Search

The COVID-19 pandemic prompted widespread closures of primary and secondary schools. Routine testing of asymptomatic students and staff members, as part of a comprehensive mitigation program, can help schools open safely. “Pooling in a pod” is a public health surveillance strategy whereby testing cohorts (pods) are based on social relationships and physical proximity. Pooled testing provides a single laboratory test result for the entire pod, rather than a separate result for each person in the pod. During the 2020-2021 school year, an independent preschool–grade 12 school in Washington, DC, used pooling in a pod for weekly on-site point-of-care testing of all staff members and students. Staff members and older students self-collected anterior nares samples, and trained staff members collected samples from younger students. Overall, 12 885 samples were tested in 1737 pools for 863 students and 264 staff members from November 30, 2020, through April 30, 2021. The average pool size was 7.4 people. The average time from sample collection to pool test result was 40 minutes. The direct testing cost per person per week was $24.24, including swabs. During the study period, 4 surveillance test pools received positive test results for COVID-19. A post-launch survey found most parents (90.3%), students (93.4%), and staff members (98.8%) were willing to participate in pooled testing with confirmatory tests for pool members who received a positive test result. The proportion of students in remote learning decreased by 62.2% for students in grades 6-12 ( P < .001) and by 92.4% for students in preschool to grade 5 after program initiation ( P < .001). Pooling in a pod is a feasible, cost-effective surveillance strategy that may facilitate safe, sustainable, in-person schooling during a pandemic.

Background and objectives Outpatient parenteral antimicrobial therapy (OPAT) for infections has been in use for nearly 40 years, and although it has been found safe and efficacious, its use has been studied primarily among otherwise healthy patients. We aimed to develop and evaluate an OPAT program for patients with cancer, particularly solid tumors. Methods We implemented multiple quality improvement interventions between June 2018 and January 2020. We retrospectively and prospectively collected data on demographics, the completeness of infectious diseases (ID) physician consultation notes, rates of laboratory test result monitoring, ID clinic follow-up, and 30-day outcomes, including unplanned OPAT-related readmissions, OPAT-related emergency center visits, and deaths. Results Completeness of ID provider notes improved from a baseline of 77 to 100% (p p p p = .027). Thirty-day unplanned OPAT-related readmission, ID clinic follow-up, 30-day emergency center visit, and death rates improved without reaching statistical significance. Conclusions Sustained efforts, multiple interventions, and multidisciplinary engagement can improve laboratory test result monitoring among solid tumor patients discharged with OPAT. Although demonstrating a decrease in unplanned readmissions through institution of a formal OPAT program among patients with solid malignancies may be more difficult compared with the general population, the program may still result in improved safety.

Laboratory test reports are often used as one of the pieces of evidence needed in proving civil environmental justice cases. This study analyses court decisions and their ability to elaborate probl...

This paper provides an introduction to laboratory databases established by Taiwan National Health Insurance Administration (NHIA) since 2015 and released for research since June 2017. The National Health Insurance (NHI) is a government-run single-payer program introduced in 1995 that now covers more than 99% of 23 million Taiwanese citizens. To prevent duplication of medication prescriptions and laboratory test and examination prescriptions, contracted health care providers are required to upload the results of laboratory tests and reports of examinations to the NHIA. The cumulative number of laboratory test results was 5.64 billion from January 2015 to the end of August 2020 for 602 types of test. There are 35 variables for each laboratory test result stored in the databases that can be used for research. However, different hospitals might use different format in reporting the results. The researchers therefore have to develop algorithms to include and exclude incompatible records and to determine whether the results are positive or negative (normal or abnormal). The NHIA suggests that researchers release their source codes of algorithms so that other researchers can modify the codes to improve inter-study comparability. Through the unique personal identification number, the laboratory data can be linked to NHI inpatient and outpatient claims data for further value-added analyses. Non-Taiwanese researchers can collaborate with Taiwan researchers to access the NHI laboratory databases.

Background: Auto-approval (also known as autoverification) is the task of automatically evaluating the consistency of a test result throughout the laboratory information system rather than its manual evaluation by the biochemists. Most of the existing auto-approval systems rely on a rule-based solution obtained from expert knowledge. However, it is a challenging issue to produce a complete and general rule-base for every single test type. To that end, the studies have relied only on a small subset of laboratory tests. Methods: The rule-based auto-approval process was re-investigated in this study, and the rules predetermined by human experts were utilized as a pre-filtering step for grouping the laboratory test result via some common criteria. Subsequently, a machine learning-based approval method, smart-approval, was proposed to approve the tests more precisely. At this point, the expert knowledge in the rule-based pre-filtering was extended by the tendency to imitate the experts’ behavior in the smart-approval step. Two novel datasets (entitled with plot and real-time datasets) containing human experts’ responses to previously studied tests have been used to train the machine learning models. Results: Experiments have been handled on several machine learning models on plot dataset to obtain the trained models based on cross-validation. Here, the random forest classifier provided the best approval performance while also outperforming the approval success of existing studies in the literature. To observe the real-time performance of these trained models, they were also evaluated on real-time unseen data for 4 months. Here, random forest reaffirmed that it was the best approval model. Conclusions: The proposed auto-approval system relying on random forest can provide convincing classification performance on both of the obtained datasets. With the correct approval rate of 98.51%, it surpasses many powerful approval methods in the literature.

BACKGROUND While researchers seek to use administrative health data to examine outcomes for individuals with sexually transmitted infections (STIs), the International Classification of Diseases, Tenth Revision, Clinical Modification (ICD-10-CM) codes used to identify persons with chlamydia and gonorrhea have not been validated. Objectives were to determine the validity of using ICD-10-CM codes to identify individuals with chlamydia and gonorrhea. METHODS We used data from electronic health records gathered from public and private health systems from October 1, 2015, to December 31, 2016. Patients were included if they were aged 13 to 44 years and received either (1) laboratory testing for chlamydia or gonorrhea or (2) an ICD-10-CM diagnosis of chlamydia, gonorrhea, or an unspecified STI. To validate ICD-10-CM codes, we calculated positive and negative predictive values, sensitivity, and specificity based on the presence of a laboratory test result. We further examined the timing of clinical diagnosis relative to laboratory testing. RESULTS The positive predictive values for chlamydia, gonorrhea, and unspecified STI ICD-10-CM codes were 87.6%, 85.0%, and 32.0%, respectively. Negative predictive values were high (>92%). Sensitivity for chlamydia diagnostic codes was 10.6%, and gonorrhea was 9.7%. Specificity was 99.9% for both chlamydia and gonorrhea. The date of diagnosis occurred on or after the date of the laboratory result for 84.8% of persons with chlamydia, 91.9% for gonorrhea, and 23.5% for unspecified STI. CONCLUSIONS Disease-specific ICD-10-CM codes accurately identify persons with chlamydia and gonorrhea. However, low sensitivities suggest that most individuals could not be identified in administrative data alone without laboratory test results.

Professional autonomy is defined as the quality or state of being independent and self-directing, having authority to make decisions, enabling professionals to exercise judgment in accordance with one’s professional knowledge base and regulatory framework. The aim of this review is to highlight the importance of professional autonomy in the running of diagnostic laboratories in Nigeria. Professional autonomy is the professional duty of care and working within the legal, ethical and regulatory frameworks that govern a profession. Pathology is the study of diseases. It is the bridge between science and medicine. While the Medical Laboratory Scientist manages the science side of pathology, Pathologist manages the medicine or clinical part of the bridge. Medical Laboratory Scientists in Nigeria are regulated by the Medical Laboratory Science Council of Nigeria (MLSCN) while Pathologists are regulated by the Medical and Dental Council of Nigeria (MDCN). The role of the Medical Laboratory Scientist as a Laboratory Manager is huge and involves the management of staff regulated by the MLSCN (Medical Laboratory Scientists, Technicians and Assistants) including support staffs, equipment, reagents and consumables in the delivery of accurate, precise, reproducible and timely diagnostic results that enable clinicians to make an informed decision in the effective management of patients. They provides medical laboratory diagnostic products and services; evaluate laboratory information management system (LIMS); report results according to SOP and protocols; maintain medical laboratory equipment performance, service, repair, replace and troubleshoot; ensure staff training and compliance; carry out instrument validation and reagent certification; forecasting and budgeting; manage diagnostic laboratory revolving funds, inventory control management of equipment, reagents and consumables; maintain medical laboratory productivity by monitoring and scheduling workload and making operational or staffing adjustment; ensures that laboratory participates in external quality assurance and have a robust internal quality control program; perform laboratory staff proficiency testing; develop SOP, procedures and protocols; train employees; maintain security and confidentiality of patient data; carry out staff recruitment, orienting, training, appraisal, counseling, retention and discipline; ensures that laboratory staff maintain their professional license and are involved in continuous professional development; review professional publications; help in the induction and orientation of new staff, trainee physicians, nurses, students and visitors to the diagnostic laboratory; perform quality audits and provide administrative support and supervision of Medical Laboratory Scientist on call. Pathologists on the other hand run their specialty-based clinics; take consults from the clinical colleagues; perform clinical audits; act as clinical liaison in the interpretation of specialized laboratory test result to their clinical colleagues; offer specialty-based clinical advice to their colleagues; be on call to manage their patients on admission as well supervise their trainee pathologist on call; train their residents; carry out clinical research; manage their clinical budget and clinical-related revolving funds. It is the best practice that the scientific aspect of the bridge is managed and headed by a Medical Laboratory Scientist while the medicine aspect is headed and managed by the Pathologist. It is against the principle of professional autonomy, harmony and holistic care for diagnostic laboratories predominantly staffed by professionals regulated by the MLSCN (Medical Laboratory Scientist, Technicians and Technicians) to be headed by another professional who is regulated by a different regulatory agency and who is not privy of the MLSCN requirements and standards required for the training, management and practice of the profession of Medical Laboratory Science. The implementation of these best evidence-based practices is needed to allow for harmony in diagnostic laboratories in Nigeria and will facilitate the rendering of best and holistic medical care to well-meaning Nigerians.

A diverse array of continuous, multi-parameter and alarm-equipped physiologic monitoring devices have been deployed in modern intensive care units (ICUs) and other critical care settings to detect changes in a patient's status. Alarm signals activated by the monitors are intended to alert caregivers to either abnormalities in a patient's normal state or device malfunctions in order to prevent adverse events, and hence improve quality of care and patient safety. The majority of patients who eventually experience adverse events such as in-hospital cardiac arrest (IHCA) frequently exhibit signs of clinical deterioration that are evidence in symptoms and abnormalities in the physiological vital signs and laboratory test results preceding the events. Unfortunately, the signs of deterioration are often unrecognized and missed by caregivers due to the widespread and well-documented alarm fatigue problem, which is chiefly attributable to the excessive number of false and nuisance alarms generated by the physiologic monitors and subsequently leads to the failure-to-rescue (FTR) problem.The overarching goal of the present dissertation is to predict patient deterioration, particularly code blue events and offer a potential solution for alarm fatigue problem by leveraging monitor alarms available from physiologic monitors and laboratory test results available in the electronic heath record (EHR) system. Several studies are performed in this dissertation to achieve this objective.First, caregivers in the ICUs undergoing alarm fatigue are typically overloaded by the overwhelming number of heterogeneous raw data that have not been utilized effectively to uncover the underlying knowledge of patient deterioration. To overcome the issue of data overload, we have developed a data fusion framework to identify multivariate combinations of monitor alarms and laboratory test results that co-occur high frequently in a time window preceding code blue events but rarely among control patients. We proposed two approaches to integrate laboratory test results with monitor alarms. We exploited the maximal frequent itemset algorithm to mine the multivariate combinations in a time window preceding code blue events. The resultant combinations are further filtered out if they also occur sufficiently often among all control patients. The remainder of combinations are termed "SuperAlarm patterns".Moreover, deploying SuperAlarm patterns to monitor patients and detection of the emerging ones can alert caregivers to the changes in the patient's status. The emerging SuperAlarm patterns are termed "SuperAlarm triggers". The consecutive SuperAlarm triggers over time generate "SuperAlarm sequences". Whereas, the SuperAlarm triggers may have redundancy that may also lead to alarm fatigue. Thereby, we developed a sequence classifier to recognize temporal patterns in SuperAlarm sequences. The sequence classifier essentially functions as a filter of SuperAlarm triggers. In addition, we tested the hypothesis that SuperAlarm sequences may contain more predictive temporal patterns than monitor alarms sequences. We proposed novel method to sample subsequences, and utilized the term frequency inverse document frequency (TFIDF) to represent the subsequences. We used the information gain (IG) to selection the most relevant SuperAlatm patterns to the code blue events, and the weighted support vector machine (SVM) to perform classification. The results have demonstrated that sequence classifier based on SuperAlarm sequences outperformed that based on monitor alarm sequences. Furthermore, a large-scale, comprehensive patient dataset is required for the development and evaluation of advanced SuperAlarm models and algorithms. To fulfill this need, we have created a SuperAlarm study database by consolidating and aggregating a large volume of physiologic and clinical temporal data. The SuperAlarm study database included patient demographics, admission-discharge-transfer (ADT) information, monitor alarms, laboratory test results, physiologic waveforms and vital signs that were collected from a cohort of a large amount of identified adult coded patients and control patients admitted to UCLA and UCSF medical centers. We designed naming codebooks to map and unify alarms and laboratory tests extracted from the two institutions. We also developed a software application to extract physiological waveforms and vital signs and save them into binary files for further analysis.Finally, we have proposed a novel representation method to convert SuperAlarm sequences into fixed-dimensional vectors, called Time Weighted Supervised Sequence Representation (TWSSR). Unlike TFIDF representation method, the TWSSR is not only a supervised weighting scheme that takes into account the distribution of sequences between coded patients and control patient, it also considers the impact of time on the weight of a SuperAlarm trigger that occurs in a SuperAlarm sequence. We used the monitor alarms and laboratory test results in the established SuperAlarm study database to mine SuperAlarm patterns and further generate SuperAlarm sequences. The support vector machine based recursive feature elimination (SVM-RFE) algorithm was applied to perform classification in conjunction with feature selection. The results suggested that the performance of the sequence classifier based on the TWSSR representation method was higher than that based on TFIDF method.In summary, we have proposed the SuperAlarm framework to integrate heterogeneous EHR and patient monitoring data to develop predictive models. This framework recognizes patterns not only across different data modalities but also across the temporal dimension through sequence classification. The SuperAlarm framework by means of data fusion could provide a potential paradigm that transforms the critical care patient monitoring into a more integrated precise system for recognizing adverse events and ensuring prompt interventions and treatments, and subsequently improve patient monitoring.

Objectives For the correct interpretation of test results, it is important to be aware of drug-laboratory test interactions (DLTIs). If DLTIs are not taken into account by clinicians, erroneous interpretation of test results may lead to a delayed or incorrect diagnosis, unnecessary diagnostic testing or therapy with possible harm for patients. A DLTI alert accompanying a laboratory test result could be a solution. The aim of this study was to test a multicentre proof of concept of an electronic clinical decision support system (CDSS) for real-time monitoring of DLTIs. Methods CDSS was implemented in three Dutch hospitals. So-called ‘clinical rules’ were programmed to alert medical specialists for possible DLTIs based on laboratory test results outside the reference range in combination with prescribed drugs. A selection of interactions from the DLTI database of the Dutch society of clinical chemistry and laboratory medicine were integrated in 43 clinical rules, including 24 tests and 25 drugs. During the period of one month all generated DTLI alerts were registered in the laboratory information system. Results Approximately 65 DLTI alerts per day were detected in each hospital. Most DLTI alerts were generated in patients from the internal medicine and intensive care departments. The most frequently reported DLTI alerts were potassium-proton pump inhibitors (16%), potassium-beta blockers (11%) and creatine kinase-statins (11%). Conclusions This study shows that it is possible to alert for potential DLTIs in real-time with a CDSS. The CDSS was successfully implemented in three hospitals. Further research must reveal its usefulness in clinical practice.

This article provides clear guidance related to appropriate testing for Clostridioides difficile (C. diff) and identifies the negative implications of inappropriate testing, repeat testing, and testing for cure. Residents of long-term care (LTC) facilities are at increased risk for developing C. diff. Complications can arise if a resident does not have an active C. diff infection (colonization) and has a positive C. diff laboratory test result. The authors share a fictional bedside story illustrating the negative consequences that can result from inappropriate C. diff testing, and present a decision tree that promotes mindful application of testing, which may result in cost savings and prevent adverse resident outcomes. Keywords: C. diff, long-term care, test, diarrhea, stool, algorithm, treatment, diagnosis

Clinical decision-making relies heavily on making a correct diagnosis. Clinicians have a responsibility to understand the full spectrum of the diagnostic information conveyed by a physical exam finding, laboratory test result, or imaging. Many laboratory tests, such as troponin and B-type natriuretic peptide (BNP), are continuous tests with many possible results. Yet, there is a tendency to dichotomize tests into positive and negative, and use sensitivity and specificity to describe the test characteristics. This approach can lead to waste of important diagnostic information and substandard clinical decision-making. The aim of this paper is to demonstrate the role of ROC curves in developing a more comprehensive understanding of diagnostic information portrayed by continuous tests to augment clinical decision-making. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1007/s11606-019-05125-0) contains supplementary material, which is available to authorized users.

In a review of 159 archived bovine autopsy cases submitted to the Georgia Veterinary Diagnostic Laboratory System from 2001 to 2017, we evaluated histologic lesions and other laboratory test results in cases diagnosed with central nervous system (CNS) disease to determine the most common disorders and the rate of definitive morphologic and etiologic diagnosis within the population. The most common breed was Aberdeen Angus or Angus (31%), and female animals comprised 60% of the overall submissions. Gross anatomic changes were described in 33% of cases that had histologic lesions. Suppurative meningoencephalitis was the most common diagnosis (28% of cases overall) and was frequently associated with bacterial sepsis. Lymphocytic meningoencephalitis without an identified etiology was diagnosed in 17% of cases. Polioencephalomalacia was the most commonly identified noninfectious diagnosis (17%). Hydrocephalus was the most common CNS comorbidity and potential congenital defect. Identification of specific agents was sporadic, and infectious disease testing was largely dependent on fluorescent antibody testing, almost all of which were negative. Our findings indicate the common differential diagnoses for cattle with neurologic signs in the southeastern United States, as well the need for a well-defined, methodical diagnostic approach, including autopsy, histology, and appropriate additional laboratory testing.

INTRODUCTION Clinicians and healthcare professionals rely heavily on health-associated standards, such as reference intervals (RIs), for appropriate laboratory test result interpretation. RIs are commonly partitioned into discrete age/sex bins based on statistical and/or clinical significance. In pediatric hematology, such partitioning does not adequately represent complex variation in analyte concentrations throughout maturation. The objective of this study was to establish continuous RIs for common hematological parameters in the healthy pediatric Canadian Laboratory Initiative on Pediatric Reference Intervals (CALIPER) cohort. METHODS Data from healthy CALIPER children and adolescents (6 months

Background . New York City (NYC) experienced an initial surge and gradual decline in the number of SARS-CoV-2-confirmed cases in 2020. A change in the pattern of laboratory test results in COVID-19 patients over this time has not been reported or correlated with patient outcome. Methods . We performed a retrospective study of routine laboratory and SARS-CoV-2 RT-PCR test results from 5,785 patients evaluated in a NYC hospital emergency department from March to June employing machine learning analysis. Results . A COVID-19 high-risk laboratory test result profile (COVID19-HRP), consisting of 21 routine blood tests, was identified to characterize the SARS-CoV-2 patients. Approximately half of the SARS-CoV-2 positive patients had the distinct COVID19-HRP that separated them from SARS-CoV-2 negative patients. SARS-CoV-2 patients with the COVID19-HRP had higher SARS-CoV-2 viral loads, determined by cycle threshold values from the RT-PCR, and poorer clinical outcome compared to other positive patients without the COVID12-HRP. Furthermore, the percentage of SARS-CoV-2 patients with the COVID19-HRP has significantly decreased from March/April to May/June. Notably, viral load in the SARS-CoV-2 patients declined, and their laboratory profile became less distinguishable from SARS-CoV-2 negative patients in the later phase. Conclusions . Our longitudinal analysis illustrates the temporal change of laboratory test result profile in SARS-CoV-2 patients and the COVID-19 evolvement in a US epicenter. This analysis could become an important tool in COVID-19 population disease severity tracking and prediction. In addition, this analysis may play an important role in prioritizing high-risk patients, assisting in patient triaging and optimizing the usage of resources.

Sources of error in laboratory tests include preanalytical, analytical, and postanalytical factors that potentially influence the integrity or interpretation of a test result. Immunoassays that are used to measure many of the endocrine biomarkers such as hormones, binding proteins, and metabolic products, are particularly susceptible to analytical interferences due to the limited specificity of antibody–antigen interactions. Endogenous substances such as lipids and bilirubin may interfere with laboratory tests when present at unusually high concentrations. Hemoglobin is a common interferent that leaks into the noncellular fraction of blood when red blood cells are disrupted during collection or storage of a blood specimen. Dietary supplements such as biotin can sometimes interfere with laboratory tests when present at high enough concentrations. Finally, the proper interpretation of a laboratory test result requires some knowledge of the sensitivity and specificity of the test, the predictive value of positive results, and the inherent biological variability of the biomarker the test measures. This chapter discusses the most common sources of error in laboratory tests used in diagnostic endocrinology. Avoidance of these sources of error maximizes the value of laboratory tests.

PURPOSE: The data in a patient’s laboratory test result is a notable resource to support clinical investigation and enhance medical research. However, for a variety of reasons, this type of data often contains a non-trivial number of missing values. For example, physicians may neglect to order tests or document the results. Such a phenomenon reduces the degree to which this data can be utilized to learn efficient and effective predictive models. To address this problem, various approaches have been developed to impute missing laboratory values; however, their performance has been limited. This is due, in part, to the fact no approaches effectively leverage the contextual information 1) in individual or 2) between laboratory test variables. METHOD: We introduce an approach to combine an unsupervised prefilling strategy with a supervised machine learning approach, in the form of extreme gradient boosting (XGBoost), to leverage both types of context for imputation purposes. We evaluated the methodology through a series of experiments on approximately 8,200 patients’ records in the MIMIC-III dataset. RESULT: The results demonstrate that the new model outperforms baseline and state-of-the-art models on 13 commonly collected laboratory test variables. In terms of the normalized root mean square derivation (nRMSD), our model exhibits an imputation improvement by over 20%, on average. CONCLUSION: Missing data imputation on the temporal variables can be largely improved via prefilling strategy and the supervised training technique, which leverages both the longitudinal and cross-sectional context simultaneously.

Objective To identify factors predicting laboratory-positive coronavirus disease (COVID-19) in pediatric patients with acute respiratory symptoms. Study design We conducted a cross-sectional analysis of a prospective cohort study. Methods Data from 1,849 individuals were analyzed. COVID-19 was confirmed (reverse transcription-quantitative polymerase chain reaction) in 15.9% and factors predicting a positive test result were evaluated through prevalence odds ratios (OR) and 95% confidence intervals (CI). Results Increasing age, personal history of obesity, and household contact with a case were associated, in multiple regression model, with increased odds of a positive test result. Young patients residing in areas with higher population-sizes were less likely to be laboratory-confirmed, as wells as those with severe respiratory symptoms. Conclusions Early identification and isolation of children and teenagers with sug-gestive symptoms of COVID-19 is important to limit viral spread. We identified several factors predicting the laboratory test result. Our findings are relevant from a public health policy perspective, particularly after the restart of in-person academic activities., Highlights • Children and teenagers play an important role in the spread of viral pathogens, including SARS-COV-2. • In this manuscript we identified factors associated with the odds of positive COVID-19 test results among children and teenager with acute respiratory symptoms. • Early identification and isolation of underaged individuals with COVID-19 may reduce the related disease burden. • Our findings may be highly relevant, from a public health policy perspective, after the restart of in-person academic activities all around the globe.

The disease caused by the new coronavirus, or COVID-19, has been recently described and became a health issue worldwide. Its diagnosis of certainty is given by polymerase chain reaction. High-resolution computed tomography, however, is useful in the current context of pandemic, especially for the most severe cases, in assessing disease extent, possible differential diagnoses and searching complications. In patients with suspected clinical symptoms and typical imaging findings, in which there is still no laboratory test result, or polymerase chain reaction is not available, the role of this test is still discussed. In addition, it is important to note that part of the patients present false-negative laboratory tests, especially in initial cases, which can delay isolation, favoring the spread of the disease. Thus, knowledge about the COVID-19 and its imaging manifestations is extremely relevant for all physicians involved in the patient care, clinicians or radiologists.

Background Diagnostics utility of the obtained laboratory test results strictly depends on their possible interpretation in the context of distinguishing of both the health and disease state as well as the desired effects of therapeutic interventions. For this purpose, it is necessary to compare the obtained results to the reference intervals. Current recommendations obligate each laboratory to determine its own reference intervals for each of examined parameters. Many laboratories are unable to define and implement their own reference intervals because it is an expensive and time-consuming procedure when using a best known - direct method. This problem is particularly evident in hard-to-access populations, such as pediatric and geriatric. An alternative solution designed to determine reference intervals is using indirect methods, which are based on the results of studies performed for diagnostic purposes in outpatients and inpatients and archived in digital medical databases, which may be subjected to statistical analysis. Methods The search for peer-reviewed articles was conducted in PubMed and Scopus databases. Variations of terms: Biological Variation, Reference Interval, Clinical Decision Limits, Laboratory Information System, Medical Laboratory, Direct Method, Indirect Method were used with different combinations of logical operators to ensure exhaustive search results. The original and review publications and recommendations best suited to the presented topic were selected from among the results of searches based on the previous list of terms from the period 2001 - 2019. Results This work presents and critically analyses the currently existing guidelines related to determining and applying reference intervals in medical diagnostic laboratories, as well as to identify both the associated problems and difficulties and perspectives concerning the ways of their establishment and implementation. Conclusions It is crucial to remember that interpretation of a laboratory test result is a process of comparison and it usefulness depends mainly on the adopted reference system or decision limits. The process of establishing reference intervals and decision limits is complex and the choice of appropriate method depends of the many biological and technical factors connected with populations and laboratory equipment differences. The knowledge of advantages and limitations of the reference interval and decision limits allows for significant enhancement of the accuracy in daily clinical practice.

Rheumatologic laboratory tests are frequently ordered by primary care physicians in patients who complain of joint pain. Clinicians should keep in mind the pretest probability of a rheumatologic disorder before ordering any test because laboratory tests in rheumatology are not diagnostic of any particular disease. Any rheumatologic laboratory test result should only be used to further refine the diagnosis, and it should not replace a thorough history and physical examination. In this article, the authors discuss the diagnostic utility of the commonly ordered rheumatologic laboratory tests based on their sensitivity, specificity, and likelihood ratios.

Objective Emergency department (ED) patients with psychiatric chief complaints undergo medical screening to rule out underlying or comorbid medical illnesses prior to transfer to a psychiatric facility. This systematic review attempts to determine the clinical utility of protocolized laboratory screening for the streamlined medical clearance of ED psychiatric patients by determining the clinical significance of individual laboratory results. Methods We searched PubMed, Embase, and Scopus using the search terms "emergency department, psychiatry, diagnostic tests, laboratories, studies, testing, screening, and clearance" up to June 2017 for studies on adult psychiatric patients. This systematic review follows the recommendations of Meta-analysis of Observational Studies in Epidemiology (MOOSE) statement. The quality of each study was rated according to the Newcastle-Ottawa quality assessment scale. Results Four independent reviewers identified 2,847 publications. We extracted data from three studies (n = 629 patients). Included studies defined an abnormal test result as any laboratory result that falls out of the normal range. A laboratory test result was deemed as "clinically significant" only when patient disposition or treatment plan was changed because of that test result. Across the three studies the prevalence of clinically significant results were low (0.0%-0.4%). Conclusions The prevalence of clinically significant laboratory test results were low, suggesting that according to the available literature, routine laboratory testing does not significantly change patient disposition. Due to the paucity of available research on this subject, we could not determine the clinical utility of protocolized laboratory screening tests for medical clearance of psychiatric patients in the ED. Future research on the utility of routine laboratory testing is important in a move toward shared decision making and patient-centered health care.

Introduction: Laboratory bias can occur during the pre-examination, examination and post-examination stages. The appropriate laboratory practice has the great impact on health care system, more than 70% patient management mainly depend on laboratory test result. Current scenario shows huge importance of the laboratory errors and its negative impact on patient treatment outcomes. Quality improvement program main aim is to evaluate the total system performance and provide appropriate protocol to improve that performance. Therefore in this study we recorded the errors occurred in pre-examination. Aim: The aim of this study was to access the importance of quality improvement program in clinical diagnostic laboratory to reduce or eliminate the diagnostic error. Materials and Methods: The present study was conducted in King Fahad Hofuf Hospital Al-Assah (KSA) clinical biochemistry laboratory during a period of 2 years from March 2016 to June 2018. A total of 458,786 tests were performed on 147,746 outpatients and inpatients. Results: A total of 4, 58,786 tests were performed in 1, 47,746 patients during the overall study period. The overall bias was recorded 4.35%. Out of total bias pre-examination bias was 3.15%, examination error was 0.2% and post-examination bias was 1% respectively. During 2 years study period no significant increase (P= 0.9) of total examination bias were found. Conclusion: As laboratory scientist professionals, we need to acquire proper strategies to maintain the quality in diagnostic laboratory and concern with the physicians provide effective health care service to the patients. We recommend regular assessments in all the laboratories to assure the quality in the health sector. Keywords: Pre-examination, Examination, Post-examination, Errors, Quality control.

Appropriate handling of ‘critical’ laboratory test result values is an essential component of timely, quality patient care. While interinstitutional variability exists,1 critical values have historically been defined as potentially ‘life-threatening’ if not attended to quickly,2 necessitating prompt notification of a responsible clinician. Given patient safety implications, timely communication of results to a provider is a common regulatory element, including: (1) Joint Commission patient safety goals,3 (2) Clinical Laboratory Improvement Amendments4 and (3) the International Organization for Standardization.5 Inpatient values comprise a significant proportion of notifications,6 and among inpatients, oncology inpatients typically constitute a substantial volume.7 After laboratory result generation, contacting a responsible clinician can be complicated by multiple barriers. Previous approaches to improve this process include using call centres, automatic pager notifications and automatic personal digital assistant (PDA) telephone notifications.8–11 In our hospital, the inpatient haematology/oncology/stem cell transplantation (H/O) service had an overall notification success rate substantially lower than the hospital average as an effect of the large volume of critical results that typically returned in a short time period at certain times of day, leading to a multidisciplinary initiative to improve the notification process. In our free-standing 360-bed paediatric hospital, ‘overall’ successful critical result notification must: (1) be acknowledged by a licenced individual provider (LIP) and (2) meet criteria for ‘timely’ notification, indicating that both outgoing notification from the laboratory/call centre and LIP acknowledgement occur within 30 min of result generation. H/O inpatients account for 15%–20% of all inpatient critical values but had a significantly lower overall successful notification rate than the hospital average. Timely outgoing notification occurred >90%, but timely LIP acknowledgement was

This paper presents a comparison of secondary electric arcs behavior for reclosing applications. The main objective of the paper is to show the differences in secondary arcs during simulations, laboratory tests and real life events. These comparisons can help engineers develop adaptive reclosing algorithms and improve power system stability. A software arc model, a laboratory test result and field events' harmonic contents were analyzed. Although the harmonics may differ in each method, they all provide enough information to be used in the reclosing algorithms.

EverStressFE is a 3D finite element modeling software that can be used to analyze the multilayer model pavement (up to four layers possible), which requires elastic modulus and Poisson's ratio of each layer as an input value. The purpose of this paper is to develop a comparison between EversStress-FE-based analysis and laboratory test results and determine the accuracy of the software. In this study, displacement and microstrain behaviors are compared. The vertical strain governing at both the top and bottom fiber of the concrete layer from the laboratory test are 38 and 44, respectively, compared to the EverStressFE result (gz

A reference interval (RI)10 is a standard component of reporting a laboratory result and is important to transform a numerical value into clinically meaningful information. An RI is intended to inform the clinical care provider that laboratory values within the interval indicate a nondiseased condition. The most common approach is to base an RI on the central 95% of laboratory test values observed for a reference population that is free of diseases that influence that laboratory test result. Because many diseases are asymptomatic, it becomes difficult to qualify people for a nondiseased condition, thus biasing the selection of reference individuals. Furthermore, information on the full complement of disease conditions that influence a laboratory test may be unknown. Thus, RIs may be influenced by inappropriately selected reference populations. Another limitation in determining an RI is obtaining an adequate sample of a reference population to make an estimate of the central 95% of results with suitable uncertainty to be meaningful for interpreting a test result. The sample size requirement becomes even larger when partitioning by sex, age, ethnicity, menstrual cycle, and other parameters is necessary for meaningful RIs. CLSI Guideline EP28-A3c describes consensus approaches and some limitations for establishing and verifying RIs. However, some of the approaches in this guideline are statistically underpowered such that uncertainties in the RIs may not be appreciated. A particularly challenging situation is the requirement for laboratories to establish an RI for a laboratory developed measurement procedure (MP) or to verify the RIs proposed by the manufacturer of an in vitro diagnostic (IVD) MP. Identifying a suitable reference population for either requirement can be very challenging. Evolution in laboratory practice is needed to enable appropriate RIs to be adopted by laboratories. We asked experts with different perspectives to address issues we all face in establishing or …

OBJECTIVES Test interpretation is an important part of the brain-to-brain loop. Poor test comments can lead to calls for explanations and impair test interpretation and possibly patient care. There has been little study on quality improvement of test result comments. The objective of this study was to investigate the impact of improvements in test comments on requests for consultation by clinicians. METHODS We monitored the volume of requests for consultation regarding test results before and after a test comment was modified. RESULTS Modifications of test comments eliminated calls for three different tests. Reductions were statistically significant for all tests (P

Background : Hemophilia A has the highest incidence, more than 80% of 172.323 cases worldwide in 2012. It is stated that clinical characteristics of hemophilia A is worse than others, so it is required to prove and to know further about the clinical characteristics and severity likelihood in all hemophilic patients in order to prevent re-bleeding and re-injury and also for a better medical response. Methods : A retrospective cross-sectional study was carried out to 43 medical records of hospitalized hemophilic patients from 2009 to 2013 in Dr Hasan Sadikin General Hospital. The inclusion criteria were a complete patient identity (name, age, sex), written chief complaint, complete physical examination (bleeding, edema, hematoma, hemarthrosis, anemic symptoms) and laboratory test results (factor level, hemoglobin, hematocrit, platelet and Activated Partial Thromboplastin Time). The data was collected from August‒October 2014, analyzed and presented using frequency distribution. Results : Most of the patients were 5-10 years old, male and had hemophilia A. The most common complaint was external bleeding, followed by edema. From 43 patients, 38 (88%) cases were classified as severe factor deficiency, had mild to severe anemia, however the platelet count in most of the cases was in normal value. About 91% cases had prolonged Activated Partial Thromboplastin Time in moderate to severe level. Conclusions : Similar with other studies worldwide, most of the hospitalized hemophilic patients have hemophilia A. Most of the patents has moderate to severe bleeding with laboratory test result between moderate to severe level as well. [AMJ.2016;3(4):605–9]

Over the past decade, controlled low-strength material (CLSM) has been used extensively as fill material in flowable fills, structural fills, and void fills. However, owing to its good flowability and low shrinkage, CLSM can be considered a heat transfer medium as long as it has sufficiently high thermal conductivity. The main purpose of this study is to evaluate the use of controlled low strength material (CLSM) as a novel grout for geothermal systems by both laboratory and field experiments. Laboratory tests were performed first on various CLSM mixtures to evaluate their performance on general characteristics coupled with thermal conductivity, and the construction cost analysis. As a laboratory test result, all CLSM mixtures satisfied aspects of the abovementioned properties. In addition, in order to prove the proficiency of CLSM based-grout for geothermal systems, a large-scale test was also conducted to verify the workability and heat exchange rate of CLSM based-grout in the field with five boreholes and two control buildings. The workability of CLSM-based grout from the field tests was in the acceptable requirements reported in ACI 229R, (1999). In addition, the heat exchange rate of the proposed CLSM from the field test was found to be better than that of silicate sand and bentonite (i.e., conventional grouts). In conclusion, good workability and sufficient heat exchange rate obtained from the field test strongly reinforced the feasible use of the proposed CLSM as a thermal grout for geothermal systems.

Background A wealth of clinical information is buried in free text of electronic health records (EHR), and converting clinical information to machine-understandable form is crucial for the secondary use of EHRs. Laboratory test results, as one of the most important types of clinical information, are written in various styles in free text of EHRs. This has brought great difficulties for data integration and utilization of EHRs. Therefore, developing technology to normalize different expressions of laboratory test results in free text is indispensable for the secondary use of EHRs. Methods In this study, we developed a knowledge-based method named LATTE (transforming lab test results), which could transform various expressions of laboratory test results into a normalized and machine-understandable format. We first identified the analyte of a laboratory test result with a dictionary-based method and then designed a series of rules to detect information associated with the analyte, including its specimen, measured value, unit of measure, conclusive phrase and sampling factor. We determined whether a test result is normal or abnormal by understanding the meaning of conclusive phrases or by comparing its measured value with an appropriate normal range. Finally, we converted various expressions of laboratory test results, either in numeric or textual form, into a normalized form as “specimen-analyte-abnormality”. With this method, a laboratory test with the same type of abnormality would have the same representation, regardless of the way that it is mentioned in free text. Results LATTE was developed and optimized on a training set including 8894 laboratory test results from 756 EHRs, and evaluated on a test set including 3740 laboratory test results from 210 EHRs. Compared to experts’ annotations, LATTE achieved a precision of 0.936, a recall of 0.897 and an F1 score of 0.916 on the training set, and a precision of 0.892, a recall of 0.843 and an F1 score of 0.867 on the test set. For 223 laboratory tests with at least two different expression forms in the test set, LATTE transformed 85.7% (2870/3350) of laboratory test results into a normalized form. Besides, LATTE achieved F1 scores above 0.8 for EHRs from 18 of 21 different hospital departments, indicating its generalization capabilities in normalizing laboratory test results. Conclusion In conclusion, LATTE is an effective method for normalizing various expressions of laboratory test results in free text of EHRs. LATTE will facilitate EHR-based applications such as cohort querying, patient clustering and machine learning. Availability LATTE is freely available for download on GitHub ( https://github.com/denglizong/LATTE ).

Background Interpreting hematology analytes in children is challenging due to the extensive changes in hematopoiesis that accompany physiological development and lead to pronounced sex- and age-specific dynamics. Continuous percentile charts from birth to adulthood allow accurate consideration of these dynamics. However, the ethical and practical challenges unique to pediatric reference intervals have restricted the creation of such percentile charts, and limitations in current approaches to laboratory test result displays restrict their use when guiding clinical decisions. Methods We employed an improved data-driven approach to create percentile charts from laboratory data collected during patient care in 10 German centers (9,576,910 samples from 358,292 patients, 412,905–1,278,987 samples per analyte). We demonstrate visualization of hematology test results using percentile charts and z-scores (www.pedref.org/hematology) and assess the potential of percentiles and z-scores to support diagnosis of different hematological diseases. Results We created percentile charts for hemoglobin, hematocrit, red cell indices, red cell count, red cell distribution width, white cell count and platelet count in girls and boys from birth to 18 years of age. Comparison of pediatricians evaluating complex clinical scenarios using percentile charts versus conventional/tabular representations shows that percentile charts can enhance physician assessment in selected example cases. Age-specific percentiles and z-scores, compared with absolute test results, improve the identification of children with blood count abnormalities and the discrimination between different hematological diseases. Conclusions The provided reference intervals enable precise assessment of pediatric hematology test results. Representation of test results using percentiles and z-scores facilitates their interpretation and demonstrates the potential of digital approaches to improve clinical decision-making.

Objectives: Patients have unique information needs to help them interpret and make decisions about laboratory test results they receive on web-based portals. However, current portals are not designed in a patient-centered way and little is known on how best to harness patients’ information needs to inform user-centered interface design of portals. We designed a patient-facing laboratory test result interface prototype based on requirement elicitation research and used a mixed-methods approach to evaluate this interface.Methods: After designing an initial test result display prototype, we used multiple evaluation methods, including focus group review sessions, expert consultation, and user testing, to make iterative design changes. For the user testing component, we recruited 14 patient-users to collect and analyze three types of data: comments made during testing sessions, responses to post-session questionnaires, and system usability scores.Results: Our initial patient-centered interface design included visual ranges of laboratory values, nontechnical descriptions of the test and result, and access to features to help patients interpret and make decisions about their results. Findings from our evaluation resulted in 6 design iterations of the interface. Results from user testing indicate that the later versions of the interface fulfilled patient’s information needs, were perceived as usable, and provided access to information and techniques that facilitated patient’s ability to derive meaning from each test result.Conclusions: Requirement elicitation studies can inform the design of a patient-facing test result interface, but considerable user-centered design efforts are necessary to create an interface that patients find useful. To promote patient engagement, health information technology designers and developers can use similar approaches to enhance user-centered software design in patient portals.

Objective The objective of this abstract is to illustrate how the Utah Department of Health processes a high volume of electronic data in an automated way. We do this by a series of rules engines that does not require human intervention. Introduction National initiatives, such as Meaningful Use, are automating the detection and reporting of reportable disease events to public health, which has led to more complete, timely, and accurate public health surveillance data. However, electronic reporting has also lead to significant increases in the number of cases reported to public health. In order for this data to be useful to public health, it must be processed and made available to epidemiologists and investigators in a timely fashion for intervention and monitoring. To meet this challenge, the Utah Department of Health (UDOH)’s Disease Control and Prevention Informatics Program (DCPIP) has developed the Electronic Message Staging Area (EMSA). EMSA is a system capable of automatically filtering, processing, and evaluating incoming electronic laboratory reporting (ELR) messages for relevance to public health, and entering those laboratory results into Utah’s integrated disease surveillance system (UT-NEDSS) without impacting the overall efficiency of UT-NEDSS or increasing the workload of epidemiologists. Methods After parsing and translating messages, EMSA runs the messages through a series of rules to determine if a test result should update an existing UT-NEDSS event, create a new UT-NEDSS event, be archived for possible use in future cases (e.g. to help identify seroconversion) or if the test result should be discarded. All of these rules can be configured specifically for each reportable condition. First, EMSA runs age-based rules. If the incoming message is too old for the indicated condition, EMSA does not continue processing and the message is discarded. EMSA then attempts to person match to determine if the person reported in the ELR message matches a known person in UT-NEDSS. If the person matches, EMSA will then evaluate whether the laboratory result should append to any events associated with the person, create a new event under that person, or create a new person and event. This process occurs through two different rule sets: whitelist rules, and test specific rules. Whitelist Rules are condition-specific and, when available, based on CDC's case definition guidelines to determine when a new lab test result should be considered part of an existing case or a catalyst to trigger a new event. Whitelist Rules run against all existing events found for the person matched, and once a single event is matched, then the more-specific test result-based rules come into play. Within an event matched by the whitelist rules, we have another set of rules based on the test result, collection date, accession number, and test status, to determine whether to add the laboratory report to the event, update an existing laboratory report, or if the laboratory report is a duplicate to be discarded. The message also runs through rules based on test and test result, and sometimes off organism, that determine whether that result can even be used to update the case or not. Whitelist rules also determine if too much time has passed since the matching event occurred for the incoming laboratory result to be appended to the matching event. Whitelist rules exist for both morbidity and contact events, and are based on timeframes such as onset date and treatment dates. If a particular incoming laboratory test result matches a known person in UT-NEDSS, and the whitelist rules determine that the laboratory result matches that person’s disease condition and can “update an existing event”, the laboratory result is run through another set of rules, called “test specific rules”. Test specific rules match incoming laboratory tests results to a UT-NEDSS disease condition, and determine whether each unique test type and test result combination can “create a new event” and/or “update an existing event”. All tests that do not meet the criteria for inclusion into UT-NEDSS, either by updating an event or creating a new event, are held in EMSA, in what is termed the “graylist” for a period of 18 months. When EMSA creates a new event, it queries the graylist to determine if a previous reported lab should be pulled and added to the new event. Graylist rules determine how far back EMSA is allowed to search for previous test results. Results From 10/10/2016 to 9/30/2017, the Utah Department of Health has received a total of 995,486 electronic messages that required processing. Of those 995,486 messages, 23,787 (2.4%) were deleted, 17,839 (1.8%) were identified as duplicates and subsequently deleted, 853,853 (85.8%) were sent to graylist, and 99,657 (10%) were added to UT-NEDSS. Of the 99,657 messages, 85,705 (86%) were processed from raw electronic messages to assignment into UT-NEDSS without any human intervention. Conclusions ELR improves the timeliness, completeness, and accuracy of laboratory reporting to public health, but often results in a significant increase in laboratory reporting to public health agencies. This increase in volume can overwhelm epidemiologists and investigators if manual processes for reviewing all incoming ELR messages are needed for processing laboratory results and entering data into surveillance systems. In order to fully leverage the benefits of ELR for public health surveillance, we knew we needed a highly automated process for receiving, parsing, translating, and entering data into UT-NEDSS that would mitigate the challenges associated with the increased volume. We developed EMSA and its series of rule sets to meet this challenge.

OBJECTIVE Point-of-care testing (POCT) is a commonly used technology that hastens the time to laboratory results in emergency departments (ED). We evaluated an ED-based POCT program on ED length of stay (LOS) and time to care, coupled with qualitative interviews of local ED stakeholders. METHODS We conducted a mixed-methods study (2012-2016) to examine the impact of POCT in a single, community ED. The quantiative analysis involved an observational before-after study comparing time to laboratory test result (POC troponin or POC chemistry) and ED LOS after implementation of POCT, using a propensity-weighted interrupted time series analysis (ITSA). A complementary qualitative analysis involved five semistructured interviews with staff using grounded theory on the benefits and challenges to ED POCT. RESULTS A total of 47,399 ED visits were included in the study (24,705 in the preintervention period and 22,694 in the postintervention period). After POCT implementation, overall laboratory testing increased marginally from 61% to 62%. Central laboratory troponin and chemistry declined by > 50% and was replaced by POCT. Prior to POCT implementation, time to troponin and chemistry had declined steadily due to other improvements in laboratory efficiency. After POCT implementation, there was an immediate 20-minute further decline (p

This paper gives the theory algorithm of material reflectivity, and works out the in-situ material reflectivity combined with in-situ conditions, researches the influence rules of material's reflectivity under practical solar radiation intensity, and the feasibility of this simple in-situ test method is researched by the comparison of in-situ test result and laboratory test result.

Background: Challenges and uncertainties with test result interpretation can lead to diagnostic errors. Primary care doctors are at a higher risk than specialists of making these errors, due to the range in complexity and severity of conditions that they encounter.Objectives: This study aimed to investigate the challenges that primary care doctors face with test result interpretation, and to identify potential countermeasures to address these.Methods: A survey was sent out to 7800 primary care doctors in South Africa. Questionnaire themes included doctors’ uncertainty with interpreting test results, mechanisms used to overcome this uncertainty, challenges with appropriate result interpretation, and perceived solutions for interpreting results.Results: Of the 552 responses received, the prevalence of challenges with result interpretation was estimated in an average of 17% of diagnostic encounters. The most commonly-reported challenges were not receiving test results in a timely manner (51% of respondents) and previous results not being easily available (37%). When faced with diagnostic uncertainty, 84% of respondents would either follow-up and reassess the patient or discuss the case with a specialist, and 67% would contact a laboratory professional. The most useful test utilisation enablers were found to be: interpretive comments (78% of respondents), published guidelines (74%), and a dedicated laboratory phone line (72%).Conclusion: Primary care doctors acknowledge uncertainty with test result interpretation. Potential countermeasures include the addition of patient-specific interpretive comments, the availability of guidelines or algorithms, and a dedicated laboratory phone line. The benefit of enhanced test result interpretation would reduce diagnostic error rates.

In today's competitive health care climate, microbiology laboratories are asked to do more work, often with limited or decreasing resources. Cost-saving strategies, successfully implemented in one or more microbiology laboratories across the globe, are listed. For each cost-saving suggestion, careful evaluation must occur prior to implementation, considering the ability and policies of the local institution and understanding that not all suggestions are workable for every laboratory. For the purpose of this article, six categories of cost-saving ideas are explored: (i) technical streamlining, (ii) workflow optimization, (iii) personnel utilization, (iv) cost avoidance, (v) reduction of service, and (vi) investing in savings. Of note, if patient outcome is not beneficially affected by the laboratory test result in question, then perhaps the test should not be performed, or at least not routinely performed.

OBJECTIVES Laboratory tests are usually requested for monitoring during outpatient parenteral antimicrobial therapy (OPAT), but these recommendations are not always followed. The purpose of this study was to determine whether rehospitalization during the OPAT course is associated with the availability of these test results to the treating physician. METHODS Electronic health records (EHRs) from all patients in the Cleveland Clinic OPAT registry with start dates from 1 January to 28 February 2011 were reviewed in a retrospective cohort study. Comprehensive data on patient and OPAT characteristics were obtained for the first OPAT course per patient. Availability of laboratory test results was defined as documentation of results of at least one recommended test in the health system's EHR. Proportions of patients rehospitalized were compared for OPAT courses with test results available and non-available. Adjustments were made for patient age, hospital length of stay, anticipated OPAT duration, OPAT site and Charlson comorbidity index score. RESULTS Four hundred patients received OPAT during the study period; 60% at home, 36% in skilled nursing facilities or long-term acute care facilities and 4% in other settings. Recommended monitoring laboratory test results were available to infectious disease physicians in 291 (73%) OPAT episodes. There were 82 patient readmissions (21%) while on OPAT. In a multivariable logistic regression model, non-availability of recommended test results was independently associated with readmissions while on OPAT (adjusted OR 2.53; 95% CI 1.36-4.73). CONCLUSIONS Non-availability of recommended test results to treating physicians for patients on OPAT is associated with increased readmissions during OPAT.

Based on continuum mechanics approach, the first step on the modeling of the stress corrosion cracking (SCC) is to understand the morphology of the cracks. Later on, it is followed by other considerations such as the chemical interaction, and electron diffusion. This paper investigates the morphology of the SCC behavior of steels with the main purpose of developing the basis of computational modeling. It also aims to give the basic sense for practical engineers in the fields as well. It mainly focuses on the morphology of the SCC on three basic common microstructures of steel: austenite, ferrite–pearlite, and martensite. The objects were taken both from real field works and from accelerated laboratory tests. The field samples were extracted from actual failed parts at known operating conditions and lifetimes. The laboratory test was an immersion in sodium hydroxide solution. The experimental parameters were controlled in such away to simulate accelerated field failures with all three microstructures. The crack depth and behavior of the stress corrosion cracking (SCC) were then analyzed after immersion test and subsequently, the mechanism of stress corrosion cracking was studied with the focus on their morphological observations. The result shows that each microstructure produces unique shape that can be used as a basis for computational model creation. Field engineers can also take advantage of the results for materials selection.

During the tunnel excavation in Zhang-Shi Expressway 2nd-Stage Project, rock burst phenomenon has occurred. Limy dolomite obtained from tunnel rock burst area is used to conduct laboratory loading rock burst test with simulation system of deep rock burst. Simultaneously, based on Particle Flow Theory and PFC3D program, a load-unload code is developed by fish language embedded in PFC3D to carry out simulation of laboratory loading rock burst test. Laboratory test result shows that the rock burst type and intensity of specimen are lagged and severe, respectively; During the test process, a spot of particles eject from the exposed surface; Obvious slabbing phenomenon can be seen on the exposed surface and the separate face of rock slab is parallel to the direction of maximal load σ1 as consistent with the actual phenomenon of engineering rock burst. In the loading rock burst simulation, the load grade, stress-step curve and failure mode of rock burst are almost consistent with the laboratory test. This simulation method describes the failure process actually and subtly, and reveals that the specimen fracture mechanism of loading rock burst is tensile type. Finally, some differences between loading and unloading tests of rock burst are discussed.

This study evaluates the filtration efficiency of a cabin filter and according filter media for fine particle (PM2.5) through laboratory tests and on road tests. Two testing system for the filter media test and filter tests were designed according to the international standard (EN1822 and ISO 11155).On road tests were completed on the real roadway conditions. In cabin particle concentration and ambient particle concentration was gotten by DustTrak(TSI). And then the filter efficiency was calculated according to the I/O ratio. The results showed the filter media’s efficiency was highest, compared the lowest efficiency of filter total efficiency. The real particle removal total efficiency on road was higher than the laboratory test result. According to the experiment data, the on road testing results (particle reductions) are approximately equal to geometrical mean of filter media efficiency and filter total efficiency.