Largest comparison between onset and relapses of acquired thrombotic thrombocytopenic purpura reveals severe neurological involvement and worse analytic parameters at debut.

It has been proposed that the onset of Acquired Thrombotic Thrombocytopenic Purpura (iTTP) is more severe than subsequent relapses; however, existing studies have limitations. We conducted a retrospective observational study to compare analytical and clinical severity of onset and relapse aTTP cases between 2012 and 2023. A total of 370 episodes of aTTP were analyzed, comprising 272 at initial diagnosis and 98 relapses. At onset, analytical parameters indicative of severity (low hemoglobin, low platelet count, and increased LDH) were significantly worse; patients had severe neurological symptoms (p<0.001) and ≥ 3 points in the TMA mortality score (p<0.001). In conclusion, the onset of aTTP is associated with worse analytical parameters and severe neurological involvement.

Movement-driven modelling reveals new patterns in disease transmission networks.

Interspecific interactions are highly relevant in the potential transmission of shared pathogens in multi-host systems. In recent decades, several technologies have been developed to study pathogen transmission, such as proximity loggers, GPS tracking devices and/or camera traps. Despite the diversity of methods aimed at detecting contacts, the analysis of transmission risk is often reduced to contact rates and the probability of transmission given the contact. However, the latter process is continuous over time and unique for each contact, and is influenced by the characteristics of the contact and the pathogen's relationship with both the host and the environment. Our objective was to assess whether a more comprehensive approach, using a movement-based model which assigns a unique transmission risk to each contact by decomposing transmission into contact formation, contact duration and host characteristics, could reveal disease transmission dynamics that are not detected with more traditional approaches. The model was built from GPS-collar data from two management systems in Spain where animal tuberculosis (TB) circulates: a national park with extensively reared endemic cattle, and an area with extensive free-range pigs and cattle farms. In addition, we evaluated the effect of the GPS device fix rate on the performance of the model. Different transmission dynamics were identified between both management systems. Considering the specific conditions under which each contact occurs (i.e. whether the contact is direct or indirect, its duration, the hosts characteristics, the environmental conditions, etc.) resulted in the identification of different transmission dynamics compared to using only contact rates. We found that fix intervals greater than 30 min in the GPS tracking data resulted in missed interactions, and intervals greater than 2 h may be insufficient for epidemiological purposes. Our study shows that neglecting the conditions under which each contact occurs may result in a misidentification of the real role of each species in disease transmission. This study describes a clear and repeatable framework to study pathogen transmission from GPS data and provides further insights to understand how TB is maintained in multi-host systems in Mediterranean environments.

Community-acquired Staphylococcus aureus skin and soft tissue infection risk assessment using hotspot analysis and risk maps: the case of California emergency departments.

BACKGROUND: Community-acquired Staphylococcus aureus (CA-Sa) skin and soft tissue infections (SSTIs) are historically associated with densely populated urban areas experiencing high poverty rates, intravenous drug use, and homelessness. However, the epidemiology of CA-Sa SSTIs in the United States has been poorly understood since the plateau of the Community-acquired Methicillin-resistant Staphylococcus aureus epidemic in 2010. This study examines the spatial variation of CA-Sa SSTIs in a large, geographically heterogeneous population and identifies neighborhood characteristics associated with increased infection risk. METHODS: Using a unique neighborhood boundary, California Medical Service Study Areas, a hotspot analysis, and estimates of neighborhood infection risk ratios were conducted for all CA-Sa SSTIs presented in non-Federal California emergency departments between 2016 and 2019. A Bayesian Poisson regression model evaluated the association between neighborhood-level infection risk and population structure, neighborhood poverty rates, and being a healthcare shortage area. RESULTS: Emergency departments in more rural and mountainous parts of California experienced a higher burden of CA-Sa SSTIs between 2016 and 2019. Neighborhoods with high infection rates were more likely to have a high percentage of adults living below the federal poverty level and be a designated healthcare shortage area. Measures of population structure were not associated with infection risk in California neighborhoods. CONCLUSIONS: Our results highlight a potential change in the epidemiology of CA-Sa SSTIs in California emergency departments. Future studies should investigate the CA-Sa burden in other geographies to identify whether this shift in epidemiology holds across other states and populations. Further, a more thorough evaluation of potential mechanisms for the clustering of infections seen across California neighborhoods is needed.

Vaccination and Nutritional Outcomes of Hemodialysis Patients Infected With SARS-CoV-2.

BACKGROUND: Patients on hemodialysis are particularly vulnerable to COVID-19 and may have a reduced response to vaccination because of a decreased immune response. The nutritional status before or during the infection could also impact on the clinical effectiveness of vaccination. OBJECTIVES: We aim to describe the evolution of clinical and nutritional biomarkers of hemodialysis patients infected with SARS-CoV-2 and to assess their association with vaccination status. METHODS: An observational, analytic, longitudinal, retrospective multicenter study was carried out in 82 patients on hemodialysis with SARS-CoV-2 infection. Nutritional status was assessed using the Geriatric Nutritional Risk Index (GNRI), anthropometry, and biochemical parameters. The association of the vaccine doses with clinical- and nutritional-related variables was also evaluated. RESULTS: The percentage of vaccinated patients was similar to that of nonvaccinated patients. Before infection, most of the patients were malnourished. They presented lower albumin, creatinine, and urea levels than the well-nourished patients. Significant deterioration of nutritional status after infection was evidenced considering GNRI score, dry weight, and body mass index. Albumin and creatinine also decreased significantly after infection, whereas C-reactive protein increased in the acute phase. Significant inverse correlation was found between the variation of post-pre GNRI scores and basal albumin and C-reactive protein at 7 days. In addition, we observed the opposite trend between albumin at 30 days and basal cholesterol. A negative value in the GNRI variation was associated with bilateral pneumonia, need for hospitalization, and nutritional support. Vaccinated patients presented substantially less bilateral pneumonia and hospitalization. No significant effects were observed between vaccine doses and the variation in nutritional status, although a positive correlation was detected with the albumin at 7 days and C-reactive protein before infection and the number of vaccine doses received. DISCUSSION: COVID-19 is associated with affectations in the nutritional status and biomarkers in hemodialysis patients. In this study, vaccines have shown a protective effect against the clinical consequences of COVID. However, they have shown limitations in preventing the deterioration of nutritional status after infection. The results highlight the importance of promoting the vaccination in these patients as well as incorporating nutritional assessment before, during, and after the infection.

Influence of base designs on the manufacturing accuracy of vat-polymerized diagnostic casts using two different technologies.

STATEMENT OF PROBLEM: Diagnostic casts can incorporate different base designs and be manufactured using different vat-polymerization technologies. However, the influence of the interrelation between the base design and the 3D printing technology on the casts' final accuracy remains unclear. PURPOSE: The purpose of this in vitro study was to assess the influence of different base designs of 3D printed casts on the accuracy of 2 vat-polymerization technologies. MATERIAL AND METHODS: A digital maxillary cast was obtained and used to generate 3 different base designs: solid (S group), honeycombed (HC group), and hollow (H group). The HC and H groups were subdivided based on the wall thickness of the cast design, resulting in 2 subgroups with thicknesses of 1 mm (HC1 and H1) and 2 mm (HC2 and H2) (N=100, n=10). Eleven reference cubes were added to each specimen for subsequent measurements. Specimens were manufactured by using 2 vat-polymerization 3D printers: Nextdent 5100 (ND group) and Sonic Mini 4K (SM4K group) and a resin material suitable for both 3D printers (Nextdent Model 2.0). A coordinate measuring machine quantified the linear and 3-dimensional discrepancies between the digital cast and each reference specimen. Trueness was defined as the average absolute dimensional discrepancy between the virtual cast and the specimens produced through additive manufacturing (AM), while precision was delineated as the standard deviation in dimensional discrepancies between the digital cast and the AM specimens. The data were analyzed using the Kruskal-Wallis and Mann-Whitney U pairwise comparison tests (α=.05). RESULTS: For the NextDent group the trueness ranged from 21.83 µm to 28.35 µm, and the precision ranged from 17.82 µm to 37.70 µm. For the Phrozen group, the trueness ranged from 45.15 µm to 64.51 µm, and the precision ranged from 33.51 µm to 48.92 µm. The Kruskal-Wallis test showed significant differences on the x-, y-, and z-axes and in the 3D discrepancy (all P<.001). On the x-axis, the Mann-Whitney U test showed significant differences for the Phrozen group between the H-2 and H-1 groups (P=.001), H-2 and S groups (P<.001), and HC-2 and S groups (P=.012). On the y-axis, significant differences were found in the Phrozen group between the H-2 and H-1 groups (P=.001), the H-2 and S, H-1 and HC-1, and HC-1 and S groups (P<.001), the H-1 and HC-2 groups (P=.007), and the HC-2 and S groups (P=.009). The NextDent group exhibited significant differences, particularly among the HC-1 and H-2 groups (P=.004), H-1 (P=.020), and HC-2 (P=.001) groups; and on the z-axis significant differences were found in the Phrozen group between the H-2 and H-1 and S groups and the HC-2 group and H-1 and S groups (both P<.001). In the NextDent group, significant differences were found between the H-2 and HC-2 (P=.047) and HC-1 (P=.028) groups. For the 3D discrepancy analysis, significant differences were found in the Phrozen group between the H-2 and H-1 and S groups (P<.001), the H-1 and HC-2 groups (P=.001), the S and HC-1 and HC-2 groups (P<.001), and the H-1 and HC-1 groups (P=.002). In the NextDent group, significant differences were observed between the H-2 and HC-1 groups (P=.012). CONCLUSIONS: The accuracy of digital casts depends on the manufacturing trinomial and base design of the casts. The honeycomb and hollow based designs provided the highest accuracy in the NextDent and Phrozen groups respectively for the material polymer tested. All specimens fell in the clinically acceptable range.

Modified Oblique Lobenhoffer (MOL) approach for posterolateral and posteromedial column access in tibial plateau fractures: a detailed cadaveric anatomical study.

BACKGROUND: Tibial plateau fractures involving posteromedial (PM) and posterolateral (PL) columns are complex injuries that require an appropriate approach. The management of the PL column in these cases can be controversial, and limitations using deep posteromedial interval approaches have been referenced. In this paper, a modification of the Lobenhoffer approach, designed to optimize the access to the PL column, is described in detail. The aim of this study was to assess the feasibility of this approach in a cadaveric anatomical study. MATERIALS AND METHODS: In total, five fresh-frozen cadaveric specimens were used for detailed anatomical study surrounding the approach. Relationships with cutaneous and deep neurovascular structures were evaluated. The exposure area of the PL and PM columns using this approach was assessed. RESULTS: The cadaveric study showed safe and adequate exposure. Oblique skin and fascia incision just medial to the posterior midline was safe to protect the medial sural cutaneous nerve and the small saphenous vein. Elevation of the popliteus and tibialis posterior muscles offered safe protection of the anterior tibial artery and popliteal neurovascular bundle during retractor placement. Adequate full proximal exposure of the PM and PL columns, including the posterolateral lateral (PLL) and posterolateral central (PLC) segments, was obtained in all specimens. CONCLUSIONS: The Modified Oblique Lobenhoffer (MOL) approach can be a feasible option to access PL and PM columns in tibial plateau fractures. LEVEL OF EVIDENCE: IV.

Monitoring Temporal Changes in SARS-CoV-2 Spike Antibody Levels and Variant-Specific Risk for Infection, Dominican Republic, March 2021-August 2022.

To assess changes in SARS-CoV-2 spike binding antibody prevalence in the Dominican Republic and implications for immunologic protection against variants of concern, we prospectively enrolled 2,300 patients with undifferentiated febrile illnesses in a study during March 2021-August 2022. We tested serum samples for spike antibodies and tested nasopharyngeal samples for acute SARS-CoV-2 infection using a reverse transcription PCR nucleic acid amplification test. Geometric mean spike antibody titers increased from 6.6 (95% CI 5.1-8.7) binding antibody units (BAU)/mL during March-June 2021 to 1,332 (95% CI 1,055-1,682) BAU/mL during May-August 2022. Multivariable binomial odds ratios for acute infection were 0.55 (95% CI 0.40-0.74), 0.38 (95% CI 0.27-0.55), and 0.27 (95% CI 0.18-0.40) for the second, third, and fourth versus the first anti-spike quartile; findings were similar by viral strain. Combining serologic and virologic screening might enable monitoring of discrete population immunologic markers and their implications for emergent variant transmission.

"Super-Spreaders" and Person-to-Person Transmission of Andes Virus in Argentina.

BACKGROUND: From November 2018 through February 2019, person-to-person transmission of Andes virus (ANDV) hantavirus pulmonary syndrome occurred in Chubut Province, Argentina, and resulted in 34 confirmed infections and 11 deaths. Understanding the genomic, epidemiologic, and clinical characteristics of person-to-person transmission of ANDV is crucial to designing effective interventions. METHODS: Clinical and epidemiologic information was obtained by means of patient report and from public health centers. Serologic testing, contact-tracing, and next-generation sequencing were used to identify ANDV infection as the cause of this outbreak of hantavirus pulmonary syndrome and to reconstruct person-to-person transmission events. RESULTS: After a single introduction of ANDV from a rodent reservoir into the human population, transmission was driven by 3 symptomatic persons who attended crowded social events. After 18 cases were confirmed, public health officials enforced isolation of persons with confirmed cases and self-quarantine of possible contacts; these measures most likely curtailed further spread. The median reproductive number (the number of secondary cases caused by an infected person during the infectious period) was 2.12 before the control measures were enforced and decreased to 0.96 after the measures were implemented. Full genome sequencing of the ANDV strain involved in this outbreak was performed with specimens from 27 patients and showed that the strain that was present (Epuyén/18-19) was similar to the causative strain (Epilink/96) in the first known person-to-person transmission of hantavirus pulmonary syndrome caused by ANDV, which occurred in El Bolsón, Argentina, in 1996. Clinical investigations involving patients with ANDV hantavirus pulmonary syndrome in this outbreak revealed that patients with a high viral load and liver injury were more likely than other patients to spread infection. Disease severity, genomic diversity, age, and time spent in the hospital had no clear association with secondary transmission. CONCLUSIONS: Among patients with ANDV hantavirus pulmonary syndrome, high viral titers in combination with attendance at massive social gatherings or extensive contact among persons were associated with a higher likelihood of transmission. (Funded by the Ministerio de Salud y Desarrollo Social de la Nación Argentina and others.).

Evaluation of the application of sequence data to the identification of outbreaks of disease using anomaly detection methods.

Anomaly detection methods have a great potential to assist the detection of diseases in animal production systems. We used sequence data of Porcine Reproductive and Respiratory Syndrome (PRRS) to define the emergence of new strains at the farm level. We evaluated the performance of 24 anomaly detection methods based on machine learning, regression, time series techniques and control charts to identify outbreaks in time series of new strains and compared the best methods using different time series: PCR positives, PCR requests and laboratory requests. We introduced synthetic outbreaks of different size and calculated the probability of detection of outbreaks (POD), sensitivity (Se), probability of detection of outbreaks in the first week of appearance (POD1w) and background alarm rate (BAR). The use of time series of new strains from sequence data outperformed the other types of data but POD, Se, POD1w were only high when outbreaks were large. The methods based on Long Short-Term Memory (LSTM) and Bayesian approaches presented the best performance. Using anomaly detection methods with sequence data may help to identify the emergency of cases in multiple farms, but more work is required to improve the detection with time series of high variability. Our results suggest a promising application of sequence data for early detection of diseases at a production system level. This may provide a simple way to extract additional value from routine laboratory analysis. Next steps should include validation of this approach in different settings and with different diseases.

Data Augmentation Effects on Highly Imbalanced EEG Datasets for Automatic Detection of Photoparoxysmal Responses.

Photosensitivity is a neurological disorder in which a person's brain produces epileptic discharges, known as Photoparoxysmal Responses (PPRs), when it receives certain visual stimuli. The current standardized diagnosis process used in hospitals consists of submitting the subject to the Intermittent Photic Stimulation process and attempting to trigger these phenomena. The brain activity is measured by an Electroencephalogram (EEG), and the clinical specialists manually look for the PPRs that were provoked during the session. Due to the nature of this disorder, long EEG recordings may contain very few PPR segments, meaning that a highly imbalanced dataset is available. To tackle this problem, this research focused on applying Data Augmentation (DA) to create synthetic PPR segments from the real ones, improving the balance of the dataset and, thus, the global performance of the Machine Learning techniques applied for automatic PPR detection. K-Nearest Neighbors and a One-Hidden-Dense-Layer Neural Network were employed to evaluate the performance of this DA stage. The results showed that DA is able to improve the models, making them more robust and more able to generalize. A comparison with the results obtained from a previous experiment also showed a performance improvement of around 20% for the Accuracy and Specificity measurements without Sensitivity suffering any losses. This project is currently being carried out with subjects at Burgos University Hospital, Spain.

Mycobacterium tuberculosis Cell Wall Antigens Induce the Formation of Immune Complexes and the Development of Vasculitis in an Experimental Murine Model.

Tuberculosis (TB) of the central nervous system (CNS) presents high mortality due to brain damage and inflammation events. The formation and deposition of immune complexes (ICs) in the brain microvasculature during Mycobacterium tuberculosis (Mtb) infection are crucial for its pathobiology. The relevance of ICs to Mtb antigens in the pathogenesis of CNS-TB has been poorly explored. Here, we aimed to establish a murine experimental model of ICs-mediated brain vasculitis induced by cell wall antigens of Mtb. We administered a cell wall extract of the prototype pathogenic Mtb strain H37Rv to male BALB/c mice by subcutaneous and intravenous routes. Serum concentration and deposition of ICs onto blood vessels were determined by polyethylene glycol precipitation, ELISA, and immunofluorescence. Histopathological changes in the brain, lung, spleen, liver, and kidney were evaluated by hematoxylin and eosin staining. Our results evidenced that vasculitis developed in the studied tissues. High serum levels of ICs and vascular deposition were evident in the brain, lung, and kidneys early after the last cell wall antigen administration. Cell wall Mtb antigens induce strong type III hypersensitivity reactions and the development of systemic vasculitis with brain vascular changes and meningitis, supporting a role for ICs in the pathogenesis of TB.

[Legionnaires' disease in Argentina: Evolution of the laboratory diagnostic strategy]. / Enfermedad del legionario en Argentina: evolución de la estrategia diagnóstica en el laboratorio.

Legionnaires' disease (LD) is severe acute pneumonia that occurs in sporadic or epidemic form, and generally requires hospitalization. The objective of this work was to describe the experience in the LD laboratory diagnostic approach in Argentina during the period 2016-2021. The laboratory analyzed 168 clinical specimens from 93 cases of suspected LD pneumonia. Laboratory tests included the detection of the soluble antigen of Legionella pneumophila serogroup 1 in urine sample, detection of DNA of Legionella spp. in lower respiratory secretions by conventional and commercial molecular methods and isolation in selective medium. LD was confirmed in 12 patients. The urinary antigen allowed the diagnosis for 8 patients. L. pneumophila was isolated from the respiratory material of 6 patients suffering from health care-associated pneumonia, who had been previously diagnosed using the commercial molecular method. Fifty percent of these cases did not show detectable urinary antigen. A single patient did not shows neither detectable antigenuria nor isolation of Legionella from the respiratory sample and was diagnosed as a confirmed case of LD by the detection of DNA of Legionella spp. by PCR directly from the respiratory secretion and the epidemiological link with another case of confirmed LD by culture. Urinary antigen detection is the first-line diagnostic test. However, the incorporation of complementary molecular methods has proved to avoid false negatives and contributed to a better understanding of the true incidence of the disease.

Use of Project ECHO in Response to COVID-19 in Countries Supported by US President's Emergency Plan for AIDS Relief.

The US Centers for Disease Control and Prevention, with funding from the US President's Plan for Emergency Relief, implements a virtual model for clinical mentorship, Project Extension for Community Healthcare Outcomes (ECHO), worldwide to connect multidisciplinary teams of healthcare workers (HCWs) with specialists to build capacity to respond to the HIV epidemic. The emergence of and quick evolution of the COVID-19 pandemic created the need and opportunity for the use of the Project ECHO model to help address the knowledge requirements of HCW responding to COVID-19 while maintaining HCW safety through social distancing. We describe the implementation experiences of Project ECHO in 5 Centers for Disease Control and Prevention programs as part of their COVID-19 response, in which existing platforms were used to rapidly disseminate relevant, up-to-date COVID-19-related clinical information to a large, multidisciplinary audience of stakeholders within their healthcare systems.

Molecular Profiling of Tumor Tissue in Mexican Patients with Colorectal Cancer.

Colorectal cancer is a heterogeneous disease with multiple genomic changes that influence the clinical management of patients; thus, the search for new molecular targets remains necessary. The aim of this study was to identify genetic variants in tumor tissues from Mexican patients with colorectal cancer, using massive parallel sequencing. A total of 4813 genes were analyzed in tumoral DNA from colorectal cancer patients, using the TruSight One Sequencing panel. From these, 192 variants with clinical associations were found distributed in 168 different genes, of which 46 variants had not been previous reported in the literature or databases, although genes harboring those variants had already been described in colorectal cancer. Enrichment analysis of the affected genes was performed using Reactome software; pathway over-representation showed significance for disease, signal transduction, and immune system subsets in all patients, while exclusive subsets such as DNA repair, autophagy, and RNA metabolism were also found. Those characteristics, whether individual or shared, could give tumors specific capabilities for survival, aggressiveness, or response to treatment. Our results can be useful for future investigations targeting specific characteristics of tumors in colorectal cancer patients. The identification of exclusive or common pathways in colorectal cancer patients could be important for better diagnosis and personalized cancer treatment.

Fatty acid oxidation of alternatively activated macrophages prevents foam cell formation, but Mycobacterium tuberculosis counteracts this process via HIF-1α activation.

The ability of Mycobacterium tuberculosis (Mtb) to persist inside host cells relies on metabolic adaptation, like the accumulation of lipid bodies (LBs) in the so-called foamy macrophages (FM), which are favorable to Mtb. The activation state of macrophages is tightly associated to different metabolic pathways, such as lipid metabolism, but whether differentiation towards FM differs between the macrophage activation profiles remains unclear. Here, we aimed to elucidate whether distinct macrophage activation states exposed to a tuberculosis-associated microenvironment or directly infected with Mtb can form FM. We showed that the triggering of signal transducer and activator of transcription 6 (STAT6) in interleukin (IL)-4-activated human macrophages (M(IL-4)) prevents FM formation induced by pleural effusion from patients with tuberculosis. In these cells, LBs are disrupted by lipolysis, and the released fatty acids enter the ß-oxidation (FAO) pathway fueling the generation of ATP in mitochondria. Accordingly, murine alveolar macrophages, which exhibit a predominant FAO metabolism, are less prone to become FM than bone marrow derived-macrophages. Interestingly, direct infection of M(IL-4) macrophages with Mtb results in the establishment of aerobic glycolytic pathway and FM formation, which could be prevented by FAO activation or inhibition of the hypoxia-inducible factor 1-alpha (HIF-1α)-induced glycolytic pathway. In conclusion, our results demonstrate that Mtb has a remarkable capacity to induce FM formation through the rewiring of metabolic pathways in human macrophages, including the STAT6-driven alternatively activated program. This study provides key insights into macrophage metabolism and pathogen subversion strategies.

The value of metabolic parameters and textural analysis in predicting prognosis in locally advanced cervical cancer treated with chemoradiotherapy.

OBJECTIVE: The aim of the study was to assess the impact of clinical and metabolic parameters derived from 18F-FDG PET/CT (positron emission tomography-computed tomography) in patients with locally advanced cervical cancer (LACC) on prognosis. METHODS: Patients with LACC of stage IB2-IVA treated by primary radiochemotherapy followed by brachytherapy were enrolled in this retrospective study. Indexes derived from standardized uptake value (SUV), metabolic tumor volume (MTV), total lesion glycolysis (TLG), and textural features of the primary tumor were measured for each patient. Overall survival (OS) and recurrence-free survival (RFS) rates were calculated according to Kaplan-Meier and survival curves were compared using the log-rank test. Uni- and multivariate analyses were performed using the Cox regression model. RESULTS: A total of 116 patients were included. Median follow-up was 58 months (range: 1-129). A total of 36 (31%) patients died. Five-year OS and RFS rates were 69 and 60%, respectively. Univariate analyses indicated that FIGO stage, the presence of hydronephrosis, high CYFRA 21.1 levels, and textural features had a significant impact on OS and RFS. MTV as well as SCC-Ag concentration were also significantly associated with OS. On multivariate analysis, the presence of hydronephrosis, CYFRA 21.1, and sphericity were independent prognostics factors for OS and RFS. Also, SCC-Ag level, MTV, and GLZLM (gray-level zone length matrix) ZLNU (zone length non-uniformity) were significantly associated with OS. CONCLUSION: Classical prognostic factors and tumor heterogeneity on pretreatment PET/CT were significantly associated with prognosis in patients with LACC.

Placebo Response and Its Predictors in Attention Deficit Hyperactivity Disorder: A Meta-Analysis and Comparison of Meta-Regression and MetaForest.

BACKGROUND: High placebo response in attention deficit hyperactivity disorder (ADHD) can reduce medication-placebo differences, jeopardizing the development of new medicines. This research aims to (1) determine placebo response in ADHD, (2) compare the accuracy of meta-regression and MetaForest in predicting placebo response, and (3) determine the covariates associated with placebo response. METHODS: A systematic review with meta-analysis of randomized, placebo-controlled clinical trial investigating pharmacological interventions for ADHD was performed. Placebo response was defined as the change from baseline in ADHD symptom severity assessed according to the 18-item, clinician-rated, DSM-based rating scale. The effect of study design-, intervention-, and patient-related covariates in predicting placebo response was studied by means of meta-regression and MetaForest. RESULTS: Ninety-four studies including 6614 patients randomized to placebo were analyzed. Overall, placebo response was -8.9 points, representing a 23.1% reduction in the severity of ADHD symptoms. Cross-validated accuracy metrics for meta-regression were R2 = 0.0012 and root mean squared error = 3.3219 for meta-regression and 0.0382 and 3.2599 for MetaForest. Placebo response among ADHD patients increased by 63% between 2001 and 2020 and was larger in the United States than in other regions of the world. CONCLUSIONS: Strong placebo response was found in ADHD patients. Both meta-regression and MetaForest showed poor performance in predicting placebo response. ADHD symptom improvement with placebo has markedly increased over the last 2 decades and is greater in the United States than the rest of the world.

Burden of Diarrhoeagenic Escherichia coli in Santa Rosa, Guatemala in active health-services surveillance during 2008-2009 and 2014-2015.

OBJECTIVE: To describe the epidemiology of laboratory-confirmed Diarrhoeagenic Escherichia coli (DEC) cases from active facility-based surveillance in Guatemala. METHODS: We collected clinical and risk factor data on enrolled patients (aged 0-52 years) with acute diarrhoea at government healthcare facilities (1 hospital and 6 clinics) in Santa Rosa, Guatemala, during 2008-2009 and 2014-2015. Stool samples were analysed, E. coli identified through culture and biochemical tests, PCR amplification of genes encoding pathotype-specific virulence factors identified specific DEC pathotypes. Healthcare-seeking adjusted incidence rates were calculated. RESULTS: A total of 3041 diarrhoea cases were captured by surveillance (647 hospitalisations (H), 2394 clinic visits (CV)); general E. coli prevalence was 17.9%. DEC pathotypes were identified in 19% (n = 95/497) and 21% (n = 450/2113) in diarrhoea H and CV, respectively. Enteropathogenic E. coli (EPEC) was most frequently isolated (8.2% (n = 41) in diarrhoea H, 12.0% (n = 255) in diarrhoea CV), followed by ETEC (6.8% (n = 34) in H, 6% (n = 128) in CV) and STEC (0.6% (n = 3) in H, 0.6% (n = 13) in CV). We did not find evidence of a difference in severity between DEC and non-DEC diarrhoea. Incidence of DEC clinic visits and hospitalisations was 648.0 and 29.3, respectively, per 10,000 persons aged ≤5 years and 36.8 and 0.4, respectively, per 10,000 persons aged >5 years. CONCLUSIONS: DEC pathotypes, especially EPEC and ETEC, were detected frequently from patients presenting with diarrhoeal illness in Santa Rosa, Guatemala. Our findings suggest that preventive interventions should be prioritised for young children.

The meaning of significant mean group differences for biomarker discovery.

Over the past decade, biomarker discovery has become a key goal in psychiatry to aid in the more reliable diagnosis and prognosis of heterogeneous psychiatric conditions and the development of tailored therapies. Nevertheless, the prevailing statistical approach is still the mean group comparison between "cases" and "controls," which tends to ignore within-group variability. In this educational article, we used empirical data simulations to investigate how effect size, sample size, and the shape of distributions impact the interpretation of mean group differences for biomarker discovery. We then applied these statistical criteria to evaluate biomarker discovery in one area of psychiatric research-autism research. Across the most influential areas of autism research, effect size estimates ranged from small (d = 0.21, anatomical structure) to medium (d = 0.36 electrophysiology, d = 0.5, eye-tracking) to large (d = 1.1 theory of mind). We show that in normal distributions, this translates to approximately 45% to 63% of cases performing within 1 standard deviation (SD) of the typical range, i.e., they do not have a deficit/atypicality in a statistical sense. For a measure to have diagnostic utility as defined by 80% sensitivity and 80% specificity, Cohen's d of 1.66 is required, with still 40% of cases falling within 1 SD. However, in both normal and nonnormal distributions, 1 (skewness) or 2 (platykurtic, bimodal) biologically plausible subgroups may exist despite small or even nonsignificant mean group differences. This conclusion drastically contrasts the way mean group differences are frequently reported. Over 95% of studies omitted the "on average" when summarising their findings in their abstracts ("autistic people have deficits in X"), which can be misleading as it implies that the group-level difference applies to all individuals in that group. We outline practical approaches and steps for researchers to explore mean group comparisons for the discovery of stratification biomarkers.

Testing and vaccination to reduce the impact of COVID-19 in nursing homes: an agent-based approach.

BACKGROUND: Efforts to protect residents in nursing homes involve non-pharmaceutical interventions, testing, and vaccine. We sought to quantify the effect of testing and vaccine strategies on the attack rate, length of the epidemic, and hospitalization. METHODS: We developed an agent-based model to simulate the dynamics of SARS-CoV-2 transmission among resident and staff agents in a nursing home. Interactions between 172 residents and 170 staff based on data from a nursing home in Los Angeles, CA. Scenarios were simulated assuming different levels of non-pharmaceutical interventions, testing frequencies, and vaccine efficacy to reduce transmission. RESULTS: Under the hypothetical scenario of widespread SARS-CoV-2 in the community, 3-day testing frequency minimized the attack rate and the time to eradicate an outbreak. Prioritization of vaccine among staff or staff and residents minimized the cumulative number of infections and hospitalization, particularly in the scenario of high probability of an introduction. Reducing the probability of a viral introduction eased the demand on testing and vaccination rate to decrease infections and hospitalizations. CONCLUSIONS: Improving frequency of testing from 7-days to 3-days minimized the number of infections and hospitalizations, despite widespread community transmission. Vaccine prioritization of staff provides the best protection strategy when the risk of viral introduction is high.