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BACKGROUND: Criteria classifying fever of unknown origin (FUO) patients remains subject to discrepancies. A minimal standardized set of investigative tests serves as the foundation for the qualitative criteria, whereas quantitative incorporates the length of evaluation (7 or 3 days). A systematic review of studies would help physicians anticipate the frequency of illness types that could influence management. METHODS: Prospective studies published in Medline (PubMed), Embase, Scopus, and Web of Science databases from January 1, 1997, to July 31, 2022, were included. A meta-analysis estimated associated pooled proportions between these criteria and diagnostic outcomes adjusted to the International Classification of Diseases, 10th edition (ICD-10) definitions. RESULTS: Five qualitative studies corresponded to an increase of 15.3% (95% CI: 2.3-28.3%, p=0.021) in undiagnosed FUO proportions compared to eleven quantitative studies. Quantitative studies had 19.7% (95% CI: 6.0-33.4%, p=0.005) more in adjusted infectious disease proportions than qualitative studies. No significant differences in proportions between FUO defining criteria were noted for adjusted noninfectious inflammatory disorders (p=0.318), oncology (p=0.901), non-inflammatory miscellaneous disorders (p=0.321), diagnostic evaluation process, gross national income (GNI), or World Health Organization (WHO) geographic region. CONCLUSIONS: Use of either qualitative or quantitative FUO criteria was associated with a statistically significant risk of over- or under-estimating infectious diseases and undiagnosed illnesses when using an ICD-10 adjusted FUO five-category system. Clinicians should anticipate differences depending on which criteria are used. While further research is warranted, qualitative criteria provide the best framework for study comparisons.
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Background: Fever of unknown origin (FUO) and inflammation of unknown origin (IUO) are syndromes commonly used as medical diagnoses. Since the existing literature has a mixture of diagnostic approaches, developing consensus-based recommendations would be helpful for clinicians, researchers, and patients. Methods: A modified Delphi process was performed from October 2022 to July 2023, involving 4 rounds of online surveys and 2 live video conferences. The panel comprised international experts recruited based on peer-reviewed published publications and studies. Results: Among 50 invited experts, 26 (52.0%) agreed to participate. Twenty-three panelists completed round 1 of the survey, 21 completed rounds 2 and 3, 20 completed round 4, and 7 participated in round 5 live video discussions. Of the participants, 18 (78.3%) were academic-based clinicians and researchers, 5 (21.7%) practiced in a community-based hospital, and 6 (26.1%) were female. Consensus was reached on 5 themes: (1) incorporating epidemiologic factors, such as geographic location and travel history; (2) updated criteria for classifying FUO or IUO; (3) initial evaluation approaches; (4) a classification system for diagnoses; and (5) recommendations for judicious limitation of empiric therapies. Experts strongly disagreed with using 2-deoxy-2-[18F] fluoro-D-glucose positron emission tomography/computed tomography as part of the diagnostic criteria for FUO. There were mixed opinions about the importance of the temperature measurement site, the 3-week minimum illness criterion, the need for a standard definition of relapsing fevers, and the use of similar evaluation strategies for FUO and IUO. Conclusions: These Delphi-generated consensus-based recommendations offer potential improvements compared with earlier definitions and a guide for clinical practice and future research.
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Fever of unknown origin (FUO) is a clinical conundrum for patients and clinicians alike, and imaging studies are often performed as part of the diagnostic workup of these patients. Recently, the Society of Nuclear Medicine and Molecular Imaging convened and approved a guideline on the use of nuclear medicine tools for FUO. The guidelines support the use of 2-18F-fluorodeoxyglucose (18F-FDG) positron emission tomography (PET)/computed tomography (CT) in adults and children with FUO. 18F-FDG PET/CT allows detection and localization of foci of hypermetabolic lesions with high sensitivity because of the 18F-FDG uptake in glycolytically active cells that may represent inflammation, infection, or neoplasia. Clinicians should consider and insurers should cover 18F-FDG PET/CT when evaluating patients with FUO, particularly when other clinical clues and preliminary studies are unrevealing.
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Fiebre de Origen Desconocido , Fluorodesoxiglucosa F18 , Medicina Nuclear , Tomografía Computarizada por Tomografía de Emisión de Positrones , Humanos , Fiebre de Origen Desconocido/diagnóstico por imagen , Tomografía Computarizada por Tomografía de Emisión de Positrones/métodos , Medicina Nuclear/métodos , Adulto , Radiofármacos , Niño , Guías de Práctica Clínica como AsuntoRESUMEN
BACKGROUND: Patients with inflammation of unknown origin (IUO) and fever of unknown origin (FUO) are commonly considered a single population. Differences in underlying causes between both groups may steer the diagnostic work-up. METHODS: PubMed, Embase, Web of Science, and ClinicalTrials.gov were searched from July 2009 through December 2023. Studies including both FUO and IUO patients with a sample size of ≥20 were considered. The primary outcome was the difference in the rate of patients affected by predefined diagnostic categories according to meeting FUO or IUO criteria. Data were pooled using random-effects models. RESULTS: A total of 8 studies met criteria for inclusion, with a total of 1452 patients (466 with IUO and 986 with FUO). The median rate of IUO patients among the included studies was 32 % (range 25-39 %). Patients with IUO had a lower likelihood of infection (OR 0.59 [95 % CI; 0.36-0.95]; I2 0 %). There were no significant differences in the rate of noninfectious inflammatory disorders, malignancies, miscellaneous disorders, or remaining undiagnosed. Comparison of diagnostic subgroups revealed that IUO patients were less likely to have systemic autoinflammatory disorders (OR 0.17 [95 % CI, 0.05-0.58]; I2 42 %) and more likely to have vasculitis (OR 2.04 [95 % CI, 1.23-3.38]; I2 21 %) and rheumatoid arthritis or spondylarthritis (OR 3.52 [95 % CI, 1.16-10.69]; I2 0 %). CONCLUSION: Based on our findings, there is little reason to assume that FUO and IUO patients would benefit from a different initial diagnostic approach.
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Fiebre de Origen Desconocido , Inflamación , Fiebre de Origen Desconocido/etiología , Humanos , Inflamación/diagnóstico , Diagnóstico DiferencialRESUMEN
With a growing emphasis on value-based reimbursement, developing quality indicators for infectious diseases has gained attention. Quality indicators for fever of unknown origin and inflammation of unknown origin are lacking. An assembled group of international experts developed 12 quality measures for these conditions, which could be validated with additional study.
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Evaluation of patients that may be infected is challenging. Imaging to identify or localize a site of infection is often limited because of the nonspecific nature of the findings on conventional imaging modalities. Available imaging methods lack the ability to determine if antibiotics are reaching the site of infection and are not optimized to follow response to therapy. Positron emission tomography (PET) is a method by which radiolabeled molecules can be used to detect metabolic perturbations or levels of expression of specific targets. The most common PET agent is the glucose analog 2-deoxy-2-[18F]fluoro-D-glucose (18F-FDG). 18F-FDG has some applicability to localizing a site of infection, but its lack of specificity limits its usefulness. There is a need for the development of pathogen-specific PET radiotracers to address the imaging shortcomings noted above. Preclinical and clinical progress has been made, but significant challenges remain.
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Fiebre de Origen Desconocido , Fluorodesoxiglucosa F18 , Humanos , Radiofármacos , Tomografía Computarizada por Rayos X/efectos adversos , Tomografía Computarizada por Rayos X/métodos , Fiebre de Origen Desconocido/diagnóstico , Fiebre de Origen Desconocido/etiología , Tomografía de Emisión de Positrones/métodos , Imagen Molecular/efectos adversosRESUMEN
Antimicrobial resistance (AMR) continues to serve as a major global health crisis. Clinicians practising in this modern era are faced with ongoing challenges in the therapeutic management of patients suffering from antimicrobial-resistant infections. A strong educational understanding and synergistic application of clinical microbiology, infectious disease and pharmacological concepts can assist the adventuring clinician in the navigation of such cases. Important items include mobilizing laboratory testing for pathogen identification and susceptibility data, harnessing an understanding of intrinsic pathogen resistance, acknowledging epidemiological resistance trends, recognizing acquired AMR mechanisms, and consolidating these considerations when constructing an ideal pharmacological plan. In this article, we outline a novel framework by which to systematically approach clinical AMR, encourage AMR-related education and optimize therapeutic decision-making in AMR-related illnesses.
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Background: Classifying fever of unknown origin (FUO) into categorical etiologies (ie, infections, noninfectious inflammatory, oncologic, miscellaneous, and undiagnosed disorders) remains unstandardized and subject to discrepancies. As some disease classifications change, a systematic review of studies would help physicians anticipate the frequency of illness types they may encounter that could influence care. Methods: We systematically reviewed prospective FUO studies published across the Medline (PubMed), Embase, Scopus, and Web of Science databases from January 1, 1997, to July 31, 2022. We performed a meta-analysis to estimate associated pooled proportions between the investigator-determined choice of disease category and those determined by the International Classification of Diseases, 10th edition (ICD-10), methodology. Results: The proportion of patients with a difference between the investigator and ICD-10-adjusted noninfectious inflammatory disorder category was 1.2% (95% CI, 0.005-0.021; P < .001), and the proportion was similar for the miscellaneous category at 1.5% (95% CI, 0.007-0.025; P < .001). The miscellaneous and noninfectious inflammatory disorders categories demonstrated significant across-study heterogeneity in the proportions of patients changing categories, with 52.7% (P = .007) and 51.0% (P = .010) I2 , respectively. Conclusions: Adjusting FUO-associated diagnoses by ICD-10 methodology was associated with a statistically significant risk of over- or underestimation of disease category frequency approximation when using a 5 FUO category system. An FUO diagnostic classification system that better reflects mechanistic understanding would assist future research and enhance comparability across heterogenous populations and different geographic regions. We propose an updated FUO classification scheme that streamlines categorizations, aligns with the current understanding of disease mechanisms, and should facilitate empirical decisions, if necessary.
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Antibacterianos , Clostridioides difficile , Infecciones por Clostridium , Microbioma Gastrointestinal , Probióticos , Antibacterianos/farmacología , Antibacterianos/uso terapéutico , Estudios de Seguimiento , Infecciones por Clostridium/microbiología , Infecciones por Clostridium/terapia , Microbioma Gastrointestinal/efectos de los fármacos , Probióticos/farmacología , Probióticos/uso terapéutico , RecurrenciaRESUMEN
OBJECTIVE: 18F-fluorodeoxyglucose positron emission tomography (18F-FDG PET) is an important imaging technique in the workup of fever of unknown origin (FUO) and inflammation of unknown origin (IUO). Studies comparing the diagnostic yield of 18F-FDG PET between both entities are lacking. METHODS: Retrospective analysis of FUO/IUO patients who underwent 18F-FDG PET between 2000 and 2019 in the University Hospitals of Leuven (Belgium). 18F-FDG PET images were assessed for accuracy and contribution towards the final diagnosis. Logistic regression was performed to evaluate the association between meeting FUO or IUO criteria and diagnostic contribution of 18F-FDG PET with and without adjustment for confounders. RESULTS: Out of 604 patients, 439 (73%, mean age 56 years, 43% female) underwent 18F-FDG PET imaging, including 349 (79%) classified as FUO and 90 (21%) as IUO. Noninfectious inflammatory disorders were significantly more frequent in the IUO group (37% versus 25%; P = 0.03). 18F-FDG PET imaging had a sensitivity of 93% (89-96%), a specificity of 35% (29-42%), and made a positive contribution to the final diagnosis in 25% (21-29%) of cases. IUO was significantly associated with contributive 18F-FDG PET imaging compared to FUO (aOR 2.21 [95% CI 1.31-3.72]; P = 0.003). Among those with contributive 18F-FDG PET imaging, giant cell arteritis (IUO 25% versus FUO 12%) and polymyalgia rheumatica (IUO 17% versus FUO 1%) were numerically more frequent in the IUO group. CONCLUSION: The diagnostic contribution of 18F-FDG PET was higher among those with IUO, most likely due to differences in diagnostic spectrum.
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Fiebre de Origen Desconocido , Fluorodesoxiglucosa F18 , Humanos , Femenino , Persona de Mediana Edad , Masculino , Fiebre de Origen Desconocido/diagnóstico por imagen , Fiebre de Origen Desconocido/etiología , Estudios Retrospectivos , Tomografía de Emisión de Positrones/métodos , Inflamación/diagnóstico por imagen , RadiofármacosRESUMEN
Background: Diagnostic outcomes for fever of unknown origin (FUO) remain with notable numbers of undiagnosed cases. A recent systemic review and meta-analysis of studies reported geographic variation in FUO-related infectious diseases. Whether geography influences types of FUO noninfectious diagnoses deserves examination. Methods: We systematically searched Medline (PubMed), Embase, Scopus, and Web of Science databases using medical subject headings published from January 1, 1997 to March 31, 2021. Prospective clinical studies investigating participants meeting adult FUO defining criteria were selected if they assessed final diagnoses. Meta-analyses were based on the random-effects model according to World Health Organization (WHO) geographical regions. Results: Nineteen studies with significant heterogeneity were analyzed, totaling 2667 participants. Noninfectious inflammatory disorders had a pooled estimate at 20.0% (95% confidence interval [CI], 17.0%-23.0%). Undiagnosed illness had a pooled estimate of 20.0% (95% CI, 14.0%-26.0%). The pooled estimate for cancer was 15.0% (95% CI, 12.0%-18.0%). Miscellaneous conditions had a pooled estimate of 6.0% (95% CI, 4.0%-8.0%). Noninfectious inflammatory disorders and miscellaneous conditions were most prevalent in the Western Pacific region with a 27.0% pooled estimate (95% CI, 20.0%-34.0%) and 9.0% (95% CI, 7.0%-11.0%), respectively. The highest pooled estimated for cancer was in the Eastern Mediterranean region at 25.0% (95% CI, 18.0%-32.0%). Adult-onset Still's disease (114 [58.5%]), systemic lupus (52 [26.7%]), and giant-cell arteritis (40 [68.9%]) predominated among the noninfectious inflammatory group. Lymphoma (164 [70.1%]) was the most common diagnosis in the cancer group. Conclusions: In this systematic review and meta-analysis, noninfectious disease diagnostic outcomes varied among WHO-defined geographies. Evaluations for FUO should include local variations in disease prevalence.
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Background: This study investigates the effect of prophylactic perioperative antibiotic use on patients with small burns [≤20% total body surface area (TBSA)] on rates of infection, graft loss, or readmission. Methods: A retrospective chart review was conducted on patients admitted to our institution's burn center between January 2020 and July 2021. Patients were included if they had a 20% or less TBSA burn with 1 or more operating room visit for burn excision and were excluded if a preoperative infection was present. Data were gathered regarding patient demographics, burn mechanism, burn characteristics, and outcome measures including infection, graft loss, and readmission. Statistical analysis was conducted by Mann-Whitney U and Fisher exact tests, and P values reported at two-sided significance of less than 0.05. Results: There were no significant differences in age, body mass index, TBSA, percent third-degree burn, or comorbidities between patients who received (n = 29) or did not receive (n = 47) prophylactic perioperative antibiotics. There was a nonsignificant trend toward higher length of stay in the prophylactic antibiotic group, possibly driven by a nonsignificant trend toward higher rates of flame injuries in this group. There was no difference in infection (P = 0.544), graft loss (P = 0.494), or 30-day readmission (P = 0.584) between the two groups. Conclusion: This study finds no significant difference in postoperative infection, graft loss, or 30-day readmission in two similar patient cohorts who received or did not receive prophylactic perioperative antibiotics for acute excision of small (≤20% TBSA) burns.
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Importance: Patients meeting the criteria for fever of unknown origin (FUO) can be evaluated with structured or nonstructured approaches, but the optimal diagnostic method is unresolved. Objective: To analyze differences in diagnostic outcomes among patients undergoing structured or nonstructured diagnostic methods applied to prospective clinical studies. Data Sources: PubMed, Embase, Scopus, and Web of Science databases with librarian-generated query strings for FUO, PUO, fever or pyrexia of unknown origin, clinical trial, and prospective studies identified from January 1, 1997, to March 31, 2021. Study Selection: Prospective studies meeting any adult FUO definition were included. Articles were excluded if patients did not precisely fit any existing adult FUO definition or studies were not classified as prospective. Data Extraction and Synthesis: Abstracted data included years of publication and study period, country, setting (eg, university vs community hospital), defining criteria and category outcome, structured or nonstructured diagnostic protocol evaluation, sex, temperature threshold and measurement, duration of fever and hospitalization before final diagnoses, and contribution of potential diagnostic clues, biochemical and immunological serologic studies, microbiology cultures, histologic analysis, and imaging studies. Structured protocols compared with nonstructured diagnostic methods were analyzed using regression models. Main Outcomes and Measures: Overall diagnostic yield was the primary outcome. Results: Among the 19 prospective trials with 2627 unique patients included in the analysis (range of patient ages, 10-94 years; 21.0%-55.3% female), diagnoses among FUO series varied across and within World Health Organization (WHO) geographic regions. Use of a structured diagnostic protocol was not significantly associated with higher odds of yielding a diagnosis compared with nonstructured protocols in aggregate (odds ratio [OR], 0.98; 95% CI, 0.65-1.49) or between Western Europe (Belgium, France, the Netherlands, and Spain) (OR, 0.95; 95% CI, 0.49-1.86) and Eastern Europe (Turkey and Romania) (OR, 0.83; 95% CI, 0.41-1.69). Despite the limited number of studies in some regions, analyses based on the 6 WHO geographic areas found differences in the diagnostic yield. Western European studies had the lowest percentage of achieving a diagnosis. Southeast Asia led with infections at 49.0%. Noninfectious inflammatory conditions were most prevalent in the Western Pacific region (34.0%), whereas the Eastern Mediterranean region had the highest proportion of oncologic explanations (24.0%). Conclusions and Relevance: In this systematic review and meta-analysis, diagnostic yield varied among WHO regions. Available evidence from prospective studies did not support that structured diagnostic protocols had a significantly better rate of achieving a diagnosis than nonstructured protocols. Clinicians worldwide should incorporate geographical disease prevalence in their evaluation of patients with FUO.
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Fiebre de Origen Desconocido , Adolescente , Adulto , Anciano , Anciano de 80 o más Años , Niño , Protocolos Clínicos , Diagnóstico por Imagen , Europa (Continente) , Femenino , Fiebre de Origen Desconocido/diagnóstico , Fiebre de Origen Desconocido/epidemiología , Fiebre de Origen Desconocido/etiología , Humanos , Masculino , Persona de Mediana Edad , Prevalencia , Estudios Prospectivos , Adulto JovenRESUMEN
Background: Fever of unknown origin (FUO) investigations yield a substantial number of patients with infectious diseases. This systematic review and meta-analysis aimed to quantify more common FUO infectious diseases etiologies and to underscore geographic variation. Methods: Four databases (PubMed, Embase, Scopus, and Web of Science) were searched for prospective studies reporting FUO rates among adult patients from 1 January 1997 to 31 March 2021. The pooled proportion for infectious diseases etiology was estimated using the random-effects meta-analysis model. Results: Nineteen prospective studies were included with 2667 total cases. No studies were available for Africa or the Americas. Overall, 37.0% (95.0% confidence interval [CI], 30.0%-44.0%) of FUO patients had an infectious disease etiology. Infections were more likely from Southeastern Asia (pooled proportion, 0.49 [95% CI, .43-.55]) than from Europe (pooled proportion, 0.31 [95% CI, .22-.41]). Among specifically reported infectious diseases (nâ =â 832), Mycobacterium tuberculosis complex predominated across all geographic regions (nâ =â 285 [34.3%]), followed by brucellosis (nâ =â 81 [9.7%]), endocarditis (nâ =â 62 [7.5%]), abscesses (nâ =â 61 [7.3%]), herpesvirus (eg, cytomegalovirus and Epstein-Barr virus) infections (nâ =â 60 [7.2%]), pneumonia (nâ =â 54 [6.5%]), urinary tract infections (nâ =â 54 [6.5%]), and enteric fever (nâ =â 40 [4.8%]). Conclusions: FUO patients from Southeastern Asia were more likely to have an infectious diseases etiology when compared to other regions. The predominant factor for this finding appears to be differences in disease prevalence among various geographical locations or other factors such as access to timely care and diagnosis. Noting epidemiological disease factors in FUO investigations could improve diagnostic yields and clinical outcomes.
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Large-scale SARS-CoV-2 molecular testing coupled with whole genome sequencing in the diagnostic laboratories is instrumental for real-time genomic surveillance. The extensive genomic, laboratory, and clinical data provide a valuable resource for understanding cases of reinfection versus prolonged RNA shedding and protracted infections. In this study, data from a total of 22,292 clinical specimens, positive by SARS-CoV-2 molecular diagnosis at Johns Hopkins clinical virology laboratory between March 11th 2020 to September 23rd 2021, were used to identify patients with two or more positive results. A total of 3,650 samples collected from 1,529 patients who had between 2 and 20 positive results were identified in a time frame that extended up to 403 days from the first positive. Cycle threshold values (Ct) were available for 1,622 samples, the median of which was over 30 by 11 days after the first positive. Extended recovery of infectious virus on cell culture was notable for up to 70 days after the first positive in immunocompromised patients. Whole genome sequencing data generated as a part of our SARS-CoV-2 genomic surveillance was available for 1,027 samples from patients that had multiple positive tests. Positive samples collected more than 10 days after initial positive with high quality sequences (coverage >90% and mean depth >100), were more likely to be from unvaccinated, or immunosuppressed patients. Reinfections with viral variants of concern were found in 3 patients more than 130 days from prior infections with a different viral clade. In 75 patients that had 2 or more high quality sequences, the acquisition of more substitutions or deletions was associated with lack of vaccination and longer time between the recovered viruses. Our study highlights the value of integrating genomic, laboratory, and clinical data for understanding the biology of SARS-CoV-2 as well as for setting a precedent for future epidemics and pandemics.
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COVID-19 , Reinfección , COVID-19/diagnóstico , Genoma Viral/genética , Genómica , Humanos , Técnicas de Diagnóstico Molecular , ARN Viral/genética , SARS-CoV-2/genéticaRESUMEN
Even well into the 21st century, infectious diseases still account for most causes of fever of unknown origin (FUO). Advances in molecular technologies, including broad-range polymerase chain reaction (PCR) of the 16S ribosomal RNA gene followed by Sanger sequencing, multiplex PCR assays, and more recently, next-generation sequencing applications, have transitioned from research methods to more commonplace in some clinical microbiology laboratories. They have the potential to supplant traditional microbial identification methods and antimicrobial susceptibility testing. Despite the remaining challenges with these technologies, publications in the past decade justify excitement about the potential to transform FUO investigations. We discuss available evidence using these molecular methods for FUO evaluations, including potential cost-benefits and future directions.
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Fiebre de Origen Desconocido , Reacción en Cadena de la Polimerasa Multiplex , Fiebre de Origen Desconocido/diagnóstico , Fiebre de Origen Desconocido/etiología , Secuenciación de Nucleótidos de Alto Rendimiento , Humanos , ARN Ribosómico 16S/genética , Informe de InvestigaciónRESUMEN
Prolonged fever of 38.3°C or higher for at least 3 weeks' duration has been termed fever of unknown origin if unexplained after preliminary investigations. Initially codified in 1961, classification with subgroups was revised in 1991. Additional changes to the definition were proposed in 1997, recommending a set of standardized initial investigations. Advances in diagnosis and management and diagnostic testing over the last 3 decades have prompted a needed update to the definition and approaches. While a 3-week fever duration remains part of the criteria, a lower temperature threshold of 38°C and revised minimum testing criteria will assist clinicians and their patients, setting a solid foundation for future research.
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Fiebre de Origen Desconocido/diagnóstico , Fiebre de Origen Desconocido/patología , Fiebre de Origen Desconocido/clasificación , HumanosRESUMEN
In this counterpoint we critically appraise the evidence supporting therapeutic drug monitoring based on the vancomycin 24-hour area under the concentration-time curve (AUC24) for serious methicillin-resistant Staphylococcus aureus infections. We reveal methodologically weaknesses and inconsistencies in the data and suggest that, in the absence of clear and convincing evidence of benefit compared with modestly reducing trough targets, alternative strategies are more likely to result in superior safety and efficacy. These include focusing on fundamental antibiotic stewardship to limit vancomycin exposure overall, achieving earlier and more complete source control, and establishing alternative therapeutic options to vancomycin. Implementation of AUC24-based therapeutic drug monitoring will take resources away from these more promising, alternative solutions.
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Staphylococcus aureus Resistente a Meticilina , Infecciones Estafilocócicas , Adulto , Antibacterianos/uso terapéutico , Área Bajo la Curva , Niño , Monitoreo de Drogas , Humanos , Pruebas de Sensibilidad Microbiana , Infecciones Estafilocócicas/tratamiento farmacológico , Vancomicina/uso terapéuticoRESUMEN
Coronavirus disease 2019 screening can evaluate large numbers of patients while reducing healthcare exposures and limiting further spread of the virus. Temperature screening has been a focal point of case detection during the pandemic because it is one of the earliest and most frequently reported manifestations of the illness. We describe important factors to consider of screened individuals as well as the measurement process and current outcomes. Optimal temperature-based screening involves both individual and environmental factors as well as reconsideration of the current fever threshold.