High-dimensional characterization of post-acute sequelae of COVID-19.

The acute clinical manifestations of COVID-19 have been well characterized1,2, but the post-acute sequelae of this disease have not been comprehensively described. Here we use the national healthcare databases of the US Department of Veterans Affairs to systematically and comprehensively identify 6-month incident sequelae-including diagnoses, medication use and laboratory abnormalities-in patients with COVID-19 who survived for at least 30 days after diagnosis. We show that beyond the first 30 days of illness, people with COVID-19 exhibit a higher risk of death and use of health resources. Our high-dimensional approach identifies incident sequelae in the respiratory system, as well as several other sequelae that include nervous system and neurocognitive disorders, mental health disorders, metabolic disorders, cardiovascular disorders, gastrointestinal disorders, malaise, fatigue, musculoskeletal pain and anaemia. We show increased incident use of several therapeutic agents-including pain medications (opioids and non-opioids) as well as antidepressant, anxiolytic, antihypertensive and oral hypoglycaemic agents-as well as evidence of laboratory abnormalities in several organ systems. Our analysis of an array of prespecified outcomes reveals a risk gradient that increases according to the severity of the acute COVID-19 infection (that is, whether patients were not hospitalized, hospitalized or admitted to intensive care). Our findings show that a substantial burden of health loss that spans pulmonary and several extrapulmonary organ systems is experienced by patients who survive after the acute phase of COVID-19. These results will help to inform health system planning and the development of multidisciplinary care strategies to reduce chronic health loss among individuals with COVID-19.

Simultaneous detection of influenza A, B and respiratory syncytial virus in wastewater samples by one-step multiplex RT-ddPCR assay.

BACKGROUND: After the occurrence of the COVID-19 pandemic, detection of other disseminated respiratory viruses using highly sensitive molecular methods was declared essential for monitoring the spread of health-threatening viruses in communities. The development of multiplex molecular assays are essential for the simultaneous detection of such viruses even at low concentrations. In the present study, a highly sensitive and specific multiplex one-step droplet digital PCR (RT-ddPCR) assay was developed for the simultaneous detection and absolute quantification of influenza A (IAV), influenza B (IBV), respiratory syncytial virus (RSV), and beta-2-microglobulin transcript as an endogenous internal control (IC B2M). RESULTS: The assay was first evaluated for analytical sensitivity and specificity, linearity, reproducibility, and recovery rates with excellent performance characteristics and then applied to 37 wastewater samples previously evaluated with commercially available and in-house quantitative real-time reverse transcription PCR (RT-qPCR) assays. IAV was detected in 16/37 (43%), IBV in 19/37 (51%), and RSV in 10/37 (27%) of the wastewater samples. Direct comparison of the developed assay with real-time RT-qPCR assays showed statistically significant high agreement in the detection of IAV (kappa Cohen's correlation coefficient: 0.834, p = 0.001) and RSV (kappa: 0.773, p = 0.001) viruses between the two assays, while the results for the detection of IBV (kappa: 0.355, p = 0.27) showed good agreement without statistical significance. CONCLUSIONS: Overall, the developed one-step multiplex ddPCR assay is cost-effective, highly sensitive and specific, and can simultaneously detect three common respiratory viruses in the complex matrix of wastewater samples even at low concentrations. Due to its high sensitivity and resistance to PCR inhibitors, the developed assay could be further used as an early warning system for wastewater monitoring.

The New Normal: Delayed Peak SARS-CoV-2 Viral Loads Relative to Symptom Onset and Implications for COVID-19 Testing Programs.

BACKGROUND: Early in the coronavirus disease 2019 (COVID-19) pandemic, peak viral loads coincided with symptom onset. We hypothesized that in a highly immune population, symptom onset might occur earlier in infection, coinciding with lower viral loads. METHODS: We assessed severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and influenza A viral loads relative to symptom duration in symptomatic adults (≥16 years) presenting for testing in Georgia (4/2022-4/2023; Omicron variant predominant). Participants provided symptom duration and recent testing history. Nasal swabs were tested by Xpert Xpress SARS-CoV-2/Flu/RSV assay and cycle threshold (Ct) values recorded. Nucleoprotein concentrations in SARS-CoV-2 polymerase chain reaction (PCR)-positive samples were measured by single molecule array. To estimate hypothetical antigen rapid diagnostic test (Ag RDT) sensitivity on each day after symptom onset, percentages of individuals with Ct value ≤30 or ≤25 were calculated. RESULTS: Of 348 newly-diagnosed SARS-CoV-2 PCR-positive individuals (65.5% women, median 39.2 years), 317/348 (91.1%) had a history of vaccination, natural infection, or both. By both Ct value and antigen concentration measurements, median viral loads rose from the day of symptom onset and peaked on the fourth/fifth day. Ag RDT sensitivity estimates were 30.0%-60.0% on the first day, 59.2%-74.8% on the third day, and 80.0%-93.3% on the fourth day of symptoms.In 74 influenza A PCR-positive individuals (55.4% women; median 35.0 years), median influenza viral loads peaked on the second day of symptoms. CONCLUSIONS: In a highly immune adult population, median SARS-CoV-2 viral loads peaked around the fourth day of symptoms. Influenza A viral loads peaked soon after symptom onset. These findings have implications for ongoing use of Ag RDTs for COVID-19 and influenza.

Multiplex Dual-Target Reverse Transcription PCR for Subtyping Avian Influenza A(H5) Virus.

An increased risk for human infection with avian influenza A(H5N1) viruses is of concern. We developed an internally controlled, dual-target reverse transcription PCR for influenza A(H5) subtyping. This test could be used to detect influenza A(H5) in clinical samples.

Correlation between Viral Wastewater Concentration and Respiratory Tests, Oregon, USA.

We evaluated the association between wastewater concentration and weekly percent positivity of patient testing for SARS-CoV-2, influenza, and respiratory syncytial virus in Oregon, USA. We found strong, positive correlations for SARS-CoV-2 (ρ = 0.84, p<0.001), influenza (ρ = 0.73, p<0.001) and respiratory syncytial virus (ρ = 0.69, p<0.001).

Electronic Health Record-Based Algorithm for Monitoring Respiratory Virus-Like Illness.

Viral respiratory illness surveillance has traditionally focused on single pathogens (e.g., influenza) and required fever to identify influenza-like illness (ILI). We developed an automated system applying both laboratory test and syndrome criteria to electronic health records from 3 practice groups in Massachusetts, USA, to monitor trends in respiratory viral-like illness (RAVIOLI) across multiple pathogens. We identified RAVIOLI syndrome using diagnosis codes associated with respiratory viral testing or positive respiratory viral assays or fever. After retrospectively applying RAVIOLI criteria to electronic health records, we observed annual winter peaks during 2015-2019, predominantly caused by influenza, followed by cyclic peaks corresponding to SARS-CoV-2 surges during 2020-2024, spikes in RSV in mid-2021 and late 2022, and recrudescent influenza in late 2022 and 2023. RAVIOLI rates were higher and fluctuations more pronounced compared with traditional ILI surveillance. RAVIOLI broadens the scope, granularity, sensitivity, and specificity of respiratory viral illness surveillance compared with traditional ILI surveillance.

HCR-Assisted RTF-EXPAR-Based Lateral Flow Analysis for Sensitive Detection of H1N1 Influenza Virus.

The H1N1 influenza virus is a significant pathogen responsible for seasonal influenza, and its frequent outbreaks pose substantial challenges to global public health. The present study successfully developed a lateral flow analysis platform that integrates reverse transcription-free exponential amplification reaction (RTF-EXPAR) and hybridization chain reaction (HCR) processes with functionalized quantum dots for the direct detection of H1N1 influenza virus RNA, eliminating the need for reverse transcription. The fluorescence signal on the band recorded with a smartphone can be utilized for the quantitative determination of the target. Interestingly, the dual signal amplification strategy exhibits high sensitivity with a remarkably low detection limit of 10 aM. Moreover, this platform exhibits excellent flexibility and universality, where the various pathogens can be determined by replacing the specific nucleic acid fragments in RTF-EXPAR. The aforementioned advantages reveal its huge potential in the early diagnosis of H1N1 influenza virus infection and developing point-of-care testing (POCT) equipment for nucleic acid analysis.

Simultaneous Detection of Infectious Diseases Using Aptamer-Conjugated Gold Nanoparticles in the Lateral Flow Immunoassay-Based Signal Amplification Platform.

Various platforms for the accurate diagnosis of infectious diseases have been studied because of the emergence of coronavirus disease (COVID-19) in 2019. Recently, it has become difficult to distinguish viruses with similar symptoms due to the continuous mutation of viruses, and there is an increasing need for a diagnostic method to detect them simultaneously. Therefore, we developed a paper-based rapid antigen diagnostic test using DNA aptamers for the simultaneous detection of influenza A, influenza B, and COVID-19. Aptamers specific for each target viral antigen were selected and attached to AuNPs for application in a rapid antigen diagnosis kit using our company's heterogeneous sandwich-type aptamer screening method (H-SELEX). We confirmed that the three viruses could be detected on the same membrane without cross-reactivity based on the high stability, specificity, and binding affinity of the selected aptamers. Further, the limit of detection was 2.89 pg·mL-1 when applied to develop signal amplification technology; each virus antigen was detected successfully in diluted nasopharyngeal samples. We believe that the developed simultaneous diagnostic kit, based on such high accuracy, can distinguish various infectious diseases, thereby increasing the therapeutic effect and contributing to the clinical field.

Long-Lasting Chemiluminescence Based on Functionalized Multicolor Protein Capsules for Multiple Visualization Detection of Avian Influenza Virus Biomarkers.

Long-lasting chemiluminescence (CL) emissions are necessary for improving the detection accuracy and expanding the application scope. Here, we have synthesized three oil-in-water (O/W) multicolor protein capsules (LCBA, F/LCBA, and RB/F/LCBA) using a simple ultrasound method and have engineered specific target-triggered catalytic hairpin assembly on their surface and chemiluminescence resonance energy transfer inside. Consequently, three multicolor capsules exhibit excellent structural stability, generate blue-, green-, and red-colored emissions when reacting with H2O2, have long-lasting CL emission over 1 h, and successfully achieve the accurate multiple visualization detection of avian influenza virus subtype targets. Without the need for complex instruments and analysis procedures, the CL imaging assays can be carried out and recorded with a common smartphone. The detection limits for visualizing H1N1, H7N9, and H5N1 are 5.5, 7.6, and 9.0 pM, respectively. There is a linear range between 20.0 and 625 pM and excellent selectivity against interfering DNA. Furthermore, visualization detection has been successfully applied for the detection of H1N1, H7N9, and H5N1 in healthy human serum samples. With these merits, this facile, ultrasensitive, and multiple visualization sensor has potential applications in point-of-care testing and early diagnosis.

SERS Platform for Integrated Enrichment, Isolation, and Identification of Multiple Respiratory Viruses in a Single Assay Using 3D Stereoscopic SERS Tags and Flocked Swabs.

Influenza (flu) and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) exhibit similar clinical symptoms, complicating the diagnosis and clinical management of these critical respiratory infections. Thus, there is an urgent need for rapid on-site detection technologies that can simultaneously detect SARS-CoV-2 and influenza A viruses. Here, we have developed the first platform that combines in situ sampling with immune swabs and multichannel surface-enhanced Raman spectroscopy (SERS) for simultaneous screening of these two respiratory viruses in a single assay. A seed-mediated growth method was used to assemble a number of silver spheres on the surface of Fe3O4@SiO2 spheres, which not only creates extensive Raman hotspots but also provides numerous sites for Raman signaling molecules, enhancing the sensing sensitivity. Integrating two specific Raman signaling molecules into the nanospheres allows for the parallel detection of both viruses, improving the efficiency of SERS signal read-out. Rapid quantitative screening of both SARS-CoV-2 and H1N1 is achievable within 15 min, with detection limits of 7.76, and 8.13 pg·mL-1 for their respective target proteins. The platform demonstrated excellent performance in testing and analyzing 98 clinical samples (SARS-CoV-2:50; influenza A:48), achieving sensitivities of 88.00, and 95.83% for SARS-CoV-2 and influenza A, respectively. Pearson's correlation analysis revealed a significant correlation with the clinical CT values (P < 0.0001), underscoring the great potential of this platform for the early, rapid, and simultaneous diagnostic discrimination of multiple pathogens.

Performance evaluation of the Panbio COVID-19/Flu A&B Panel for detection of SARS-CoV-2, influenza A, and influenza B antigens using mid-turbinate nasal swabs.

The Panbio COVID-19/Flu A&B Panel (Abbott) is an in vitro diagnostic rapid test designed for the qualitative detection of nucleocapsid proteins SARS-CoV-2 and nucleoprotein influenza A and B antigens in nasal mid-turbinate (NMT) swab specimens from symptomatic individuals meeting COVID-19 and influenza clinical and/or epidemiological criteria. This study, the largest global one to date using fresh samples, aimed to assess the diagnostic sensitivity and specificity of the Panbio COVID-19/Flu A&B Panel in freshly collected NMT swab specimens from individuals suspected of respiratory viral infection consistent with COVID-19 and/or influenza within the first 5 days of symptom onset compared with results obtained with the cobas SARS-CoV-2 and influenza A/B qualitative assay (cobas 6800/8800 systems), which were tested using nasopharyngeal swab samples. A total of 512 evaluable subjects were enrolled in the COVID-19 cohort across 18 sites, and 1,148 evaluable subjects were enrolled in the influenza cohort across 22 sites in the Asia-Pacific, Europe, and the USA. The Panbio COVID-19/Flu A&B Panel demonstrated a sensitivity of 80.4% and a specificity of 99.7% for COVID-19. For influenza A, the sensitivity and specificity rates were 80.6% and 99.3%, respectively. Likewise, for influenza B, the sensitivity and specificity rates were 80.8% and 99.4%, respectively. In conclusion, the Panbio COVID-19/Flu A&B Panel emerges as a suitable rapid test for detecting COVID-19 and influenza in symptomatic subjects across diverse global populations, exhibiting high sensitivity. The assay achieved a sensitivity of 94.4% in samples with Ct ≤24 for COVID-19 and 92.6% in samples with Ct ≤30 for influenza A and B. IMPORTANCE: The Panbio COVID-19/Flu A&B Panel is a suitable rapid test for detecting COVID-19 and influenza in symptomatic subjects across diverse global populations, exhibiting high sensitivity. The assay achieved a sensitivity of 94.0% in samples with Ct ≤24 for COVID-19 and 92.6% in samples with Ct ≤30 for influenza A and B.

Nucleic acid-based electrochemical biosensor for detection of influenza B by gold nanoparticles.

The influenza virus is a pervasive pathogen that exhibits increased prevalence during colder seasons, resulting in a significant annual occurrence of infections. Notably, pharmaceutical interventions effective against influenza A strains often exhibit limited efficacy against influenza B variants. Against this backdrop, the need for innovative approaches to accurately and swiftly differentiate and detect influenza B becomes evident. Biosensors play a pivotal role in this detection process, offering rapid, specific, and sensitive identification of the virus, facilitating timely intervention and containment efforts. Oligonucleotide sequences targeting the conserved B/Victoria/2/87 influenza virus NP region were designed. Nasopharyngeal swabs were collected from patients suspected of influenza virus infection, and viral RNA was extracted. RNA quality was assessed through one-step PCR. cDNA synthesis was performed using random hexamers, and real-time PCR quantified the influenza genome. Gold nanoparticles were immobilized on a surface to immobilize the specific DNA probe, and electrochemical hybridization was electrochemically followed. The biosensor exhibited high selectivity and effective distinction of complementary sequences from mismatches and influenza virus cDNA genome. The biosensor successfully detected the influenza B virus genome in real samples. Non-influenza samples yielded no significant hybridization signals. The comparison between the results obtained from the biosensor and real-time PCR revealed full agreement of these methods. The biosensor utilized electrochemical detection of hybridization and proved effective in detecting the influenza B virus genome with high specificity, sensitivity, and selectivity. Comparative analysis with real-time PCR underscored the accuracy and potential applicability of the biosensor in rapid and specific virus detection. This innovative approach holds promise for future diagnostic and epidemiological applications in detecting influenza B virus and other pathogens.

MUC5AC: A potential biomarker of severity in pediatric patients infected with influenza.

Numerous factors can increase the risk of severe influenza; however, a majority of severe cases occur in previously healthy children. Identification of high-risk children is important for targeted preventive interventions and prompt treatment. The aim of this study was to evaluate MUC5AC as a biomarker for influenza disease severity in children. For this, a prospective cohort study was conducted in 2019. Children hospitalized with acute respiratory infection (ARI) with confirmed positive influenza infection were enrolled. Influenza cases were identified by reverse transcriptase-polymerase chain reaction. Life-threatening disease (LTD) was defined by the need for intensive care and ventilatory support. MUC5AC, epidemiologic, and clinical risk factors were assessed. Three hundred and forty-two patients were hospitalized with ARI, of which 49 (14%) had confirmed influenza infection and 6 (12%) of them developed LTD. MUC5AC levels were higher in those patients with mild disease compared to cases with poorer outcomes. Our results show that the severity of influenza infection in children is significantly associated with low levels of MUC5AC. These findings suggest its potential as a suitable biomarker for predicting disease severity.

Risk factors for prolonged mechanical ventilation in critically ill patients with influenza-related acute respiratory distress syndrome.

BACKGROUND: Patients with influenza-related acute respiratory distress syndrome (ARDS) are critically ill and require mechanical ventilation (MV) support. Prolonged mechanical ventilation (PMV) is often seen in these cases and the optimal management strategy is not established. This study aimed to investigate risk factors for PMV and factors related to weaning failure in these patients. METHODS: This retrospective cohort study was conducted by eight medical centers in Taiwan. All patients in the intensive care unit with virology-proven influenza-related ARDS requiring invasive MV from January 1 to March 31, 2016, were included. Demographic data, critical illness data and clinical outcomes were collected and analyzed. PMV is defined as mechanical ventilation use for more than 21 days. RESULTS: There were 263 patients with influenza-related ARDS requiring invasive MV enrolled during the study period. Seventy-eight patients had PMV. The final weaning rate was 68.8% during 60 days of observation. The mortality rate in PMV group was 39.7%. Risk factors for PMV were body mass index (BMI) > 25 (kg/m2) [odds ratio (OR) 2.087; 95% confidence interval (CI) 1.006-4.329], extracorporeal membrane oxygenation (ECMO) use (OR 6.181; 95% CI 2.338-16.336), combined bacterial pneumonia (OR 4.115; 95% CI 2.002-8.456) and neuromuscular blockade use over 48 h (OR 2.8; 95% CI 1.334-5.879). In addition, risk factors for weaning failure in PMV patients were ECMO (OR 5.05; 95% CI 1.75-14.58) use and bacteremia (OR 3.91; 95% CI 1.20-12.69). CONCLUSIONS: Patients with influenza-related ARDS and PMV have a high mortality rate. Risk factors for PMV include BMI > 25, ECMO use, combined bacterial pneumonia and neuromuscular blockade use over 48 h. In addition, ECMO use and bacteremia predict unsuccessful weaning in PMV patients.

Differences of respiratory mechanics in mechanical ventilation of acute respiratory distress syndrome between patients with COVID-19 and Influenza A.

BACKGROUND: Whether COVID-19-induced acute respiratory distress syndrome (ARDS) should be approached differently in terms of mechanical ventilation therapy compared to other virus-induced ARDS is debatable. Therefore, we aimed to ascertain whether the respiratory mechanical characteristics of COVID-19-induced ARDS differ from those of influenza A induced ARDS, in order to establish a rationale for mechanical ventilation therapy in COVID-19-induced ARDS. METHODS: This was a retrospective cohort study comparing patients with COVID-19-induced ARDS and influenza A induced ARDS. We included intensive care unit (ICU) patients with COVID-19 or Influenza A aged ≥ 19, who were diagnosed with ARDS according to the Berlin definition between January 2015 and July 2021. Ventilation parameters for respiratory mechanics were collected at specific times on days one, three, and seven after intubation. RESULTS: The median age of the 87 participants was 71.0 (62.0-78.0) years old, and 63.2% were male. The ratio of partial pressure of oxygen in arterial blood to the fractional of inspiratory oxygen concentration in COVID-19-induced ARDS was lower than that in influenza A induced ARDS during the initial stages of mechanical ventilation (influenza A induced ARDS 216.1 vs. COVID-19-induced ARDS 167.9, p = 0.009, day 1). The positive end expiratory pressure remained consistently higher in the COVID-19 group throughout the follow-up period (7.0 vs. 10.0, p < 0.001, day 1). COVID-19 and influenza A initially showed different directions for peak inspiratory pressure and dynamic compliance; however, after day 3, both groups exhibited similar directions. Dynamic driving pressure exhibited opposite trends between the two groups during mechanical ventilation. CONCLUSIONS: Respiratory mechanics show clear differences between COVID-19-induced ARDS and influenza A induced ARDS. Based on these findings, we can consider future treatment strategies for COVID-19-induced ARDS.

Influenza A, Influenza B, human respiratory syncytial virus and SARSCoV-2 molecular diagnostics and epidemiology in the post COVID-19 era.

BACKGROUND: The concurrent circulation of SARS-CoV-2 with other respiratory viruses is unstoppable and represents a new diagnostic reality for clinicians and clinical microbiology laboratories. Multiplexed molecular testing on automated platforms that focus on the simultaneous detection of multiple respiratory viruses in a single tube is a useful approach for current and future diagnosis of respiratory infections in the clinical setting. METHODS: Two time periods were included in the study: from February to April 2022, an early 2022 period, during the gradual lifting of COVID-19 prevention measures in the country, and from October 2022 to April 2023, the 2022/23 respiratory infections season. We analysed a total of 1,918 samples in the first period and 18,131 respiratory samples in the second period using a multiplex molecular assay for the simultaneous detection of Influenza A (Flu-A), Influenza B (Flu-B), Human Respiratory Syncytial Virus (HRSV) and SARS-CoV-2. RESULTS: The results from early 2022 showed a strong dominance of SARS-CoV-2 infections with 1,267/1,918 (66.1%) cases. Flu-A was detected in 30/1,918 (1.6%) samples, HRSV in 14/1,918 (0.7%) samples, and Flu-B in 2/1,918 (0.1%) samples. Flu-A/SARS-CoV-2 co-detections were observed in 11/1,267 (0.9%) samples, and HRSV/SARS-CoV-2 co-detection in 5/1,267 (0.4%) samples. During the 2022/23 winter respiratory season, SARS-CoV-2 was detected in 1,738/18,131 (9.6%), Flu-A in 628/18,131 (3.5%), Flu-B in 106/18,131 (0.6%), and HRSV in 505/18,131 (2.8%) samples. Interestingly, co-detections were present to a similar extent as in early 2022. CONCLUSION: The results show that the multiplex molecular approach is a valuable tool for the simultaneous laboratory diagnosis of SARS-CoV-2, Flu-A/B, and HRSV in hospitalized and outpatients. Infections with Flu-A/B, and HRSV occurred shortly after the COVID-19 control measures were lifted, so a strong reoccurrence of various respiratory infections and co-detections in the post COVID-19 period was to be expected.

Microfluidic paper-based chemiluminescence sensing platform based on functionalized CaCO3 for time-resolved multiplex detection of avian influenza virus biomarkers.

Multiplex detection can enhance diagnostic precision and improve diagnostic efficiency, providing important assistance for epidemiological investigation and epidemic prevention. There is a great need for multi-detection sensing platforms to accurately diagnose diseases. Herein, we reported a µPAD-based chemiluminescence (CL) assay for ultrasensitive multiplex detection of AIV biomarkers, based on three DNAzyme/Lum/PEI/CaCO3. Three time-resolved CL signals were sequentially generated with detection limits of 0.32, 0.34, and 0.29 pM for H1N1, H7N9, and H5N1, respectively, and with excellent selectivity against interfering DNA. The recovery test in human serum displayed satisfactory analysis capabilities for complex biological samples. The µPAD-based CL assay achieved multiplex detection within 70 s, with a high time resolution of 20 s. The proposed strategy has the advantages of low cost, high sensitivity, good selectivity, and wide time resolution, the µPAD-based CL assay has shown great potential in the early and accurate diagnosis of diseases.

Application of peripheral blood routine parameters in the diagnosis of influenza and Mycoplasma pneumoniae.

OBJECTIVES: Influenza and Mycoplasma pneumoniae infections often present concurrent and overlapping symptoms in clinical manifestations, making it crucial to accurately differentiate between the two in clinical practice. Therefore, this study aims to explore the potential of using peripheral blood routine parameters to effectively distinguish between influenza and Mycoplasma pneumoniae infections. METHODS: This study selected 209 influenza patients (IV group) and 214 Mycoplasma pneumoniae patients (MP group) from September 2023 to January 2024 at Nansha Division, the First Affiliated Hospital of Sun Yat-sen University. We conducted a routine blood-related index test on all research subjects to develop a diagnostic model. For normally distributed parameters, we used the T-test, and for non-normally distributed parameters, we used the Wilcoxon test. RESULTS: Based on an area under the curve (AUC) threshold of ≥ 0.7, we selected indices such as Lym# (lymphocyte count), Eos# (eosinophil percentage), Mon% (monocyte percentage), PLT (platelet count), HFC# (high fluorescent cell count), and PLR (platelet to lymphocyte ratio) to construct the model. Based on these indicators, we constructed a diagnostic algorithm named IV@MP using the random forest method. CONCLUSIONS: The diagnostic algorithm demonstrated excellent diagnostic performance and was validated in a new population, with an AUC of 0.845. In addition, we developed a web tool to facilitate the diagnosis of influenza and Mycoplasma pneumoniae infections. The results of this study provide an effective tool for clinical practice, enabling physicians to accurately diagnose and differentiate between influenza and Mycoplasma pneumoniae infection, thereby offering patients more precise treatment plans.

Development and validation of a rapid five-minute nucleic acid extraction method for respiratory viruses.

BACKGROUND: The rapid transmission and high pathogenicity of respiratory viruses significantly impact the health of both children and adults. Extracting and detecting their nucleic acid is crucial for disease prevention and treatment strategies. However, current extraction methods are laborious and time-consuming and show significant variations in nucleic acid content and purity among different kits, affecting detection sensitivity and efficiency. Our aim is to develop a novel method that reduces extraction time, simplifies operational steps, and ensures high-quality acquisition of respiratory viral nucleic acid. METHODS: We extracted respiratory syncytial virus (RSV) nucleic acid using reagents with different components and analyzed cycle threshold (Ct) values via quantitative real-time polymerase chain reaction (qRT-PCR) to optimize and validate the novel lysis and washing solution. The performance of this method was compared against magnetic bead, spin column, and precipitation methods for extracting nucleic acid from various respiratory viruses. The clinical utility of this method was confirmed by comparing it to the standard magnetic bead method for extracting clinical specimens of influenza A virus (IAV). RESULTS: The solution, composed of equal parts glycerin and ethanol (50% each), offers an innovative washing approach that achieved comparable efficacy to conventional methods in a single abbreviated cycle. When combined with our A Plus lysis solution, our novel five-minute nucleic acid extraction (FME) method for respiratory viruses yielded superior RNA concentrations and purity compared to traditional methods. FME, when used with a universal automatic nucleic acid extractor, demonstrated similar efficiency as various conventional methods in analyzing diverse concentrations of respiratory viruses. In detecting respiratory specimens from 525 patients suspected of IAV infection, the FME method showed an equivalent detection rate to the standard magnetic bead method, with a total coincidence rate of 95.43% and a kappa statistic of 0.901 (P < 0.001). CONCLUSIONS: The FME developed in this study enables the rapid and efficient extraction of nucleic acid from respiratory samples, laying a crucial foundation for the implementation of expedited molecular diagnosis.

Development and validation of nomogram for predicting the risk of transferring to the ICU for children with influenza.

OBJECTIVE: Development of a nomogram model for predicting the magnitude of risk of transferring hospitalized children with influenza to the ICU. METHODS: In a single-center retrospective study, 318 children with influenza who were hospitalized in our hospital from January 2018 to August 2023 were collected as study subjects. Children with influenza were randomly assigned to the training set and validation set in a ratio of 4:1. In the training set, risk factors were identified using univariate and multivariate logistic regression analyses, and a nomogram model was created on this basis. The validation set was used to evaluate the predictive power of the model. RESULTS: Multifactorial logistic regression analysis revealed six independent risk factors for transfer to the ICU in hospitalized children with influenza, including elevated peripheral white blood cell counts, elevated large platelet ratios, reduced mean platelet width, reduced complement C3, elevated serum globulin levels, and reduced total immunoglobulin M levels. Using these six metrics as predictors to construct a nomogram graphical model, the C-index was 0.970 (95% Cl: 0.953-0.988). The areas under the curve for the training and validation sets were 0.966 (95%Cl 0.947-0.985) and 0.919 (95%Cl 0.851-0.986), respectively. CONCLUSION: A nomogram for predicting the risk of transferring to the ICU for children with influenza was developed and validated, which demonstrates good calibration and clinical benefits.