Predictors of emotional well-being following a 'false positive' breast cancer screening result

Using a short-term longitudinal design, and consistent with a stress and coping perspective, this study examined the main and stress-buffering effects of social support and coping on emotional well-being following a 'false positive' breast cancer screening result. Immediately prior to obtaining results of follow-up assessment, 178 women completed measures of emotional well-being, stress appraisal, coping strategies and social support. Six weeks later, 85 women found to be cancer free completed a measure of well-being. Hierarchical regression analyses were used to examine the effects of social support and coping on well-being after controlling for initial well-being and stress appraisal. Consistent with predictions, avoidant coping was associated with higher levels of emotional well-being and social support was found to have a stress buffering effect on well-being. Active-cognitive coping strategies had a stress-buffering effect on well-being. Findings suggest that social support and coping do influence emotional well-being following recall for follow-up assessment of a 'false positive' breast cancer screening result.

Optimized hash for network path encoding with minimized false positives

The Bloom filter is a space efficient randomized data structure for representing a set and supporting membership queries. Bloom filters intrinsically allow false positives. However, the space savings they offer outweigh the disadvantage if the false positive rates are kept sufficiently low. Inspired by the recent application of the Bloom filter in a novel multicast forwarding fabric, this paper proposes a variant of the Bloom filter, the optihash. The optihash introduces an optimization for the false positive rate at the stage of Bloom filter formation using the same amount of space at the cost of slightly more processing than the classic Bloom filter. Often Bloom filters are used in situations where a fixed amount of space is a primary constraint. We present the optihash as a good alternative to Bloom filters since the amount of space is the same and the improvements in false positives can justify the additional processing. Specifically, we show via simulations and numerical analysis that using the optihash the false positives occurrences can be reduced and controlled at a cost of small additional processing. The simulations are carried out for in-packet forwarding. In this framework, the Bloom filter is used as a compact link/route identifier and it is placed in the packet header to encode the route. At each node, the Bloom filter is queried for membership in order to make forwarding decisions. A false positive in the forwarding decision is translated into packets forwarded along an unintended outgoing link. By using the optihash, false positives can be reduced. The optimization processing is carried out in an entity termed the Topology Manger which is part of the control plane of the multicast forwarding fabric. This processing is only carried out on a per-session basis, not for every packet. The aim of this paper is to present the optihash and evaluate its false positive performances via simulations in order to measure the influence of different parameters on the false positive rate. The false positive rate for the optihash is then compared with the false positive probability of the classic Bloom filter.

Microbiological evaluation of milk samples positive to California Mastitis Test in dairy buffalo cows (Buballus bubalis)

In order to observe the microbiological status of CMT positive samples, 734 apparently health mammary quarters from buffalo cows were submitted to physical evaluation, strip cup test and CMT. After milk samples inoculation in 10% ovine blood agar base media and in MacConkey agar and incubation under aerobic condition for 72 hours at 37 degrees C, identification was proceeded. According to CMT, 227 quarters (30,93%) were positive, among them 73 (32,16%) presented 1+ reaction, 53 (23,35%) were 2+ and 101 (44,49%) were 3+. Microbiological exams of such samples were positive in 147 (64,76%) out of 227 CMT positive samples and among the remaining 72 (31,72%) were negative and 8 (3,52) were contaminated. In the 147 microbiological positive samples 204 bacteria were found in pure or associated growth and the most frequent agents were: Corynebacterium sp (59,25%); Staphylococcus sp (17,65%) among which 86,11% were coagulase negative and 13,89% were coagulase positive; and Micrococcus sp (6,37%). The results revealed that, excluding the eight contaminated samples, 147 (67,12%) quarters out of 219 CMT positive could be considered as bacteria-carrier and that even in a smaller percentage false-positive results can cause problems in a sanitary program for mastitis control in dairy buffalo cows.

False positivity of gamma-glutamyl transpeptidase measurement in urine

Although enzymuria tends to be associated to renal injury, there are no studies that have evaluated the presence of the enzyme gamma-glutamyl transpeptidase (GGT) spectrophotometry in the urine using a non-nephrotoxic agent (Nerium oleander) in order to evaluate the possibility of false positive results. The urinary GGT/urinary creatinine concentration ratio (uGGT/uCr) of 10 healthy dogs was calculated and posteriorly confronted with data from clinical evaluation, hematological and serum biochemical profiles, creatinine clearance (CrC), urinalysis, urine protein/creatinine ratio (UPC), electrocardiogram, systemic blood pressure (SBP) and light and electron microscopy. The results for kidney histology, SBP, UPC and CrC were not significantly different in any of the time-points analyzed. However, uGGT/uCr was significantly higher when measured 4 hours and 24 hours after administration of N. oleander. The measurement of the urinary GGT enzyme, as performed in many studies, yielded false positive results in dogs poisoned by a non-nephrotoxic agent.

Negative and positive predictive values of nerve monitoring in thyroidectomy

Background Recurrent nerve injury is 1 of the most important complications of thyroidectomy. During the last decade, nerve monitoring has gained increasing acceptance in several centers as a method to predict and to document nerve function at the end of the operation. We evaluated the efficacy of a nerve monitoring system in a series of patients who underwent thyroidectomy and critically analyzed the negative predictive value (NPV) and positive predictive value (PPV) of the method. Methods. NIM System efficacy was prospectively analyzed in 447 patients who underwent thyroidectomy between 2001 and 2008 (366 female/81 male; 420 white/47 nonwhite; 11 to 82 years of age; median, 43 years old). There were 421 total thyroidectomies and 26 partial thyroidectomies, leading to 868 nerves at risk. The gold standard to evaluate inferior laryngeal nerve function was early postoperative videolaryngoscopy, which was repeated after 4 to 6 months in all patients with abnormal endoscopic findings. Results. At the early evaluation, 858 nerves (98.8%) presented normal videolaryngoscopic features after surgery. Ten paretic/paralyzed nerves (1.2%) were detected (2 unexpected unilateral paresis, 2 unexpected bilateral paresis, 1 unexpected unilateral paralysis, 1 unexpected bilateral paralyses, and 1 expected unilateral paralysis). At the late videolaryngoscopy, only 2 permanent nerve paralyses were noted (0.2%), with an ultimate result of 99.8% functioning nerves. Nerve monitoring showed absent or markedly reduced electrical activity at the end of the operations in 25/868 nerves (2.9%), including all 10 endoscopically compromised nerves, with 15 false-positive results. There were no false-negative results. Therefore, the PPV was 40.0%, and the NPV was 100%. Conclusions. In the present series, nerve monitoring had a very high PPV but a low NPV for the detection of recurrent nerve injury. (C) 2011 Wiley Periodicals, Inc. Head Neck 34: 175-179, 2012

False -positives and false-negatives in tests for trend

False-positive and false-negative values were calculated for five different designs of the trend test and it was demonstrated that a design suggested by Portier and Hoel in 1984 for a different problem produced the lowest false-positive and false-negative rates when applied to historical spontaneous tumor rate data for Fischer Rats. ^

A study of potential serum markers for a diagnosis of gram-positive and gram-negative bacterial sepsis

Sepsis continues to be a major cause of morbidity and mortality as it can readily lead tosevere sepsis, septic shock, multiple organ failure and death. The onset can be rapid and difficult to define clinically. Despite the numerous candidate markers proposed in the literature, to date a serum marker for sepsis has not been found. The aim of this study was to assay the serum of clinically diagnosed patients with eithera Gram-negative or Gram- positive bacterial sepsis for elevated levels of nine potentialmarkers of sepsis, using commercially produced enzyme linked immunosorbent assays(ELISA). The purpose was to find a test marker for sepsis that would be helpful toclinicians in cases of uncertain sepsis and consequently expose false positive BC'scaused by skin or environmental contaminants. Nine test markers were assayed including IL-6, IL-I 0, ILI2, TNF-α, lipopolysaccharide binding protein, procalcitonin, sE-selectin, sICAM -1 and a potential differential marker for Gram-positive sepsis- anti-lipid S antibody. A total of 445 patients were enrolled into this study from the Queen Elizabeth Hospital and Selly Oak Hospital (Birmingham). The results showed that all the markers were elevated in patients with sepsis and that patients with a Gram-negative sepsis consistently produced higher median/range serum levels than those with a Gram-positive sepsis. No single marker was able to identify all the septic patients. Combining two markers caused the sensitivities and specificities for a diagnosis of sepsis to increase to within a 90% to 100% range. By a process of elimination the markers that survived into the last phase were IL-6 with sICAM -1, and anti-lipid S IgG assays Defining cut-off levels for a diagnosis of sepsis became problematic and a semi-blind trial was devised to test the markers in the absence of both clinical details and positive blood cultures. Patients with pyrexia of unknown origin and negative BC were included in this phase (4). The results showed that IL-6 with sICAM-l are authentic markers of sepsis. There was 82% agreement between the test marker diagnosis and the clinical diagnosis for sepsis in patients with a Gram-positive BC and 78% agreement in cases of Gram-negative Be. In the PUO group the test markers identified 12 cases of sepsis and the clinical diagnosis 15. The markers were shown to differentiate between early sepsis and sepsis, inflammatory responses and infection. Anti-lipid S with IL-6 proved be a sensitive marker for Gram-positive infections/sepsis.

False identification of other microorganisms as Staphylococcus aureus in Southern Nigeria

Purpose: Staphylococcus aureus is the causative agent of many infections and the advent MRSA has drawn much attention to it. However, some organisms have been noted to be wrongly identified as S. aureus through phenotypic identifications leading to wrong treatment of infections. This study is therefore undertaken to evaluate the rate of false identification of other organisms as S. aureus in Southern Nigeria. Methods: 507 microorganisms which have been previously identified as S. aureus in 8 States in Southern Nigeria through characteristic morphology on blood agar, Gram staining, growth and fermentation on Mannitol Salt Agar and coagulase formation were collected. All the isolates were identified in this study through sequencing of 16S rRNA and detection of spa gene. The percentages of true and false identities were determined. Results: Of the 507 isolates previously identified as S. aureus, only 54 (11 %) were confirmed as S. aureus while the rest were coagulase negative Staphylococci (85 % misidentification rate), Bacillus sp. (12 % misidentification rate), and Brevibacterium sp. (3 % misidentification rate). Conclusion: A high rate of false positive identification of S. aureus which could lead to the misuse of antibiotics in emergency situation has been identified in this study. The use of standard methods for the identification of S. aureus at all times is highly recommended.

The STRATIFY tool and clinical judgment were poor predictors of falling in an acute hospital setting

Objective: To compare the effectiveness of the STRATIFY falls tool with nurses’ clinical judgments in predicting patient falls. Study Design and Setting: A prospective cohort study was conducted among the inpatients of an acute tertiary hospital. Participants were patients over 65 years of age admitted to any hospital unit. Sensitivity, specificity, and positive predictive value (PPV) and negative predictive values (NPV) of the instrument and nurses’ clinical judgments in predicting falls were calculated. Results: Seven hundred and eighty-eight patients were screened and followed up during the study period. The fall prevalence was 9.2%. Of the 335 patients classified as being ‘‘at risk’’ for falling using the STRATIFY tool, 59 (17.6%) did sustain a fall (sensitivity50.82, specificity50.61, PPV50.18, NPV50.97). Nurses judged that 501 patients were at risk of falling and, of these, 60 (12.0%) fell (sensitivity50.84, specificity50.38, PPV50.12, NPV50.96). The STRATIFY tool correctly identified significantly more patients as either fallers or nonfallers than the nurses (P50.027). Conclusion: Considering the poor specificity and high rates of false-positive results for both the STRATIFY tool and nurses’ clinical judgments, we conclude that neither of these approaches are useful for screening of falls in acute hospital settings.

Augmenting RatSLAM using FAB-MAP-based visual data association

This paper investigates the use of the FAB-MAP appearance-only SLAM algorithm as a method for performing visual data association for RatSLAM, a semi-metric full SLAM system. While both systems have shown the ability to map large (60-70km) outdoor locations of approximately the same scale, for either larger areas or across longer time periods both algorithms encounter difficulties with false positive matches. By combining these algorithms using a mapping between appearance and pose space, both false positives and false negatives generated by FAB-MAP are significantly reduced during outdoor mapping using a forward-facing camera. The hybrid FAB-MAP-RatSLAM system developed demonstrates the potential for successful SLAM over large periods of time.

Detection of anomalies from user profiles generated from system logs

We describe research into the identification of anomalous events and event patterns as manifested in computer system logs. Prototype software has been developed with a capability that identifies anomalous events based on usage patterns or user profiles, and alerts administrators when such events are identified. To reduce the number of false positive alerts we have investigated the use of different user profile training techniques and introduce the use of abstractions to group together applications which are related. Our results suggest that the number of false alerts that are generated is significantly reduced when a growing time window is used for user profile training and when abstraction into groups of applications is used.

Data flow analysis of embedded program expressions

Data flow analysis techniques can be used to help assess threats to data confidentiality and integrity in security critical program code. However, a fundamental weakness of static analysis techniques is that they overestimate the ways in which data may propagate at run time. Discounting large numbers of these false-positive data flow paths wastes an information security evaluator's time and effort. Here we show how to automatically eliminate some false-positive data flow paths by precisely modelling how classified data is blocked by certain expressions in embedded C code. We present a library of detailed data flow models of individual expression elements and an algorithm for introducing these components into conventional data flow graphs. The resulting models can be used to accurately trace byte-level or even bit-level data flow through expressions that are normally treated as atomic. This allows us to identify expressions that safely downgrade their classified inputs and thereby eliminate false-positive data flow paths from the security evaluation process. To validate the approach we have implemented and tested it in an existing data flow analysis toolkit.