Detecting the skewness of data from the five-number summary and its application in meta-analysis

Wu Z., Yang D.

The novel coronavirus disease 2019 (COVID-19), which is caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is leading to a worldwide pandemic. Except representative manifestation of pneumonia and acute respiratory symptoms, COVID-19 patients have also shown different levels of liver injury or liver dysfunction. The aim of our study was to explore the probable clinical severity and mortality of COVID-19 patients and their liver dysfunction. A combination of computer and manual retrieval was used to search in Medline through PubMed, EMBASE and Web of Science. Review Manager 5.3 software was used to examine the heterogeneity among the studies and to calculate the combined effect value (OR, 95CI). Subgroup analysis, sensitivity analysis, and publication bias test were also performed. We found a significant connection between liver dysfunction and mortality of COVID-19 patients with a pooled OR of 1.98 (95% CI 1.39–2.82; P = 0.0002). There was a significant association between AST and severity of COVID-19 with a pooled OR of 4.48 (95% CI 3.24–7.21; P < 0.001), and a pooled WMD of 3.35 (95% CI, 2.07 to 4.64; P < 0.001). In addition, there was a significant difference between TBIL and severity of COVID-19, with a pooled OR of 1.91 (95% CI 1.40–2.60; P < 0.001), and with a pooled WMD of 1.18 (95% CI, 0.78 to 1.58; P < 0.001). The mortality and severity of COVID-19 patients are significantly associated with liver dysfunction. The non-survivors and severe COVID-19 patients have elevated serum AST levels than the survivors and non-severe COVID-19 patients. The results of this study form a basis for better clinical liver management of patients with COVID-19.

Shi J., Tong T., Wang Y., Genton M.G.

Shi J., Luo D., Weng H., Zeng X., Lin L., Chu H., Tong T.

When reporting the results of clinical studies, some researchers may choose the five-number summary (including the sample median, the first and third quartiles, and the minimum and maximum values) rather than the sample mean and standard deviation (SD), particularly for skewed data. For these studies, when included in a meta-analysis, it is often desired to convert the five-number summary back to the sample mean and SD. For this purpose, several methods have been proposed in the recent literature and they are increasingly used nowadays. In this article, we propose to further advance the literature by developing a smoothly weighted estimator for the sample SD that fully utilizes the sample size information. For ease of implementation, we also derive an approximation formula for the optimal weight, as well as a shortcut formula for the sample SD. Numerical results show that our new estimator provides a more accurate estimate for normal data and also performs favorably for non-normal data. Together with the optimal sample mean estimator in Luo et al., our new methods have dramatically improved the existing methods for data transformation, and they are capable to serve as rules of thumb in meta-analysis for studies reported with the five-number summary. Finally for practical use, an Excel spreadsheet and an online calculator are also provided for implementing our optimal estimators.

Wang L., He W., Yu X., Hu D., Bao M., Liu H., Zhou J., Jiang H.

SummaryObjective To investigate the characteristics and prognostic factors in the elderly patients with COVID-19. Methods Consecutive cases over 60 years old with COVID-19 in Renmin Hospital of Wuhan University from Jan 1 to Feb 6, 2020 were included. The primary outcomes were death and survival till March 5. Data of demographics, clinical features, comorbidities, laboratory tests and complications were collected and compared for different outcomes. Cox regression was performed for prognostic factors. Results 339 patients with COVID-19 (aged 71±8 years,173 females (51%)) were enrolled, including 80 (23.6%) critical, 159 severe (46.9%) and 100 moderate (29.5%) cases. Common comorbidities were hypertension (40.8%), diabetes (16.0%) and cardiovascular disease (15.7%). Common symptoms included fever (92.0%), cough (53.0%), dyspnea (40.8%) and fatigue (39.9%). Lymphocytopenia was a common laboratory finding (63.2%). Common complications included bacterial infection (42.8%), liver enzyme abnormalities (28.7%) and acute respiratory distress syndrome (21.0%). Till Mar 5, 2020, 91 cases were discharged (26.8%), 183 cases stayed in hospital (54.0%) and 65 cases (19.2%) were dead. Shorter length of stay was found for the dead compared with the survivors (5 (3–8) vs. 28 (26–29), P < 0.001). Symptoms of dyspnea (HR 2.35, P = 0.001), comorbidities including cardiovascular disease (HR 1.86, P = 0.031) and chronic obstructive pulmonary disease (HR 2.24, P = 0.023), and acute respiratory distress syndrome (HR 29.33, P < 0.001) were strong predictors of death. And a high level of lymphocytes was predictive of better outcome (HR 0.10, P < 0.001). Conclusions High proportion of severe to critical cases and high fatality rate were observed in the elderly COVID-19 patients. Rapid disease progress was noted in the dead with a median survival time of 5 days after admission. Dyspnea, lymphocytopenia, comorbidities including cardiovascular disease and chronic obstructive pulmonary disease, and acute respiratory distress syndrome were predictive of poor outcome. Close monitoring and timely treatment should be performed for the elderly patients at high risk.

Chen T., Dai Z., Mo P., Li X., Ma Z., Song S., Chen X., Luo M., Liang K., Gao S., Zhang Y., Deng L., Xiong Y.

Abstract Background In December 2019, the coronavirus disease 2019 (COVID-19) emerged in Wuhan city and spread rapidly throughout China and the world. In this study, we aimed to describe the clinical course and outcomes of older patients with COVID-19. Methods This is a retrospective investigation of hospitalized older patients with confirmed COVID-19 at Zhongnan Hospital of Wuhan University from January 1, 2020, to February 10, 2020. Results In total, 203 patients were diagnosed with COVID-19, with a median age of 54 years (interquartile range, 41–68; range, 20–91 years). Men accounted for 108 (53.2%) of the cases, and 55 patients (27.1%) were more than 65 years of age. Among patients who were 65 years and older, the mortality rate was 34.5% (19/55), which was significantly higher than that of the younger patients at 4.7% (7/148). Common symptoms of older patients with COVID-19 included fever (94.5%; n = 52), dry cough (69.1%; n = 38), and chest distress (63.6%; n = 35). Compared with young patients, older patients had more laboratory abnormalities and comorbidities. Through a multivariate analysis of the causes of death in older patients, we found that males, comorbidities, time from disease onset to hospitalization, abnormal kidney function, and elevated procalcitonin levels were all significantly associated with death. Conclusions In the recent outbreak of COVID-19, our local hospital in Wuhan found that patients aged 65 and older had greater initial comorbidities, more severe symptoms, and were more likely to experience multiorgan involvement and death, as compared to younger patients.

Du R., Liang L., Yang C., Wang W., Cao T., Li M., Guo G., Du J., Zheng C., Zhu Q., Hu M., Li X., Peng P., Shi H.

The aim of this study was to identify factors associated with the death of patients with COVID-19 pneumonia caused by the novel coronavirus SARS-CoV-2.All clinical and laboratory parameters were collected prospectively from a cohort of patients with COVID-19 pneumonia who were hospitalised to Wuhan Pulmonary Hospital (Wuhan City, Hubei Province, China) between 25 December 2019 and 7 February 2020. Univariate and multivariate logistic regression was performed to investigate the relationship between each variable and the risk of death of COVID-19 pneumonia patients.In total, 179 patients with COVID-19 pneumonia (97 male and 82 female) were included in the present prospective study, of whom 21 died. Univariate and multivariate logistic regression analysis revealed that age ≥65 years (OR 3.765, 95% CI 1.146‒17.394; p=0.023), pre-existing concurrent cardiovascular or cerebrovascular diseases (OR 2.464, 95% CI 0.755‒8.044; p=0.007), CD3+CD8+ T-cells ≤75 cells·μL−1 (OR 3.982, 95% CI 1.132‒14.006; p<0.001) and cardiac troponin I ≥0.05 ng·mL−1 (OR 4.077, 95% CI 1.166‒14.253; p<0.001) were associated with an increase in risk of mortality from COVID-19 pneumonia. In a sex-, age- and comorbid illness-matched case–control study, CD3+CD8+ T-cells ≤75 cells·μL−1 and cardiac troponin I ≥0.05 ng·mL−1 remained as predictors for high mortality from COVID-19 pneumonia.We identified four risk factors: age ≥65 years, pre-existing concurrent cardiovascular or cerebrovascular diseases, CD3+CD8+ T-cells ≤75 cells·μL−1 and cardiac troponin I ≥0.05 ng·mL−1. The latter two factors, especially, were predictors for mortality of COVID-19 pneumonia patients.

Zhou F., Yu T., Du R., Fan G., Liu Y., Liu Z., Xiang J., Wang Y., Song B., Gu X., Guan L., Wei Y., Li H., Wu X., Xu J., et. al.

SummaryBackground Since December, 2019, Wuhan, China, has experienced an outbreak of coronavirus disease 2019 (COVID-19), caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Epidemiological and clinical characteristics of patients with COVID-19 have been reported but risk factors for mortality and a detailed clinical course of illness, including viral shedding, have not been well described. Methods In this retrospective, multicentre cohort study, we included all adult inpatients (≥18 years old) with laboratory-confirmed COVID-19 from Jinyintan Hospital and Wuhan Pulmonary Hospital (Wuhan, China) who had been discharged or had died by Jan 31, 2020. Demographic, clinical, treatment, and laboratory data, including serial samples for viral RNA detection, were extracted from electronic medical records and compared between survivors and non-survivors. We used univariable and multivariable logistic regression methods to explore the risk factors associated with in-hospital death. Findings 191 patients (135 from Jinyintan Hospital and 56 from Wuhan Pulmonary Hospital) were included in this study, of whom 137 were discharged and 54 died in hospital. 91 (48%) patients had a comorbidity, with hypertension being the most common (58 [30%] patients), followed by diabetes (36 [19%] patients) and coronary heart disease (15 [8%] patients). Multivariable regression showed increasing odds of in-hospital death associated with older age (odds ratio 1·10, 95% CI 1·03–1·17, per year increase; p=0·0043), higher Sequential Organ Failure Assessment (SOFA) score (5·65, 2·61–12·23; p

Sun R.W., Cheung S.F.

In this study we investigated the influence of data nonnormality in the primary studies on meta-analysis of the standardized mean difference (SMD) for a two-independent-group design. The bias, mean squared error, and confidence interval coverage probability of the mean effect sizes under different types of population distributions were compared. Also, the performance of the Q test was examined. The results showed that oppositely skewed distributions (i.e., distributions skewed in different directions) showed poor performance for point and interval estimates of mean effect sizes in meta-analysis, especially when the tails were pointing toward each other. The previously found adverse impacts due to nonnormality in primary studies do not disappear when primary studies with nonnormal data are meta-analyzed, even when the average sample size and number of studies are large. The results also showed that, when the tails were pointing toward each other, the Type I error rates of the Q test were inflated. We suggest that the impact of violating the assumption of normality should not be ignored in meta-analysis.

Balduzzi S., Rücker G., Schwarzer G.

ObjectiveMeta-analysis is of fundamental importance to obtain an unbiased assessment of the available evidence. In general, the use of meta-analysis has been increasing over the last three decades with mental health as a major research topic. It is then essential to well understand its methodology and interpret its results. In this publication, we describe how to perform a meta-analysis with the freely available statistical software environment R, using a working example taken from the field of mental health.MethodsR package meta is used to conduct standard meta-analysis. Sensitivity analyses for missing binary outcome data and potential selection bias are conducted with R package metasens. All essential R commands are provided and clearly described to conduct and report analyses.ResultsThe working example considers a binary outcome: we show how to conduct a fixed effect and random effects meta-analysis and subgroup analysis, produce a forest and funnel plot and to test and adjust for funnel plot asymmetry. All these steps work similar for other outcome types.ConclusionsR represents a powerful and flexible tool to conduct meta-analyses. This publication gives a brief glimpse into the topic and provides directions to more advanced meta-analysis methods available in R.

Bono R., Blanca M.J., Arnau J., Gómez-Benito J.

Statistical analysis is crucial for research and the choice of analytical technique should take into account the specific distribution of data. Although the data obtained from health, educational, and social sciences research are often not normally distributed, there are very few studies detailing which distributions are most likely to represent data in these disciplines. The aim of this systematic review was to determine the frequency of appearance of the most common non-normal distributions in the health, educational, and social sciences. The search was carried out in the Web of Science (WOS) database, from which we retrieved the abstracts of papers published between 2010 and 2015. The selection was made on the basis of the title and the abstract, and was performed independently by two reviewers. The inter-rater reliability for article selection was high (Cohen’s kappa = 0.84), and agreement regarding the type of distribution reached 96.5%. A total of 262 abstracts were included in the final review. The distribution of the response variable was reported in 231 of these abstracts, while in the remaining 31 it was merely stated that the distribution was non-normal. In terms of their frequency of appearance, the most-common non-normal distributions can be ranked in descending order as follows: gamma, negative binomial, multinomial, binomial, lognormal, and exponential. In addition to identifying the distributions most commonly used in empirical studies these results will help researchers to decide which distributions should be included in simulation studies examining statistical procedures.

Yamaguchi Y., Maruo K., Partlett C., Riley R.D.

In a random effects meta-analysis model, true treatment effects for each study are routinely assumed to follow a normal distribution. However, normality is a restrictive assumption and the misspecification of the random effects distribution may result in a misleading estimate of overall mean for the treatment effect, an inappropriate quantification of heterogeneity across studies and a wrongly symmetric prediction interval. We focus on problems caused by an inappropriate normality assumption of the random effects distribution, and propose a novel random effects meta-analysis model where a Box-Cox transformation is applied to the observed treatment effect estimates. The proposed model aims to normalise an overall distribution of observed treatment effect estimates, which is sum of the within-study sampling distributions and the random effects distribution. When sampling distributions are approximately normal, non-normality in the overall distribution will be mainly due to the random effects distribution, especially when the between-study variation is large relative to the within-study variation. The Box-Cox transformation addresses this flexibly according to the observed departure from normality. We use a Bayesian approach for estimating parameters in the proposed model, and suggest summarising the meta-analysis results by an overall median, an interquartile range and a prediction interval. The model can be applied for any kind of variables once the treatment effect estimate is defined from the variable. A simulation study suggested that when the overall distribution of treatment effect estimates are skewed, the overall mean and conventional I 2 from the normal random effects model could be inappropriate summaries, and the proposed model helped reduce this issue. We illustrated the proposed model using two examples, which revealed some important differences on summary results, heterogeneity measures and prediction intervals from the normal random effects model. The random effects meta-analysis with the Box-Cox transformation may be an important tool for examining robustness of traditional meta-analysis results against skewness on the observed treatment effect estimates. Further critical evaluation of the method is needed.

Luo D., Wan X., Liu J., Tong T.

The era of big data is coming, and evidence-based medicine is attracting increasing attention to improve decision making in medical practice via integrating evidence from well designed and conducted clinical research. Meta-analysis is a statistical technique widely used in evidence-based medicine for analytically combining the findings from independent clinical trials to provide an overall estimation of a treatment effectiveness. The sample mean and standard deviation are two commonly used statistics in meta-analysis but some trials use the median, the minimum and maximum values, or sometimes the first and third quartiles to report the results. Thus, to pool results in a consistent format, researchers need to transform those information back to the sample mean and standard deviation. In this article, we investigate the optimal estimation of the sample mean for meta-analysis from both theoretical and empirical perspectives. A major drawback in the literature is that the sample size, needless to say its importance, is either ignored or used in a stepwise but somewhat arbitrary manner, e.g. the famous method proposed by Hozo et al. We solve this issue by incorporating the sample size in a smoothly changing weight in the estimators to reach the optimal estimation. Our proposed estimators not only improve the existing ones significantly but also share the same virtue of the simplicity. The real data application indicates that our proposed estimators are capable to serve as “rules of thumb” and will be widely applied in evidence-based medicine.

Wan X., Wang W., Liu J., Tong T.

In systematic reviews and meta-analysis, researchers often pool the results of the sample mean and standard deviation from a set of similar clinical trials. A number of the trials, however, reported the study using the median, the minimum and maximum values, and/or the first and third quartiles. Hence, in order to combine results, one may have to estimate the sample mean and standard deviation for such trials. In this paper, we propose to improve the existing literature in several directions. First, we show that the sample standard deviation estimation in Hozo et al.’s method (BMC Med Res Methodol 5:13, 2005) has some serious limitations and is always less satisfactory in practice. Inspired by this, we propose a new estimation method by incorporating the sample size. Second, we systematically study the sample mean and standard deviation estimation problem under several other interesting settings where the interquartile range is also available for the trials. We demonstrate the performance of the proposed methods through simulation studies for the three frequently encountered scenarios, respectively. For the first two scenarios, our method greatly improves existing methods and provides a nearly unbiased estimate of the true sample standard deviation for normal data and a slightly biased estimate for skewed data. For the third scenario, our method still performs very well for both normal data and skewed data. Furthermore, we compare the estimators of the sample mean and standard deviation under all three scenarios and present some suggestions on which scenario is preferred in real-world applications. In this paper, we discuss different approximation methods in the estimation of the sample mean and standard deviation and propose some new estimation methods to improve the existing literature. We conclude our work with a summary table (an Excel spread sheet including all formulas) that serves as a comprehensive guidance for performing meta-analysis in different situations.

Viechtbauer W.

de Lima F.R., Molino G.O., Ruelas M.G., Barbosa E.C., Silva P.H., Guimarães F.B., Petrucci A.B., Silva G.H., Sbardelotto Â.E., Lança S.B., Garbacka A.

Heybati S., Malone S., Heybati K., Deng J., Zhou F., Roy A., Patel S., Muscedere J., Heffernan P.

Oliva J.G., Prado C.A., de Assis G.L., Figueiredo G.A., Ribeiro L.V., Porto M.A., Duarte M.F., Ribeiro N.N., Silva V.F., Coelho E.R.

Pereira M.A., Ferreira M.Y., Sousa M.P., Paula I.D., Ribeiro V.E., Soares V.G., de Oliveira C.M., Gonçalves O.R., Ribeiro F.V., Cabral S.G., Pereira A.F., Parmera J.B., Portela D.M., Brito H.N., Noleto G.S.

Dagher D., Kashir I., Mahboob O., Al-Turki N., Khan M.

Lech G.E., Vidotto L.M., Sturmer C.M., da Silveira C.A., Kasakewitch J.P., Lima D.L., Zhou Y., Choi J., Camacho D., Moran-Atkin E.

Zhu R., Zhang Z., Zhang N., Zhong H., Zhou F., Zhang X., Liu C., Huang Y., Yuan Y., Wang Y., Li C., Shi H., Rillig M.C., Dang F., Ren H., et. al.

Understanding how ecosystems respond to ubiquitous microplastic (MP) pollution is crucial for ensuring global food security. Here, we conduct a multiecosystem meta-analysis of 3,286 data points and reveal that MP exposure leads to a global reduction in photosynthesis of 7.05 to 12.12% in terrestrial plants, marine algae, and freshwater algae. These reductions align with those estimated by a constructed machine learning model using current MP pollution levels, showing that MP exposure reduces the chlorophyll content of photoautotrophs by 10.96 to 12.84%. Model estimates based on the identified MP-photosynthesis nexus indicate annual global losses of 4.11 to 13.52% (109.73 to 360.87 MT·y −1 ) for main crops and 0.31 to 7.24% (147.52 to 3415.11 MT C·y −1 ) for global aquatic net primary productivity induced by MPs. Under scenarios of efficient plastic mitigation, e.g., a ~13% global reduction in environmental MP levels, the MP-induced photosynthesis losses are estimated to decrease by ~30%, avoiding a global loss of 22.15 to 115.73 MT·y −1 in main crop production and 0.32 to 7.39 MT·y −1 in seafood production. These findings underscore the urgency of integrating plastic mitigation into global hunger and sustainability initiatives.

Zhang J., Wan Y., Liu L., Tang Y., Li P., Huang H.

Abstract Background Rituximab (RTX) is utilized for treating connective tissue disease-associated interstitial lung disease (CTD-ILD) by eliminating pathogenic B cells, yet its clinical benefit remains debated. This study evaluates RTX's efficacy and safety in CTD-ILD. Methods A literature search was conducted in PubMed, Embase, and Cochrane Library for studies on RTX in CTD-ILD up to May 24, 2024. The Joanna Briggs Institute checklist assessed study quality. Changes in forced vital capacity (FVC%) and diffusing capacity of the lungs for carbon monoxide (DLCO%) before and after RTX use were compared, and analyzed between RTX and control groups. Results 1052 CTD-ILD patients from 40 studies were analyzed. RTX significantly improved FVC% (WMD = 7.10, 95% CI = 4.58-9.62, P &lt; 0.05) and DLCO% (WMD = 5.26, 95% CI = 2.86-7.65, P &lt; 0.01), and reduced the modified Rodnan skin score (mRSS) (WMD = −6.58, 95% CI = −8.27 to −4.89, P &lt; 0.01) and prednisone dose (WMD = −6.94, 95% CI = −11.96 to −1.92, P &lt; 0.01). Among RTX-treated patients, 30.3% improved, 45.3% remained stable, and 10.0% progressed. Adverse effects included infection (22.4%), hospitalization (6.7%), and mortality (5.0%). Conclusions RTX significantly enhances lung function in CTD-ILD patients, as shown in this systematic review and meta-analysis. Systematic review registration PROSPERO, identifier CRD42024520084.

Mekontso J.G., Nnang J.Y., Tembi T.B., Kortim A.B., Nguefang G.L., Wagner J., Bernstein M.

Mousavi S.M., Younesian S., Ejtahed H.

Wang L., Zhou J., Jing S., Liu B., Fang J., Xue T.

Kronenberger D., Zimmers T., Ralston R., Runco D.

ABSTRACTBackgroundGrowth Differentiation Factor 15 (GDF15), a nonspecific inflammatory marker and member of the TGF‐β superfamily, has a well‐established role in both inflammation and metabolic modulation, but lacks a comprehensive paediatric literature review. In several adult disease states, including cancer cachexia and pregnancy, circulation and expression of GDF15 has been of clinical and scientific interest, but little published paediatric data exists. As such, we aim to summarize existing paediatric studies.MethodsThis review follows the PRISMA‐ScR guidelines for reporting and aims to summarize existing paediatric studies including GDF15, describe disease entities in which GDF15 has been investigated including existing reference ranges, and identify literature gaps to present future clinical and research direction. Our search strategy queried Ovid MEDLINE, Ovid Embase, Cochrane Library and Scopus databases to find original scientific articles measuring GDF15 from birth through children up to age 18. Data relating to study participant demographic and disease pathology, GDF15 measurement methods and clinical outcomes of interest were extracted.ResultsSixty‐two studies were included, classified as cardiac, endocrine, mitochondrial, hematologic, neonatal, oncologic, infectious, rheumatologic, renal, neurologic or healthy. While several entities demonstrated elevated GDF15, the highest median GDF15 levels were observed in cardiac arrest 7089 pg/mL (interquartile range 3805–13 306) and mitochondrial diseases 4640 pg/mL (1896–14 064). In certain conditions, including cardiac stress, polycystic ovarian syndrome (PCOS), Kawasaki Disease (KD) and certain mitochondrial myopathies GDF15 can normalize with disease treatment or resolution. Of healthy children studied, GDF15 levels were highest in healthy neonates and followed a predictable pattern, decreasing over time. Mean and standard deviation values of GDF15 in healthy children were 343.8 ± 221.0 pg/mL, with a range of 90–1134 pg/mL for study averages.ConclusionsCirculating GDF15 has been studied in a variety of paediatric diseases. However, variable evaluated outcome measures and GDF15 measurement methodologies prevent generalizability and direct comparison of these published studies. Validating normal GDF15 levels in children with standardized and reproducible methodology will help clarify GDF15's utility as a diagnostic marker of disease, a necessary step to elucidate clinical implications of GDF15 over expression and its potential as a therapeutic target.

Zhong Z., Fan F., Lv J., Wang Z., Wang B., Deng C., Sun L.

Gut bacteria that potential produce short-chain fatty acids (SCFAs) influences the recovery of motor function in the host in patients with spinal cord injury (SCI). We aimed to conduct a review and meta-analysis of the literature on gut microbiota in SCI patients. Following the Preferred Reporting Project for Systematic Review and Meta-Analysis (PRISMA), we searched Embase, PubMed, Cochrane Library, Web of Science (WOS) and ClinicalTrials.gov. The search period was from inception to March 31, 2024. We reported standardized mean differences (d) with 95% confidence intervals (CI) and used funnel plots and Egger tests to assess publication bias. The subacute of SCI data set revealed the microflora changes in the subacute phase, and meta-analysis summarized the changes in the chronic phase. Eleven studies (720 participants) were included, 2 phyla, 1 order, and 14 genus meta-analyses performed. No substantial heterogeneity was observed, and significant publication bias was not found among the studies included. In the subacute phase of spinal cord injury, the relative abundance of Bacteroidetes, Clostridiales, Faecalbacterium, Ruminococcus, Coprococcus, Lachnospira, Dorea, Prevotella, Roseburia, Atopobium, Bifidobacterium, Bacteroides, and Blautia increased. Firmicutes and Lactobacillus decreased. In the chronic phase, Firmicutes decreased in the SCI group. Bifidobacterium, Bacteroides, Blautia, and Eubacterium were found to have a higher average proportion of abundance in patients with SCI compared to non-SCI persons, and Clostridiales, Ruminococcus, Faecalbacterium, Coprococcus, and Lachnospira showed a lower relative abundance in SCI. The genus of potential SCFAs-producing bacteria is lower in the chronic phase of spinal cord injury than in the subacute phase, and gut dysbiosis is present in both the subacute and chronic phases.

Cai X., Ling W., Cai X., Yan M., Zhang Y., Xu J.

ObjectivesSepsis-associated hypotension or shock is a critical stage of sepsis, and a current clinical emergency that has high mortality and multiple complications. A new restrictive fluid resuscitation therapy has been applied, and its influence on patients’ renal function remains unclear. The purpose of this study is to evaluate the influence of restrictive fluid resuscitation on incidence of severe acute kidney injury (AKI) in adult patients with sepsis hypotension and shock compared with usual care.DesignSystematic review and meta-analysis using the Grades of Recommendation, Assessment, Development and Evaluation (GRADE) approach.Data sourcesPubMed, Embase, Web of Science and Cochrane Library were searched through 1 November 2024.Eligibility criteriaWe included randomised controlled trials that compared restrictive fluid resuscitation with liberal fluid therapy on patients with sepsis-associated hypotension and shock, to find out their effect on the incidence of severe AKI. Severe AKI was defined as the AKI network score 2–3 or Kidney Disease Improving Global Outcomes stages 2 and 3.Data extraction and synthesisTwo independent reviewers used standardised methods to search, screen and code included trials. Risk of bias was assessed using the Cochrane Systematic Review Handbook for randomised clinical trials. Meta-analysis was conducted using random effects models. Sensitivity and subgroup analyses, trial sequential analysis (TSA), Egger’s test and the trim-and-fill method were performed. Findings were summarised in GRADE evidence profiles and synthesised qualitatively.ResultsNine trials (3718 participants) were included in this research and the analysis was conducted in random effects model. There was a significant difference in the incidence of severe AKI (risk ratio 0.87, 95% CI 0.79 to 0.96, p=0.006; I2=0%) and the duration of mechanical ventilation (mean difference −41.14, 95% CI −68.80 to −13.48; p=0.004; I2=74%) between patients receiving restrictive fluid resuscitation and patients receiving liberal fluid resuscitation. TSA showed that the cumulative amount of participants met the required information size, the positive conclusion had been confirmed. The GRADE assessment results demonstrated moderate confidence in the incidence of severe AKI, as well as the results of all second outcomes except the Intensive Care Unit length of stay (ICU LOS), which received limited confidence. The result of incidence of worse AKI was rated as of high certainty.ConclusionsIt is conclusive that fluid restriction strategy is superior to usual care when it comes to reducing the incidence of severe AKI in sepsis-associated hypotension and shock. Shorter duration of ventilation is concerned with fluid restriction as well, but the heterogeneity is substantial. GRADE assessments confirmed moderate and above certainty. Traditional fluid resuscitation therapy has the potential to be further explored for improvements to be more precise and appropriate for a better prognosis.PROSPERO registration numberCRD42023449239.

Bitar A., Almahder D., A. Jouini J., Alsaid B.

Background: This study investigated the link between arterial tortuosity and cervical artery dissection, focusing on carotid and vertebral tortuosity indices, as well as carotid tortuosity classifications (kinking, looping, and coiling). Methods: We searched PubMed, SCOPUS, Web of Science, and Google Scholar from database inception to January 2024. The inclusion criteria encompassed human studies on tortuosity and cervical, carotid, or vertebral artery dissection. Exclusion criteria included case reports, non-English studies, and studies solely on connective tissue disorders and diseases. Quality and risk of bias were assessed using the Newcastle-Ottawa Scale. Random-effects model was employed for mean differences and odds ratios. When meta-analysis was not feasible, we summarized and integrated the results narratively. Results: Seven studies, involving 507 dissected patients and 582 non-dissected patients, were included. In a meta-analysis of 3 studies, vertebral tortuosity favored the dissection cases [MD = 3.58, 95% CI: 2.21–4.95]. The mean carotid tortuosity difference was not statistically significant in a meta-analysis of 2 studies [MD = 2.27, 95% CI: −0.16–4.70]. In the classification analysis, 2 studies indicated no conclusive association between kinking, coiling, and cervical arteries dissection. Regarding carotid classification and internal carotid artery dissection, meta-analyses only showed a significant association with kinking, but the result was inconclusive. Conclusion: Tortuosity index screenings may help prevent cervical artery dissection among at-risk individuals. However, the association with specific tortuosity classifications remains inconclusive, and further research is needed to validate these findings. Standardized measurement criteria are crucial for future studies.