Methicillin-resistant Staphylococcus aureus in Finland: recent changes in the epidemiology, long-term facility aspects, and phenotypic and molecular detection of isolates

Staphylococcus aureus is one of the most important bacteria that cause disease in humans, and methicillin-resistant S. aureus (MRSA) has become the most commonly identified antibiotic-resistant pathogen in many parts of the world. MRSA rates have been stable for many years in the Nordic countries and the Netherlands with a low MRSA prevalence in Europe, but in the recent decades, MRSA rates have increased in those low-prevalence countries as well. MRSA has been established as a major hospital pathogen, but has also been found increasingly in long-term facilities (LTF) and in communities of persons with no connections to the health-care setting. In Finland, the annual number of MRSA isolates reported to the National Infectious Disease Register (NIDR) has constantly increased, especially outside the Helsinki metropolitan area. Molecular typing has revealed numerous outbreak strains of MRSA, some of which have previously been associated with community acquisition. In this work, data on MRSA cases notified to the NIDR and on MRSA strain types identified with pulsed-field gel electrophoresis (PFGE), multilocus sequence typing (MLST), and staphylococcal cassette chromosome mec (SCCmec) typing at the National Reference Laboratory (NRL) in Finland from 1997 to 2004 were analyzed. An increasing trend in MRSA incidence in Finland from 1997 to 2004 was shown. In addition, non-multi-drug resistant (NMDR) MRSA isolates, especially those resistant only to methicillin/oxacillin, showed an emerging trend. The predominant MRSA strains changed over time and place, but two internationally spread epidemic strains of MRSA, FIN-16 and FIN-21, were related to the increase detected most recently. Those strains were also one cause of the strikingly increasing invasive MRSA findings. The rise of MRSA strains with SCCmec types IV or V, possible community-acquired MRSA was also detected. With questionnaires, the diagnostic methods used for MRSA identification in Finnish microbiology laboratories and the number of MRSA screening specimens studied were reviewed. Surveys, which focused on the MRSA situation in long-term facilities in 2001 and on the background information of MRSA-positive persons in 2001-2003, were also carried out. The rates of MRSA and screening practices varied widely across geographic regions. Part of the NMDR MRSA strains could remain undetected in some laboratories because of insufficient diagnostic techniques used. The increasing proportion of elderly population carrying MRSA suggests that MRSA is an emerging problem in Finnish long-term facilities. Among the patients, 50% of the specimens were taken on a clinical basis, 43% on a screening basis after exposure to MRSA, 3% on a screening basis because of hospital contact abroad, and 4% for other reasons. In response to an outbreak of MRSA possessing a new genotype that occurred in a health care ward and in an associated nursing home of a small municipality in Northern Finland in autumn 2003, a point-prevalence survey was performed six months later. In the same study, the molecular epidemiology of MRSA and methicillin-sensitive S. aureus (MSSA) strains were also assessed, the results to the national strain collection compared, and the difficulties of MRSA screening with low-level oxacillin-resistant isolates encountered. The original MRSA outbreak in LTF, which consisted of isolates possessing a nationally new PFGE profile (FIN-22) and internationally rare MLST type (ST-27), was confined. Another previously unrecognized MRSA strain was found with additional screening, possibly indicating that current routine MRSA screening methods may be insufficiently sensitive for strains possessing low-level oxacillin resistance. Most of the MSSA strains found were genotypically related to the epidemic MRSA strains, but only a few of them had received the SCCmec element, and all those strains possessed the new SCCmec type V. In the second largest nursing home in Finland, the colonization of S. aureus and MRSA, and the role of screening sites along with broth enrichment culture on the sensitivity to detect S. aureus were studied. Combining the use of enrichment broth and perineal swabbing, in addition to nostrils and skin lesions swabbing, may be an alternative for throat swabs in the nursing home setting, especially when residents are uncooperative. Finally, in order to evaluate adequate phenotypic and genotypic methods needed for reliable laboratory diagnostics of MRSA, oxacillin disk diffusion and MIC tests to the cefoxitin disk diffusion method at both +35°C and +30°C, both with or without an addition of sodium chloride (NaCl) to the Müller Hinton test medium, and in-house PCR to two commercial molecular methods (the GenoType® MRSA test and the EVIGENETM MRSA Detection test) with different bacterial species in addition to S. aureus were compared. The cefoxitin disk diffusion method was superior to that of oxacillin disk diffusion and to the MIC tests in predicting mecA-mediated resistance in S. aureus when incubating at +35°C with or without the addition of NaCl to the test medium. Both the Geno Type® MRSA and EVIGENETM MRSA Detection tests are usable, accurate, cost-effective, and sufficiently fast methods for rapid MRSA confirmation from a pure culture.

Placental abruption : Studies on incidence, risk factors and potential predictive biomarkers

Placental abruption, one of the most significant causes of perinatal mortality and maternal morbidity, occurs in 0.5-1% of pregnancies. Its etiology is unknown, but defective trophoblastic invasion of the spiral arteries and consequent poor vascularization may play a role. The aim of this study was to define the prepregnancy risk factors of placental abruption, to define the risk factors during the index pregnancy, and to describe the clinical presentation of placental abruption. We also wanted to find a biochemical marker for predicting placental abruption early in pregnancy. Among women delivering at the University Hospital of Helsinki in 1997-2001 (n=46,742), 198 women with placental abruption and 396 control women were identified. The overall incidence of placental abruption was 0.42%. The prepregnancy risk factors were smoking (OR 1.7; 95% CI 1.1, 2.7), uterine malformation (OR 8.1; 1.7, 40), previous cesarean section (OR 1.7; 1.1, 2.8), and history of placental abruption (OR 4.5; 1.1, 18). The risk factors during the index pregnancy were maternal (adjusted OR 1.8; 95% CI 1.1, 2.9) and paternal smoking (2.2; 1.3, 3.6), use of alcohol (2.2; 1.1, 4.4), placenta previa (5.7; 1.4, 23.1), preeclampsia (2.7; 1.3, 5.6) and chorioamnionitis (3.3; 1.0, 10.0). Vaginal bleeding (70%), abdominal pain (51%), bloody amniotic fluid (50%) and fetal heart rate abnormalities (69%) were the most common clinical manifestations of placental abruption. Retroplacental blood clot was seen by ultrasound in 15% of the cases. Neither bleeding nor pain was present in 19% of the cases. Overall, 59% went into preterm labor (OR 12.9; 95% CI 8.3, 19.8), and 91% were delivered by cesarean section (34.7; 20.0, 60.1). Of the newborns, 25% were growth restricted. The perinatal mortality rate was 9.2% (OR 10.1; 95% CI 3.4, 30.1). We then tested selected biochemical markers for prediction of placental abruption. The median of the maternal serum alpha-fetoprotein (MSAFP) multiples of median (MoM) (1.21) was significantly higher in the abruption group (n=57) than in the control group (n=108) (1.07) (p=0.004) at 15-16 gestational weeks. In multivariate analysis, elevated MSAFP remained as an independent risk factor for placental abruption, adjusting for parity ≥ 3, smoking, previous placental abruption, preeclampsia, bleeding in II or III trimester, and placenta previa. MSAFP ≥ 1.5 MoM had a sensitivity of 29% and a false positive rate of 10%. The levels of the maternal serum free beta human chorionic gonadotrophin MoM did not differ between the cases and the controls. None of the angiogenic factors (soluble endoglin, soluble fms-like tyrosine kinase 1, or placental growth factor) showed any difference between the cases (n=42) and the controls (n=50) in the second trimester. The levels of C-reactive protein (CRP) showed no difference between the cases (n=181) and the controls (n=261) (median 2.35 mg/l [interquartile range {IQR} 1.09-5.93] versus 2.28 mg/l [IQR 0.92-5.01], not significant) when tested in the first trimester (mean 10.4 gestational weeks). Chlamydia pneumoniae specific immunoglobulin G (IgG) and immunoglobulin A (IgA) as well as C. trachomatis specific IgG, IgA and chlamydial heat-shock protein 60 antibody rates were similar between the groups. In conclusion, although univariate analysis identified many prepregnancy risk factors for placental abruption, only smoking, uterine malformation, previous cesarean section and history of placental abruption remained significant by multivariate analysis. During the index pregnancy maternal alcohol consumption and smoking and smoking by the partner turned out to be the major independent risk factors for placental abruption. Smoking by both partners multiplied the risk. The liberal use of ultrasound examination contributed little to the management of women with placental abruption. Although second-trimester MSAFP levels were higher in women with subsequent placental abruption, clinical usefulness of this test is limited due to low sensitivity and high false positive rate. Similarly, angiogenic factors in early second trimester, or CRP levels, or chlamydial antibodies in the first trimester failed to predict placental abruption.

Detecting Earnings Management Using Neural Networks

Detecting Earnings Management Using Neural Networks. Trying to balance between relevant and reliable accounting data, generally accepted accounting principles (GAAP) allow, to some extent, the company management to use their judgment and to make subjective assessments when preparing financial statements. The opportunistic use of the discretion in financial reporting is called earnings management. There have been a considerable number of suggestions of methods for detecting accrual based earnings management. A majority of these methods are based on linear regression. The problem with using linear regression is that a linear relationship between the dependent variable and the independent variables must be assumed. However, previous research has shown that the relationship between accruals and some of the explanatory variables, such as company performance, is non-linear. An alternative to linear regression, which can handle non-linear relationships, is neural networks. The type of neural network used in this study is the feed-forward back-propagation neural network. Three neural network-based models are compared with four commonly used linear regression-based earnings management detection models. All seven models are based on the earnings management detection model presented by Jones (1991). The performance of the models is assessed in three steps. First, a random data set of companies is used. Second, the discretionary accruals from the random data set are ranked according to six different variables. The discretionary accruals in the highest and lowest quartiles for these six variables are then compared. Third, a data set containing simulated earnings management is used. Both expense and revenue manipulation ranging between -5% and 5% of lagged total assets is simulated. Furthermore, two neural network-based models and two linear regression-based models are used with a data set containing financial statement data from 110 failed companies. Overall, the results show that the linear regression-based models, except for the model using a piecewise linear approach, produce biased estimates of discretionary accruals. The neural network-based model with the original Jones model variables and the neural network-based model augmented with ROA as an independent variable, however, perform well in all three steps. Especially in the second step, where the highest and lowest quartiles of ranked discretionary accruals are examined, the neural network-based model augmented with ROA as an independent variable outperforms the other models.

On the use of weather radar for mesoscale applications in northern conditions

Mesoscale weather phenomena, such as the sea breeze circulation or lake effect snow bands, are typically too large to be observed at one point, yet too small to be caught in a traditional network of weather stations. Hence, the weather radar is one of the best tools for observing, analyzing and understanding their behavior and development. A weather radar network is a complex system, which has many structural and technical features to be tuned, from the location of each radar to the number of pulses averaged in the signal processing. These design parameters have no universal optimal values, but their selection depends on the nature of the weather phenomena to be monitored as well as on the applications for which the data will be used. The priorities and critical values are different for forest fire forecasting, aviation weather service or the planning of snow ploughing, to name a few radar-based applications. The main objective of the work performed within this thesis has been to combine knowledge of technical properties of the radar systems and our understanding of weather conditions in order to produce better applications able to efficiently support decision making in service duties for modern society related to weather and safety in northern conditions. When a new application is developed, it must be tested against ground truth . Two new verification approaches for radar-based hail estimates are introduced in this thesis. For mesoscale applications, finding the representative reference can be challenging since these phenomena are by definition difficult to catch with surface observations. Hence, almost any valuable information, which can be distilled from unconventional data sources such as newspapers and holiday shots is welcome. However, as important as getting data is to obtain estimates of data quality, and to judge to what extent the two disparate information sources can be compared. The presented new applications do not rely on radar data alone, but ingest information from auxiliary sources such as temperature fields. The author concludes that in the future the radar will continue to be a key source of data and information especially when used together in an effective way with other meteorological data.