Abstract Aims/Introduction To evaluate the differences in cardiac autonomic function, cardiac structure and diastolic function between individuals with diabetic foot (DF) and those with diabetes but without DF. Materials and Methods A total of 413 individuals with DF and 437 without DF who underwent a 24‐h electrocardiogram Holter and a Doppler echocardiogram were included. The heart rate variability parameters to evaluate cardiac autonomic function, and the indices for the assessment of cardiac structure and left ventricular (LV) diastolic function, including left atrium, LV posterior wall thickness, interventricular septum and E/e′ ratio, were measured or calculated. Propensity score matching was used for the sensitivity analysis to minimize potential imbalance. Results In both the crude and propensity score matching analyses, significant differences were observed in heart rate variability between individuals with and without DF, as evidenced by lower standard deviation of the normal sinus interval, lower low‐frequency power/high‐frequency power ratio, lower standard deviation of the 5‐min average RR intervals, lower low‐frequency power, lower percentage of normal adjacent RR interval difference >50 ms, lower root mean square of successive RR interval differences and lower high‐frequency power (all P < 0.05). In multivariate analysis, DF showed an independent negative correlation with the aforementioned indices of heart rate variability (all P < 0.05). Individuals with DF showed higher left atrium, LV posterior wall thickness, interventricular septum and a higher E/e′ ratio than those without DF in the crude analysis (all P < 0.05), whereas these indices were no longer associated with DF in the multivariate analysis and the propensity score matching analyses. Conclusions Cardiac autonomic modulation was more severely impaired in individuals with DF than in their counterparts without DF. There has been insufficient evidence to demonstrate the independent association of DF and LV diastolic dysfunction.

BackgroundIn recent years, there has been a growing trend in the utilization of observational studies that make use of routinely collected healthcare data (RCD). These studies rely on algorithms to identify specific health conditions (e.g. diabetes or sepsis) for statistical analyses. However, there has been substantial variation in the algorithm development and validation, leading to frequently suboptimal performance and posing a significant threat to the validity of study findings. Unfortunately, these issues are often overlooked.MethodsWe systematically developed guidance for the development, validation, and evaluation of algorithms designed to identify health status (DEVELOP-RCD). Our initial efforts involved conducting both a narrative review and a systematic review of published studies on the concepts and methodological issues related to algorithm development, validation, and evaluation. Subsequently, we conducted an empirical study on an algorithm for identifying sepsis. Based on these findings, we formulated specific workflow and recommendations for algorithm development, validation, and evaluation within the guidance. Finally, the guidance underwent independent review by a panel of 20 external experts who then convened a consensus meeting to finalize it.ResultsA standardized workflow for algorithm development, validation, and evaluation was established. Guided by specific health status considerations, the workflow comprises four integrated steps: assessing an existing algorithm's suitability for the target health status; developing a new algorithm using recommended methods; validating the algorithm using prescribed performance measures; and evaluating the impact of the algorithm on study results. Additionally, 13 good practice recommendations were formulated with detailed explanations. Furthermore, a practical study on sepsis identification was included to demonstrate the application of this guidance.ConclusionsThe establishment of guidance is intended to aid researchers and clinicians in the appropriate and accurate development and application of algorithms for identifying health status from RCD. This guidance has the potential to enhance the credibility of findings from observational studies involving RCD.

Background: Sedation strategies have not been well established for patients being treated with invasive mechanical ventilation (MV). This study aimed to compare the potential effects of alternative sedation strategies - including early deep-to-light sedation (DTLS), continuous deep sedation (CDS) and continuous light sedation (CLS, the currently recommended strategy) - on ventilator, intensive care unit (ICU) or hospital mortality. Methods: A cohort study was conducted using two large validated ICU databases, including the Registry of Healthcare-associated Infections in ICUs in China (ICU-HAI) and the Medical Information Mart for Intensive Care (MIMIC). Patients who received MV for more than 3 days with one of three sedation strategies were included. Multivariable survival analyses with inverse probability-weighted competing risk models were conducted separately for ICU-HAI and MIMIC cohorts. Adjusted estimates were pooled using fixed-effects models. Results: In total, 6700 patients (2627 ICU-HAI, 4073 MIMIC) were included in the cohort study, of whom 2689 received CLS, 2079 CDS and 1932 DTLS. Compared to CLS, DTLS was associated with lower ICU mortality (9.3% vs. 11.0%; pooled adjusted HR 0.78, 95% CI 0.66-0.94) and hospital mortality (16.0% vs. 14.1%; 0.86, CI 0.74-1.00); and CDS was associated with higher ventilator mortality (32.8% vs. 7.0%; 4.65, 3.91-5.53), ICU mortality (40.6% vs. 11.0%; 3.39, 2.95-3.90) and hospital mortality (46.8% vs. 14.1%; 3.27, 2.89-3.71) than CLS. All HRs were qualitatively consistent in both cohorts. Conclusions: Compared to the continuous light sedation, early deep-to-light sedation strategy was associated with improved patient outcomes, and continuous deep sedation was confirmed with poorer patient outcomes.

There is a growing demand for the use of high-quality real-world evidence (RWE) to support regulatory decision-making worldwide and in China, which highlights the need for conducting literature reviews to evaluate the available data and evidence. This study aims to review the use of RWE in Chinese regulatory decisions and to summarize relevant regulatory and methodological considerations to inform the future use of RWE in China. We identified policy documents, technical guidance documents, and cases on official Chinese government websites and extracted their contents separately. We consulted experts from the National Medical Products Administration (NMPA) and academic institutes and searched case-related articles for enrichment. We also searched and included articles related to the use of RWE/Real-world data in Chinese regulatory decisions. Six trial versions of technical guidance documents, 7 case studies, and 40 articles related to the Chinese regulatory decisions were included in this study. Based on the technical guidance, data quality, and appropriate study design and statistical analysis are the main concerns for RWE generation. The cases and articles related to regulatory decisions revealed 9 main concerns, including data sources and applicability, data quality, strength of existing evidence, appropriate study design and statistical analysis, regulated and transparent process for analysis and evidence generation, product safety and efficacy, product characteristics and clinical needs, ethical considerations and data security, and communicate adequately with regulatory authorities. Among these concerns, data issues are central. Preliminary attempts have been made by the NMPA to promote the use of RWE, but substantial challenges still remain.

Background: The prevalence and outcomes of coronavirus 2019 (COVID-19) among patients using glucocorticoids and immunosuppressants remain controversial. Aim: The study aims to investigate the impact of immunosuppressants especially glucocorticoids on patients in the Autoimmune Bullous Diseases Cohort of West China Hospital (AIBDWCH) during COVID-19. Methods: We conducted a cross-sectional survey from December 7, 2022, to February 8, 2023, using questionnaires administered either face-to-face or by phone. COVID-19 cases were classified as confirmed, probable, or suspected according to World Health Organization criteria. Patients were divided into Group A (confirmed and probable cases) and Group B (suspected and other cases). The impact of glucocorticoids and immunosuppressive agents on COVID-19 disease and progression was evaluated with logistic regression models. Results: This study included 111 patients with pemphigus. Overweight patients had a reduced risk of confirmed COVID-19 (odds ratio [OR] 0.35 [95 % CI 0.13 -0.97], p = 0.045). Patients treated with a medium dose of prednisone during the pandemic had a lower incidence of COVID-19 compared to those on low doses, though the difference was not statistically significant. No independent effects of age, sex, comorbidities, and therapies were observed. No significant differences were found in COVID-19 symptoms among different therapy groups. Conclusions: Treatment with immunosuppressants, particularly glucocorticoids at low -to -medium doses, did not elevate COVID-19 risk in pemphigus patients. Consistent outcomes across treatments confirm the safety of these therapies during the pandemic.

OBJECTIVE:Time-varying treatments are common in observational studies. However, when assessing treatment effects, the methodological framework has not been systematically established for handling time-varying treatments. This study aimed to examine the current methods for dealing with time-varying treatments in observational studies and developed practical recommendations. METHODS:We searched PubMed from 2000 to 2021 for methodological articles about time-varying treatments, and qualitatively summarized the current methods for handling time-varying treatments. Subsequently, we developed practical recommendations through interactive internal group discussions and consensus by a panel of external experts. RESULTS:Of the 36 eligible reports (22 methodological reviews, 10 original studies, 2 tutorials and 2 commentaries), most examined statistical methods for time-varying treatments, and only a few discussed the overarching methodological process. Generally, there were three methodological components to handle time-varying treatments. These included the specification of treatment which may be categorized as three scenarios (i.e., time-independent treatment, static treatment regime, or dynamic treatment regime); definition of treatment status which could involve three approaches (i.e., intention-to-treat, per-protocol, or as-treated approach); and selection of analytic methods. Based on the review results, a methodological workflow and a set of practical recommendations were proposed through two consensus meetings. CONCLUSIONS:There is no consensus process for assessing treatment effects in observational studies with time-varying treatments. Previous efforts were dedicated to developing statistical methods. Our study proposed a stepwise workflow with practical recommendations to assist the practice.

OBJECTIVE:To assess whether the use of Tanreqing (TRQ) Injection could show improvements in time to extubation, intensive care unit (ICU) mortality, ventilator-associated events (VAEs) and infection-related ventilator associated complication (IVAC) among patients receiving mechanical ventilation (MV).METHODS:A time-dependent cox-regression analysis was conducted using data from a well-established registry of healthcare-associated infections at ICUs in China. Patients receiving continuous MV for 3 days or more were included. A time-varying exposure definition was used for TRQ Injection, which were recorded on daily basis. The outcomes included time to extubation, ICU mortality, VAEs and IVAC. Time-dependent Cox models were used to compare the clinical outcomes between TRQ Injection and non-use, after controlling for the influence of comorbidities/conditions and other medications with both fixed and time-varying covariates. For the analyses of time to extubation and ICU mortality, Fine-Gray competing risk models were also used to measure competing risks and outcomes of interest.RESULTS:Overall, 7,685 patients were included for the analyses of MV duration, and 7,273 patients for the analysis of ICU mortality. Compared to non-use, patients with TRQ Injection had a lower risk of ICU mortality (Hazards ratios (HR) 0.761, 95% CI, 0.581-0.997), and was associated with a higher hazard for time to extubation (HR 1.105, 95% CI, 1.005-1.216), suggesting a beneficial effect on shortened time to extubation. No significant differences were observed between TRQ Injection and non-use regarding VAEs (HR 1.057, 95% CI, 0.912-1.225) and IVAC (HR 1.177, 95% CI, 0.929-1.491). The effect estimates were robust when using alternative statistic models, applying alternative inclusion and exclusion criteria, and handling missing data by alternative approaches.CONCLUSION:Our findings suggested that the use of TRQ Injection might lower mortality and improve time to extubation among patients receiving MV, even after controlling for the factor that the use of TRQ changed over time.

Background The clinical characteristics of early-onset type 2 diabetes (T2D) patients are not fully understood. To address this gap, we conducted a cohort study to evaluate clinical characteristics and disease burden in the new-onset T2D population, especially regarding the progression of diseases. Methods This cohort study was conducted using a population-based database. Patients who were diagnosed with T2D were identified from the database and were classified into early- (age < 40) and late-onset (age ≥ 40) groups. A descriptive analysis was performed to compare clinical characteristics and disease burden between early- and late-onset T2D patients. The progression of disease was compared using Kaplan‒Meier analysis. Results A total of 652,290 type 2 diabetic patients were included. Of those, 21,347 were early-onset patients, and 300,676 were late-onset patients. Early-onset T2D patients had poorer glycemic control than late-onset T2D patients, especially at the onset of T2D (HbA1c: 9.3 [7.5, 10.9] for early-onset vs. 7.7 [6.8, 9.2] for late-onset, P < 0.001; random blood glucose: 10.9 [8.0, 14.3] for early-onset vs. 8.8 [6.9, 11.8] for late-onset, P < 0.001). Insulin was more often prescribed for early-onset patients (15.2%) than for late-onset patients (14.8%). Hypertension (163.0 [28.0, 611.0] days) and hyperlipidemia (114.0 [19.0, 537.0] days) progressed more rapidly among early-onset patients, while more late-onset patients developed hypertension (72.7% vs. 60.1%, P < 0.001), hyperlipidemia (65.4% vs. 51.0%, P < 0.001), cardiovascular diseases (66.0% vs. 26.7%, P < 0.001) and chronic kidney diseases (5.5% vs. 2.1%, P < 0.001) than early-onset patients. Conclusions Our study results indicate that patients with newly diagnosed early-onset T2D had earlier comorbidities of hypertension and hyperlipidemia. Both clinical characteristics and treatment patterns suggest that the degree of metabolic disturbance is more severe in patients with early-onset type 2 diabetes. This highlights the importance of promoting healthy diets or lifestyles to prevent T2D onset in young adults.

Background . The global impact of coronavirus 2019 (COVID‐19) has raised concerns about the management of psoriasis patients, especially among those using biologics. Methods . We conducted a survey‐based research among Omicron‐infected (confirmed, probable, and suspected ones) psoriasis patients in the department of dermatology, West China Hospital, Sichuan University, from January 9th to January 22nd, 2023. We collected demographic and clinical information (psoriasis‐ and COVID‐19‐related) and conducted statistics analysis. Results . Of the 240 patients enrolled, they were classified by the psoriatic treatment, as biologics ( n = 138), nonbiological systematic treatment ( n = 52), and topical treatment or without pharmacological treatment ( n = 50). This study showed the characteristics of Omicron‐related symptoms and cutaneous signs in patients. We observed that patients who received topical treatment or without pharmacological treatment had a lower risk of presenting with COVID‐19 symptoms in the fully adjusted logistic model (OR = 0.40, 95% CI: 0.18–0.90, and P = 0.025). Moreover, in the model for skin manifestations, nonbiological systematic treatment (OR = 2.15, 95% CI: 1.08–4.27, and P = 0.029) and high BMI (OR = 1.10, 95% CI: 1.00–1.20, and P = 0.042) were correlative factors. Conclusions . Our data suggested that differential psoriatic treatment might be a correlative factor in developing symptomatic or asymptomatic Omicron infection and presenting cutaneous signs.

BACKGROUND AND OBJECTIVES:Among observational studies of routinely collected health data (RCD) for exploring treatment effects, algorithms are used to identify study variables. However, the extent to which algorithms are reliable and impact the credibility of effect estimates is far from clear. This study aimed to investigate the validation of algorithms for identifying study variables from RCD, and examine the impact of alternative algorithms on treatment effects. METHODS:We searched PubMed for observational studies published in 2018 that used RCD to explore drug treatment effects. Information regarding the reporting, validation, and interpretation of algorithms was extracted. We summarized the reporting and methodological characteristics of algorithms and validation. We also assessed the divergence in effect estimates given alternative algorithms by calculating the ratio of estimates of the primary vs. alternative analyses. RESULTS:A total of 222 studies were included, of which 93 (41.9%) provided a complete list of algorithms for identifying participants, 36 (16.2%) for exposure, and 132 (59.5%) for outcomes, and 15 (6.8%) for all study variables including population, exposure, and outcomes. Fifty-nine (26.6%) studies stated that the algorithms were validated, and 54 (24.3%) studies reported methodological characteristics of 66 validations, among which 61 validations in 49 studies were from the cross-referenced validation studies. Of those 66 validations, 22 (33.3%) reported sensitivity and 16 (24.2%) reported specificity. A total of 63.6% of studies reporting sensitivity and 56.3% reporting specificity used test-result-based sampling, an approach that potentially biases effect estimates. Twenty-eight (12.6%) studies used alternative algorithms to identify study variables, and 24 reported the effects estimated by primary analyses and sensitivity analyses. Of these, 20% had differential effect estimates when using alternative algorithms for identifying population, 18.2% for identifying exposure, and 45.5% for classifying outcomes. Only 32 (14.4%) studies discussed how the algorithms may affect treatment estimates. CONCLUSION:In observational studies of RCD, the algorithms for variable identification were not regularly validated, and-even if validated-the methodological approach and performance of the validation were often poor. More seriously, different algorithms may yield differential treatment effects, but their impact is often ignored by researchers. Strong efforts, including recommendations, are warranted to improve good practice.

PURPOSE:The present study was conducted to investigate the association of admission lactate with mortality in severe community-acquired pneumonia (SCAP).METHODS:We performed a retrospective, observational, cohort study on adult SCAP patients admitted to intensive care unit (ICU) in West China Hospital of Sichuan University between December 2011 and December 2018. The primary outcome was hospital mortality. Univariate and then multivariate analysis were performed to identify independent risk factors for hospital mortality. The association of admission lactate categories with hospital mortality was examined in three logistic regression models and Kaplan-Meier plots. We also applied restricted cubic splines to estimate the potential non-linear associations.RESULTS:In total, 2275 SCAP patients were included. Admission lactate remained a significant factor for mortality after multivariate regression (OR: 1.085; 95% CI: 1.033,1.141; by continuous variable). After lactate was categorized into quartiles and the confounders were fully adjusted, compared with the quartile 1, ORs (95% CIs) of hospital mortality for quartile 2, quartile 3 and quartile 4 were 1.001 (0.759-1.321), 1.153 (0.877-1.516) and 1.593 (1.202-2.109), respectively (P for trend =0.001). Survival curves indicated that elevated lactate was associated with poor prognosis (P < 0.001). Moreover, this association was non-linear, indicating that increased lactate has the most notable impact on mortality within the range of 1.5 to 4 mmol/L (P non-linear: 0.029 for hospital mortality; 0.004 for ICU mortality).CONCLUSION:Elevated admission lactate has a significant, independent, and potentially non-linear association with increased mortality in SCAP patients.

We study the effects of centralized health management based on hot spring resorts on the physical examination index and sleep quality of people at high risk of chronic diseases. We recruited 114 volunteers at high risk of chronic diseases. We then divided them into 57 in the intervention group and 57 in the control group. The intervention group collectively received 4 weeks (28 days) of comprehensive health management interventions at Tongjing Hotspring Resort, including regular schedules, balanced diet, appropriate exercise, targeted health education, etc. The main outcomes are physical examination indicators (height, weight, waist circumference, blood pressure, lipids, and glucose) and sleep quality. Both groups underwent a questionnaire and physical examination at baseline, 2 weeks and 4 weeks. Intragroup comparisons grouped by exposure criteria showed decreases in BMI, waist circumference, triglycerides, total cholesterol, and blood glucose in the intervention group at both 2 and 4 weeks (all P < 0.05); however, in the control group, only triglycerides decreased at 4 weeks (P < 0.05). Intergroup comparisons showed BMI and waist circumference were significantly lower in the intervention group than in the control group at 4 weeks (all P < 0.05). Intragroup comparisons of insomnia severity index (ISI) scores showed a significant decrease in the intervention group at both 2 and 4 weeks (all P < 0.001) with no significant change in the control group (P > 0.05). Intergroup comparisons showed that the insomnia severity index (ISI) scores were significantly higher in the intervention group than in the control group at baseline (P = 0.006) but became significantly lower than the control group at 2 and 4 weeks (all P < 0.001). Thus, this pattern significantly improved BMI, waist circumference, triglycerides, and sleep in the intervention group.Trial registration numberChinese Clinical Trials Registry: ChiCTR2100053201, registered 14 Nov 2021. (Retroactive Registration)

Early and accurate identification of patients with acute pancreatitis (AP) at high risk of persistent acute respiratory failure (PARF) is crucial. We sought to determine the accuracy of simplified Lung Injury Prediction Score (sLIPS) and simplified Early Acute Lung Injury (sEALI) for predicting PARF in ward AP patients. Consecutive AP patients in a training cohort from West China Hospital of Sichuan University (n = 912) and a validation cohort from The First Affiliated Hospital of Nanchang University (n = 1033) were analyzed. PARF was defined as oxygen in arterial blood/fraction of inspired oxygen < 300 mmHg that lasts for > 48 h. The sLIPS was composed by shock (predisposing condition), alcohol abuse, obesity, high respiratory rate, low oxygen saturation, high oxygen requirement, hypoalbuminemia, and acidosis (risk modifiers). The sEALI was calculated from oxygen 2 to 6 L/min, oxygen > 6 L/min, and high respiratory rate. Both indices were calculated on admission. PARF developed in 16

BACKGROUND:Low quality of life (QoL) in patients with non-small cell lung cancer (NSCLC) receiving adjuvant chemotherapy after radical resection is a major global health issue. High-quality evidence for the effectiveness of Shenlingcao oral liquid (SOL) as a complementary treatment in this patients is lacking at present. PURPOSE:To determine whether complementary SOL treatment in NSCLC patients receiving adjuvant chemotherapy would yield greater improvements in QoL than chemotherapy alone. STUDY DESIGN:We conducted a multicenter, randomized controlled trial of stages IIA-IIIA NSCLC patients undergoing adjuvant chemotherapy in seven hospitals. METHODS:Using stratified blocks, participants were randomized in a 1:1 ratio to receive SOL combined with conventional chemotherapy or conventional chemotherapy alone. The primary outcome was the change in global QoL from baseline to the fourth chemotherapy cycle, and intention-to-treat analysis was applied with a mixed-effect model. Secondary outcomes were functional QoL, symptoms, and performance status scores at the 6-month follow-up. Missing data were handled with multiple imputation and a pattern-mixture model. RESULTS:Among 516 randomized patients, 446 (86.43%) completed the study. After the fourth chemotherapy cycle, in comparison with the control group, patients receiving SOL showed a lower reduction in mean global QoL (-2.76 vs. -14.11; mean difference [MD], 11.34; 95% confidence interval [CI], 8.28 to 14.41), greater improvement in physical function (MD, 11.61; 95% CI, 8.57 to 14.65), role function (MD, 10.15; 95% CI, 5.75 to 14.54), and emotional function (MD, 4.71; 95% CI, 1.85 to 7.57), and greater improvements in lung cancer-related symptoms (e.g., fatigue, nausea/vomiting, and appetite loss) and performance status during the 6-month follow-up period (treatment main effect, p < 0.05). CONCLUSION:SOL treatment for NSCLC patients receiving adjuvant chemotherapy can significantly improve QoL and performance status within 6 months after radical resection. TRIAL REGISTRATION:ClinicalTrials.gov identifier: NCT03712969.

Background Routinely collected health data (RCD) are important resource for exploring drug treatment effects. Adequate reporting of data source profiles may increase the credibility of evidence generated from these data. This study conducted a systematic literature review to evaluate the reporting characteristics of databases used by RCD studies to explore the effects of drug treatment. Methods Observational studies published in 2018 that used RCD to explore the effects of drug treatment were identified by searching PubMed. We categorized eligible reports into two groups by journal impact factor (IF), including the top 5 general medical journals (NEJM, Lancet, JAMA, BMJ and JAMA Internal Medicine) and the other journals. The reporting characteristics of the databases used were described and compared between the two groups and between studies citing and not citing database references. Results A total of 222 studies were included, of which 53 (23.9%) reported that they applied data linkage, 202 (91.0%) reported the type of database, and 211 (95.0%) reported the coverage of the data source. Only 81 (36.5%) studies reported the timeframe of the database. Studies in high-impact journals were more likely to report that they applied data linkage (65.1% vs. 20.2%) and used electronic medical records (EMR) (73.7% vs. 30.0%) and national data sources (77.8% vs. 51.3%) than those published in other medical journals. There were 137/222 (61.7%) cited database references. Studies with database-specific citations had better reporting of the data sources and were more likely to publish in high-impact journals than those without (mean IF, 6.08 vs. 4.09). Conclusions Some deficits were found in the reporting quality of databases in studies that used RCD to explore the effects of drug treatment. Studies citing database-specific references may provide detailed information regarding data source characteristics. The adoption of reporting guidelines and education on their use is urgently needed to promote transparency by research groups.

BackgroundTime-varying drug treatments are common in studies using routinely collected health data (RCD) for assessing treatment effects. This study aimed to examine how these studies reported, handled, and interpreted time-varying drug treatments.MethodsA systematic search was conducted on PubMed from 2018 to 2020. Eligible studies were those used RCD to explore drug treatment effects. We summarized the reporting characteristics and methods employed for handling time-varying treatments. Logistic regressions were performed to investigate the association between study characteristics and the reporting of time-varying treatments.ResultsTwo hundred and fifty-six studies were included, and 225 (87.9%) studies involved time-varying treatments. Of these, 24 (10.7%) reported the proportion of time-varying treatments and 105 (46.7%) reported methods used to handle time-varying treatments. Multivariable logistic regression showed that medical studies, prespecified protocol, and involvement of methodologists were associated with a higher likelihood of reporting the methods applied to handle time-varying treatments. Among the 105 studies that reported methods, as-treated analyses were the most commonly used analysis sets, which were employed in 73.9%, 75.3% and 88.2% of studies that reported approaches for treatment discontinuation, treatment switching and treatment add-on. Among the 225 studies involved time-varying treatments, 27 (12.0%) acknowledged the potential bias introduced by treatment change, of which 14 (51.9%) suggested that potential biases may impact acceptance or rejection of the null hypothesis.ConclusionsAmong observational studies using RCD, the underreporting about the presence and methods for handling time-varying treatments was largely common. The potential biases due to time-varying treatments have frequently been disregarded. Collaborative endeavors are strongly needed to enhance the prevailing practices.

Background No personalized prediction model or standardized algorithm exists to identify those at high risk of death among severe community-acquired pneumonia (SCAP) patients with chronic obstructive pulmonary disease (COPD). The aim of this study was to investigate the risk factors and to develop a useful nomogram for prediction of mortality in those patients. Methods We performed a retrospective, observational, cohort study in the intensive care unit (ICU) of West China Hospital, Sichuan University with all consecutive SCAP patients with COPD between December 2011 and December 2018. The clinical data within 24 h of admission to ICU were collected. The primary outcome was hospital mortality. We divided the patients into training and testing cohorts (70% versus 30%) randomly. In the training cohort, univariate and multivariate logistic regression analysis were used to identify independent risk factors applied to develop a nomogram. The prediction model was assessed in both training and testing cohorts. Results Finally, 873 SCAP patients with COPD were included, among which the hospital mortality was 41.4%. In training cohort, the independent risk factors for hospital mortality were increased age, diabetes, chronic renal diseases, decreased systolic blood pressure (SBP), and elevated fibrinogen, interleukin 6 (IL-6) and blood urea nitrogen (BUN). The C index was 0.840 (95% CI 0.809–0.872) in training cohort and 0.830 (95% CI 0.781–0.878) in testing cohort. Furthermore, the time-dependent AUC, calibration plots, DCA and clinical impact curves indicated the model had good predictive performance. Significant association of risk stratification based on nomogram with mortality was also found (P for trend < 0.001). The restricted cubic splines suggested that estimated associations between these predictors and hospital mortality were all linear relationships. Conclusion We developed a prediction model including seven risk factors for hospital mortality in patients with SCAP and COPD. It can be used for early risk stratification in clinical practice after more external validation.

高风险植入类无源医疗器械的上市后监测是医疗器械风险管理的重要环节,通过对高风险医疗器械上市后安全性信号的监测和评价,最大限度地控制医疗器械潜在的风险,保证医疗器械安全、有效地使用,避免发生群体性严重后果,是医疗器械生产、经营、使用机构和技术监测部门的共同职责。为了更好地促进和辅助高风险植入类无源医疗器械的上市后监测,本专家共识采用系统性文献回顾、专题小组讨论和专家咨询过程,系统梳理国内外医疗器械上市后风险监测现状,并提出适宜于我国国情的高风险植入类无源医疗器械上市后风险监测模式和高风险医疗器械风险监测关键技术。

Introduction Time-varying exposure is an important issue that should be addressed in longitudinal observational studies using routinely collected data (RCD) for drug treatment effects. How well investigators designed, analysed and reported time-varying exposure, and to what extent the divergence that can be observed between different methods used for handling time-varying exposure in these studies remains uncertain. We will conduct a cross-sectional study to comprehensively address this question. Methods and analysis We have developed a comprehensive search strategy to identify all studies exploring drug treatment effects including both effectiveness and safety that used RCD and were published in core journals between 2018 and 2020. We will collect information regarding general study characteristics, data source profile, methods for handling time-varying exposure, results and the interpretation of findings from each eligibility. Paired reviewers will screen and extract data, resolving disagreements through discussion. We will describe the characteristics of included studies, and summarise the method used for handling time-varying exposure in primary analysis and sensitivity analysis. We will also compare the divergence between different approaches for handling time-varying exposure using ratio of risk ratios. Ethics and dissemination No ethical approval is required because the data we will use do not include individual patient data. Findings will be disseminated through peer-reviewed publications.

Supplemental Digital Content is available in the text. OBJECTIVES: Fluid therapy is an important component of intensive care management, however, optimal fluid management is unknown. The relationship between fluid balance and ventilator-associated events has not been well established. This study investigated the dose-response relationship between fluid balance and ventilator-associated events. DESIGN: Nested case-control study. SETTING: The study was based on a well-established, research-oriented registry of healthcare-associated infections at ICUs of West China Hospital system (Chengdu, China). PATIENTS: A total of 1,528 ventilator-associated event cases with 3,038 matched controls, who consistently underwent mechanical ventilation for at least 4 days from April 1, 2015, to December 31, 2018, were included. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: We calculated cumulative fluid balance within 4 days prior to ventilator-associated event occurrence. A weighted Cox proportional hazards model with restricted cubic splines was used to evaluate the dose-response relationship. A nonlinear relationship between fluid balance and all three tiers of ventilator-associated events, patients with fluid balance between –1 and 0 L had the lowest risk (p < 0.05 for nonlinear test). The risk of ventilator-associated event was significantly higher in patients with positive fluid balance (4 d cumulative fluid balance: 1 L: 1.19; 3 L: 1.92; 5 L: 2.58; 7 L: 3.24), but not in those with negative fluid balance (–5 L: 1.34; –3 L: 1.14; –1 L: 0.98). CONCLUSIONS: There was nonlinear relationship between fluid balance and all three tiers of ventilator-associated event, with an fluid balance between –1 and 0 L corresponding to the lowest risk. Positive but not negative fluid balance increased the risk of ventilator-associated events, with higher positive fluid balance more likely to lead to ventilator-associated events.