The new school absentees reporting system for pandemic influenza A/H1N1 2009 infection in Japan

Objective

To evaluate the new Japanese School Absentees Reporting System for Infectious Disease (SARSID) for pandemic influenza A/H1N1 2009 infection in comparison with the National epidemiological Surveillance of Infectious Disease (NESID).

Methods

We used data of 53,223 students (97.7%) in Takamatsu city Japan. Data regarding school absentees in SARSID was compared with that in NESID from Oct 13, 2009 to Jan 12, 2010.

Results

Similar trends were observed both in SARSID and NESID. However, the epidemic trend for influenza in SARSID was thought to be more sensitive than that in NESID.

Conclusion

The epidemic trend for influenza among school-aged children could be easily and rapidly assessed by SARSID compared to NESID. SARSID might be useful for detecting the epidemic trend of influenza.     

Assisted Knowledge Discovery for the Maintenance of Clinical Guidelines

Background

Improving antibiotic prescribing practices is an important public-health priority given the widespread antimicrobial resistance. Establishing clinical practice guidelines is crucial to this effort, but their development is a complex task and their quality is directly related to the methodology and source of knowledge used.

Objective

We present the design and the evaluation of a tool (KART) that aims to facilitate the creation and maintenance of clinical practice guidelines based on information retrieval techniques.

Methods

KART consists of three main modules 1) a literature-based medical knowledge extraction module, which is built upon a specialized question-answering engine; 2) a module to normalize clinical recommendations based on automatic text categorizers; and 3) a module to manage clinical knowledge, which formalizes and stores clinical recommendations for further use. The evaluation of the usability and utility of KART followed the methodology of the cognitive walkthrough.

Results

KART was designed and implemented as a standalone web application. The quantitative evaluation of the medical knowledge extraction module showed that 53% of the clinical recommendations generated by KART are consistent with existing clinical guidelines. The user-based evaluation confirmed this result by showing that KART was able to find a relevant antibiotic for half of the clinical scenarios tested. The automatic normalization of the recommendation produced mixed results among end-users.

Conclusions

We have developed an innovative approach for the process of clinical guidelines development and maintenance in a context where available knowledge is increasing at a rate that cannot be sustained by humans. In contrast to existing knowledge authoring tools, KART not only provides assistance to normalize, formalize and store clinical recommendations, but also aims to facilitate knowledge building.     

Variability in pediatric infectious disease consultants' recommendations for management of community-acquired pneumonia

Background

Community-acquired pneumonia (CAP) is a common childhood infection. CAP complications, such as parapneumonic empyema (PPE), are increasing and are frequently caused by antibiotic-resistant organisms. No clinical guidelines currently exist for management of pediatric CAP and no published data exist about variations in antibiotic prescribing patterns. Our objectives were to describe variation in CAP clinical management for hospitalized children by pediatric infectious disease consultants and to examine associations between recommended antibiotic regimens and local antibiotic resistance levels.

Methods

We surveyed pediatric members of the Emerging Infections Network, which consists of 259 pediatric infectious disease physicians. Participants responded regarding their recommended empiric antibiotic regimens for hospitalized children with CAP with and without PPE and their recommendations for duration of therapy. Participants also provided information about the prevalence of penicillin non-susceptible S. pneumoniae and methicillin-resistant S. aureus (MRSA) in their community.

Results

We received 148 responses (57%). For uncomplicated CAP, respondents were divided between recommending beta-lactams alone (55%) versus beta-lactams in combination with another class (40%). For PPE, most recommended a combination of a beta-lactam plus an anti-MRSA agent, however, they were divided between clindamycin (44%) and vancomycin (57%). The relationship between reported antibiotic resistance and empiric regimen was mixed. We found no relationship between aminopenicillin use and prevalence of penicillin non-suscepetible S. pneumoniae or clindamycin use and clindamycin resistance, however, respondents were more likely to recommend an anti-MRSA agent when MRSA prevalence increased.

Conclusions

Substantial variability exists in recommendations for CAP management. Development of clinical guidelines via antimicrobial stewardship programs and dissemination of data about local antibiotic resistance patterns represent opportunities to improve care.     

Use of the D-R model to define trends in the emergence of Ceftazidime-resistant Escherichia coli in China

Objective

To assess the efficacy of the D-R model for defining trends in the appearance of Ceftazidime-resistant Escherichia coli.

Methods

Actual data related to the manifestation of Ceftazidime-resistant E. coli spanning years 1996–2009 were collected from the China National Knowledge Internet. These data originated from 430 publications encompassing 1004 citations of resistance. The GM(1,1) and the novel D-R models were used to fit current data and from this, predict trends in the appearance of the drug-resistant phenotype. The results were evaluated by Relative Standard Error (RSE), Mean Absolute Deviation (MAD) and Mean Absolute Error (MAE).

Results

Results from the D-R model showed a rapid increase in the appearance of Ceftazidime-resistant E. coli in this region of the world. These results were considered accurate based upon the minor values calculated for RSE, MAD and MAE, and were equivalent to or better than those generated by the GM(1,1) model.

Conclusion

The D-R model which was originally created to define trends in the transmission of swine viral diseases can be adapted to evaluating trends in the appearance of Ceftazidime-resistant E. coli. Using only a limited amount of data to initiate the study, our predictions closely mirrored the changes in drug resistance rates which showed a steady increase through 2005, a decrease between 2005 and 2008, and a dramatic inflection point and abrupt increase beginning in 2008. This is consistent with a resistance profile where changes in drug intervention temporarily delayed the upward trend in the appearance of the resistant phenotype; however, resistance quickly resumed its upward momentum in 2008 and this change was better predicted using the D-R model. Additional work is needed to determine if this pattern of “increase-control-increase” is indicative of Ceftazidime-resistant E. coli or can be generally ascribed to bacteria acquiring resistance to drugs in the absence of alternative intervention.     

The Use of Machine Learning Methodologies to Analyse Antibiotic and Biocide Susceptibility in Staphylococcus aureus

Background

The rise of antibiotic resistance in pathogenic bacteria is a significant problem for the treatment of infectious diseases. Resistance is usually selected by the antibiotic itself; however, biocides might also co-select for resistance to antibiotics. Although resistance to biocides is poorly defined, different in vitro studies have shown that mutants presenting low susceptibility to biocides also have reduced susceptibility to antibiotics. However, studies with natural bacterial isolates are more limited and there are no clear conclusions as to whether the use of biocides results in the development of multidrug resistant bacteria.

Methods

The main goal is to perform an unbiased blind-based evaluation of the relationship between antibiotic and biocide reduced susceptibility in natural isolates of Staphylococcus aureus. One of the largest data sets ever studied comprising 1632 human clinical isolates of S. aureus originated worldwide was analysed. The phenotypic characterization of 13 antibiotics and 4 biocides was performed for all the strains. Complex links between reduced susceptibility to biocides and antibiotics are difficult to elucidate using the standard statistical approaches in phenotypic data. Therefore, machine learning techniques were applied to explore the data.

Results

In this pioneer study, we demonstrated that reduced susceptibility to two common biocides, chlorhexidine and benzalkonium chloride, which belong to different structural families, is associated to multidrug resistance. We have consistently found that a minimum inhibitory concentration greater than 2 mg/L for both biocides is related to antibiotic non-susceptibility in S. aureus.

Conclusions

Two important results emerged from our work, one methodological and one other with relevance in the field of antibiotic resistance. We could not conclude on whether the use of antibiotics selects for biocide resistance or vice versa. However, the observation of association between multiple resistance and two biocides commonly used may be of concern for the treatment of infectious diseases in the future.     

Health outcome measures in atopic dermatitis: a systematic review of trends in disease severity and quality-of-life instruments 1985-2010

Background

A number of disease-severity and quality-of-life (QoL) instruments have emerged in atopic dermatitis (AD) in the last decade.

Objectives

To identify trends in outcomes instruments used in AD clinical trials and to provide a useful summary of the dimensions and validation studies for the most commonly used measures.

Method

All randomized control trials (RCTs) from 1985 to 2010 in the treatment of AD were examined.

Results

Among the 791 RCTs reviewed, we identified 20 disease-severity and 14 QoL instruments. Of these outcomes instruments, few have been validated. SCORAD, EASI, IGA and SASSAD were the most commonly used disease-severity instruments and CDLQI, DFI, DLQI and IDQOL were the most frequently used QoL measures.

Limitations

The small number of RCTs using QoL scales makes identifying trends for QoL instruments difficult.

Conclusion

Overall, there is an increase in the use of disease-severity and QoL instruments in AD clinical trials.     

Early-Onset Ventilator-Associated Pneumonia in Adults Randomized Clinical Trial: Comparison of 8 versus 15 Days of Antibiotic Treatment

Purpose

The optimal treatment duration for ventilator-associated pneumonia is based on one study dealing with late-onset of the condition. Shortening the length of antibiotic treatment remains a major prevention factor for the emergence of multiresistant bacteria.

Objective

To demonstrate that 2 different antibiotic treatment durations (8 versus 15 days) are equivalent in terms of clinical cure for early-onset ventilator-associated pneumonia.

Methods

Randomized, prospective, open, multicenter trial carried out from 1998 to 2002.

Measurements

The primary endpoint was the clinical cure rate at day 21. The mortality rate was evaluated on days 21 and 90.

Results

225 patients were included in 13 centers. 191 (84.9%) patients were cured: 92 out of 109 (84.4%) in the 15 day cohort and 99 out of 116 (85.3%) in the 8 day cohort (difference = 0.9%, odds ratio = 0.929). 95% two-sided confidence intervals for difference and odds ratio were [−8.4% to 10.3%] and [0.448 to 1.928] respectively. Taking into account the limits of equivalence (10% for difference and 2.25 for odds ratio), the objective of demonstrative equivalence between the 2 treatment durations was fulfilled. Although the rate of secondary infection was greater in the 8 day than the 15 day cohort, the number of days of antibiotic treatment remained lower in the 8 day cohort. There was no difference in mortality rate between the 2 groups on days 21 and 90.

Conclusion

Our results suggest that an 8-day course of antibiotic therapy is safe for early-onset ventilator-associated pneumonia in intubated patients.

Trial Registration

ClinicalTrials.gov {"type":"clinical-trial","attrs":{"text":"NCT01559753","term_id":"NCT01559753"}}NCT01559753     

A Hybrid Model for Predicting the Prevalence of Schistosomiasis in Humans of Qianjiang City,China

Backgrounds/Objective

Schistosomiasis is still a major public health problem in China, despite the fact that the government has implemented a series of strategies to prevent and control the spread of the parasitic disease. Advanced warning and reliable forecasting can help policymakers to adjust and implement strategies more effectively, which will lead to the control and elimination of schistosomiasis. Our aim is to explore the application of a hybrid forecasting model to track the trends of the prevalence of schistosomiasis in humans, which provides a methodological basis for predicting and detecting schistosomiasis infection in endemic areas.

Methods

A hybrid approach combining the autoregressive integrated moving average (ARIMA) model and the nonlinear autoregressive neural network (NARNN) model to forecast the prevalence of schistosomiasis in the future four years. Forecasting performance was compared between the hybrid ARIMA-NARNN model, and the single ARIMA or the single NARNN model.

Results

The modelling mean square error (MSE), mean absolute error (MAE) and mean absolute percentage error (MAPE) of the ARIMA-NARNN model was 0.1869×10⁻⁴, 0.0029, 0.0419 with a corresponding testing error of 0.9375×10⁻⁴, 0.0081, 0.9064, respectively. These error values generated with the hybrid model were all lower than those obtained from the single ARIMA or NARNN model. The forecasting values were 0.75%, 0.80%, 0.76% and 0.77% in the future four years, which demonstrated a no-downward trend.

Conclusion

The hybrid model has high quality prediction accuracy in the prevalence of schistosomiasis, which provides a methodological basis for future schistosomiasis monitoring and control strategies in the study area. It is worth attempting to utilize the hybrid detection scheme in other schistosomiasis-endemic areas including other infectious diseases.     

The Impact of Different Antibiotic Regimens on the Emergence of Antimicrobial-Resistant Bacteria

Backgroud

The emergence and ongoing spread of antimicrobial-resistant bacteria is a major public health threat. Infections caused by antimicrobial-resistant bacteria are associated with substantially higher rates of morbidity and mortality compared to infections caused by antimicrobial-susceptible bacteria. The emergence and spread of these bacteria is complex and requires incorporating numerous interrelated factors which clinical studies cannot adequately address.

Methods/Principal Findings

A model is created which incorporates several key factors contributing to the emergence and spread of resistant bacteria including the effects of the immune system, acquisition of resistance genes and antimicrobial exposure. The model identifies key strategies which would limit the emergence of antimicrobial-resistant bacterial strains. Specifically, the simulations show that early initiation of antimicrobial therapy and combination therapy with two antibiotics prevents the emergence of resistant bacteria, whereas shorter courses of therapy and sequential administration of antibiotics promote the emergence of resistant strains.

Conclusions/Significance

The principal findings suggest that (i) shorter lengths of antibiotic therapy and early interruption of antibiotic therapy provide an advantage for the resistant strains, (ii) combination therapy with two antibiotics prevents the emergence of resistance strains in contrast to sequential antibiotic therapy, and (iii) early initiation of antibiotics is among the most important factors preventing the emergence of resistant strains. These findings provide new insights into strategies aimed at optimizing the administration of antimicrobials for the treatment of infections and the prevention of the emergence of antimicrobial resistance.     

Comparative genomic analysis of Acinetobacter baumannii clinical isolates reveals extensive genomic variation and diverse antibiotic resistance determinants

Background

Acinetobacter baumannii is an important nosocomial pathogen that poses a serious health threat to immune-compromised patients. Due to its rapid ability to develop multidrug resistance (MDR), A. baumannii has increasingly become a focus of attention worldwide. To better understand the genetic variation and antibiotic resistance mechanisms of this bacterium at the genomic level, we reported high-quality draft genome sequences of 8 clinical isolates with various sequence types and drug susceptibility profiles.

Results

We sequenced 7 MDR and 1 drug-sensitive clinical A. baumannii isolates and performed comparative genomic analysis of these draft genomes with 16 A. baumannii complete genomes from GenBank. We found a high degree of variation in A. baumannii, including single nucleotide polymorphisms (SNPs) and large DNA fragment variations in the AbaR-like resistance island (RI) regions, the prophage and the type VI secretion system (T6SS). In addition, we found several new AbaR-like RI regions with highly variable structures in our MDR strains. Interestingly, we found a novel genomic island (designated as GI_BJ4) in the drug-sensitive strain BJ4 carrying metal resistance genes instead of antibiotic resistance genes inserted into the position where AbaR-like RIs commonly reside in other A. baumannii strains. Furthermore, we showed that diverse antibiotic resistance determinants are present outside the RIs in A. baumannii, including antibiotic resistance-gene bearing integrons, the bla_OXA-23-containing transposon Tn2009, and chromosomal intrinsic antibiotic resistance genes.

Conclusions

Our comparative genomic analysis revealed that extensive genomic variation exists in the A. baumannii genome. Transposons, genomic islands and point mutations are the main contributors to the plasticity of the A. baumannii genome and play critical roles in facilitating the development of antibiotic resistance in the clinical isolates.

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2164-15-1163) contains supplementary material, which is available to authorized users.     

Do Seasons Have an Influence on the Incidence of Depression? The Use of an Internet Search Engine Query Data as a Proxy of Human Affect

Background

Seasonal depression has generated considerable clinical interest in recent years. Despite a common belief that people in higher latitudes are more vulnerable to low mood during the winter, it has never been demonstrated that human''s moods are subject to seasonal change on a global scale. The aim of this study was to investigate large-scale seasonal patterns of depression using Internet search query data as a signature and proxy of human affect.

Methodology/Principal Findings

Our study was based on a publicly available search engine database, Google Insights for Search, which provides time series data of weekly search trends from January 1, 2004 to June 30, 2009. We applied an empirical mode decomposition method to isolate seasonal components of health-related search trends of depression in 54 geographic areas worldwide. We identified a seasonal trend of depression that was opposite between the northern and southern hemispheres; this trend was significantly correlated with seasonal oscillations of temperature (USA: r = −0.872, p<0.001; Australia: r = −0.656, p<0.001). Based on analyses of search trends over 54 geological locations worldwide, we found that the degree of correlation between searching for depression and temperature was latitude-dependent (northern hemisphere: r = −0.686; p<0.001; southern hemisphere: r = 0.871; p<0.0001).

Conclusions/Significance

Our findings indicate that Internet searches for depression from people in higher latitudes are more vulnerable to seasonal change, whereas this phenomenon is obscured in tropical areas. This phenomenon exists universally across countries, regardless of language. This study provides novel, Internet-based evidence for the epidemiology of seasonal depression.     

Systematic Review of the Literature and Evidence-Based Recommendations for Antibiotic Prophylaxis in Trauma: Results from an Italian Consensus of Experts

Background

Antibiotic prophylaxis is frequently administered in severe trauma. However, the risk of selecting resistant bacteria, a major issue especially in critical care environments, has not been sufficiently investigated. The aim of the present study was to provide guidelines for antibiotic prophylaxis for four different trauma-related clinical conditions, taking into account the risks of antibiotic-resistant bacteria selection, thus innovating previous guidelines in the field.

Methods

The MEDLINE database was searched for studies comparing antibiotic prophylaxis to controls (placebo or no antibiotic administration) in four clinical traumatic conditions that were selected on the basis of the traumatic event frequency and/or infection severity. The selected studies focused on the prevention of early ventilator associated pneumonia (VAP) in comatose patients with traumatic brain injury, of meningitis in severe basilar skull fractures, of wound infections in long-bone open fractures. Since no placebo-controlled study was available for deep surgical site-infections prevention in abdominal trauma with enteric contamination, we compared 24-hour and 5-day antibiotic prophylaxis policies. A separate specific research focused on the question of antibiotic-resistant bacteria selection caused by antibiotic prophylaxis, an issue not adequately investigated by the selected studies. Randomised trials, reviews, meta-analyses, observational studies were included. Data extraction was carried out by one author according to a predefined protocol, using an electronic form. The strength of evidence was stratified and recommendations were given according to the Grading of Recommendations Assessment, Development and Evaluation (GRADE) criteria.

Results

Uncertain evidence deserving further studies was found for two-dose antibiotic prophylaxis for early VAP prevention in comatose patients. In the other cases the risk of resistant-bacteria selection caused by antibiotic administration for 48 hours or more, outweighed potential benefits.

Conclusions

When accounting for antibiotic-resistant bacteria selection we found no evidence in favour of antibiotic prophylaxis lasting two or more days in the studied clinical conditions.     

Distribution of Serotypes,Vaccine Coverage,and Antimicrobial Susceptibility Pattern of Streptococcus Pneumoniae in Children Living in SAARC Countries: A Systematic Review

Introduction

Each SAARC nation falls in the zone of high incidence of pneumococcal disease but there is a paucity of literature estimating the burden of pneumococcal disease in this region.

Objective

To identify the prevalent serotypes causing invasive pneumococcal disease in children of SAARC countries, to determine the coverage of these serotypes by the available vaccines, and to determine the antibiotic resistance pattern of Streptococcus pneumoniae.

Methods

We searched major electronic databases using a comprehensive search strategy, and additionally searched the bibliography of the included studies and retrieved articles till July 2014. Both community and hospital based observational studies which included children aged ≤12 years as/or part of the studied population in SAARC countries were included.

Results

A total of 17 studies were included in the final analysis. The period of surveillance varied from 12–96 months (median, 24 months). The most common serotypes country-wise were as follows: serotype 1 in Nepal; serotype 14 in Bangladesh and India; serotype 19F in Sri Lanka and Pakistan. PCV-10 was found to be suitable for countries like India, Nepal, Bangladesh, and Sri Lanka, whereas PCV-13 may be more suitable for Pakistan. An increasing trend of non-susceptibility to antibiotics was noted for co-trimoxazole, erythromycin and chloramphenicol, whereas an increasing trend of susceptibility was noted for penicillin.

Conclusion

Due to paucity of recent data in majority of the SAARC countries, urgent large size prospective studies are needed to formulate recommendations for specific pneumococcal vaccine introduction and usage of antimicrobial agents in these regions.     

Rising Midlife Obesity Will Worsen Future Prevalence of Dementia

Background

Midlife body weight status has been found to affect late life dementia outcomes. A cohort projections model was developed to assess the impact of midlife body mass index (BMI) profile on dementia in older Australians.

Methods

A baseline projection using age-sex specific dementia prevalence rates was constructed and the results of scenarios that took account of midlife BMI were compared with those from population ageing only.

Results

This modelling predicts that if the rising trend in midlife obesity and declining trend in midlife normal weight in Australia are to be taken into account in projecting future numbers of Australians with dementia then the number of people aged 65 or more years with dementia, by 2050, would be 14% higher than that expected from demographic ageing only. If midlife obesity prevalence was decreased to 20% and normal weight increased to 40% over the period of 2015–2025, then dementia cases among persons aged 65–69 years would be lower by about 10% in 2050 compared with the “doing nothing to stop current trends in obesity” projection.

Conclusion

The rising tide of obesity in Australian adults will increase the dementia epidemic expected in future years.     

Treatment-Related Death in Patients with Small-Cell Lung Cancer in Phase III Trials over the Last Two Decades

Introduction

Treatment-related death (TRD) remains a serious problem in small-cell lung cancer (SCLC), despite recent improvements in supportive care. However, few studies have formally assessed time trends in the proportion of TRD over the past two decades. The aim of this study was to determine the frequency and pattern of TRD over time.

Methods

We examined phase 3 trials conducted between 1990 and 2010 to address the role of systemic treatment for SCLC. The time trend was assessed using linear regression analysis.

Results

In total, 97 trials including nearly 25,000 enrolled patients were analyzed. The overall TRD proportion was 2.95%. Regarding the time trend, while it was not statistically significant, it tended to decrease, with a 0.138% decrease per year and 2.76% decrease per two decades. The most common cause of death was febrile neutropenia without any significant time trend in its incidence over the years examined (p = 0.139). However, deaths due to febrile neutropenia as well as all causes in patients treated with non-platinum chemotherapy increased significantly (p = 0.033).

Conclusions

The overall TRD rate has been low, but not negligible, in phase III trials for SCLC over the past two decades.     

Quinolone resistance in absence of selective pressure: the experience of a very remote community in the Amazon forest

Background

Quinolones are potent broad-spectrum bactericidal agents increasingly employed also in resource-limited countries. Resistance to quinolones is an increasing problem, known to be strongly associated with quinolone exposure. We report on the emergence of quinolone resistance in a very remote community in the Amazon forest, where quinolones have never been used and quinolone resistance was absent in 2002.

Methods

The community exhibited a considerable level of geographical isolation, limited contact with the exterior and minimal antibiotic use (not including quinolones). In December 2009, fecal carriage of antibiotic resistant Escherichia coli was investigated in 120 of the 140 inhabitants, and in 48 animals reared in the community. All fluoroquinolone-resistant isolates were genotyped and characterized for the mechanisms of plasmid- and chromosomal-mediated quinolone resistance.

Principal Findings

Despite the characteristics of the community remained substantially unchanged during the period 2002–2009, carriage of quinolone-resistant E. coli was found to be common in 2009 both in humans (45% nalidixic acid, 14% ciprofloxacin) and animals (54% nalidixic acid, 23% ciprofloxacin). Ciprofloxacin-resistant isolates of human and animal origin showed multidrug resistance phenotypes, a high level of genetic heterogeneity, and a combination of GyrA (Ser83Leu and Asp87Asn) and ParC (Ser80Ile) substitutions commonly observed in fluoroquinolone-resistant clinical isolates of E. coli.

Conclusions

Remoteness and absence of antibiotic selective pressure did not protect the community from the remarkable emergence of quinolone resistance in E. coli. Introduction of the resistant strains from antibiotic-exposed settings is the most likely source, while persistence and dissemination in the absence of quinolone exposure is likely mostly related with poor sanitation. Interventions aimed at reducing the spreading of resistant isolates (by improving sanitation and water/food safety) are urgently needed to preserve the efficacy of quinolones in resource-limited countries, as control strategies based only on antibiotic restriction policies are unlikely to succeed in those settings.