中医封包治疗老年男性患者尿潴留疗效观察

目的探讨中医封包治疗老年男性患者尿潴留的临床效果。方法将117例老年男性尿潴留患者随机分为两组,观察组(中医封包治疗)59例,对照组(诱导排尿)58例。两组观察自行排尿及尿潴留症状缓解情况,并判断疗效。结果观察组39例自行排尿,有效率66.1%,对照组25例自行排尿,有效率43.1%,两组比较差异有统计学意义(χ~2=6.243,P=0.012)。结论中医封包治疗老年男性患者尿潴留效果优于传统诱导排尿方法,是适合老年男性尿潴留患者的简便、安全无创,经济有效的方法。     

锐利器械不同保护法的效果研究

目的:研究尖锐器械在低温灭菌过程中的保护方法。方法:将2012年9月~201 3年6月供应室清洗后的再生穿刺针类器械741个,随机分为头皮针软管组、尿管组,分别使用头皮针软管、尿管做成保护帽,对锐利器械采取保护措施,并与2010年1月~3月使用纱布保护套的335个尖锐器械作对比,对其保护效果进行研究。结果:头皮针软管组包装及器械完好性达100%;尿管组纸塑袋包装破损32个,破损率8.7%,10个器械发生损坏占2.7%;纱布组管纸塑袋破损71个,破损率21.2%,器械损坏29个,破损率8.66%;三组包装破损率比较P<0.05,头皮针软管组、尿管组器械破损率分别与纱布组比较P<0.05,差异均有统计学意义。结论:头皮针软管能保护尖锐器械及包装的完好性,可根据器械的规格型号及数量选取相应的保护措施,以达院感要求。     

全自动血型仪2种不同交叉配血流程比较

目的通过对供血者标本采用2种不同工作流程,观察交叉配血结果的一致性及所用时间,为临床工作提供最佳的工作流程。方法分别采用供血者压积红细胞标本、供血者稀释为1%悬液红细胞标本和相同的受血者标本在全自动血型仪上进行主侧交叉配血试验,比较全自动血型仪交叉配血结果的一致性。分别比较供血者压积红细胞标本工作流程和供血者稀释为1%悬液红细胞标本工作流程供血者血液标本前处理,标本处理中,标本后处理,及标本全程处理所用的平均时间。结果供血者压积红细胞标本和供血者稀释为1%悬液红细胞标本全自动血型仪交叉配血结果差异无统计学意义(U=0,P0.05)。供血者压积红细胞标本和供血者稀释为1%悬液红细胞标本工作流程供血者血液标本标本前处理、标本处理中平均用时比较,差异无统计学意义(t=0.692、t=0.562,P0.05),标本后处理和标本全程处理平均用时差异有统计学意义(t=146.485、t=67.053,P0.05)。结论供血者稀释为1%悬液红细胞标本工作流程,其标本后处理,标本全程处理所用的平均时间更短,更加适合标本量大的医院在临床工作中使用。     

Clinical phenotyping in selected national networks: demonstrating the need for high-throughput,portable, and computational methods

ObjectiveThe combination of phenomic data from electronic health records (EHR) and clinical data repositories with dense biological data has enabled genomic and pharmacogenomic discovery, a first step toward precision medicine. Computational methods for the identification of clinical phenotypes from EHR data will advance our understanding of disease risk and drug response, and support the practice of precision medicine on a national scale.MethodsBased on our experience within three national research networks, we summarize the broad approaches to clinical phenotyping and highlight the important role of these networks in the progression of high-throughput phenotyping and precision medicine. We provide supporting literature in the form of a non-systematic review.ResultsThe practice of clinical phenotyping is evolving to meet the growing demand for scalable, portable, and data driven methods and tools. The resources required for traditional phenotyping algorithms from expert defined rules are significant. In contrast, machine learning approaches that rely on data patterns will require fewer clinical domain experts and resources.ConclusionsMachine learning approaches that generate phenotype definitions from patient features and clinical profiles will result in truly computational phenotypes, derived from data rather than experts. Research networks and phenotype developers should cooperate to develop methods, collaboration platforms, and data standards that will enable computational phenotyping and truly modernize biomedical research and precision medicine.     

Validation and utilisation of a digital version of the survey instrument for natural history,Aetiology and Prevalence of Patellofemoral pain studies (eSNAPPS)

ObjectiveThis study validated the newly adapted electronic SNAPPS (eSNAPPS) against the original paper SNAPPS. Subsequently, the study estimated the prevalence of PFP in running participants and spectators attending three mass-participant running events in the United Kingdom by using the eSNAPPS tool.DesignThis study had two parts. Firstly, a validation of the original paper version of the SNAPPS tool. Secondly, if validation was achieved, eSNAPPS was used in a prevalence study.ParticipantsA convenience sample of running participants and spectators aged 18–40 years attending the mass participation running events.Main outcome measureThe 12-month prevalence of PFP.Results: eSNAPPS was valid in identifying those with PFP (ICC 0.99 for Overall agreement, p < 0.0001). In the prevalence study, a total of 1080 running participants and spectators completed the eSNAPPS. The overall prevalence of PFP was 17.4% (95%CI: 15.2%, 19.8%); 20.5% of males (16.5, 24.9) and 15.7% of females (13.1, 18.7) had PFP. Prevalence was 17.4% (15.2, 19.8) in spectators and 16.7% in running participants (14.5, 19.0).ConclusionThe overall PFP prevalence in this study was slightly smaller than those previously reported in the literature. Findings also show that there were similar prevalence estimates in spectators and running participants.     

Psychometric properties of the Neck OutcOme Score,Neck Disability Index,and Short Form–36 were evaluated in patients with neck pain

ObjectiveTo assess reliability, construct validity, responsiveness, and interpretability for Neck OutcOme Score (NOOS), Neck Disability Index (NDI), and Short Form–36 (SF-36) in neck pain patients.Study Design and SettingInternal consistency was assessed by Cronbach alpha. Test-retest reliability was evaluated by intraclass correlation coefficient (ICC), and measurement error was estimated from the standard error of measurement. Responsiveness was assessed as standardized response mean (SRM) and interpretability from the minimal important difference (MID). Construct validity was tested correlating subscale scores from NOOS and SF-36 and NDI items.ResultsAt baseline, 196 neck pain patients were included. Cronbach α was adequate for most NOOS subscales, NDI, and SF-36 with few exceptions. Good to excellent reliability was found for NOOS subscales (ICC 0.88–0.95), for NDI, and for SF-36 with few exceptions. For NOOS, minimal detectable changes varied between 1.1 and 1.9, and construct validity was supported. SRMs were higher for NOOS subscales (0.19–0.42), compared to SF-36 and NDI. MID values varied between 15.0 and 24.1 for NOOS subscales.ConclusionsIn conclusion, the NOOS is a reliable, valid, and responsive measure of self-reported disability in neck pain patients, performing at least as well or better than the commonly used SF-36 and NDI.