HIV treatment outcomes among people who acquired HIV via injecting drug use in the Asia‐Pacific region: a longitudinal cohort study

INTRODUCTIONData on HIV treatment outcomes in people who inject drugs (PWID) in the Asia‐Pacific are sparse despite the high burden of drug use. We assessed immunological and virological responses, AIDS‐defining events and mortality among PWID receiving antiretroviral therapy (ART).METHODSWe investigated HIV treatment outcomes among people who acquired HIV via injecting drug use in the TREAT Asia HIV Observational Database (TAHOD) between January 2003 and March 2019. Trends in CD4 count and viral suppression (VS, HIV viral load <1000 copies/mL) were assessed. Factors associated with mean CD4 changes were analysed using repeated measures linear regression, and combined AIDS event and mortality were analysed using survival analysis.RESULTSOf 622 PWID from 12 countries in the Asia‐Pacific, 93% were male and the median age at ART initiation was 31 years (IQR, 28 to 34). The median pre‐ART CD4 count was 71 cells/µL. CD4 counts increased over time, with a mean difference of 401 (95% CI, 372 to 457) cells/µL at year‐10 (n = 78). Higher follow‐up HIV viral load and pre‐ART CD4 counts were associated with smaller increases in CD4 counts. Among 361 PWID with ≥1 viral load after six months on ART, proportions with VS were 82%, 88% and 93% at 2‐, 5‐ and 10‐years following ART initiation. There were 52 new AIDS‐defining events and 50 deaths during 3347 person‐years of follow‐up (PYS) (incidence 3.05/100 PYS, 95% CI, 2.51 to 3.70). Previous AIDS or TB diagnosis, lower current CD4 count and adherence <95% were associated with combined new AIDS‐defining event and death.CONCLUSIONSDespite improved outcomes over time, our findings highlight the need for rapid ART initiation and adherence support among PWID within Asian settings.     

A simple scoring system to estimate perioperative mortality following liver resection for primary liver malignancy—the Hepatectomy Risk Score (HeRS)

BackgroundSelection of the optimal treatment modality for primary liver cancers remains complex, balancing patient condition, liver function, and extent of disease. In individuals with preserved liver function, liver resection remains the primary approach for treatment with curative intent but may be associated with significant mortality. The purpose of this study was to establish a simple scoring system based on Model for End-stage Liver Disease (MELD) and extent of resection to guide risk assessment for liver resections.MethodsThe 2005–2015 NSQIP database was queried for patients undergoing liver resection for primary liver malignancy. We first developed a model that incorporated the extent of resection (1 point for major hepatectomy) and a MELD-Na score category of low (MELD-Na =6, 1 point), medium (MELD-Na =7–10, 2 points) or high (MELD-Na >10, 3 points) with a score range of 1–4, called the Hepatic Resection Risk Score (HeRS). We tested the predictive value of this model on the dataset using logistic regression. We next developed an optimal multivariable model using backwards sequential selection of variables under logistic regression. We performed K-fold cross validation on both models. Receiver operating characteristics were plotted and the optimal sensitivity and specificity for each model were calculated to obtain positive and negative predictive values.ResultsA total of 4,510 patients were included. HeRS was associated with increased odds of 30-day mortality [HeRS =2: OR =3.23 (1.16–8.99), P=0.025; HeRS =3: OR =6.54 (2.39–17.90), P<0.001; HeRS =4: OR =13.69 (4.90–38.22), P<0.001]. The AUC for this model was 0.66. The AUC for the optimal multivariable model was higher at 0.76. Under K-fold cross validation, the positive predictive value (PPV) and negative predictive value (NPV) of these two models were similar at PPV =6.4% and NPV =97.7% for the HeRS only model and PPV =8.4% and NPV =98.1% for the optimal multivariable model.ConclusionsThe HeRS offers a simple heuristic for estimating 30-day mortality after resection of primary liver malignancy. More complicated models offer better performance but at the expense of being more difficult to integrate into clinical practice.     

Comparative effectiveness of robotic and open radical prostatectomy

Radical prostatectomy (RP) has undergone a remarkable transformation from open to minimally-invasive surgery over the last two decades. However, it is important to recognize there is still conflicting evidence regarding key outcomes. We aimed to summarize current literature on comparative effectiveness of robotic and open RP for key outcomes including oncologic results, health-related quality of life (HRQOL) measures, safety and postoperative complications, and healthcare costs. The bulk of the paper will discuss and interpret limitations of current data. Finally, we will also highlight future directions of both surgical approaches and its potential impact on health care delivery.     

Clinical prediction models to predict the risk of multiple binary outcomes: a comparison of approaches

Clinical prediction models (CPMs) can predict clinically relevant outcomes or events. Typically, prognostic CPMs are derived to predict the risk of a single future outcome. However, there are many medical applications where two or more outcomes are of interest, meaning this should be more widely reflected in CPMs so they can accurately estimate the joint risk of multiple outcomes simultaneously. A potentially naïve approach to multi‐outcome risk prediction is to derive a CPM for each outcome separately, then multiply the predicted risks. This approach is only valid if the outcomes are conditionally independent given the covariates, and it fails to exploit the potential relationships between the outcomes. This paper outlines several approaches that could be used to develop CPMs for multiple binary outcomes. We consider four methods, ranging in complexity and conditional independence assumptions: namely, probabilistic classifier chain, multinomial logistic regression, multivariate logistic regression, and a Bayesian probit model. These are compared with methods that rely on conditional independence: separate univariate CPMs and stacked regression. Employing a simulation study and real‐world example, we illustrate that CPMs for joint risk prediction of multiple outcomes should only be derived using methods that model the residual correlation between outcomes. In such a situation, our results suggest that probabilistic classification chains, multinomial logistic regression or the Bayesian probit model are all appropriate choices. We call into question the development of CPMs for each outcome in isolation when multiple correlated or structurally related outcomes are of interest and recommend more multivariate approaches to risk prediction.     

What is the impact of day care on older people with long-term conditions: A systematic review

There is a lack of robust evidence regarding outcomes for day care use among older people living with long-term conditions (LTCs). Day care is provided by independent, private and voluntary and charitable sectors. This systematic review aims to establish current evidence of outcomes for older people with LTCs attending day care services and outcomes on carers, across all service models. Narrative synthesis of quantitative and qualitative data was undertaken. The review adhered to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. A systematic literature search was carried out across eight electronic databases and reference lists of key journals between 2004 and October 2020 were searched. Searches returned 1,202 unique titles. Forty-five articles from 16 countries met the criteria on review of title, abstract and full article. There is limited evidence suggesting improved levels of perceived psychological health, quality of life, perceived general health, physical health and functioning for older people attending day care who have LTCs. The respite function of day care resulted in positive outcomes for carers. Studies evaluating outcomes for participants or carers were limited in quantity and quality. There is limited information regarding outcomes for day care attendance for older people with multiple LTCs from existing literature. Further research focusing on LTCs and day care attendance would benefit this field.     

改良新产程模式管理硬膜外麻醉无痛分娩产程对母婴结局的影响

目的探讨应用改良新产程模式管理硬膜外麻醉无痛分娩产程对母婴结局的影响。方法选取2018年1月-2020年2月在长春市妇产医院自愿行硬膜外麻醉无痛分娩的单胎初产足月妊娠产妇220例为研究对象,随机分为观察组和对照组,每组各110例。观察组产妇应用改良新产程模式管理无痛分娩,对照组产妇应用新产程模式管理产程无痛分娩。观察两种产程管理模式管理产程对母婴结局影响。结果观察组产妇潜伏期、加速期及第二产程时间均较对照组明显缩短,差异均有统计学意义(均P<0.01)。两组产妇剖宫产率和产后出血率比较,差异无统计学意义(P>0.05)。观察组产妇阴道助产率明显低于对照组,差异有统计学意义(P<0.05)。观察组产妇产后出血量明显少于对照组,差异有统计学意义(P<0.05)。观察组新生儿脐动脉血pH值<7.2比例低于对照组,差异有统计学意义(P<0.05)。结论采用改良新产程模式管理的硬膜外麻醉无痛分娩产妇产程时限明显缩短,阴道助产率降低,产后出血量明显减少,新生儿脐动脉血pH值<7.2比例明显降低,因此改良新产程模式管理产程,可有效保证母婴安全。     

子痫前期患者血清AFP、D-二聚体、PLGF水平对母体及妊娠结局影响

目的:分析子痫前期(PE)患者血清甲胎蛋白(AFP)、D-二聚体(D-dimer)及胎盘生长因子(PLGF)水平对母体及妊娠结局的影响。方法:将本院2016年1月-2018年9月收治的330例PE患者分轻度PE组(n=117)、重度PE组(n=213),另选同期本院住院待产的正常妊娠产妇30例为对照组,检测各组孕妇血清AFP、D-dimer、PLGF水平,绘制受试者工作特征(ROC)曲线分析对PE的诊断预测效能;Spearman相关性分析各检测指标与病情的相关性;对PE患者妊娠结局的预测效能。结果:PE组与对照组AFP比较无差异(P>0.05),但D-dimer水平PE组高于对照组,PLGF低于对照组(P<0.05);D-dimer AUC值最高(387.51μg/L),预测PE的敏感度、特异度为80.6%、100.0%;PLGF AUC值次之(217.33pg/ml),预测PE的敏感度为96.7%,高于D-dimer。不同病情严重程度的PE患者血清AFP、PLGF水平未见差异(P>0.05),但D-dimer轻度PE组低于重度PE组(P<0.05)。AFP与PE病情程度未见相关性(r=0.093,P=0.078),D-dimer与PE病情程度正相关(r=0.796,P=0.000),PLGF与PE病情程度负相关(r=0.114,P=0.031)。PE患者中,母体发生并发症、胎儿结局不良者血清D-dimer水平高于无并发症、胎儿结局良好者(P<0.05),AFP、PLGF未见差异(P>0.05);D-dimer对PE患者并发症可发挥一定预测效能,以579.53μg/L为cut-off,预测PE患者并发症的敏感度、特异度为80.9%、61.9%,另两项血清指标对妊娠结局的预测效能不佳。结论:血清AFP、D-dimer、PLGF3个指标中,D-dimer对PE的预测价值及其与PE病情的相关性最为显著,用于预测PE患者母体并发症具有一定敏感度,但特异度不佳。