A culture-free biphasic approach for sensitive and rapid detection of pathogens in dried whole-blood matrix.

Blood stream infections (BSIs) cause high mortality, and their rapid detection remains a significant diagnostic challenge. Timely and informed administration of antibiotics can significantly improve patient outcomes. However, blood culture, which takes up to 5 d for a negative result, followed by PCR remains the gold standard in diagnosing BSI. Here, we introduce a new approach to blood-based diagnostics where large blood volumes can be rapidly dried, resulting in inactivation of the inhibitory components in blood. Further thermal treatments then generate a physical microscale and nanoscale fluidic network inside the dried matrix to allow access to target nucleic acid. The amplification enzymes and primers initiate the reaction within the dried blood matrix through these networks, precluding any need for conventional nucleic acid purification. High heme background is confined to the solid phase, while amplicons are enriched in the clear supernatant (liquid phase), giving fluorescence change comparable to purified DNA reactions. We demonstrate single-molecule sensitivity using a loop-mediated isothermal amplification reaction in our platform and detect a broad spectrum of pathogens, including gram-positive methicillin-resistant and methicillin-susceptible Staphylococcus aureus bacteria, gram-negative Escherichia coli bacteria, and Candida albicans (fungus) from whole blood with a limit of detection (LOD) of 1.2 colony-forming units (CFU)/mL from 0.8 to 1 mL of starting blood volume. We validated our assay using 63 clinical samples (100% sensitivity and specificity) and significantly reduced sample-to-result time from over 20 h to <2.5 h. The reduction in instrumentation complexity and costs compared to blood culture and alternate molecular diagnostic platforms can have broad applications in healthcare systems in developed world and resource-limited settings.

Spontaneous Loculated Bilateral Hydropneumothoraces in a Patient with Recent COVID-19 Infection.

A 53-year-old male presented to the emergency room with chest pain, shortness of breath, and back pain. He had recently recovered from COVID-19 infection and returned home on room air. Chest imaging showed bilateral hydropneumothoraces that were not present on the imaging performed during his prior admission three weeks ago. The patient was treated with bilateral chest tube drainage and oxygen support and responded well to treatment. This case represents a unique occurrence of spontaneous loculated bilateral hydropneumothoraces in the context of recent clinical recovery from COVID-19 infection requiring inpatient treatment. This case highlights the importance of an awareness of a potential sequela of COVID-19 that may occur even after presumed clinical recovery.

Microfluidic point-of-care device for detection of early strains and B.1.1.7 variant of SARS-CoV-2 virus.

Since the beginning of the COVID-19 pandemic, several mutations of the SARS-CoV-2 virus have emerged. Current gold standard detection methods for detecting the virus and its variants are based on PCR-based diagnostics using complex laboratory protocols and time-consuming steps, such as RNA isolation and purification, and thermal cycling. These steps limit the translation of technology to the point-of-care and limit accessibility to under-resourced regions. While PCR-based assays currently offer the possibility of multiplexed gene detection, and commercial products of single gene PCR and isothermal LAMP at point-of-care are also now available, reports of isothermal assays at the point-of-care with detection of multiple genes are lacking. Here, we present a microfluidic assay and device to detect and differentiate the Alpha variant (B.1.1.7) from the SARS-CoV-2 virus early strains in saliva samples. The detection assay, which is based on isothermal RT-LAMP amplification, takes advantage of the S-gene target failure (SGTF) to differentiate the Alpha variant from the SARS-CoV-2 virus early strains using a binary detection system based on spatial separation of the primers specific to the N- and S-genes. We use additively manufactured plastic cartridges in a low-cost optical reader system to successfully detect the SARS-CoV-2 virus from saliva samples (positive amplification is detected with concentration ≥10 copies per µL) within 30 min. We demonstrate that our platform can discriminate the B.1.1.7 variant (USA/CA_CDC_5574/2020 isolate) from SARS-CoV-2 negative samples, but also from the SARS-CoV-2 USA-WA1/2020 isolate. The reliability of the developed point-of-care device was confirmed by testing 38 clinical saliva samples, including 20 samples positive for Alpha variant (sensitivity > 90%, specificity = 100%). This study highlights the current relevance of binary-based testing, as the new Omicron variant also exhibits S-gene target failure and could be tested by adapting the approach presented here.

Reverse Transcription Loop-Mediated Isothermal Amplification Assay for Ultrasensitive Detection of SARS-CoV-2 in Saliva and Viral Transport Medium Clinical Samples.

The COVID-19 pandemic has underscored the shortcomings in the deployment of state-of-the-art diagnostics platforms. Although several polymerase chain reaction (PCR)-based techniques have been rapidly developed to meet the growing testing needs, such techniques often need samples collected through a swab, the use of RNA extraction kits, and expensive thermocyclers in order to successfully perform the test. Isothermal amplification-based approaches have also been recently demonstrated for rapid severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) detection by minimizing sample preparation while also reducing the instrumentation and reaction complexity. In addition, there are limited reports of saliva as the sample source, and some of these indicate inferior sensitivity when comparing reverse transcription loop-mediated isothermal amplification (RT-LAMP) with PCR-based techniques. In this paper, we demonstrate an improved sensitivity assay from saliva using a two-step RT-LAMP assay, where a short 10 min RT step is performed with only B3 and backward inner primers before the final reaction. We show that while the one-step RT-LAMP demonstrates satisfactory results, the optimized two-step approach allows detection of only few molecules per reaction and performs significantly better than the one-step RT-LAMP and conventional two-step RT-LAMP approaches with all primers included in the RT step. We show control measurements with RT-PCR, and importantly, we demonstrate RNA extraction-free RT-LAMP-based assays for detection of SARS-CoV-2 from viral transport media and saliva clinical samples.

COVID-19 Point-of-Care Diagnostics: Present and Future.

Point-of-care (POC) detection technologies that enable decentralized, rapid, sensitive, low-cost diagnostics of COVID-19 infection are urgently needed around the world. With many technologies approved for commercialization in the past 10 months, the field of COVID-19 POC diagnostics is rapidly evolving. In this Perspective, we analyze the current state of POC technologies for the diagnosis and monitoring of COVID-19 infection and discuss future challenges in COVID-19 diagnostics. As the COVID-19 pandemic becomes endemic, the advances gained during this past year will likely also be utilized for future prediction of emerging outbreaks and pandemics.

Diagnostic and prognostic capabilities of a biomarker and EMR-based machine learning algorithm for sepsis.

Sepsis is a major cause of mortality among hospitalized patients worldwide. Shorter time to administration of broad-spectrum antibiotics is associated with improved outcomes, but early recognition of sepsis remains a major challenge. In a two-center cohort study with prospective sample collection from 1400 adult patients in emergency departments suspected of sepsis, we sought to determine the diagnostic and prognostic capabilities of a machine-learning algorithm based on clinical data and a set of uncommonly measured biomarkers. Specifically, we demonstrate that a machine-learning model developed using this dataset outputs a score with not only diagnostic capability but also prognostic power with respect to hospital length of stay (LOS), 30-day mortality, and 3-day inpatient re-admission both in our entire testing cohort and various subpopulations. The area under the receiver operating curve (AUROC) for diagnosis of sepsis was 0.83. Predicted risk scores for patients with septic shock were higher compared with patients with sepsis but without shock (p < 0.0001). Scores for patients with infection and organ dysfunction were higher compared with those without either condition (p < 0.0001). Stratification based on predicted scores of the patients into low, medium, and high-risk groups showed significant differences in LOS (p < 0.0001), 30-day mortality (p < 0.0001), and 30-day inpatient readmission (p < 0.0001). In conclusion, a machine-learning algorithm based on electronic medical record (EMR) data and three nonroutinely measured biomarkers demonstrated good diagnostic and prognostic capability at the time of initial blood culture.

Publisher Correction: Combining Biomarkers with EMR Data to Identify Patients in Different Phases of Sepsis.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Renal Cell Carcinoma Presenting as Pleural Effusion.

Renal cell carcinoma is well-known for its propensity to present in unusual ways, and renal cell carcinoma presenting as pleural effusion is extremely rare. Pleural effusion secondary to renal cell carcinoma constitutes only about 1% to 2% of all malignant pleural effusions. We report the case of a 34-year-old man with no significant past medical or surgical history who presented in the Emergency Department with dyspnea. Chest x-ray demonstrated right-sided pleural effusion; computed tomography (CT) reported right-sided effusion in the pleura with suspicious mass in the upper border of left kidney. CT-guided pleural tap was performed and cytology was positive for vimentin and common acute lymphocytic leukemia antigen (CD10), leading to the diagnosis of primary renal cell carcinoma presenting as unilateral pleural effusion. While lungs are the common site of metastasis, the presentation of renal cell carcinoma as pleural effusion or pleural metastasis without lung involvement is rare.

Combining Biomarkers with EMR Data to Identify Patients in Different Phases of Sepsis.

Sepsis is a leading cause of death and is the most expensive condition to treat in U.S. hospitals. Despite targeted efforts to automate earlier detection of sepsis, current techniques rely exclusively on using either standard clinical data or novel biomarker measurements. In this study, we apply machine learning techniques to assess the predictive power of combining multiple biomarker measurements from a single blood sample with electronic medical record data (EMR) for the identification of patients in the early to peak phase of sepsis in a large community hospital setting. Combining biomarkers and EMR data achieved an area under the receiver operating characteristic (ROC) curve (AUC) of 0.81, while EMR data alone achieved an AUC of 0.75. Furthermore, a single measurement of six biomarkers (IL-6, nCD64, IL-1ra, PCT, MCP1, and G-CSF) yielded the same predictive power as collecting an additional 16 hours of EMR data(AUC of 0.80), suggesting that the biomarkers may be useful for identifying these patients earlier. Ultimately, supervised learning using a subset of biomarker and EMR data as features may be capable of identifying patients in the early to peak phase of sepsis in a diverse population and may provide a tool for more timely identification and intervention.

Gluteal compartment syndrome: a case report.

INTRODUCTION: Gluteal compartment syndrome is a rare, often unrecognized syndrome that may manifest as renal failure, sepsis, and death. Delay in diagnosis can result in significant morbidity and possible mortality. We report a case of occult gluteal compartment syndrome causing unresolving rhabdomyolysis. CASE PRESENTATION: A 50-year-old Caucasian American man with history of chronic obstructive pulmonary disease was admitted status post fall and loss of consciousness for an unknown duration. Initial work-up revealed severe rhabdomyolysis, opioid abuse and acute renal failure. Inspite of three days of intensive therapy his condition did not improve and his renal failure worsened. On improvement of his condition three days later, he indicated some discomfort in his right hip. Physical examination was significant for swelling of the right gluteal region, which was tender and firm on palpation. A non-contrast CT scan showed evidence of gluteal compartment syndrome and emergent surgery resulted in significant improvement of his condition. CONCLUSION: Gluteal compartment syndrome most commonly occurs in individuals with altered mental status due to drugs or alcohol, who remain in one position for an extended period of time. This prolonged compression leads to muscle damage, edema, and a full-blown compartment syndrome. Due to its anatomic location and rarity, diagnosis is often missed or delayed, resulting in significant morbidity and possible mortality. The mainstay of treatment is fasciotomy.