (82.5%), avoidance of transmission to others (84.7%), and advice from healthcare professionals to receive vaccination (83.4%) were key enablers, while concerns about possible side effects (41.2%), the effectiveness of the vaccine (42.6%), and not having enough information (48.1%) were barriers. Twenty participants were interviewed. The findings were congruent with the survey results. Five themes were identified as follows: (1) Perceived importance of influenza vaccination, (2) Sphere of influence, (3) Healthcare schemes and medical subsidies, (4) Psychological impediments, and (5) Inconsistent emphases at various touch points. Conclusions: Greater public health efforts are needed to reach out to the larger population of older adults of different living arrangements and those concerned about the possible side effects and effectiveness of the influenza vaccine. Healthcare professionals need to provide more information to address these concerns, especially during COVID-19, to encourage vaccine uptake.

Hematopoietic stem cell transplantation activity in China 2020-2021 during the SARS-CoV-2 pandemic: a report from the Chinese Blood and Marrow Transplantation Registry Group.

Between 2020 and 2021, 31,525 hematopoietic stem cell transplantations (HSCTs) were reported to the Chinese Blood and Marrow Transplantation Registry Group (CBMTRG) throughout mainland China. In this report, we describe the activity and current trends for HSCT in China during the SARS-CoV-2 pandemic. In 2020, a total of 13,415 cases of HSCT were reported from 166 transplant teams, and 75% (10,042 cases) were allogeneic HSCTs. In 2021, a total of 18,110 cases of HSCT were reported from 174 transplant teams, and 70% (12,744 cases) were allogeneic HSCTs. Haploidentical donor (HID) transplantation accounted for 63% (7977 cases) of allogeneic HSCTs in 2021. The most common indications for allogeneic HSCT for malignant disease were acute myeloid leukemia (AML) (37%) and acute lymphoblastic leukemia (ALL) (23%), and the largest proportion of nonmalignant disease comprised aplastic anemia (AA) (13%). The PB stem cell source accounted for 41% of HIDs and 75% of MSDs. The BuCy-based regimen (57%) was the most popular conditioning regimen for allogeneic HSCT, followed by the BuFlu-based regimen (28%) and TBI-based regimen (11%). This survey provides comprehensive information about the current activities and might benefit clinical physicians' decision planning for HSCT.

Impact of the COVID-19 pandemic on cardiac implantable electronic device implantation in China: Insights from 2 years of changing pandemic conditions.

Background: A substantial reduction in the number of cardiac implantable electronic device (CIED) implantation was reported in the early stages of the COVID-19 pandemic. None of the studies have yet explored changes in CIED implantation during the following pandemic. Objective: To explore changes in CIED implantation during the COVID-19 pandemic from 2020 to 2021. Methods: From 2019 to 2021, 177,263 patients undergone CIED implantation from 1,227 hospitals in China were included in the analysis. Generalized linear models measured the differences in CIED implantation in different periods. The relationship between changes in CIED implantation and COVID-19 cases was assessed by simple linear regression models. Results: Compared with the pre-COVID-19 period, the monthly CIED implantation decreased by 17.67% (95% CI: 16.62-18.72%, p < 0.001) in 2020. In 2021, the monthly number of CIED implantation increased by 15.60% (95% CI: 14.34-16.85%, p < 0.001) compared with 2020. For every 10-fold increase in the number of COVID-19 cases, the monthly number of pacemaker implantation decreased by 429 in 2021, while it decreased by 676 in 2020. The proportion of CIED implantation in secondary medical centers increased from 52.84% in 2019 to 56.77% in 2021 (p < 0.001). For every 10-fold increase in regional accumulated COVID-19 cases, the proportion of CIED implantation in secondary centers increased by 6.43% (95% CI: 0.47-12.39%, p = 0.036). Conclusion: The impact of the COVID-19 pandemic on the number of CIED implantation is diminishing in China. Improving the ability of secondary medical centers to undertake more operations may be a critical way to relieve the strain on healthcare resources during the epidemic.

Impact of the COVID-19 pandemic on cardiac implantable electronic device implantation in China: Insights from 2 years of changing pandemic conditions

Background A substantial reduction in the number of cardiac implantable electronic device (CIED) implantation was reported in the early stages of the COVID-19 pandemic. None of the studies have yet explored changes in CIED implantation during the following pandemic. Objective To explore changes in CIED implantation during the COVID-19 pandemic from 2020 to 2021. Methods From 2019 to 2021, 177,263 patients undergone CIED implantation from 1,227 hospitals in China were included in the analysis. Generalized linear models measured the differences in CIED implantation in different periods. The relationship between changes in CIED implantation and COVID-19 cases was assessed by simple linear regression models. Results Compared with the pre-COVID-19 period, the monthly CIED implantation decreased by 17.67% (95% CI: 16.62–18.72%, p < 0.001) in 2020. In 2021, the monthly number of CIED implantation increased by 15.60% (95% CI: 14.34–16.85%, p < 0.001) compared with 2020. For every 10-fold increase in the number of COVID-19 cases, the monthly number of pacemaker implantation decreased by 429 in 2021, while it decreased by 676 in 2020. The proportion of CIED implantation in secondary medical centers increased from 52.84% in 2019 to 56.77% in 2021 (p < 0.001). For every 10-fold increase in regional accumulated COVID-19 cases, the proportion of CIED implantation in secondary centers increased by 6.43% (95% CI: 0.47–12.39%, p = 0.036). Conclusion The impact of the COVID-19 pandemic on the number of CIED implantation is diminishing in China. Improving the ability of secondary medical centers to undertake more operations may be a critical way to relieve the strain on healthcare resources during the epidemic.

Correlation coefficient-directed label-free characterization of native proteins by surface-enhanced Raman spectroscopy.

Investigation of proteins in their native state is the core of proteomics towards better understanding of their structures and functions. Surface-enhanced Raman spectroscopy (SERS) has shown its unique advantages in protein characterization with fingerprint information and high sensitivity, which makes it a promising tool for proteomics. It is still challenging to obtain SERS spectra of proteins in the native state and evaluate the native degree. Here, we constructed 3D physiological hotspots for a label-free dynamic SERS characterization of a native protein with iodide-modified 140 nm Au nanoparticles. We further introduced the correlation coefficient to quantitatively evaluate the variation of the native degree, whose quantitative nature allows us to explicitly investigate the Hofmeister effect on the protein structure. We realized the classification of a protein of SARS-CoV-2 variants in 15 min, which has not been achieved before. This study offers an effective tool for tracking the dynamic structure of proteins and biomedical research.

Induction of Broadly Cross-Reactive Antibody Responses to SARS-CoV-2 Variants by S1 Nanoparticle Vaccines.

Despite the rapid deployment of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) vaccines, the emergence of SARS-CoV-2 variants and reports of their immune evasion characteristics have led to an urgent need for novel vaccines that confer potent cross-protective immunity. In this study, we constructed three different SARS-CoV-2 spike S1-conjugated nanoparticle vaccine candidates that exhibited high structural homogeneity and stability. Notably, these vaccines elicited up to 50-times-higher neutralizing antibody titers than the S1 monomer in mice. Crucially, it was found that the S1-conjugated nanoparticle vaccine could elicit comparable levels of neutralizing antibodies against wild-type or emerging variant SARS-CoV-2, with cross-reactivity to SARS-CoV and Middle East respiratory syndrome coronavirus (MERS-CoV), the effect of which could be further enhanced using our designed nanoparticles. Our results indicate that the S1-conjugated nanoparticles are promising vaccine candidates with the potential to elicit potent and cross-reactive immunity against not only wild-type SARS-CoV-2, but also its variants of concern, variants of interest, and even other pathogenic betacoronaviruses. IMPORTANCE The emergence of SARS-CoV-2 variants led to an urgent demand for a broadly effective vaccine against the threat of variant infection. The spike protein S1-based nanoparticle designed in our study could elicit a comprehensive humoral response toward different SARS-CoV-2 variants of concern and variants of interest and will be helpful to combat COVID-19 globally.

Association of Mannose-Binding Lectin 2 Gene Polymorphism with Tuberculosis Based on Mycobacterium tuberculosis Lineages.

Purpose: Polymorphisms in MBL2 may contribute to the susceptibility to tuberculosis. The aim of the present study was to determine the associations of the polymorphisms of five loci (rs1800450, rs1800451, rs7096206, rs7095891, and rs11003125) in the MBL2 gene with susceptibility to tuberculosis and specific lineages of Mycobacterium tuberculosis causing tuberculosis in the Uyghur population of Xinjiang, China. Methods: From January 2019 to January 2020, we enrolled 170 Uyghur tuberculosis patients as the case group and 147 Uyghur staff with no clinical symptoms as the control group from four designated tuberculosis hospitals in southern Xinjiang, China. The polymorphisms of five loci in MBL2 of human were detected by sequencing. Whole-genome sequencing was applied in 68 M. tuberculosis isolates from the case group and the data were used to perform genealogy analysis. Results: The distributions of allele and genotype frequencies of five loci in MBL2 varied little between the case and control groups and varied little among the groups, including those infected with different lineages of M. tuberculosis and the control (except those of rs11003125), the P values were all >0.05. The distribution of alleles of rs11003125 was statistically different between patients infected with lineages 3 and 4 M. tuberculosis (χ 2=7.037, P=0.008). The C allele and CC genotype of rs11003125 were found to be protective factors against lineage 4 infection when compared to lineage 3 (ORs were 0.190 and 0.158, respectively; 95% confidence intervals were 0.053~0.690 and 0.025~0.999, respectively). Conclusion: Our results suggested that human's susceptibility to tuberculosis is affected both by the host genetic polymorphisms and the lineage of the M. tuberculosis that people were exposed to. However, due to the limitation of the sample size in the present study, larger sample size and more rigorous design should be guaranteed in future studies.

Global Research Status of Multiple Organ Dysfunction Syndrome During 2001-2021: A 20-Year Bibliometric Analysis.

Background: Multiple Organ Dysfunction Syndrome (MODS) is a major cause of high morbidity and mortality among patients in intensive care units (ICU). Although numerous basic and clinical researches on MODS have been conducted, there is still a long way to go to prevent patients from entering this stage. To our knowledge, no bibliometric analyses of MODS have been reported, this study, therefore, was conducted to reveal MODS research status and trends during 2001-2021. Methods: All relevant literature covering MODS during 2001-2021 were extracted from Web of Science. An online analysis platform of literature metrology was used to analyze the publication trends. VOSviewer software was used to collect and analyze the keywords and research hotspots related to MODS. Results: As of July 31, 2021, a total of 994 MODS-related articles from 2001 to 2021 were identified. The United States accounted for the largest number of publications (31.1%), followed by China and Germany, with 186 and 75 publications, respectively. Among all the institutions, the University of Pittsburgh published the most papers related to MODS (21). Critical Care Medicine published the most papers in this field (106). Professor Moore EE, who had the most citation frequency (1847), made great achievements in MODS research. Moreover, analysis of the keywords identified three MODS research hotspot clusters: "mechanism-related research," "clinical research," and "diagnostic research." Conclusions: The United States maintained a top position worldwide and made the most outstanding contribution in the MODS field. In terms of publication, China was next only to the United States, but there was a disproportion between the quantity of publications and citation frequency. The institution University of Pittsburgh and journal Critical Care Medicine represent the highest level of research in this field. During the 20 years from 2001 to 2021, basic MODS research has been in-depth yet progressed relatively slowly recently, but the outbreak of COVID-19 has to some extent set off an upsurge of clinical research in MODS field.

A Meta-Analysis of Accuracy and Sensitivity of CRISPR and Chest CT in COVID‑19 Diagnosis (preprint)

Objective: To clarify the accuracy of clusters of regularly spaced short palindrome repeats (CRISPR) technology and chest CT in the diagnosis of Corona Virus Disease2019(COVID-19). Methods: The term "Corona Virus Disease " "clustered regularly spaced short palindromic repeats" "CRISPR", "chest CT", "sensitivity and specificity" as the subject words or keywords were searched in databases such as Pubmed, Embase, Cochrane Library, Wiley and Scopus and Chinese academic databases (such as CNKI, Wanfang and Chongqing VIP data) for relevant literature on the use of CRISPR technology and chest CT for the diagnosis of COVID-19. Meta-analysis was performed after literature screening, quality assessment and data extraction . Results: A total of 418 articles were retrieved, and 17 articles were finally included. The results showed that the combined sensitivity of CRISPR technology for diagnosing new coronary pneumonia infection was 0.96 [95% CI (0.93, 0.98)], and the combined specificity was 1.00 [95% CI (0.92, 1.00)], the combined positive likelihood ratio is 458.69 [95%CI (11.51, 18280.8)], the combined negative likelihood ratio is 0.04 [95% CI (0.02, 0.07)], the area under the SROC curve is 0.99 [95%CI(0.97,0.99)]. The combined sensitivity of chest CT in diagnosing new coronary pneumonia infection was 0.94 [95%CI (0.83, 0.98)], combined specificity was 0.55 [95% CI (0.22, 0.83)], combined diagnostic odds ratio was 19.90 [95% CI (7.88, 50.25)], the combined positive likelihood ratio is 2.08 [95%CI (1.00, 4.32)], the combined negative likelihood ratio is 0.10 [95% CI (0.05, 0.23)], the area under the SROC curve is 0.91 [95% CI (0.88, 0.93)]. The Deek funnel chart indicates that there is no potential publication bias among the included studies (PCRISPR = 0.03, P chest CT = 0.55). Conclusion: CRISPR technology has a better ability to detect infections in patients with COVID-19, and is better than chest CT in disease diagnosis. CRISPR technology, especially non-SHERLOCK type and multi-target gene detection, can be used to diagnose COVID-19 with higher accuracy ,and can be used for large-scale population screening.

Inflammation-related adverse reactions following vaccination potentially indicate a stronger immune response.

Concerns about vaccine safety are an important reason for vaccine hesitancy, however, limited information is available on whether common adverse reactions following vaccination affect the immune response. Data from three clinical trials of recombinant vaccines were used in this post hoc analysis to assess the correlation between inflammation-related solicited adverse reactions (ISARs, including local pain, redness, swelling or induration and systematic fever) and immune responses after vaccination. In the phase III trial of the bivalent HPV-16/18 vaccine (Cecolin®), the geometric mean concentrations (GMCs) for IgG anti-HPV-16 and -18 (P<0.001) were significantly higher in participants with any ISAR following vaccination than in those without an ISAR. Local pain, induration, swelling and systemic fever were significantly correlated with higher GMCs for IgG anti-HPV-16 and/or anti-HPV-18, respectively. Furthermore, the analyses of the immunogenicity bridging study of Cecolin® and the phase III trial of a hepatitis E vaccine yielded similar results. Based on these results, we built a scoring model to quantify the inflammation reactions and found that the high score of ISAR indicates the strong vaccine-induced antibody level. In conclusion, this study suggests inflammation-related adverse reactions following vaccination potentially indicate a stronger immune response.

Public Mobility Data Enables COVID-19 Forecasting and Management at Local and Global Scales

Policymakers everywhere are working to determine the set of restrictions that will effectively contain the spread of COVID-19 without excessively stifling economic activity. We show that publicly available data on human mobility — collected by Google, Facebook, and other providers — can be used to evaluate the effectiveness of non-pharmaceutical interventions and forecast the spread of COVID-19. This approach relies on simple and transparent statistical models, and involves minimal assumptions about disease dynamics. We demonstrate the effectiveness of this approach using local and regional data from China, France, Italy, South Korea, and the United States, as well as national data from 80 countries around the world.

Influence of the First-wave COVID-19 Pandemic on Emergency Acute Coronary Syndrome: a Multicenter Retrospective Study From a Non-epicenter Region (preprint)

Background: The COVID-19 pandemic presented severe challenges to emergency practice of acute coronary syndrome (ACS). However, poor evidence was shown on ACS in a non-hot-spot region. We sought to clarify the influence of the first-wave COVID-19 pandemic on emergency ACS from a non-epicenter region. Methods: : This retrospective multicenter study was conducted in emergency ACS patients during the pandemic (from 2020-01-23 to 2020-03-29) and the ones during the same period in 2019. Clinical characteristics, timeline parameters and treatment strategies were compared between different groups. Association of the pandemic with non-invasive therapy was further assessed. Results: : Compared with 2019, ACS had a drop in admission (267 cases vs. 475 cases) and invasive therapy (140 cases vs. 318 cases). Also, process delays were detected including the period from symptom onset to first medical contact (S-to-FMC, 5h vs. 2.5h), the period from FMC to electrocardiogram (ECG) completed (8min vs. 4min) and the period from FMC to dual antiplatelet therapy (FMC-to-DAPT, 25min vs. 19min). Primary percutaneous coronary intervention (PPCI) decreased by 54.9% in STEMI and early invasive therapy decreased by 59.2% in NSTE-ACS. The proportion of invasive therapy in NSTE-ACS decreased more than in STEMI (16.9% vs. 10.1%) with longer process delay. The pandemic was associated with increased non-PPCI in STEMI (OR=1.707, 95%CI 1.082-2.692, P=0.021) and elevated medication in NSTE-ACS (OR=2.029, 95%CI 1.268-3.247, P=0.003), respectively. Conclusion: Even in a non-epicenter region, the first-wave COVID-19 pandemic caused a significant reduction of invasive therapy and evident process delays in emergency ACS.

Elaboration of a Radiomics Strategy for the Prediction of the Re-positive Cases in the Discharged Patients With COVID-19.

Objective: A considerable part of COVID-19 patients were found to be re-positive in the SARS-CoV-2 RT-PCR test after discharge. Early prediction of re-positive COVID-19 cases is of critical importance in determining the isolation period and developing clinical protocols. Materials and Methods: Ninety-one patients discharged from Wanzhou Three Gorges Central Hospital, Chongqing, China, from February 10, 2020 to March 3, 2020 were administered nasopharyngeal swab SARS-CoV-2 tests within 12-14 days, and 50 eligible patients (32 male and 18 female) with completed data were enrolled. Average age was 48 ± 11.5 years. All patients underwent non-enhanced chest CT on admission. A total of 568 radiomics features were extracted from the CT images, and 17 clinical factors were collected based on the medical record. Student's t-test and support vector machine-based recursive feature elimination (SVM-RFE) method were used to determine an optimal subset of features for the discriminative model development. Results: After Student's t-test, 62 radiomics features showed significant inter-group differences (p < 0.05) between the re-positive and negative cases, and none of the clinical features showed significant differences. These significant features were further selected by SVM-RFE algorithm, and a more compact feature subset containing only two radiomics features was finally determined, achieving the best predictive performance with the accuracy and area under the curve of 72.6% and 0.773 for the identification of the re-positive case. Conclusion: The proposed radiomics method has preliminarily shown potential in identifying the re-positive cases among the recovered COVID-19 patients after discharge. More strategies are to be integrated into the current pipeline to improve its precision, and a larger database with multi-clinical enrollment is required to extensively verify its performance.

Air quality in Nanjing during COVID-19 lockdown period

In order to investigate the impact of COVID-19 lockdown on air quality in Nanjing, the air pollutants observed from January 25 to February 10, in 2020（COVID-19 lockdown period） in Nanjing and its surrounding cities was analyzed. During the lockdown period with poor atmospheric diffusion conditions, the concentrations of PM2.5, PM10, NO2, SO2, and CO decreased obviously, with the value of 36, 44, 5, 22μg/m3 and 1.1 mg/m3, whereasO3 increased by 4%. The net effectiveness of the emission reduction measures was calculated through comparisons of concentrations of air pollutants between and before COVID in the similar meteorological conditions. Concentrations of PM2.5, PM10, SO2, NO2 and CO decreased by 41.7%, 45.3%, 14.3%, 43.5% and 18.2%, respectively, whereasO3 increased by 4.8%. Compared to capital cities of the Yangtze River Delta in the same period, the largest decline of SO2 and the medium decline of the other pollutions were appeared in Nanjing. The diurnal variation concentration of PM2.5 and PM10 changed from double peak to single peak, due to the disappearance of nighttime sub-peak of particle. The concentration ofO3 increased significantly at night, which was resulted from that sharp reduction of traffic sources weaken the titration reaction of NO toO3. The peak ofO3 during the daytime depended on the variation of the ratio of VOCs to NOx due to the emission control.

Design and Evaluation of Multiplex One-Step Reverse Transcription PCR-Dipstick Chromatography Method for the Analysis of Seven Respiratory Pathogens.

Influenza A, influenza B, severe acute respiratory syndrome coronavirus 2, adenovirus, respiratory syncytial virus, Mycoplasma pneumoniae, and Chlamydophila pneumoniae are common pathogens that can cause severe pneumonia and other symptoms, resulting in acute lower respiratory tract infections. The objective of this study was to design and evaluate a sensitive and specific multiplex one-step reverse transcription PCR (RT-PCR)-dipstick chromatography method for simultaneous rapid detection of these seven pathogens. Streptavidin-coated blue latex particles were used to read out a positive signal. Based on the DNA-DNA hybridization of oligonucleotide sequences (Tag) for forward primer with the complementary oligonucleotide sequence (cTag) on the dipstick and biotin-streptavidin interactions, PCR products were able to be illuminated visually on the dipstick. The specificity and the limit of detection (LOD) were also evaluated. Moreover, the clinical performance of this method was compared with Sanger sequencing for 896 samples. No cross reaction with other pathogens was found, confirming the high specificity of this method. The LOD was 10 copies/µL for each of the tested pathogens, and the whole procedure took less than 40 min. Using 896 samples, the sensitivity and specificity were shown to be no lower than 94.5%. The positive predictive value was higher than 82.1%, and the negative predictive value was higher than 99.5%. The kappa value between the PCR-dipstick chromatography method and Sanger sequencing ranged from 0.869 to 0.940. In summary, our one-step RT-PCR-dipstick chromatography method is a sensitive and specific tool for rapidly detecting multiplex respiratory pathogens.

A Scoring System for Predicting the Prognosis of Late-Onset Severe Pneumonia after Allogeneic Hematopoietic Stem Cell Transplantation.

Late-onset severe pneumonia (LOSP) is defined as severe pneumonia developing during the late phase of allogeneic hematopoietic stem cell transplantation (allo-HSCT). Because of the high mortality in patients with LOSP, it is important to identify prognostic factors. In this study, we aimed to develop a risk score system with broad applicability that can help predict the risk of LOSP-associated mortality. We retrospectively analyzed 100 patients with LOSP after allo-HSCT between June 2009 and July 2017. The assessment variables included immune, nutritional, and metabolic parameters at the onset of LOSP. Of these 100 patients, 45 (45%) eventually died, and 55 (55%) were positive for organisms, most commonly viruses. In the multivariate analysis, higher monocyte count (≥0.20 × 109/L versus <0.20 × 109/L; P = .001), higher albumin level (≥30.5 g/L versus <30.5 g/L; P = .044), lower lactic dehydrogenase level (<250 U/L versus ≥250 U/L; P = .008) and lower blood urea nitrogen concentration (<7.2 mmol/L versus ≥7.2 mmol/L; P = .026) at the onset of LOSP were significantly associated with better 60-day survival. A risk score system based on the foregoing results showed that the probability of 60-day survival decreased with increasing risk factors, from 96.3% in the low-risk group to 49.1% in the intermediate-risk group and 12.5% in the high-risk group. Our results indicate that this scoring system using 4 variables can stratify patients with different probabilities of survival after LOSP, which suggests that patients' immune, nutritional, and metabolic status are crucial factors in determining outcome.