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We hypothesized that a computerized clinical decision support tool for Clostridium difficile testing would reduce unnecessary inpatient tests, resulting in fewer laboratory-identified events. Census-adjusted interrupted time-series analyses demonstrated significant reductions of 41% fewer tests and 31% fewer hospital-onset C. difficile infection laboratory-identified events following this intervention.
Approximate parametric prediction intervals are obtained for an unobserved random variable when the amount of data on which to base the estimation is large. Applications include the construction of approximate confidence intervals in empirical Bayes estimation.
Plasmodium knowlesi has risen in importance as a zoonotic parasite that has been causing regular episodes of malaria throughout South East Asia. The P. knowlesi genome sequence generated in 2008 highlighted and confirmed many similarities and differences in Plasmodium species, including a global view of several multigene families, such as the large SICAvar multigene family encoding the variant antigens known as the schizont-infected cell agglutination proteins. However, repetitive DNA sequences are the bane of any genome project, and this and other Plasmodium genome projects have not been immune to the gaps, rearrangements and other pitfalls created by these genomic features. Today, long-read PacBio and chromatin conformation technologies are overcoming such obstacles. Here, based on the use of these technologies, we present a highly refined de novo P. knowlesi genome sequence of the Pk1(A+) clone. This sequence and annotation, referred to as the ‘MaHPIC Pk genome sequence’, includes manual annotation of the SICAvar gene family with 136 full-length members categorized as type I or II. This sequence provides a framework that will permit a better understanding of the SICAvar repertoire, selective pressures acting on this gene family and mechanisms of antigenic variation in this species and other pathogens.
Introduction: Point of care ultrasonography (PoCUS) is an established tool in the initial management of hypotensive patients in the emergency department (ED). It has been shown rule out certain shock etiologies, and improve diagnostic certainty, however evidence on benefit in the management of hypotensive patients is limited. We report the findings from our international multicenter RCT assessing the impact of a PoCUS protocol on diagnostic accuracy, as well as other key outcomes including mortality, which are reported elsewhere. Methods: Recruitment occurred at 4 North American and 3 Southern African sites. Screening at triage identified patients (SBP<100 mmHg or shock index >1) who were randomized to either PoCUS or control groups. Scans were performed by PoCUS-trained physicians. Demographics, clinical details and findings were collected prospectively. Initial and secondary diagnoses were recorded at 0 and 60 minutes, with ultrasound performed in the PoCUS group prior to secondary assessment. Final chart review was blinded to initial impressions and PoCUS findings. Categorical data was analyzed using Fishers two-tailed test. Our sample size was powered at 0.80 (α:0.05) for a moderate effect size. Results: 258 patients were enrolled with follow-up fully completed. Baseline comparisons confirmed effective randomization. The perceived shock category changed more frequently in the PoCUS group 20/127 (15.7%) vs. control 7/125 (5.6%); RR 2.81 (95% CI 1.23 to 6.42; p=0.0134). There was no significant difference in change of diagnostic impression between groups PoCUS 39/123 (31.7%) vs control 34/124 (27.4%); RR 1.16 (95% CI 0.786 to 1.70; p=0.4879). There was no significant difference in the rate of correct category of shock between PoCUS (118/127; 93%) and control (113/122; 93%); RR 1.00 (95% CI 0.936 to 1.08; p=1.00), or for correct diagnosis; PoCUS 90/127 (70%) vs control 86/122 (70%); RR 0.987 (95% CI 0.671 to 1.45; p=1.00). Conclusion: This is the first RCT to compare PoCUS to standard care for undifferentiated hypotensive ED patients. We found that the use of PoCUS did change physicians’ perceived shock category. PoCUS did not improve diagnostic accuracy for category of shock or diagnosis.
Introduction: Point of care ultrasound (PoCUS) is an established tool in the initial management of patients with undifferentiated hypotension in the emergency department (ED). While PoCUS protocols have been shown to improve early diagnostic accuracy, there is little published evidence for any mortality benefit. We report the findings from our international multicenter randomized controlled trial, assessing the impact of a PoCUS protocol on survival and key clinical outcomes. Methods: Recruitment occurred at 7 centres in North America (4) and South Africa (3). Scans were performed by PoCUS-trained physicians. Screening at triage identified patients (SBP<100 or shock index>1), randomized to PoCUS or control (standard care and no PoCUS) groups. Demographics, clinical details and study findings were collected prospectively. Initial and secondary diagnoses were recorded at 0 and 60 minutes, with ultrasound performed in the PoCUS group prior to secondary assessment. The primary outcome measure was 30-day/discharge mortality. Secondary outcome measures included diagnostic accuracy, changes in vital signs, acid-base status, and length of stay. Categorical data was analyzed using Fishers test, and continuous data by Student T test and multi-level log-regression testing. (GraphPad/SPSS) Final chart review was blinded to initial impressions and PoCUS findings. Results: 258 patients were enrolled with follow-up fully completed. Baseline comparisons confirmed effective randomization. There was no difference between groups for the primary outcome of mortality; PoCUS 32/129 (24.8%; 95% CI 14.3-35.3%) vs. Control 32/129 (24.8%; 95% CI 14.3-35.3%); RR 1.00 (95% CI 0.869 to 1.15; p=1.00). There were no differences in the secondary outcomes; ICU and total length of stay. Our sample size has a power of 0.80 (α:0.05) for a moderate effect size. Other secondary outcomes are reported separately. Conclusion: This is the first RCT to compare PoCUS to standard care for undifferentiated hypotensive ED patients. We did not find any mortality or length of stay benefits with the use of a PoCUS protocol, though a larger study is required to confirm these findings. While PoCUS may have diagnostic benefits, these may not translate into a survival benefit effect.
Introduction: Point of Care Ultrasound (PoCUS) protocols are commonly used to guide resuscitation for emergency department (ED) patients with undifferentiated non-traumatic hypotension. While PoCUS has been shown to improve early diagnosis, there is a minimal evidence for any outcome benefit. We completed an international multicenter randomized controlled trial (RCT) to assess the impact of a PoCUS protocol on key resuscitation markers in this group. We report diagnostic impact and mortality elsewhere. Methods: The SHoC-ED1 study compared the addition of PoCUS to standard care within the first hour in the treatment of adult patients presenting with undifferentiated hypotension (SBP<100 mmHg or a Shock Index >1.0) with a control group that did not receive PoCUS. Scans were performed by PoCUS-trained physicians. 4 North American, and 3 South African sites participated in the study. Resuscitation outcomes analyzed included volume of fluid administered in the ED, changes in shock index (SI), modified early warning score (MEWS), venous acid-base balance, and lactate, at one and four hours. Comparisons utilized a T-test as well as stratified binomial log-regression to assess for any significant improvement in resuscitation amount the outcomes. Our sample size was powered at 0.80 (α:0.05) for a moderate effect size. Results: 258 patients were enrolled with follow-up fully completed. Baseline comparisons confirmed effective randomization. There was no significant difference in mean total volume of fluid received between the control (1658 ml; 95%CI 1365-1950) and PoCUS groups (1609 ml; 1385-1832; p=0.79). Significant improvements were seen in SI, MEWS, lactate and bicarbonate with resuscitation in both the PoCUS and control groups, however there was no difference between groups. Conclusion: SHOC-ED1 is the first RCT to compare PoCUS to standard of care in hypotensive ED patients. No significant difference in fluid used, or markers of resuscitation was found when comparing the use of a PoCUS protocol to that of standard of care in the resuscitation of patients with undifferentiated hypotension.
Introduction: Point of care ultrasound (PoCUS) has become an established tool in the initial management of patients with undifferentiated hypotension in the emergency department (ED). Current established protocols (e.g. RUSH and ACES) were developed by expert user opinion, rather than objective, prospective data. Recently the SHoC Protocol was published, recommending 3 core scans; cardiac, lung, and IVC; plus other scans when indicated clinically. We report the abnormal ultrasound findings from our international multicenter randomized controlled trial, to assess if the recommended 3 core SHoC protocol scans were chosen appropriately for this population. Methods: Recruitment occurred at seven centres in North America (4) and South Africa (3). Screening at triage identified patients (SBP<100 or shock index>1) who were randomized to PoCUS or control (standard care with no PoCUS) groups. All scans were performed by PoCUS-trained physicians within one hour of arrival in the ED. Demographics, clinical details and study findings were collected prospectively. A threshold incidence for positive findings of 10% was established as significant for the purposes of assessing the appropriateness of the core recommendations. Results: 138 patients had a PoCUS screen completed. All patients had cardiac, lung, IVC, aorta, abdominal, and pelvic scans. Reported abnormal findings included hyperdynamic LV function (59; 43%); small collapsing IVC (46; 33%); pericardial effusion (24; 17%); pleural fluid (19; 14%); hypodynamic LV function (15; 11%); large poorly collapsing IVC (13; 9%); peritoneal fluid (13; 9%); and aortic aneurysm (5; 4%). Conclusion: The 3 core SHoC Protocol recommendations included appropriate scans to detect all pathologies recorded at a rate of greater than 10 percent. The 3 most frequent findings were cardiac and IVC abnormalities, followed by lung. It is noted that peritoneal fluid was seen at a rate of 9%. Aortic aneurysms were rare. This data from the first RCT to compare PoCUS to standard care for undifferentiated hypotensive ED patients, supports the use of the prioritized SHoC protocol, though a larger study is required to confirm these findings.
It is well-nigh impossible to give, in a short report, an adequate idea of the enormous activity in Variable-Star Astronomy during the past three years. Without attempting to be complete I shall give a summary of the most important recent occurrences in this field of research.
Statistical data for eclipsing binaries were given by Gaposchkin (Veröff. Berlin-Bab. 9, Heft 5), for long-period variable stars by Ludendorff (Sitz.-ber. Ak. d. Wiss. Berlin, 1932), Thomas (Veröff. Berlin-Bab. 9, Heft 4) and Sterne and L. Campbell (Harvard Annals).
Some valuable catalogues have been issued: a Finding List for Observers of Eclipsing Variables by Dugan (Princeton Contr. No. 15), a Catalogue of Eclipsing Variables, together with a Program of Investigations, by Martinoff (Engelhardt Obs. Bull. No. 2), a Catalogue and Ephemeris of Short-period Cepheids by Zessewitsch (Len. Un. A. 0. Bull. No. 3).
This report of Commission 35, as in past reports, consists of some details of only a few selected topics. This is necessary because a survey of the entire field of stellar formation, structure, stability, evolution, pulsation, and explosions for the three year period from mid-1981 to mid-1984 would be excessively long. Our topics here, in order from the most massive stellar classes to the least are: Massive Stars (R.M. Humphreys), Rotation in Late Type Stars (W. Benz), Helioseismology (J. Christensen-Dalsgaard), Planetary Nebula Central Stars (E.M. Sion), Pulsations in Hot Degenerate Dwarf Stars (A.N. Cox and S.D. Kawaler), and White Dwarfs (V. Weidemann). There is some overlap in the reviewing of these last three reports because the topics are very closely related. Concentration in this dying stage of stellar evolution seems appropriate because of the great current interest in these matters.
The field of variable-star research is so broad that no report of this nature could possibly mention all the papers that have appeared in the last three years. It is hoped, however, that the reviews below include the most important work and identify the most significant trends. This report comprises ten sections on as many different research topics, each written by a different member of Commission 27. In addition there are (in Section 12) three short reports about ongoing activities of the commission. The commission president is very grateful to the authors of the individual contributions who have worked so conscientously.
The Commission again subscribes to a number of the good resolutions it has made in the past, for example, to follow the almost universal practice of counting the observed times, either in decimals of a day or in hours and minutes, from Greenwich mean noon, even though one is convinced that the rest of the world should adopt U.T.; and to prepare a chart, identifying the variable and the comparison stars, to form a part of the discovery announcement of a variable which cannot be easily identified through a Durchmusterung number and which is bright enough to invite further observation.
Civilian suicide rates vary by occupation in ways related to occupational stress exposure. Comparable military research finds suicide rates elevated in combat arms occupations. However, no research has evaluated variation in this pattern by deployment history, the indicator of occupation stress widely considered responsible for the recent rise in the military suicide rate.
The joint associations of Army occupation and deployment history in predicting suicides were analysed in an administrative dataset for the 729 337 male enlisted Regular Army soldiers in the US Army between 2004 and 2009.
There were 496 suicides over the study period (22.4/100 000 person-years). Only two occupational categories, both in combat arms, had significantly elevated suicide rates: infantrymen (37.2/100 000 person-years) and combat engineers (38.2/100 000 person-years). However, the suicide rates in these two categories were significantly lower when currently deployed (30.6/100 000 person-years) than never deployed or previously deployed (41.2–39.1/100 000 person-years), whereas the suicide rate of other soldiers was significantly higher when currently deployed and previously deployed (20.2–22.4/100 000 person-years) than never deployed (14.5/100 000 person-years), resulting in the adjusted suicide rate of infantrymen and combat engineers being most elevated when never deployed [odds ratio (OR) 2.9, 95% confidence interval (CI) 2.1–4.1], less so when previously deployed (OR 1.6, 95% CI 1.1–2.1), and not at all when currently deployed (OR 1.2, 95% CI 0.8–1.8). Adjustment for a differential ‘healthy warrior effect’ cannot explain this variation in the relative suicide rates of never-deployed infantrymen and combat engineers by deployment status.
Efforts are needed to elucidate the causal mechanisms underlying this interaction to guide preventive interventions for soldiers at high suicide risk.
We describe the efficacy of enhanced infection control measures, including those recommended in the Centers for Disease Control and Prevention’s 2012 carbapenem-resistant Enterobacteriaceae (CRE) toolkit, to control concurrent outbreaks of carbapenemase-producing Enterobacteriaceae (CPE) and extensively drug-resistant Acinetobacter baumannii (XDR-AB).
Before-after intervention study.
Fifteen-bed surgical trauma intensive care unit (ICU).
We investigated the impact of enhanced infection control measures in response to clusters of CPE and XDR-AB infections in an ICU from April 2009 to March 2010. Polymerase chain reaction was used to detect the presence of blaKPC and resistance plasmids in CRE. Pulsed-field gel electrophoresis was performed to assess XDR-AB clonality. Enhanced infection-control measures were implemented in response to ongoing transmission of CPE and a new outbreak of XDR-AB. Efficacy was evaluated by comparing the incidence rate (IR) of CPE and XDR-AB before and after the implementation of these measures.
The IR of CPE for the 12 months before the implementation of enhanced measures was 7.77 cases per 1,000 patient-days, whereas the IR of XDR-AB for the 3 months before implementation was 6.79 cases per 1,000 patient-days. All examined CPE shared endemic blaKPC resistance plasmids, and 6 of the 7 XDR-AB isolates were clonal. Following institution of enhanced infection control measures, the CPE IR decreased to 1.22 cases per 1,000 patient-days (P = .001), and no more cases of XDR-AB were identified.
Use of infection control measures described in the Centers for Disease Control and Prevention’s 2012 CRE toolkit was associated with a reduction in the IR of CPE and an interruption in XDR-AB transmission.
• The individual matching of controls to cases in a case-control study may be used to control for confounding or background variables at the design stage of the study.
• Matching in a case-control study has some parallels with pair matching in experimental designs. It uses one of the most basic methods of error control, comparing like with like.
• The simplest type of matched case-control study takes a matched-pair form, in which each matched set comprises one case and one control.
• Matched case-control studies require a special form of analysis. The most common approach is to allow arbitrary variations between matched sets and to employ a conditional logistic regression analysis.
• An alternative analysis suitable in some situations uses a regression formulation based on the matching variables.
An important and quite often fruitful principle in investigating the design and analysis of an observational study is to consider what would be appropriate for a comparable randomized experiment. What steps would be taken in such an experiment to achieve secure and precise conclusions? To what extent can these steps be followed in the observational context and what can be done to limit the loss of security of interpretation inherent in most observational situations?
In Chapter 2 we studied the dependence of a binary outcome, Y, on a single binary explanatory variable, the exposure, X.
The case-subcohort design, often called simply the case-cohort design, is an alternative to the nested case-control design for case-control sampling within a cohort.
The primary feature of a case-subcohort study is the ‘subcohort’, which is a random sample from the cohort and which serves as the set of potential controls for all cases. The study comprises the subcohort plus all additional cases, that is, those not in the subcohort.
In an analysis using event times the cases are compared with members of the subcohort who are at risk at their event time, using a pseudo-partial likelihood. This results in estimates of hazard ratios.
An advantage of this design is that the same subcohort can be used to study cases of different types.
A simpler form of case-subcohort study disregards event times and is sometimes referred to as a case-base study or hybrid epidemiologic design. In this the subcohort enables estimation of risk ratios and odds ratios.
In this chapter we continue the discussion of studies described broadly as involving case-control sampling within a cohort. In the nested case-control design, discussed in Chapter 7, cases are compared with controls sampled from the risk set at each event time. A feature of the nested case-control design is that the sampled controls are specific to a chosen outcome and therefore cannot easily be re-used in studies of other outcomes of interest if these occur at different time points; in principle, at least, a new set of controls must be sampled for each outcome studied though some methods have been developed that do enable the re-use of controls.
Logistic regression can be used to estimate odds ratios using data from a case-control sample as though the data had arisen prospectively. This allows regression adjustment for background and confounding variables and makes possible the estimation of odds ratios for continuous exposures using case-control data.
The logistic regression of case-control data gives the correct estimates of log odds ratios, and their standard errors are as given by the inverse of the information matrix.
The logistic regression model is in a special class of regression models for estimating exposure-outcome associations that may be used to analyse case-control study data as though they had arisen prospectively. Another regression model of this type is the proportional odds model. For other models, including the additive risk model, case-control data alone cannot provide estimates of the appropriate parameters.
Absolute risks cannot be estimated from case-control data without additional information on the proportions of cases and controls in the underlying population.
The previous chapters have introduced the key features of case-control studies but their content has been restricted largely to the study of single binary exposure variables. We now give a more general development. The broad features used for interpretation are as before:
• a study population of interest, from which the case-control sample is taken;
• a sampling model constituting the model under which the case-control data arise and which includes a representation of the data collection process;
• an inverse model representing the population dependence of the response on the explanatory variables; this model is the target for interpretation.
In two-stage case-control designs, limited information is obtained on individuals in a first-stage sample and used in the sampling of individuals at the second stage, where full information on exposures and other variables is obtained. The first stage may be a random sample or a case-control sample; the second stage is a case-control sample, possibly within strata. The major aim of these designs is to gain efficiency.
Two-stage studies can be analysed using likelihood-based arguments that extend the general formulation based on logistic regression.
Special sampling designs for matched case-control studies include countermatching, which uses some information on individuals in the potential pool of controls to select controls in such a way as to maximize the informativeness of the case-control sets.
Family groupings can be used in case-control-type studies, and there is a growing literature in the epidemiological, statistical and genetics fields. In one approach, cases are matched to a sibling or other relative.
So far we have discussed case-control studies in which cases and controls are sampled, in principle at random, from the underlying population on the basis of their outcome status. We have also considered extensions, including matched studies and stratified sampling, in both of which it is assumed that some features of individuals in the underlying population are easily ascertained. Sometimes it is useful to consider alternative ways of sampling in a case-control study. In this chapter we discuss some special case-control sampling designs.