Background: The concerning frequency of K. pneumoniae in various recreational settings, is noteworthy, especially regarding multi-drug resistant (MDR) strains. This superbug is linked to the rapid spread of plasmids carrying these resistance genes. The objective of this study was to evaluate the spatiotemporal prevalence of MDR-K. pneumoniae in the Kitagata hot spring, Southwestern Uganda.
Methods: A laboratory-based descriptive longitudinal study was conducted between May and July 2023. During rainy and dry seasons, we collected eighty water samples in the morning and evening from the hot spring. The temperature at each point was measured prior to sample collection, and two samples were obtained at varying depths. 5 mL of each homogenized sample were pre-enriched in brain heart infusion broth, and subsequently in both blood and violet red bile agar. The Kirby-Bauer disk diffusion method was performed, followed by the detection of carbapenemase (CR) and extended-spectrum β-lactamase (ESBL) production. Polymerase chain reaction showed resistance genes viz. blaTEM,blaCTX-M and blaKPC. Data were analyzed using SPSS-20 to obtain chi-square tests and regression analysis.
Results: K. pneumoniae accounted for 30.0% of isolates obtained from Kitagata hot springs, with all isolates classified as multi-drug resistant. All isolates were resistant to ampicillin, rifampicin, ceftazidime, and azithromycin (79.2%). Additionally, 95.8% of isolates harbored blaTEM gene alone and both blaTEM and blaCTX genes, followed by blaKPC alone (33.3%), with 25% harboring all three resistance genes. During the dry season, K. pneumoniae had a higher prevalence (35.0%) compared to the wet season (25.0%). The prevalence of MDR-K. pneumoniae significantly increased over the course of the study. The presence of the three studied resistance genes in the isolates showed a positive correlation with the second phase of sample collection and the dry season but exhibited a negative correlation with temperature, except for isolates harboring either blaTEM alone or blaTEM+KPC+CTX genes.
Conclusion: Kitagata hot spring serves as a hotspot for continuous dissemination and acquisition of MDR-K. pneumoniae harboring resistance genes that encode for ESBL and CR production. The healthcare sector ought to implement an ongoing monitoring and surveillance system as well as robust antimicrobial resistance stewardship programs aimed at delivering health education to the community.
背景：值得注意的是，肺炎克氏菌在各种娱乐环境中频频出现，尤其是耐多药（MDR）菌株。这种超级细菌与携带这些耐药基因的质粒的快速传播有关。本研究旨在评估乌干达西南部基塔加塔温泉中 MDR-K. 肺炎病菌的时空流行情况：方法：2023 年 5 月至 7 月期间进行了一项基于实验室的描述性纵向研究。在雨季和旱季，我们每天早晚从温泉中采集 80 份水样。样本采集前测量了每个点的温度，并在不同深度采集了两个样本。每个匀浆样本取 5 毫升，先在脑心输液肉汤中富集，然后在血液和紫红胆汁琼脂中富集。采用柯比鲍尔盘扩散法，然后检测碳青霉烯酶（CR）和广谱β-内酰胺酶（ESBL）的产生情况。聚合酶链反应显示耐药基因为 bla TEM、bla CTX-M 和 bla KPC。使用 SPSS-20 对数据进行了卡方检验和回归分析：结果：在北形温泉的分离株中，肺炎双球菌占 30.0%，所有分离株都具有多重耐药性。所有分离株都对氨苄西林、利福平、头孢他啶和阿奇霉素（79.2%）具有耐药性。此外，95.8%的分离株仅携带 bla TEM 基因，或同时携带 bla TEM 和 bla CTX 基因，其次是仅携带 bla KPC（33.3%），25%的分离株同时携带这三种耐药基因。在旱季，肺炎克雷伯菌的感染率（35.0%）高于雨季（25.0%）。在研究过程中，耐药型肺炎克氏菌的感染率明显增加。除了单独携带 bla TEM 或 bla TEM+KPC+CTX 基因的分离物外，所研究的三种耐药基因在分离物中的存在与样本采集的第二阶段和旱季呈正相关，但与温度呈负相关：结论：北形温泉是MDR-K. 肺炎病菌持续传播和获得的热点，这些病菌携带编码ESBL和CR产生的耐药基因。医疗保健部门应实施持续的监测和监控系统，以及旨在向社区提供健康教育的强有力的抗菌药耐药性管理计划。
{"title":"Monitoring Multi-Drug Resistant <i>Klebsiella pneumoniae</i> in Kitagata Hot Spring, Southwestern Uganda: A Public Health Implication.","authors":"Kaltume Umar Hambali, Emmanuel Eilu, Sunil Kumar, Abdullateef Opeyemi Afolabi, Naheem Adekilekun Tijani, Yusuf Olusola Faseun, Martin Odoki, Christine Gechemba Mokaya, Danladi Makeri, Shango Patience Emmanuel Jakheng, Vidya Sankarapandian, Rasheed Omotayo Adeyemo, Taofeek Tope Adegboyega, Ismail Abiola Adebayo, Ibrahim Ntulume, Saheed Adekunle Akinola","doi":"10.2147/IDR.S472998","DOIUrl":"10.2147/IDR.S472998","url":null,"abstract":"<p><strong>Background: </strong>The concerning frequency of <i>K. pneumoniae</i> in various recreational settings, is noteworthy, especially regarding multi-drug resistant (MDR) strains. This superbug is linked to the rapid spread of plasmids carrying these resistance genes. The objective of this study was to evaluate the spatiotemporal prevalence of MDR-<i>K. pneumoniae</i> in the Kitagata hot spring, Southwestern Uganda.</p><p><strong>Methods: </strong>A laboratory-based descriptive longitudinal study was conducted between May and July 2023. During rainy and dry seasons, we collected eighty water samples in the morning and evening from the hot spring. The temperature at each point was measured prior to sample collection, and two samples were obtained at varying depths. 5 mL of each homogenized sample were pre-enriched in brain heart infusion broth, and subsequently in both blood and violet red bile agar. The Kirby-Bauer disk diffusion method was performed, followed by the detection of carbapenemase (CR) and extended-spectrum β-lactamase (ESBL) production. Polymerase chain reaction showed resistance genes <i>viz. bla</i> <sub>TEM,</sub> <i>bla</i> <sub>CTX-M</sub> and <i>bla</i> <sub>KPC</sub>. Data were analyzed using SPSS-20 to obtain chi-square tests and regression analysis.</p><p><strong>Results: </strong><i>K. pneumoniae</i> accounted for 30.0% of isolates obtained from Kitagata hot springs, with all isolates classified as multi-drug resistant. All isolates were resistant to ampicillin, rifampicin, ceftazidime, and azithromycin (79.2%). Additionally, 95.8% of isolates harbored <i>bla</i> <sub>TEM</sub> gene alone and both <i>bla</i> <sub>TEM</sub> and <i>bla</i> <sub>CTX</sub> genes, followed by <i>bla</i> <sub>KPC</sub> alone (33.3%), with 25% harboring all three resistance genes. During the dry season, <i>K. pneumoniae</i> had a higher prevalence (35.0%) compared to the wet season (25.0%). The prevalence of MDR-<i>K. pneumoniae</i> significantly increased over the course of the study. The presence of the three studied resistance genes in the isolates showed a positive correlation with the second phase of sample collection and the dry season but exhibited a negative correlation with temperature, except for isolates harboring either <i>bla</i> <sub>TEM</sub> alone or <i>bla</i> <sub>TEM+KPC+CTX</sub> genes.</p><p><strong>Conclusion: </strong>Kitagata hot spring serves as a hotspot for continuous dissemination and acquisition of MDR-<i>K. pneumoniae</i> harboring resistance genes that encode for ESBL and CR production. The healthcare sector ought to implement an ongoing monitoring and surveillance system as well as robust antimicrobial resistance stewardship programs aimed at delivering health education to the community.</p>","PeriodicalId":13577,"journal":{"name":"Infection and Drug Resistance","volume":null,"pages":null},"PeriodicalIF":2.9,"publicationDate":"2024-08-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11315647/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141916597","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Background: To identify risk factors for acquiring HAIs in COVID-19 patients and establish visual prediction model. Methods: Data was extracted from Xinglin Hospital Infection Monitoring System to analyze COVID-19 patients diagnosed between December 1, 2022, and March 1, 2023. Univariate and multivariate analyses were conducted to identify risk factors. Predictive signature was developed by selected variables from lasso, logistic regression, and their intersection and union. Models were compared using DeLong’s t-tests. Likelihood ratio (LR) and Youden’s index was used to evaluate the predictive performance. Nomogram was constructed using optimal variables ensemble, prediction accuracy was evaluated using AUC, DCA and calibration curve. Results: Total of 739 patients met the criteria, of which 53 (7.2%) were HAIs. NSAIDs, surgery, fungi and MDRO detected, hormone drugs and LYMR were independent risk factors. Lasso model screened seven variables, and logistic model identified six risk factors. Union model performed the best with the maximum of the Youden’s index is 0.703, the sensitivity is 95.6%, the specificity is 74.7%, the LR is 3.778. The best AUC of union model is 0.953 (0.928– 0.978), and the accuracy is 87.5%. DCA indicated that the union model provided the best net benefits and calibration curve demonstrated good predictive agreement. Conclusions: HAIs prediction in COVID-19 patients is feasible and beneficial to improve prognosis. Physicians can use this nomogram to identify high-risk COVID-19 populations for HAIs and tailor follow-up strategies.
{"title":"Risk Factors and Nomogram Prediction Model for Healthcare-Associated Infections (HAIs) in COVID-19 Patients","authors":"Zhanjie Li, Jian Li, Chuanlong Zhu, Shengyuan Jiao","doi":"10.2147/idr.s472387","DOIUrl":"https://doi.org/10.2147/idr.s472387","url":null,"abstract":"<strong>Background:</strong> To identify risk factors for acquiring HAIs in COVID-19 patients and establish visual prediction model.<br/><strong>Methods:</strong> Data was extracted from Xinglin Hospital Infection Monitoring System to analyze COVID-19 patients diagnosed between December 1, 2022, and March 1, 2023. Univariate and multivariate analyses were conducted to identify risk factors. Predictive signature was developed by selected variables from lasso, logistic regression, and their intersection and union. Models were compared using DeLong’s <em>t</em>-tests. Likelihood ratio (LR) and Youden’s index was used to evaluate the predictive performance. Nomogram was constructed using optimal variables ensemble, prediction accuracy was evaluated using AUC, DCA and calibration curve.<br/><strong>Results:</strong> Total of 739 patients met the criteria, of which 53 (7.2%) were HAIs. NSAIDs, surgery, fungi and MDRO detected, hormone drugs and LYMR were independent risk factors. Lasso model screened seven variables, and logistic model identified six risk factors. Union model performed the best with the maximum of the Youden’s index is 0.703, the sensitivity is 95.6%, the specificity is 74.7%, the LR is 3.778. The best AUC of union model is 0.953 (0.928– 0.978), and the accuracy is 87.5%. DCA indicated that the union model provided the best net benefits and calibration curve demonstrated good predictive agreement.<br/><strong>Conclusions:</strong> HAIs prediction in COVID-19 patients is feasible and beneficial to improve prognosis. Physicians can use this nomogram to identify high-risk COVID-19 populations for HAIs and tailor follow-up strategies.<br/><br/>","PeriodicalId":13577,"journal":{"name":"Infection and Drug Resistance","volume":null,"pages":null},"PeriodicalIF":3.9,"publicationDate":"2024-08-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141883481","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Darja Sadovska, Anda Nodieva, Ilva Pole, Anda Vīksna, Jānis Ķimsis, Iveta Ozere, Inga Norvaiša, Ineta Bogdanova, Dace Bandere, Renāte Ranka
Background: Current tuberculosis treatment regimens primarily rely on phenotypic drug susceptibility testing and rapid molecular assays. Although whole-genome sequencing (WGS) offers a promising alternative, disagreements between phenotypic and molecular testing methods remain. In this retrospective study, we compared the phenotypic and WGS-predicted drug resistance profiles of paired Mycobacterium tuberculosis isolates with small genetic distances (≤ 10 single nucleotide variants) obtained from patients with longitudinal single-episode or recurrent tuberculosis. Additionally, we investigated the distribution of drug-resistance-conferring variants among the identified M. tuberculosis genotypes. Methods: Paired M. tuberculosis isolates from 46 patients with pulmonary tuberculosis (2002– 2019) were analyzed. Spoligotyping was performed for all the isolates. WGS data were processed using TB-Profiler software to genotype the strains and detect variants in M. tuberculosis genes associated with drug resistance. The significance of these variants was evaluated using the M. tuberculosis variant catalog developed by the World Health Organization. Phenotypic drug susceptibility test results were obtained from patients’ medical records. Results: Among the 46 isolate pairs, 25 (54.3%) harbored drug-resistance-associated variants, with 20 demonstrating identical WGS-predicted drug resistance profiles. Drug-resistant isolate pairs belonged to Lineages 2 and 4, with the most common sub-lineages being 2.2.1 (SIT1 and SIT190 spoligotypes), and 4.3.3 (SIT42). Agreement between phenotypic and WGS-based drug susceptibility testing was highest (> 90%) for rifampicin, isoniazid, ethambutol, fluoroquinolones, streptomycin, and amikacin when calculated for M. tuberculosis isolates or isolate pairs. In most discordant cases, isolate pairs harbored variants that could cause low- or moderate-level resistance or were previously associated with variable minimum inhibitory concentrations. Notably, such discrepancies mostly occurred in one isolate from the pair. In addition, differences in resistance-related variant distributions among M. tuberculosis genotypes were observed for most of the analyzed drugs. Conclusion: The simultaneous performance of phenotypic and WGS-based drug susceptibility testing creates the most accurate drug resistance profile for M. tuberculosis isolates and eliminates important limitations of each method.
{"title":"Discordance Between Phenotypic and WGS-Based Drug Susceptibility Testing Results for Some Anti-Tuberculosis Drugs: A Snapshot Study of Paired Mycobacterium tuberculosis Isolates with Small Genetic Distance","authors":"Darja Sadovska, Anda Nodieva, Ilva Pole, Anda Vīksna, Jānis Ķimsis, Iveta Ozere, Inga Norvaiša, Ineta Bogdanova, Dace Bandere, Renāte Ranka","doi":"10.2147/idr.s468997","DOIUrl":"https://doi.org/10.2147/idr.s468997","url":null,"abstract":"<strong>Background:</strong> Current tuberculosis treatment regimens primarily rely on phenotypic drug susceptibility testing and rapid molecular assays. Although whole-genome sequencing (WGS) offers a promising alternative, disagreements between phenotypic and molecular testing methods remain. In this retrospective study, we compared the phenotypic and WGS-predicted drug resistance profiles of paired <em>Mycobacterium tuberculosis</em> isolates with small genetic distances (≤ 10 single nucleotide variants) obtained from patients with longitudinal single-episode or recurrent tuberculosis. Additionally, we investigated the distribution of drug-resistance-conferring variants among the identified <em>M. tuberculosis</em> genotypes.<br/><strong>Methods:</strong> Paired <em>M. tuberculosis</em> isolates from 46 patients with pulmonary tuberculosis (2002– 2019) were analyzed. Spoligotyping was performed for all the isolates. WGS data were processed using TB-Profiler software to genotype the strains and detect variants in <em>M. tuberculosis</em> genes associated with drug resistance. The significance of these variants was evaluated using the <em>M. tuberculosis</em> variant catalog developed by the World Health Organization. Phenotypic drug susceptibility test results were obtained from patients’ medical records.<br/><strong>Results:</strong> Among the 46 isolate pairs, 25 (54.3%) harbored drug-resistance-associated variants, with 20 demonstrating identical WGS-predicted drug resistance profiles. Drug-resistant isolate pairs belonged to Lineages 2 and 4, with the most common sub-lineages being 2.2.1 (SIT1 and SIT190 spoligotypes), and 4.3.3 (SIT42). Agreement between phenotypic and WGS-based drug susceptibility testing was highest (> 90%) for rifampicin, isoniazid, ethambutol, fluoroquinolones, streptomycin, and amikacin when calculated for <em>M. tuberculosis</em> isolates or isolate pairs. In most discordant cases, isolate pairs harbored variants that could cause low- or moderate-level resistance or were previously associated with variable minimum inhibitory concentrations. Notably, such discrepancies mostly occurred in one isolate from the pair. In addition, differences in resistance-related variant distributions among <em>M. tuberculosis</em> genotypes were observed for most of the analyzed drugs.<br/><strong>Conclusion:</strong> The simultaneous performance of phenotypic and WGS-based drug susceptibility testing creates the most accurate drug resistance profile for <em>M. tuberculosis</em> isolates and eliminates important limitations of each method.<br/><br/>","PeriodicalId":13577,"journal":{"name":"Infection and Drug Resistance","volume":null,"pages":null},"PeriodicalIF":3.9,"publicationDate":"2024-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141871444","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Wei Tang, Ying Liu, Xin Li, Guiyun Leng, Ju Gao, Yawu Wang, Jie Yao, Zhou Liu, Qiang Zhou, Yuanhong Xu
Purpose: This study aimed to investigate the microbiological characteristics of clinically isolated Staphylococcus aureus with different hemolytic phenotypes in China. Materials and Methods: Using the three-point inoculation method, the hemolytic phenotypes of 1295 clinically isolated S. aureus strains were detected and categorized. Antimicrobial susceptibility testing of all strains was performed using a VITEK 2 Compact System. After sample size matching, plasma coagulase activity, catalase activity, mRNA expression of hemolysin genes (hla, hlb, hlc, and hld), biofilm formation, growth kinetics, inflammatory response of macrophages and cytotoxicity of S. aureus with different hemolytic phenotypes using the rabbit plasma kit, the catalase test on slides, qRT-PCR, crystal violet staining, the microcultivation assay, the ELISA kits, and the CCK-8 assay, respectively. Results: Seven categories of hemolytic phenotypes were identified. Accordingly, strains were categorized into seven different groups, including S. aureus with complete hemolytic phenotype (SCHP), S. aureus with weak hemolytic phenotype (SWHP), S. aureus with incomplete hemolytic phenotype 1 (SIHP-1), SIHP-2, SIHP-3, SIHP-4 and SIHP-5, the last three of which were reported for the first time. Except for the hemolytic phenotype, all seven groups differed in clinical isolation rates, antibiotic resistance profile, plasma coagulase activity, mRNA expression of hemolysin genes, biofilm formation, growth kinetics, inflammatory response of macrophages, and cytotoxicity. Conclusion:S. aureus with different hemolytic phenotypes have distinctive microbiological characteristics. Clinical microbiologists need to be vigilant about the hemolytic phenotypes when culturing S. aureus strains, and actively enhance communication with clinicians to optimize the treatment of infection.
{"title":"Microbiological Characteristics of Clinically Isolated Staphylococcus aureus with Different Hemolytic Phenotypes in China","authors":"Wei Tang, Ying Liu, Xin Li, Guiyun Leng, Ju Gao, Yawu Wang, Jie Yao, Zhou Liu, Qiang Zhou, Yuanhong Xu","doi":"10.2147/idr.s466416","DOIUrl":"https://doi.org/10.2147/idr.s466416","url":null,"abstract":"<strong>Purpose:</strong> This study aimed to investigate the microbiological characteristics of clinically isolated <em>Staphylococcus aureus</em> with different hemolytic phenotypes in China.<br/><strong>Materials and Methods:</strong> Using the three-point inoculation method, the hemolytic phenotypes of 1295 clinically isolated <em>S. aureus</em> strains were detected and categorized. Antimicrobial susceptibility testing of all strains was performed using a VITEK 2 Compact System. After sample size matching, plasma coagulase activity, catalase activity, mRNA expression of hemolysin genes (<em>hla, hlb, hlc</em>, and <em>hld</em>), biofilm formation, growth kinetics, inflammatory response of macrophages and cytotoxicity of <em>S. aureus</em> with different hemolytic phenotypes using the rabbit plasma kit, the catalase test on slides, qRT-PCR, crystal violet staining, the microcultivation assay, the ELISA kits, and the CCK-8 assay, respectively.<br/><strong>Results:</strong> Seven categories of hemolytic phenotypes were identified. Accordingly, strains were categorized into seven different groups, including <em>S. aureus</em> with complete hemolytic phenotype (SCHP), <em>S. aureus</em> with weak hemolytic phenotype (SWHP), <em>S. aureus</em> with incomplete hemolytic phenotype 1 (SIHP-1), SIHP-2, SIHP-3, SIHP-4 and SIHP-5, the last three of which were reported for the first time. Except for the hemolytic phenotype, all seven groups differed in clinical isolation rates, antibiotic resistance profile, plasma coagulase activity, mRNA expression of hemolysin genes, biofilm formation, growth kinetics, inflammatory response of macrophages, and cytotoxicity.<br/><strong>Conclusion:</strong> <em>S. aureus</em> with different hemolytic phenotypes have distinctive microbiological characteristics. Clinical microbiologists need to be vigilant about the hemolytic phenotypes when culturing <em>S. aureus</em> strains, and actively enhance communication with clinicians to optimize the treatment of infection.<br/><br/><strong>Keywords:</strong> <em>Staphylococcus aureus</em>, hemolytic phenotype, hemolysin, microbiological characteristics, antibiotic resistance<br/>","PeriodicalId":13577,"journal":{"name":"Infection and Drug Resistance","volume":null,"pages":null},"PeriodicalIF":3.9,"publicationDate":"2024-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141871445","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Purpose: This study aimed to improve the understanding of sporotrichosis by analyzing the epidemiological characteristics, clinical manifestations, mycological features, and pathological characteristics of the disease in eastern China. Methods: Clinical data of 49 patients diagnosed with cutaneous sporotrichosis in dermatology clinics over a 20-year period were collected and analyzed retrospectively. The analysis included patient demographics, occupations, clinical types, lesion sites, misdiagnosis rates, laboratory investigations, treatment and outcomes. Results: The study included 22 male and 27 female patients, with a mean age of 52.4 years. Farmers (42.86%) and manual workers (28.57%) had a higher risk of infection. The most common clinical types were lymphocutaneous (30.61%) and fixed (69.39%), predominantly affecting the face and upper limbs. Misdiagnosis as other infectious skin diseases occurred in 35 patients (71.43%). Fungal culture and histopathological examination were important diagnostic tools. Treatment with oral itraconazole for three months led to relief and regression of the skin lesions in most patients, although a few experienced recurrences. Conclusion: Cutaneous sporotrichosis mainly affects individuals working in agriculture and manual labour, with lymphocutaneous and fixed types being the predominant clinical manifestations. The high misdiagnosis rate emphasizes the importance of early recognition, accurate diagnosis and standardized treatment for the prognosis and cure of sporotrichosis. Fungal culture and histopathological examination are essential for diagnosis, and oral itraconazole is an effective treatment option.
{"title":"Clinical Analysis of Patients Diagnosed with Cutaneous Sporotrichosis in China","authors":"Yunyan Zheng, Weiwei Shi, Huiying Wang, Ruzhi Zhang","doi":"10.2147/idr.s471280","DOIUrl":"https://doi.org/10.2147/idr.s471280","url":null,"abstract":"<strong>Purpose:</strong> This study aimed to improve the understanding of sporotrichosis by analyzing the epidemiological characteristics, clinical manifestations, mycological features, and pathological characteristics of the disease in eastern China.<br/><strong>Methods:</strong> Clinical data of 49 patients diagnosed with cutaneous sporotrichosis in dermatology clinics over a 20-year period were collected and analyzed retrospectively. The analysis included patient demographics, occupations, clinical types, lesion sites, misdiagnosis rates, laboratory investigations, treatment and outcomes.<br/><strong>Results:</strong> The study included 22 male and 27 female patients, with a mean age of 52.4 years. Farmers (42.86%) and manual workers (28.57%) had a higher risk of infection. The most common clinical types were lymphocutaneous (30.61%) and fixed (69.39%), predominantly affecting the face and upper limbs. Misdiagnosis as other infectious skin diseases occurred in 35 patients (71.43%). Fungal culture and histopathological examination were important diagnostic tools. Treatment with oral itraconazole for three months led to relief and regression of the skin lesions in most patients, although a few experienced recurrences.<br/><strong>Conclusion:</strong> Cutaneous sporotrichosis mainly affects individuals working in agriculture and manual labour, with lymphocutaneous and fixed types being the predominant clinical manifestations. The high misdiagnosis rate emphasizes the importance of early recognition, accurate diagnosis and standardized treatment for the prognosis and cure of sporotrichosis. Fungal culture and histopathological examination are essential for diagnosis, and oral itraconazole is an effective treatment option.<br/><br/><strong>Keywords:</strong> sporotrichosis, cutaneous form, clinical analysis, epidemiology, misdiagnosis<br/>","PeriodicalId":13577,"journal":{"name":"Infection and Drug Resistance","volume":null,"pages":null},"PeriodicalIF":3.9,"publicationDate":"2024-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141873247","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Background: Multidrug- and rifampicin-resistant tuberculosis (MDR/RR-TB) with high mortality remains a public health crisis and health security threat. This study aimed to explore the predictive value of nutritional indices for all-cause mortality (ACM) in MDR/RR-TB patients. Methods: We retrospectively recruited MDR/RR-TB patients between January 2015 and December 2021, randomly assigning them to training and validation cohorts. Patients were divided into high nutritional risk groups (HNRGs) and low nutritional risk groups (LNRGs) based on the optimal cut-off value obtained from receiver operating characteristic (ROC) analyses of the hemoglobin-albumin-lymphocyte-platelet (HALP) score, prognostic nutritional index (PNI), and controlling nutritional status (CONUT) score. In the training cohort, Kaplan-Meier survival curves and Log rank tests were used to compare overall survival (OS) between the groups. Cox risk proportion regression analyses were used to explore the risk factors of ACM in patients with MDR/RR-TB. The predictive performance of ACM was assessed using area under the curve (AUC), sensitivity and specificity of ROC analyses. Results: A total of 524 MDR/RR-TB patients, with 255 in the training cohort and 269 in the validation cohort, were included. Survival analyses in the training cohort revealed significantly lower OS in the HNRGs compared to the LNRGs. After adjusting for covariates, multivariate analysis identified low HALP score, low PNI and high CONUT score were independent risk factors for ACM in MDR/RR-TB patients. ROC analyses demonstrated good predictive performance for ACM with AUCs of 0.765, 0.783, 0.807, and 0.811 for HALP score, PNI, CONUT score, and their combination, respectively. Similar results were observed in the validation set. Conclusion: HALP score, PNI, and CONUT scores could effectively predict ACM in patients with MDR/RR-TB. Hence, routine screening for malnutrition should be given more attention in clinical practice to identify MDR/RR-TB patients at higher risk of mortality and provide them with nutritional support to reduce mortality.
{"title":"Nutritional Indices Predict All Cause Mortality in Patients with Multi-/Rifampicin-Drug Resistant Tuberculosis","authors":"Shengling Hu, Jinqiang Guo, Zhe Chen, Fengyun Gong, Qi Yu","doi":"10.2147/idr.s457146","DOIUrl":"https://doi.org/10.2147/idr.s457146","url":null,"abstract":"<strong>Background:</strong> Multidrug- and rifampicin-resistant tuberculosis (MDR/RR-TB) with high mortality remains a public health crisis and health security threat. This study aimed to explore the predictive value of nutritional indices for all-cause mortality (ACM) in MDR/RR-TB patients.<br/><strong>Methods:</strong> We retrospectively recruited MDR/RR-TB patients between January 2015 and December 2021, randomly assigning them to training and validation cohorts. Patients were divided into high nutritional risk groups (HNRGs) and low nutritional risk groups (LNRGs) based on the optimal cut-off value obtained from receiver operating characteristic (ROC) analyses of the hemoglobin-albumin-lymphocyte-platelet (HALP) score, prognostic nutritional index (PNI), and controlling nutritional status (CONUT) score. In the training cohort, Kaplan-Meier survival curves and Log rank tests were used to compare overall survival (OS) between the groups. Cox risk proportion regression analyses were used to explore the risk factors of ACM in patients with MDR/RR-TB. The predictive performance of ACM was assessed using area under the curve (AUC), sensitivity and specificity of ROC analyses.<br/><strong>Results:</strong> A total of 524 MDR/RR-TB patients, with 255 in the training cohort and 269 in the validation cohort, were included. Survival analyses in the training cohort revealed significantly lower OS in the HNRGs compared to the LNRGs. After adjusting for covariates, multivariate analysis identified low HALP score, low PNI and high CONUT score were independent risk factors for ACM in MDR/RR-TB patients. ROC analyses demonstrated good predictive performance for ACM with AUCs of 0.765, 0.783, 0.807, and 0.811 for HALP score, PNI, CONUT score, and their combination, respectively. Similar results were observed in the validation set.<br/><strong>Conclusion:</strong> HALP score, PNI, and CONUT scores could effectively predict ACM in patients with MDR/RR-TB. Hence, routine screening for malnutrition should be given more attention in clinical practice to identify MDR/RR-TB patients at higher risk of mortality and provide them with nutritional support to reduce mortality.<br/><br/>","PeriodicalId":13577,"journal":{"name":"Infection and Drug Resistance","volume":null,"pages":null},"PeriodicalIF":3.9,"publicationDate":"2024-07-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141871446","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Background: The Tigray region of Ethiopia, which has been affected by civil war from 2020 to 2022, is facing an increase in tuberculosis in the damaged health system. Our study employed mathematical modeling to predict the incidence of tuberculosis and its trends during the war and in the post-conflict setting of Tigray, Northern Ethiopia. Methods: We predicted the incidence of tuberculosis from 2020 to 2025 in Tigray using the SEIRD model in the context of the recent war and compared it with its counterfactual trend in the absence of war. The counterfactual trend was forecasted using an autoregressive integrated moving average (ARIMA) model for stationary time-series data. We performed rolling origin cross-validation for ARIMA and sensitivity analysis for the SEIRD model. The initial tuberculosis data and model parameters were obtained from the Institute for Health Metrics and Evaluation and the literature, respectively. Results: Between 2000 and 2017, the incidence of tuberculosis in Tigray decreased at an annual rate of 3.0%. Shortly before the war, the incidence of tuberculosis in the region was 178 per 100,000 people. In a counterfactual scenario where there was no war, the incidence was projected to decrease to 144.3 in 2022 and 126.3 in 2025. However, owing to the war and siege, the SEIRD-projected incidence of tuberculosis would have increased to 965.5 (95% CI: 958.5– 972.7) in 2022 and 372.4 (95% CI: 367.7– 376.6) in 2025. Over 800 cases of tuberculosis per 100,000 people were attributed to the war in 2022. In the postwar period, the incidence is projected to decrease by 30% by 2023. Conclusion: The Tigray War reversed a two-decade decline in tuberculosis cases, causing a five-fold increase compared to the no-war scenario. Urgent interventions are needed to support tuberculosis prevention, testing, and treatment, particularly in key and vulnerable populations.
{"title":"Predicting Tuberculosis Incidence and Its Trend in Tigray, Ethiopia: A Reality-Counterfactual Modeling Approach","authors":"Gebremedhin Berhe Gebregergs, Gebretsadik Berhe, Kibrom Gebreslasie Gebrehiwot, Afework Mulugeta","doi":"10.2147/idr.s464787","DOIUrl":"https://doi.org/10.2147/idr.s464787","url":null,"abstract":"<strong>Background:</strong> The Tigray region of Ethiopia, which has been affected by civil war from 2020 to 2022, is facing an increase in tuberculosis in the damaged health system. Our study employed mathematical modeling to predict the incidence of tuberculosis and its trends during the war and in the post-conflict setting of Tigray, Northern Ethiopia.<br/><strong>Methods:</strong> We predicted the incidence of tuberculosis from 2020 to 2025 in Tigray using the SEIRD model in the context of the recent war and compared it with its counterfactual trend in the absence of war. The counterfactual trend was forecasted using an autoregressive integrated moving average (ARIMA) model for stationary time-series data. We performed rolling origin cross-validation for ARIMA and sensitivity analysis for the SEIRD model. The initial tuberculosis data and model parameters were obtained from the Institute for Health Metrics and Evaluation and the literature, respectively.<br/><strong>Results:</strong> Between 2000 and 2017, the incidence of tuberculosis in Tigray decreased at an annual rate of 3.0%. Shortly before the war, the incidence of tuberculosis in the region was 178 per 100,000 people. In a counterfactual scenario where there was no war, the incidence was projected to decrease to 144.3 in 2022 and 126.3 in 2025. However, owing to the war and siege, the SEIRD-projected incidence of tuberculosis would have increased to 965.5 (95% CI: 958.5– 972.7) in 2022 and 372.4 (95% CI: 367.7– 376.6) in 2025. Over 800 cases of tuberculosis per 100,000 people were attributed to the war in 2022. In the postwar period, the incidence is projected to decrease by 30% by 2023.<br/><strong>Conclusion:</strong> The Tigray War reversed a two-decade decline in tuberculosis cases, causing a five-fold increase compared to the no-war scenario. Urgent interventions are needed to support tuberculosis prevention, testing, and treatment, particularly in key and vulnerable populations.<br/><br/>","PeriodicalId":13577,"journal":{"name":"Infection and Drug Resistance","volume":null,"pages":null},"PeriodicalIF":3.9,"publicationDate":"2024-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141771192","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Enas M Al-Khlifeh, Ibrahim S Alkhazi, Majed Abdullah Alrowaily, Mansoor Alghamdi, Malek Alrashidi, Ahmad S Tarawneh, Ibraheem M Alkhawaldeh, Ahmad B Hassanat
Background: The incidence of microorganisms with extended-spectrum beta-lactamase (ESBL) is on the rise, posing a significant public health concern. The current application of machine learning (ML) focuses on predicting bacterial resistance to optimize antibiotic therapy. This study employs ML to forecast the occurrence of bacteria that generate ESBL and demonstrate resistance to multiple antibiotics (MDR). Methods: Six popular ML algorithms were initially trained on antibiotic resistance test patient reports (n = 489) collected from Al-Hussein/Salt Hospital in Jordan. Trained outcome models predict ESBL and multidrug resistance profiles based on microbiological and patients’ clinical data. The results were utilized to select the optimal ML method to predict ESBL’s most associated features. Results:Escherichia coli (E. coli, 82%) was the most commonly identified microbe generating ESBL, displaying multidrug resistance. Urinary tract infections (UTIs) constituted the most frequently observed clinical diagnosis (68.7%). Classification and Regression Trees (CART) and Random Forest (RF) classifiers emerged as the most effective algorithms. The relevant features associated with the emergence of ESBL include age and different classes of antibiotics, including cefuroxime, ceftazidime, cefepime, trimethoprim/ sulfamethoxazole, ciprofloxacin, and gentamicin. Fosfomycin nitrofurantoin, piperacillin/tazobactam, along with amikacin, meropenem, and imipenem, had a pronounced inverse relationship with the ESBL class. Conclusion: CART and RF-based ML algorithms can be employed to predict the most important features of ESBL. The significance of monitoring trends in ESBL infections is emphasized to facilitate the administration of appropriate antibiotic therapy.
背景：具有广谱β-内酰胺酶（ESBL）的微生物的发病率呈上升趋势，给公共卫生带来了重大隐患。目前机器学习（ML）的应用主要集中在预测细菌耐药性以优化抗生素治疗。本研究利用 ML 预测产生 ESBL 并对多种抗生素（MDR）表现出耐药性的细菌的发生率：六种流行的 ML 算法最初是在约旦 Al-Hussein/Salt 医院收集的抗生素耐药性测试患者报告（n = 489）上进行训练的。训练结果模型根据微生物学和患者临床数据预测 ESBL 和多重耐药性概况。结果用于选择最佳 ML 方法，以预测 ESBL 最相关的特征：结果：大肠埃希氏菌（E. coli，82%）是最常见的产生 ESBL 的微生物，具有多重耐药性。尿路感染（UTI）是最常见的临床诊断（68.7%）。分类与回归树（CART）和随机森林（RF）分类器是最有效的算法。与ESBL出现相关的特征包括年龄和不同类别的抗生素，包括头孢呋辛、头孢唑肟、头孢吡肟、三甲双胍/磺胺甲噁唑、环丙沙星和庆大霉素。硝基呋喃妥因、哌拉西林/他唑巴坦、阿米卡星、美罗培南和亚胺培南与 ESBL 类有明显的反比关系：结论：基于CART和RF的ML算法可用于预测ESBL最重要的特征。结论：CART和基于RF的ML算法可用于预测ESBL最重要的特征，强调了监测ESBL感染趋势的重要性，以促进适当的抗生素治疗。
{"title":"Extended Spectrum beta-Lactamase Bacteria and Multidrug Resistance in Jordan are Predicted Using a New Machine-Learning system","authors":"Enas M Al-Khlifeh, Ibrahim S Alkhazi, Majed Abdullah Alrowaily, Mansoor Alghamdi, Malek Alrashidi, Ahmad S Tarawneh, Ibraheem M Alkhawaldeh, Ahmad B Hassanat","doi":"10.2147/idr.s469877","DOIUrl":"https://doi.org/10.2147/idr.s469877","url":null,"abstract":"<strong>Background:</strong> The incidence of microorganisms with extended-spectrum beta-lactamase (ESBL) is on the rise, posing a significant public health concern. The current application of machine learning (ML) focuses on predicting bacterial resistance to optimize antibiotic therapy. This study employs ML to forecast the occurrence of bacteria that generate ESBL and demonstrate resistance to multiple antibiotics (MDR).<br/><strong>Methods:</strong> Six popular ML algorithms were initially trained on antibiotic resistance test patient reports (n = 489) collected from Al-Hussein/Salt Hospital in Jordan. Trained outcome models predict ESBL and multidrug resistance profiles based on microbiological and patients’ clinical data. The results were utilized to select the optimal ML method to predict ESBL’s most associated features.<br/><strong>Results:</strong> <em>Escherichia coli</em> (<em>E. coli</em>, 82%) was the most commonly identified microbe generating ESBL, displaying multidrug resistance. Urinary tract infections (UTIs) constituted the most frequently observed clinical diagnosis (68.7%). Classification and Regression Trees (CART) and Random Forest (RF) classifiers emerged as the most effective algorithms. The relevant features associated with the emergence of ESBL include age and different classes of antibiotics, including cefuroxime, ceftazidime, cefepime, trimethoprim/ sulfamethoxazole, ciprofloxacin, and gentamicin. Fosfomycin nitrofurantoin, piperacillin/tazobactam, along with amikacin, meropenem, and imipenem, had a pronounced inverse relationship with the ESBL class.<br/><strong>Conclusion:</strong> CART and RF-based ML algorithms can be employed to predict the most important features of ESBL. The significance of monitoring trends in ESBL infections is emphasized to facilitate the administration of appropriate antibiotic therapy. <br/><br/>","PeriodicalId":13577,"journal":{"name":"Infection and Drug Resistance","volume":null,"pages":null},"PeriodicalIF":3.9,"publicationDate":"2024-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141771105","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Abstract: Acute respiratory infections contribute to morbidity and mortality worldwide. The common cause of this deadly disease is a virus, and one of the most commonly found is the influenza virus. Influenza viruses have several capabilities in infection, including utilizing the host’s machinery to survive within cells and replicate safely. This review aims to examine the literature on how influenza viruses use host machinery, including endocytosis and autophagy, for their internalization and replication within cells. This review method involves a literature search by examining articles published in the PubMed and Scopus databases. The keywords used were “Endocytosis” OR “Autophagy” AND “Influenza Virus”. Eighteen articles were included due to inclusion and exclusion criteria. GTPases switch, and V-ATPase plays a key role in the endocytic machinery hijacked by influenza viruses to enter host cells. On the other hand, LC3 and Atg5 facilitate influenza-induced apoptosis via the autophagic pathway. In conclusion, influenza viruses primarily use clathrin-mediated endocytosis to enter cells and avoid degradation during endosomal maturation by exiting endosomes for transfer to the nucleus for replication. It also uses autophagy to induce apoptosis to continue replication. The capability of the influenza viruses to hijack endocytosis and autophagy mechanisms could be critical points for further research. Therefore, we discuss how the influenza virus utilizes both endocytosis and autophagy and the approach for a new strategic therapy targeting those mechanisms.
{"title":"The Roles of Endocytosis and Autophagy at the Cellular Level During Influenza Virus Infection: A Mini-Review","authors":"Sulpiana, Riezki Amalia, Nur Atik","doi":"10.2147/idr.s471204","DOIUrl":"https://doi.org/10.2147/idr.s471204","url":null,"abstract":"<strong>Abstract:</strong> Acute respiratory infections contribute to morbidity and mortality worldwide. The common cause of this deadly disease is a virus, and one of the most commonly found is the influenza virus. Influenza viruses have several capabilities in infection, including utilizing the host’s machinery to survive within cells and replicate safely. This review aims to examine the literature on how influenza viruses use host machinery, including endocytosis and autophagy, for their internalization and replication within cells. This review method involves a literature search by examining articles published in the PubMed and Scopus databases. The keywords used were “Endocytosis” OR “Autophagy” AND “Influenza Virus”. Eighteen articles were included due to inclusion and exclusion criteria. GTPases switch, and V-ATPase plays a key role in the endocytic machinery hijacked by influenza viruses to enter host cells. On the other hand, LC3 and Atg5 facilitate influenza-induced apoptosis via the autophagic pathway. In conclusion, influenza viruses primarily use clathrin-mediated endocytosis to enter cells and avoid degradation during endosomal maturation by exiting endosomes for transfer to the nucleus for replication. It also uses autophagy to induce apoptosis to continue replication. The capability of the influenza viruses to hijack endocytosis and autophagy mechanisms could be critical points for further research. Therefore, we discuss how the influenza virus utilizes both endocytosis and autophagy and the approach for a new strategic therapy targeting those mechanisms.<br/><br/><strong>Keywords:</strong> Autophagy, endocytosis, influenza virus, virus internalization<br/>","PeriodicalId":13577,"journal":{"name":"Infection and Drug Resistance","volume":null,"pages":null},"PeriodicalIF":3.9,"publicationDate":"2024-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141771107","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Abstract: Cryptococcus neoformans is a type of fungal infection, which primarily affects the central nervous system and lungs of immunocompromised individuals. Spinal infections are known to be a rare manifestation of cryptococcosis. Herein, we report a case of a patient with isolated nonspecific spinal lesions at the T10 vertebra. The patient received non-surgical treatment with antifungal drugs, resulting in satisfactory clinical outcomes.
{"title":"Isolated Cryptococcal Infection of the Thoracic Spine in an Immunocompetent Patient","authors":"Wensen Pi, Yang Liu, Haidan Chen, Hongwei Zhao","doi":"10.2147/idr.s472521","DOIUrl":"https://doi.org/10.2147/idr.s472521","url":null,"abstract":"<strong>Abstract:</strong> Cryptococcus neoformans is a type of fungal infection, which primarily affects the central nervous system and lungs of immunocompromised individuals. Spinal infections are known to be a rare manifestation of cryptococcosis. Herein, we report a case of a patient with isolated nonspecific spinal lesions at the T10 vertebra. The patient received non-surgical treatment with antifungal drugs, resulting in satisfactory clinical outcomes.<br/><br/><strong>Keywords:</strong> cryptococcal, thoracic spine<br/>","PeriodicalId":13577,"journal":{"name":"Infection and Drug Resistance","volume":null,"pages":null},"PeriodicalIF":3.9,"publicationDate":"2024-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141771111","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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