Biomarker-guided duration of antibiotic treatment in children hospitalised with confirmed or suspected bacterial infection: statistical analysis plan for the BATCH trial and PRECISE sub-study.

INTRODUCTION: The BATCH trial is a multi-centre randomised controlled trial to compare procalcitonin-guided management of severe bacterial infection in children with current management. PRECISE is a mechanistic sub-study embedded into the BATCH trial. This paper describes the statistical analysis plan for the BATCH trial and PRECISE sub-study. METHODS: The BATCH trial will assess the effectiveness of an additional procalcitonin test in children (aged 72 h to 18 years) hospitalised with suspected or confirmed bacterial infection to guide antimicrobial prescribing decisions. Participants will be enrolled in the trial from randomisation until day 28 follow-up. The co-primary outcomes are duration of intravenous antibiotic use and a composite safety outcome. Target sample size is 1942 patients, based on detecting a 1-day reduction in intravenous antibiotic use (90% power, two-sided) and on a non-inferiority margin of 5% risk difference in the composite safety outcome (90% power, one-sided), while allowing for up to 10% loss to follow-up. RESULTS: Baseline characteristics will be summarised overall, by trial arm, and by whether patients were recruited before or after the pause in recruitment due to the COVID-19 pandemic. In the primary analysis, duration of intravenous antibiotic use will be tested for superiority using Cox regression, and the composite safety outcome will be tested for non-inferiority using logistic regression. The intervention will be judged successful if it reduces the duration of intravenous antibiotic use without compromising safety. Secondary analyses will include sensitivity analyses, pre-specified subgroup analyses, and analysis of secondary outcomes. Two sub-studies, including PRECISE, involve additional pre-specified subgroup analyses. All analyses will be adjusted for the balancing factors used in the randomisation, namely centre and patient age. CONCLUSION: We describe the statistical analysis plan for the BATCH trial and PRECISE sub-study, including definitions of clinical outcomes, reporting guidelines, statistical principles, and analysis methods. The trial uses a design with co-primary superiority and non-inferiority endpoints. The analysis plan has been written prior to the completion of follow-up. TRIAL REGISTRATION: BATCH: ISRCTN11369832, registered 20 September 2017, doi.org/10.1186/ISRCTN11369832. PRECISE: ISRCTN14945050, registered 17 December 2020, doi.org/10.1186/ISRCTN14945050.

Point-of-care neutrophil CD64 as a rule in diagnostic test for bacterial infections in the emergency department.

INTRODUCTION: Bacterial infections are frequently seen in the emergency department (ED), but can be difficult to distinguish from viral infections and some non-infectious diseases. Common biomarkers such as c-reactive protein (CRP) and white blood cell (WBC) counts fail to aid in the differential diagnosis. Neutrophil CD64 (nCD64), an IgG receptor, is suggested to be more specific for bacterial infections. This study investigated if nCD64 can distinguish bacterial infections from other infectious and non-infectious diseases in the ED. METHODS: All COVID-19 suspected patients who visited the ED and for which a definitive diagnosis was made, were included. Blood was analyzed using an automated flow cytometer within 2 h after presentation. Patients were divided into a bacterial, viral, and non-infectious disease group. We determined the diagnostic value of nCD64 and compared this to those of CRP and WBC counts. RESULTS: Of the 291 patients presented at the ED, 182 patients were included with a definitive diagnosis (bacterial infection n = 78; viral infection n = 64; non-infectious disease n = 40). ROC-curves were plotted, with AUCs of 0.71 [95%CI: 0.64-0.79], 0.77 [0.69-0.84] and 0.64 [0.55-0.73] for nCD64, WBC counts and CRP, respectively. In the bacterial group, nCD64 MFI was significantly higher compared to the other groups (p < 0.01). A cut-off of 9.4 AU MFI for nCD64 corresponded with a positive predictive value of 1.00 (sensitivity of 0.27, a specificity of 1.00, and an NPV of 0.64). Furthermore, a diagnostic algorithm was constructed which can serve as an example of what a future biomarker prediction model could look like. CONCLUSION: For patients in the ED presenting with a suspected infection, nCD64 measured with automatic flow cytometry, has a high specificity and positive predictive value for diagnosing a bacterial infection. However, a low nCD64 cannot rule out a bacterial infection. For future purposes, nCD64 should be combined with additional tests to form an algorithm that adequately diagnoses infectious diseases.

Immediate and long-term changes in the epidemiology, infection spectrum, and clinical characteristics of viral and bacterial respiratory infections in Western China after the COVID-19 outbreak: a modeling study.

BACKGROUND: The impact of COVID-19 on the epidemiology, clinical characteristics, and infection spectrum of viral and bacterial respiratory infections in Western China is unknown. METHODS: We conducted an interrupted time series analysis based on surveillance of acute respiratory infections (ARI) in Western China to supplement the available data. RESULTS: The positive rates of influenza virus, Streptococcus pneumoniae, and viral and bacterial coinfections decreased, but parainfluenza virus, respiratory syncytial virus, human adenovirus, human rhinovirus, human bocavirus, non-typeable Haemophilus influenzae, Mycoplasma pneumoniae, and Chlamydia pneumoniae infections increased after the onset of the COVID-19 epidemic. The positive rate for viral infection in outpatients and children aged <5 years increased, but the positive rates of bacterial infection and viral and bacterial coinfections decreased, and the proportion patients with clinical symptoms of ARI decreased after the onset of the COVID-19 epidemic. Non-pharmacological interventions reduced the positive rates of viral and bacterial infections in the short term but did not have a long-term limiting effect. Moreover, the proportion of ARI patients with severe clinical symptoms (dyspnea and pleural effusion) increased in the short term after COVID-19, but in the long-term, it decreased. CONCLUSIONS: The epidemiology, clinical characteristics, and infection spectrum of viral and bacterial infections in Western China have changed, and children will be a high-risk group for ARI after the COVID-19 epidemic. In addition, the reluctance of ARI patients with mild clinical symptoms to seek medical care after COVID-19 should be considered. In the post-COVID-19 era, we need to strengthen the surveillance of respiratory pathogens.

The evolving relationship between COVID-19 and serious bacterial infection evaluation in febrile neonates.

AIM: The COVID-19 omicron variant surge highlighted the evolving impact of COVID-19. Febrile infants <60 days old are high risk for serious bacterial infections (SBI). This study evaluated the rate of SBI based on COVID-19 infection. METHODS: We conducted a retrospective chart review at an urban, academic paediatric emergency department. The study enrolled infants 60 days old or less with documented fever. The primary outcome was SBI diagnosed by blood, urine, and/or cerebrospinal fluid cultures. We compared the rate of SBI between COVID-19 groups with an omicron variant and 29- to 60-day-old subgroup analyses. RESULTS: Two hundred and thirty-three (233) infants meet the criteria. The incidence of SBI was 18.7% in the COVID-19 negative and 1.7% in the COVID-19-positive group which is statistically significant (p < 0.001). Omicron subgroup analysis did not achieve statistical significance (p = 0.62) while COVID-19-positive infants 29-60 days old had a statistically significant lower rate of SBI (p = 0.006). CONCLUSION: The omicron variant surge provided an additional understanding of the impact of COVID-19 on these high-risk infants. These results can lead to decreased invasive testing and exposure to antibiotics as well as examine the utility of viral testing for risk stratification.

Differentiating between bacterial and viral infections by estimated CRP velocity.

PURPOSE: Differentiating between acute viral and bacterial infection is challenging due to the similarity in symptom presentation. Blood tests can assist in the diagnosis, but they reflect the immediate status and fail to consider the dynamics of an inflammatory response with time since symptom onset. We applied estimated C-reactive protein (CRP) velocity (eCRPv), as derived from the admission CRP level divided by time from symptom onset, in order to better distinguish between viral and bacterial infections. METHODS: This cross-sectional study included patients admitted to the emergency department with a confirmed viral (n = 83) or bacterial (n = 181) infection. eCRPv was defined as the ratio between the absolute CRP level upon admission to time from symptom onset (in hours). Absolute CRP and eCRPv values were compared between the 3 groups. RESULTS: Bacterial patients presented with higher CRP levels (133 mg/L) upon admission compared to viral patients (23.31 mg/L) (P < 0.001). Their median value of eCRPv velocity was 4 times higher compared to the viral patients (1.1 mg/L/h compared 0.25 mg/L/h, P < 0.001). Moreover, in intermediate values of CRP (100-150 mg/L) upon admission, in which the differential diagnosis is controversial, high eCRPv is indicative of bacterial infection, eCRPv >4 mg/L/h represents only bacterial patients. CONCLUSIONS: During an acute febrile illness, the eCRPv value can be used for rapid differentiation between bacterial and viral infection, especially in patients with high CRP values. This capability can potentially expedite the provision of appropriate therapeutic management. Further research and validation may open new applications of the kinetics of inflammation for rapid diagnosis of an infectious vs. a viral source of fever.

Systematic comparison of published host gene expression signatures for bacterial/viral discrimination.

BACKGROUND: Measuring host gene expression is a promising diagnostic strategy to discriminate bacterial and viral infections. Multiple signatures of varying size, complexity, and target populations have been described. However, there is little information to indicate how the performance of various published signatures compare to one another. METHODS: This systematic comparison of host gene expression signatures evaluated the performance of 28 signatures, validating them in 4589 subjects from 51 publicly available datasets. Thirteen COVID-specific datasets with 1416 subjects were included in a separate analysis. Individual signature performance was evaluated using the area under the receiving operating characteristic curve (AUC) value. Overall signature performance was evaluated using median AUCs and accuracies. RESULTS: Signature performance varied widely, with median AUCs ranging from 0.55 to 0.96 for bacterial classification and 0.69-0.97 for viral classification. Signature size varied (1-398 genes), with smaller signatures generally performing more poorly (P < 0.04). Viral infection was easier to diagnose than bacterial infection (84% vs. 79% overall accuracy, respectively; P < .001). Host gene expression classifiers performed more poorly in some pediatric populations (3 months-1 year and 2-11 years) compared to the adult population for both bacterial infection (73% and 70% vs. 82%, respectively; P < .001) and viral infection (80% and 79% vs. 88%, respectively; P < .001). We did not observe classification differences based on illness severity as defined by ICU admission for bacterial or viral infections. The median AUC across all signatures for COVID-19 classification was 0.80 compared to 0.83 for viral classification in the same datasets. CONCLUSIONS: In this systematic comparison of 28 host gene expression signatures, we observed differences based on a signature's size and characteristics of the validation population, including age and infection type. However, populations used for signature discovery did not impact performance, underscoring the redundancy among many of these signatures. Furthermore, differential performance in specific populations may only be observable through this type of large-scale validation.

COVID-19 and Serious Bacterial Infection in Febrile Infants Less Than 60 Days Old.

INTRODUCTION: The pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) led to the coronavirus disease 2019 (COVID-19) pandemic that drastically impacted the United States. The evidence was not clear on how SARS-CoV-2 infection impacted children, given the high prevalence of SAR-CoV-2 infection. Febrile infants less than 60 days old are an ongoing challenge to risk-stratify for serious bacterial infection (SBI), including urinary tract infection (UTI), bacteremia, and meningitis. We hypothesized there would be a lower rate of SBI in SARS-CoV-2 positive febrile infants compared to those SARS-CoV-2 negative. METHODS: This was a retrospective chart review with a nested, age-matched, case-control study performed from March 2020-June 2021. Infants less than 60 days old presenting with fever were assigned groups based on SARS-CoV-2 infection. Blood, urine, and cerebrospinal fluid cultures were used as the gold standard to diagnose SBI. We compared overall rate of SBI as well as individual rates of SBI between each group. We performed a subgroup analysis evaluating the age group 29-60 days old. RESULTS: A total of 164 subjects met criteria for analysis: 30 COVID-19 positive and 134 COVID-19 negative subjects. Rate of SBI was 17.9% (95% confidence interval [CI]: 11.8-25.5%) in the COVID-19 negative group compared to 0% (95% CI: 0.0%-11.1%) in the COVID-19 group, which demonstrated statistical significance (p = 0.008). In the age-matched data, we found statistical significance for any SBI (p = <0.001). For individual rates of SBI, we found statistical significance for UTI (p = <0.001) and bacteremia (p = <0.001). The 29-60 days-old subgroup analysis did not achieve statistical significance (p = 0.11). CONCLUSION: This study demonstrated the utility of including SARS-CoV-2 infection as part of the risk stratification of febrile infants less than 60 days old. While overall there is a low incidence of bacteremia and meningitis in this age group, these results can contribute to existing literature and potentially help decrease invasive testing and exposure to broad-spectrum antibiotics.

Observational Study on Secondary Bacterial Infection and the Use of Antibiotics in COVID-19 Patients Treated in a Tertiary Referral Hospital.

BACKGROUND: Data on secondary bacterial infection in patients with COVID-19 in Indonesia are still limited, while the use of empirical antibiotics continues to increase. This study aims to determine the secondary bacterial infection rate in hospitalized COVID-19 patients and factors related to secondary bacterial infection. METHODS: This is a retrospective cohort study on hospitalized COVID-19 patients undergoing treatment at Cipto Mangunkusumo Hospital from March 2020 to September 2020. Secondary bacterial infection is defined as the identification of a bacterial pathogen from a microbiological examination. RESULTS: From a total of 255 subjects, secondary infection was identified in 14.5%. Predictors of secondary infection were early symptoms of shortness of breath (OR 5.31, 95% CI 1.3 - 21.5), decreased consciousness (OR 4.81, 95% CI 1.77 - 13.0), length of stay > 12 days (OR 8.2, 95% CI 2.9 - 23.3), and central venous catheter placement (OR 3.0, 95% CI 1.1 - 8.0) The most common pathogen of secondary bacterial infection is Acinetobacter sp. (n=9; 28%). Empirical antibiotics were administered to 82.4% of subjects with predominant use of macrolides (n=141; 32.4%). CONCLUSION: The secondary bacterial infection rate in COVID-19 was 14.5% and is associated with dyspnea, decreased consciousness, length of stay >12 days, and central venous catheter placement. The use of antibiotics in COVID-19 reaches 82.4% and requires special attention to prevent the occurrence of antibiotic resistance.

Negative predictive value of procalcitonin to rule out bacterial respiratory co-infection in critical covid-19 patients.

BACKGROUND: Procalcitonin (PCT) and C-Reactive Protein (CRP) are useful biomarkers to differentiate bacterial from viral or fungal infections, although the association between them and co-infection or mortality in COVID-19 remains unclear. METHODS: The study represents a retrospective cohort study of patients admitted for COVID-19 pneumonia to 84 ICUs from ten countries between (March 2020-January 2021). Primary outcome was to determine whether PCT or CRP at admission could predict community-acquired bacterial respiratory co-infection (BC) and its added clinical value by determining the best discriminating cut-off values. Secondary outcome was to investigate its association with mortality. To evaluate the main outcome, a binary logistic regression was performed. The area under the curve evaluated diagnostic performance for BC prediction. RESULTS: 4635 patients were included, 7.6% fulfilled BC diagnosis. PCT (0.25[IQR 0.1-0.7] versus 0.20[IQR 0.1-0.5]ng/mL, p<0.001) and CRP (14.8[IQR 8.2-23.8] versus 13.3 [7-21.7]mg/dL, p=0.01) were higher in BC group. Neither PCT nor CRP were independently associated with BC and both had a poor ability to predict BC (AUC for PCT 0.56, for CRP 0.54). Baseline values of PCT<0.3ng/mL, could be helpful to rule out BC (negative predictive value 91.1%) and PCT≥0.50ng/mL was associated with ICU mortality (OR 1.5,p<0.001). CONCLUSIONS: These biomarkers at ICU admission led to a poor ability to predict BC among patients with COVID-19 pneumonia. Baseline values of PCT<0.3ng/mL may be useful to rule out BC, providing clinicians a valuable tool to guide antibiotic stewardship and allowing the unjustified overuse of antibiotics observed during the pandemic, additionally PCT≥0.50ng/mL might predict worsening outcomes.

Potential and promising marker for serious bacterial infections in children: Delta neutrophil index.

AIM: This study aimed to evaluate the usefulness and accuracy of the delta neutrophil index (DNI), an index expressing the number of immature granulocytes as a proportion of the total, as an inflammatory marker in predicting serious bacterial infections (SBIs). METHODS: Paediatric patients admitted to our hospital with fever were divided into four groups: SBI, non-SBI, COVID-19 and control group. White blood cell count, absolute neutrophil count, C-reactive protein and the DNI were recorded, and their accuracy in predicting SBI was evaluated. RESULTS: Mean DNI was 4.96 ± 8.38 in the SBI group (150 patients), 0.67 ± 1.68 in the non-SBI group (397 patients), 0.29 ± 0.99 in the COVID-19 group (112 patients) and 0.14 ± 0.21 in the control group (102 patients). The DNI was significantly higher in the SBI group compared with the non-SBI (P < 0.001); the non-SBI group also had higher levels than the COVID-19 group (P = 0.005). One percent increase in the DNI increased the SBI rate 1.36 times (odds ratio 1.36 (95% confidence interval 1.23-1.49), P < 0.001). Based on the determined cut-off value (>2.5%), the DNI (odds ratio 6.27 (95% confidence interval 3.85-10.21), P < 0.001) significantly predicted SBIs with 90.4% specificity and 47.7% sensitivity. CONCLUSIONS: SBIs in childrenare associated with an increase in DNI levels. Compared to other biomarkers, the DNI had higher specificity in predicting SBIs. The DNI may also be usefulin differentiating bacterial and non-bacterial infections in individualclinical syndromes. Currently, there is no evidence that serum DNI aids indifferentiating COVID-19 and upper respiratory tract infection.

Predictive model for bacterial co-infection in patients hospitalized for COVID-19: a multicenter observational cohort study.

OBJECTIVE: The aim of our study was to build a predictive model able to stratify the risk of bacterial co-infection at hospitalization in patients with COVID-19. METHODS: Multicenter observational study of adult patients hospitalized from February to December 2020 with confirmed COVID-19 diagnosis. Endpoint was microbiologically documented bacterial co-infection diagnosed within 72 h from hospitalization. The cohort was randomly split into derivation and validation cohort. To investigate risk factors for co-infection univariable and multivariable logistic regression analyses were performed. Predictive risk score was obtained assigning a point value corresponding to ß-coefficients to the variables in the multivariable model. ROC analysis in the validation cohort was used to estimate prediction accuracy. RESULTS: Overall, 1733 patients were analyzed: 61.4% males, median age 69 years (IQR 57-80), median Charlson 3 (IQR 2-6). Co-infection was diagnosed in 110 (6.3%) patients. Empirical antibiotics were started in 64.2 and 59.5% of patients with and without co-infection (p = 0.35). At multivariable analysis in the derivation cohort: WBC ≥ 7.7/mm3, PCT ≥ 0.2 ng/mL, and Charlson index ≥ 5 were risk factors for bacterial co-infection. A point was assigned to each variable obtaining a predictive score ranging from 0 to 5. In the validation cohort, ROC analysis showed AUC of 0.83 (95%CI 0.75-0.90). The optimal cut-point was ≥2 with sensitivity 70.0%, specificity 75.9%, positive predictive value 16.0% and negative predictive value 97.5%. According to individual risk score, patients were classified at low (point 0), intermediate (point 1), and high risk (point ≥ 2). CURB-65 ≥ 2 was further proposed to identify patients at intermediate risk who would benefit from early antibiotic coverage. CONCLUSIONS: Our score may be useful in stratifying bacterial co-infection risk in COVID-19 hospitalized patients, optimizing diagnostic testing and antibiotic use.

Elucidating the role of procalcitonin as a biomarker in hospitalized COVID-19 patients.

Our objectives were to evaluate the role of procalcitonin in identifying bacterial co-infections in hospitalized COVID-19 patients and quantify antibiotic prescribing during the 2020 pandemic surge. Hospitalized COVID-19 patients with both a procalcitonin test and blood or respiratory culture sent on admission were included in this retrospective study. Confirmed co-infection was determined by an infectious diseases specialist. In total, 819 patients were included; 335 (41%) had an elevated procalcitonin (>0.5 ng/mL) and of these, 42 (13%) had an initial bacterial co-infection. Positive predictive value of elevated procalcitonin for co-infection was 13% while the negative predictive value was 94%. Ninety-six percent of patients with an elevated procalcitonin received antibiotics (median 6 days of therapy), compared to 82% with low procalcitonin (median 4 days of therapy) (adjusted OR:3.3, P < 0.001). We observed elevated initial procalcitonin in many COVID patients without concurrent bacterial co-infections which potentially contributed to antibiotic over-prescribing.

Dexamethasone and tocilizumab treatment considerably reduces the value of C-reactive protein and procalcitonin to detect secondary bacterial infections in COVID-19 patients.

BACKGROUND: Procalcitonin (PCT) and C-reactive protein (CRP) were previously shown to have value for the detection of secondary infections in critically ill COVID-19 patients. However, since the introduction of immunomodulatory therapy, the value of these biomarkers is unclear. We investigated PCT and CRP kinetics in critically ill COVID-19 patients treated with dexamethasone with or without tocilizumab, and assessed the value of these biomarkers to detect secondary bacterial infections. METHODS: In this prospective study, 190 critically ill COVID-19 patients were divided into three treatment groups: no dexamethasone, no tocilizumab (D-T-), dexamethasone, no tocilizumab (D+T-), and dexamethasone and tocilizumab (D+T+). Serial data of PCT and CRP were aligned on the last day of dexamethasone treatment, and kinetics of these biomarkers were analyzed between 6 days prior to cessation of dexamethasone and 10 days afterwards. Furthermore, the D+T- and D+T+ groups were subdivided into secondary infection and no-secondary infection groups to analyze differences in PCT and CRP kinetics and calculate detection accuracy of these biomarkers for the occurrence of a secondary infection. RESULTS: Following cessation of dexamethasone, there was a rebound in PCT and CRP levels, most pronounced in the D+T- group. Upon occurrence of a secondary infection, no significant increase in PCT and CRP levels was observed in the D+T- group (p = 0.052 and p = 0.08, respectively). Although PCT levels increased significantly in patients of the D+T+ group who developed a secondary infection (p = 0.0003), this rise was only apparent from day 2 post-infection onwards. CRP levels remained suppressed in the D+T+ group. Receiver operating curve analysis of PCT and CRP levels yielded area under the curves of 0.52 and 0.55, respectively, which are both markedly lower than those found in the group of COVID-19 patients not treated with immunomodulatory drugs (0.80 and 0.76, respectively, with p values for differences between groups of 0.001 and 0.02, respectively). CONCLUSIONS: Cessation of dexamethasone in critically ill COVID-19 patients results in a rebound increase in PCT and CRP levels unrelated to the occurrence of secondary bacterial infections. Furthermore, immunomodulatory treatment with dexamethasone and tocilizumab considerably reduces the value of PCT and CRP for detection of secondary infections in COVID-19 patients.

Pulmonary bacterial infections in adult patients hospitalized for COVID-19 in standard wards.

OBJECTIVES: During the COVID-19 pandemic, antibiotic use was very common. However, bacterial co-/secondary infections with coronaviruses remain largely unknown in standard wards. We aimed to investigate the characteristics of pulmonary bacterial infections associated with COVID-19 in hospitalized patients. METHODS: A retrospective monocentric observational study was conducted in Bichat hospital, France, between February 26 and April 22, 2020. All patients hospitalized in standard wards with COVID-19 (positive nasopharyngeal PCR and/or typical aspect on CT-scan) and diagnosed with pulmonary bacterial infection (positive bacteriological samples) were included. Bacteriological and clinical data were collected from the microbiology laboratories and patient's medical records. RESULTS: Twenty-three bacteriological samples from 22 patients were positive out of 2075 screened samples (1.1%) from 784 patients (2.8%). Bacterial infection occurred within a median of 10 days after COVID-19 onset. Diagnosis of pulmonary bacterial infection was suspected on increase of oxygen requirements (20/22), productive cough or modification of sputum aspect (17/22), or fever (10/22). Positive samples included 13 sputum cultures, one FilmArray® assay on sputum samples, one bronchoalveolar lavage, six blood cultures, and two pneumococcal urinary antigen tests. The most frequent bacteria were Pseudomonas aeruginosa (6/23), Staphylococcus aureus (5/23), Streptococcus pneumoniae (4/23), Enterococcus faecalis (3/23), and Klebsiella aerogenes (3/23). No Legionella urinary antigen test was positive. Four out of 496 nasopharyngeal PCR tests (0.8%) were positive for intracellular bacteria (two Bordetella pertussis and two Mycoplasma pneumonia). CONCLUSIONS: Pulmonary bacterial secondary infections and co-infections with SARS-CoV-2 are uncommon. Antibiotic use should remain limited in the management of COVID-19.

Recent Advances in the Use of Mesoporous Silica Nanoparticles for the Diagnosis of Bacterial Infections.

Public awareness of infectious diseases has increased in recent months, not only due to the current COVID-19 outbreak but also because of antimicrobial resistance (AMR) being declared a top-10 global health threat by the World Health Organization (WHO) in 2019. These global issues have spiked the realization that new and more efficient methods and approaches are urgently required to efficiently combat and overcome the failures in the diagnosis and therapy of infectious disease. This holds true not only for current diseases, but we should also have enough readiness to fight the unforeseen diseases so as to avoid future pandemics. A paradigm shift is needed, not only in infection treatment, but also diagnostic practices, to overcome the potential failures associated with early diagnosis stages, leading to unnecessary and inefficient treatments, while simultaneously promoting AMR. With the development of nanotechnology, nanomaterials fabricated as multifunctional nano-platforms for antibacterial therapeutics, diagnostics, or both (known as "theranostics") have attracted increasing attention. In the research field of nanomedicine, mesoporous silica nanoparticles (MSN) with a tailored structure, large surface area, high loading capacity, abundant chemical versatility, and acceptable biocompatibility, have shown great potential to integrate the desired functions for diagnosis of bacterial infections. The focus of this review is to present the advances in mesoporous materials in the form of nanoparticles (NPs) or composites that can easily and flexibly accommodate dual or multifunctional capabilities of separation, identification and tracking performed during the diagnosis of infectious diseases together with the inspiring NP designs in diagnosis of bacterial infections.

Antibiotic Overuse for COVID-19: Are We Adding Insult to Injury?

In this study, we described the proportion of COVID-19 patients started on antibiotics empirically and the work-ups performed to diagnose bacterial superinfection. We used a retrospective cohort study design involving medical records of symptomatic, hospitalized COVID-19 patients who were admitted to these centers. A total of 481 patients were included, with a median age of 41.0 years (interquartile range, 28-58.5 years). A total of 72.1% (N = 347) of COVID-19 patients received antibiotics, either before or during admission. This is troublesome because none of the patients' bacterial culture or inflammatory markers, such as the erythrocyte sedimentation rate or C-reactive protein, were evaluated, and only 73 (15.2%) underwent radiological investigations. Therefore, national COVID-19 guidelines should emphasize the rational use of antibiotics for the treatment of COVID-19, a primarily viral disease. Integrating antimicrobial stewardship into the COVID-19 response and expanding microbiological capacities in low-income countries are indispensable. Otherwise, we risk one pandemic aggravating another.

Development of Integrated Systems for On-Site Infection Detection.

The modern healthcare system faces an unrelenting threat from microorganisms, as evidenced by global outbreaks of new viral diseases, emerging antimicrobial resistance, and the rising incidence of healthcare-associated infections (HAIs). An effective response to these threats requires rapid and accurate diagnostic tests that can identify causative pathogens at the point of care (POC). Such tests could eliminate diagnostic uncertainties, facilitating patient triaging, minimizing the empiric use of antimicrobial drugs, and enabling targeted treatments. Current standard methods, however, often fail to meet the needs of rapid diagnosis in POC settings. Culture-based assays entail long processing times and require specialized laboratory infrastructure; nucleic acid (NA) tests are often limited to centralized hospitals due to assay complexity and high costs. Here we discuss two new POC tests developed in our groups to enable the rapid diagnosis of infection. The first is nanoPCR that takes advantages of core-shell magnetoplasmonic nanoparticles (MPNs): (i) Au shell significantly accelerates thermocycling via volumetric, plasmonic light-to-heat conversion and (ii) a magnetic core enables sensitive in situ fluorescent detection via magnetic clearing. By adopting a Ferris wheel module, the system expedites multisamples in parallel with a minimal setup. When applied to COVID-19 diagnosis, nanoPCR detected SARS-CoV-2 RNA down to 3.2 copy/µL within 17 min. In particular, nanoPCR diagnostics accurately identified COVID-19 cases in clinical samples (n = 150), validating its clinical applicability. The second is a polarization anisotropy diagnostic (PAD) system that exploits the principle of fluorescence polarization (FP) as a detection modality. Fluorescent probes were designed to alter their molecular weight upon recognizing target NAs. This event modulates the probes' tumbling rate (Brownian motion), which leads to changes in FP. The approach is robust against environmental noise and benefits from the ratiometric nature of the signal readout. We applied PAD to detect clinically relevant HAI bacteria (Escherichia coli, Klebsiella pneumoniae, Acinetobacter baumannii, Pseudomonas aeruginosa, and Staphylococcus aureus). The PAD assay demonstrated detection sensitivity down to the single bacterium level and determined both drug resistance and virulence status. In summary, these new tests have the potential to become powerful tools for rapid diagnosis in the infectious disease space. They do not require highly skilled personnel or labor-intensive analyses, and the assays are quick and cost-effective. These attributes will make nanoPCR and PAD well-aligned with a POC workflow to aid physicians to initiate prompt and informed patient treatment.