Aerosolized Colistin for the Treatment of Multidrug-resistant Acinetobacter baumannii Pneumonia: Experience in a Tertiary Care Hospital in Northern Taiwan

Background/PurposeVentilator-associated pneumonia (VAP) due to multidrug-resistant (MDR) Acinetobacter baumannii in critically ill patients presents an emerging challenge to clinicians. Administration of aerosolized colistin as an adjunctive therapy is one therapeutic option mentioned in limited evidence-based studies. This study aimed to evaluate the effectiveness of adjunctive aerosolized colistin treatment for VAP due to MDR pathogens.MethodsWe retrospectively reviewed the medical records of patients who had received aerosolized colistin for treatment of VAP due to MDR A. baumannii in our hospital from August to December 2008.ResultsForty-five patients were enrolled in our study. The mean age was 71 ± 15 years. The mean Acute Physiological and Chronic Health Evaluation II (APACHE II) scores on the day of intensive care unit admission and on the first day of aerosolized colistin administration were 22.5 ± 6.7 and 18.9 ± 5.7, respectively. The mean duration of intensive care unit stay was 34 ± 16 days. The mean daily dosage of aerosolized colistin was 4.29 ± 0.82 million IU, and the mean duration of administration was 10.29 days. Seventeen patients (37.8%) had a favorable microbiological outcome and 26 (57.8%) showed a clinical response. Mortality due to all causes was 42.2%. No adverse effects related to inhaled colistin were recorded.ConclusionAerosolized colistin may be considered as an adjunct to intravenous treatments in patients with VAP due to colistin-susceptible MDR A. baumannii in critically ill patients

Clinical characteristics and treatment outcomes of patients with tubo-ovarian abscess at a tertiary care hospital in Northern Taiwan

Background/PurposeControversy exists regarding the need for surgical intervention in patients with tubo-ovarian abscess (TOA). This study was aimed at investigating the clinical characteristics and treatment outcomes in patients with TOA at a tertiary care hospital in Taiwan.MethodsThe medical records of 83 patients who presented at the hospital with TOA between January 1, 2006, and December 31, 2007, were retrospectively reviewed. Outcomes of patients who received medical treatment alone or underwent surgical intervention were analyzed using univariate and logistic regression analyses.ResultsAmong the 83 patients with TOA, 13 patients (15.7%) underwent surgical intervention, and 70 patients (84.3%) received medical treatment alone. Significant variables related to surgical treatment in the univariate analysis were length of stay (short vs. long; t = −2.267, p = 0.026), department of admission (emergency room vs. outpatient department; χ2 = 7.459, p = 0.006), number of live births (nulliparous vs. multiparous; χ2 = 18.202, p = 0.001), and C-reactive protein (CRP) level (high vs. low; t = −2.250, p = 0.028). Logistic regression analysis performed to determine influential factors for surgical treatment showed that the operation odds ratio of three to four live births versus no live births was 33.995 (p = 0.043) and that of two live births versus no live births was 13.598 (p = 0.026).ConclusionPatients with TOA who underwent surgery had a longer duration of hospitalization. Among the patients who underwent surgical intervention, those admitted to the emergency room had higher CRP levels and were more likely to be multiparous

Genome-wide identification of specific oligonucleotides using artificial neural network and computational genomic analysis

<p>Abstract</p> <p>Background</p> <p>Genome-wide identification of specific oligonucleotides (oligos) is a computationally-intensive task and is a requirement for designing microarray probes, primers, and siRNAs. An artificial neural network (ANN) is a machine learning technique that can effectively process complex and high noise data. Here, ANNs are applied to process the unique subsequence distribution for prediction of specific oligos.</p> <p>Results</p> <p>We present a novel and efficient algorithm, named the integration of ANN and BLAST (IAB) algorithm, to identify specific oligos. We establish the unique marker database for human and rat gene index databases using the hash table algorithm. We then create the input vectors, via the unique marker database, to train and test the ANN. The trained ANN predicted the specific oligos with high efficiency, and these oligos were subsequently verified by BLAST. To improve the prediction performance, the ANN over-fitting issue was avoided by early stopping with the best observed error and a k-fold validation was also applied. The performance of the IAB algorithm was about 5.2, 7.1, and 6.7 times faster than the BLAST search without ANN for experimental results of 70-mer, 50-mer, and 25-mer specific oligos, respectively. In addition, the results of polymerase chain reactions showed that the primers predicted by the IAB algorithm could specifically amplify the corresponding genes. The IAB algorithm has been integrated into a previously published comprehensive web server to support microarray analysis and genome-wide iterative enrichment analysis, through which users can identify a group of desired genes and then discover the specific oligos of these genes.</p> <p>Conclusion</p> <p>The IAB algorithm has been developed to construct SpecificDB, a web server that provides a specific and valid oligo database of the probe, siRNA, and primer design for the human genome. We also demonstrate the ability of the IAB algorithm to predict specific oligos through polymerase chain reaction experiments. SpecificDB provides comprehensive information and a user-friendly interface.</p

Genome-wide identification of specific oligonucleotides using artificial neural network and computational genomic analysis

<p>Abstract</p> <p>Background</p> <p>Genome-wide identification of specific oligonucleotides (oligos) is a computationally-intensive task and is a requirement for designing microarray probes, primers, and siRNAs. An artificial neural network (ANN) is a machine learning technique that can effectively process complex and high noise data. Here, ANNs are applied to process the unique subsequence distribution for prediction of specific oligos.</p> <p>Results</p> <p>We present a novel and efficient algorithm, named the integration of ANN and BLAST (IAB) algorithm, to identify specific oligos. We establish the unique marker database for human and rat gene index databases using the hash table algorithm. We then create the input vectors, via the unique marker database, to train and test the ANN. The trained ANN predicted the specific oligos with high efficiency, and these oligos were subsequently verified by BLAST. To improve the prediction performance, the ANN over-fitting issue was avoided by early stopping with the best observed error and a k-fold validation was also applied. The performance of the IAB algorithm was about 5.2, 7.1, and 6.7 times faster than the BLAST search without ANN for experimental results of 70-mer, 50-mer, and 25-mer specific oligos, respectively. In addition, the results of polymerase chain reactions showed that the primers predicted by the IAB algorithm could specifically amplify the corresponding genes. The IAB algorithm has been integrated into a previously published comprehensive web server to support microarray analysis and genome-wide iterative enrichment analysis, through which users can identify a group of desired genes and then discover the specific oligos of these genes.</p> <p>Conclusion</p> <p>The IAB algorithm has been developed to construct SpecificDB, a web server that provides a specific and valid oligo database of the probe, siRNA, and primer design for the human genome. We also demonstrate the ability of the IAB algorithm to predict specific oligos through polymerase chain reaction experiments. SpecificDB provides comprehensive information and a user-friendly interface.</p

Biomarkers in long COVID-19: A systematic review

PurposeLong COVID, also known as post-acute sequelae of COVID-19, refers to the constellation of long-term symptoms experienced by people suffering persistent symptoms for one or more months after SARS-CoV-2 infection. Blood biomarkers can be altered in long COVID patients; however, biomarkers associated with long COVID symptoms and their roles in disease progression remain undetermined. This study aims to systematically evaluate blood biomarkers that may act as indicators or therapeutic targets for long COVID.MethodsA systematic literature review in PubMed, Embase, and CINAHL was performed on 18 August 2022. The search keywords long COVID-19 symptoms and biomarkers were used to filter out the eligible studies, which were then carefully evaluated.ResultsIdentified from 28 studies and representing six biological classifications, 113 biomarkers were significantly associated with long COVID: (1) Cytokine/Chemokine (38, 33.6%); (2) Biochemical markers (24, 21.2%); (3) Vascular markers (20, 17.7%); (4) Neurological markers (6, 5.3%); (5) Acute phase protein (5, 4.4%); and (6) Others (20, 17.7%). Compared with healthy control or recovered patients without long COVID symptoms, 79 biomarkers were increased, 29 were decreased, and 5 required further determination in the long COVID patients. Of these, up-regulated Interleukin 6, C-reactive protein, and tumor necrosis factor alpha might serve as the potential diagnostic biomarkers for long COVID. Moreover, long COVID patients with neurological symptoms exhibited higher levels of neurofilament light chain and glial fibrillary acidic protein whereas those with pulmonary symptoms exhibited a higher level of transforming growth factor beta.ConclusionLong COVID patients present elevated inflammatory biomarkers after initial infection. Our study found significant associations between specific biomarkers and long COVID symptoms. Further investigations are warranted to identify a core set of blood biomarkers that can be used to diagnose and manage long COVID patients in clinical practice

Incidence, risk factors and causes of death in an HIV care programme with a large proportion of injecting drug users.

Objectives  To identify factors influencing mortality in an HIV programme providing care to large numbers of injecting drug users (IDUs) and patients co-infected with hepatitis C (HCV). Methods  A longitudinal analysis of monitoring data from HIV-infected adults who started antiretroviral therapy (ART) between 2003 and 2009 was performed. Mortality and programme attrition rates within 2 years of ART initiation were estimated. Associations with individual-level factors were assessed with multivariable Cox and piece-wise Cox regression. Results  A total of 1671 person-years of follow-up from 1014 individuals was analysed. Thirty-four percent of patients were women and 33% were current or ex-IDUs. 36.2% of patients (90.8% of IDUs) were co-infected with HCV. Two-year all-cause mortality rate was 5.4 per 100 person-years (95% CI, 4.4-6.7). Most HIV-related deaths occurred within 6 months of ART start (36, 67.9%), but only 5 (25.0%) non-HIV-related deaths were recorded during this period. Mortality was higher in older patients (HR = 2.50; 95% CI, 1.42-4.40 for ≥40 compared to 15-29 years), and in those with initial BMI < 18.5 kg/m(2) (HR = 3.38; 95% CI, 1.82-5.32), poor adherence to treatment (HR = 5.13; 95% CI, 2.47-10.65 during the second year of therapy), or low initial CD4 cell count (HR = 4.55; 95% CI, 1.54-13.41 for <100 compared to ≥100 cells/μl). Risk of death was not associated with IDU status (P = 0.38). Conclusion  Increased mortality was associated with late presentation of patients. In this programme, death rates were similar regardless of injection drug exposure, supporting the notion that satisfactory treatment outcomes can be achieved when comprehensive care is provided to these patients

Difference in imipenem, meropenem, sulbactam, and colistin nonsusceptibility trends among three phenotypically undifferentiated Acinetobacter baumannii complex in a medical center in Taiwan, 1997–2007

BackgroundTo determine whether the susceptibilities and the trends of nonsusceptibility of imipenem, meropenem, sulbactam, and colistin differed among Acinetobacter baumannii, Acinetobacter genomic species 3 (AGS 3), and Acinetobacter genomic species 13TU (AGS 13TU) over 11 years.MethodsA total of 1,039 nonduplicate blood isolates of A baumannii complex from bacteremic patients between 1997 and 2007 were collected at Taipei Veterans General Hospital and were identified to the species level using a multiplex polymerase chain reaction method and sequence analysis of 16S–23S intergenic spacer. The minimal inhibitory concentrations of antibiotics were determined by the agar dilution method.ResultsThe nonsusceptibility rates of carbepenems and sulbactam were highest in A baumannii, which also showed a trend toward increasing rate of carbapenems nonsusceptibility over the 11-year period of the study. AGS 13TU had the highest nonsusceptible rate to colistin, comparably increasing trend of carbapenem nonsusceptiblity as that of A baumannii, and is the only species with increasing sulbactam nonsusceptibility. AGS 3 had the lowest rate of nonsusceptibility to all four antimicrobial agents.ConclusionAlthough A baumannii had the highest nonsusceptibility rate to imipenem, meropenem, and sulbactam over the years, the higher rate of colistin nonsusceptibility and the emergence of nonsusceptibility of carbapenems and sulbactam in AGS 13TU suggested that this species might cause a great problem in the near future