Curative-intent radiotherapy (RT) or chemoradiation (CRT) of squamous cell carcinoma of the head and neck (HNSCC) produces high survival rates, but is associated with substantial toxicity. However, ...there are no commonly accepted quality metrics for early mortality in radiation oncology. To assess the applicability of early mortality as a clinical quality indicator, this study investigated the temporal distribution, risk factors and trends of 90- and 180-day overall and non-cancer mortality in a nationwide cohort of HNSCC patients treated with RT/CRT.
Information on all HNSCC patients treated with curative-intent RT/CRT in Denmark between 2000 and 2017 was obtained from the national Danish Head and Neck Cancer Group clinical database. Deaths in patients with residual or recurrent disease after RT/CRT were classified as cancer-related. Possible risk factors were investigated using logistic regression analysis.
Data from 11 419 patients were extracted. In total, 90- and 180-day mortality risks were 3.1% and 7.1%, respectively. There was a uniform temporal distribution of 180-day mortality. In multivariable analysis, increasing age, stage, performance status, earlier treatment year and hypopharyngeal cancer were significantly associated with an increased risk (P < 0.05). Risk factor estimates were comparable for 90- versus 180-day mortality as well as for overall versus non-cancer mortality. Between 2000 and 2017 there was a significant decrease in 180-day mortality, which was driven by a reduction in cancer-related events.
The distribution of 180-day overall and non-cancer mortality did not indicate a well-defined early high-risk period. Moreover, risk factor estimates were highly similar across risk periods and groups. Taken together, our findings question the applicability of early mortality as a standard metric for treatment-associated toxicity.
•Early mortality after radical radiotherapy was investigated in a national head–neck cancer cohor.t•90- and 180-day mortality risks were 3.1% and 7.1%, respectively•Early mortality decreased between 2000 and 2017.•There were no indications of an early high-risk period after treatment initiation.•Introducing early mortality as a clinical quality indicator is questionable
A prospective, multicentre, population-based surveillance programme for Candida bloodstream infections was implemented in five metropolitan areas of Spain to determine its incidence and the ...prevalence of antifungal resistance, and to identify predictors of death. Between May 2010 and April 2011, Candida isolates were centralized to a reference laboratory for species identification by DNA sequencing and for susceptibility testing by EUCAST reference procedure. Prognostic factors associated with early (0–7 days) and late (8–30 days) death were analysed using logistic regression modelling. We detected 773 episodes: annual incidence of 8.1 cases/100 000 inhabitants, 0.89/1000 admissions and 1.36/10 000 patient-days. Highest incidence was found in infants younger than 1 year (96.4/100 000 inhabitants). Candida albicans was the predominant species (45.4%), followed by Candida parapsilosis (24.9%), Candida glabrata (13.4%) and Candida tropicalis (7.7%). Overall, 79% of Candida isolates were susceptible to fluconazole. Cumulative mortality at 7 and 30 days after the first episode of candidaemia was 12.8% and 30.6%, respectively. Multivariate analysis showed that therapeutic measures within the first 48 h may improve early mortality: antifungal treatment (OR 0.51, 95% CI 0.27–0.95) and central venous catheter removal (OR 0.43, 95% CI 0.21–0.87). Predictors of late death included host factors (e.g. patients' comorbid status and signs of organ dysfunction), primary source (OR 1.63, 95% CI 1.03–2.61), and severe sepsis or septic shock (OR 1.77, 95% CI 1.05–3.00). In Spain, the proportion of Candida isolates non-susceptible to fluconazole is higher than in previous reports. Early mortality may be improved with strict adherence to guidelines.
ABSTRACT
Background
Emergency departments (ED) are becoming increasingly overwhelmed, increasing poor outcomes. Triage scores aim to optimize the waiting time and prioritize the resource usage. ...Artificial intelligence (AI) algorithms offer advantages for creating predictive clinical applications.
Objective
Evaluate a state-of-the-art machine learning model for predicting mortality at the triage level and, by validating this automatic tool, improve the categorization of patients in the ED.
Design
An institutional review board (IRB) approval was granted for this retrospective study. Information of consecutive adult patients (ages 18–100) admitted at the emergency department (ED) of one hospital were retrieved (January 1, 2012–December 31, 2018). Features included the following: demographics, admission date, arrival mode, referral code, chief complaint, previous ED visits, previous hospitalizations, comorbidities, home medications, vital signs, and Emergency Severity Index (ESI). The following outcomes were evaluated:
early mortality
(up to 2 days post ED registration) and
short-term mortality
(2–30 days post ED registration). A gradient boosting model was trained on data from years 2012–2017 and examined on data from the final year (2018). The area under the curve (AUC) for mortality prediction was used as an outcome metric. Single-variable analysis was conducted to develop a
nine-point triage score
for early mortality.
Key Results
Overall, 799,522 ED visits were available for analysis. The early and short-term mortality rates were 0.6% and 2.5%, respectively. Models trained on the full set of features yielded an AUC of 0.962 for early mortality and 0.923 for short-term mortality. A model that utilized the nine features with the highest single-variable AUC scores (age, arrival mode, chief complaint, five primary vital signs, and ESI) yielded an AUC of 0.962 for early mortality.
Conclusion
The gradient boosting model shows high predictive ability for screening patients at risk of early mortality utilizing data available at the time of triage in the ED.
While toxin-harboring Vibrio parahaemolyticus has been previously established as the causative agent of early mortality syndrome (EMS) or acute hepatopancreatic necrosis disease (AHPND) in shrimp, ...information on the mechanistic processes that happen in the host during infection is still lacking. Here, we examined the expression responses of the shrimp hemocyte transcriptome to V. parahaemolyticus AHPND (VPAHPND) by RNA sequencing (RNA-seq). Using libraries (SRA accession number SRP137285) prepared from shrimp hemocytes under experimental conditions, a reference library was de novo assembled for gene expression analysis of VPAHPND-challenged samples at 0, 3/6, and 48 h post infection (hpi). Using the library from 0-hpi as the control, 359 transcripts were found to be differentially expressed in the 3/6-hpi library, while 429 were differentially expressed in the 48-hpi library. The expression patterns reported in the RNA-seq of 9 representative genes such as anti-lipopolysaccharide factor (LvALF), crustin p (CRU), serpin 3 (SER), C-type lectin 3 (CTL), clottable protein 2 (CLO), mitogen-activated protein kinase kinase 4 (MKK4), P38 mitogen-activated protein kinase (P38), protein kinase A regulatory subunit 1 (PKA) and DNAJ homolog subfamily C member 1-like (DNJ) were validated by qRT-PCR. The expression of these genes was also analyzed in shrimp that were injected with the partially purified VPAHPND toxin. A VPAHPND toxin-responsive gene, LvALF was identified, and its function was characterized by RNA interference. LvALF knockdown resulted in significantly rapid increase of shrimp mortality caused by toxin injection. Protein-protein interaction analysis by molecular docking suggested that LvALF possibly neutralizes VPAHPND toxin through its LPS-binding domain. The data generated in this study provide preliminary insights into the differences in the immune response of shrimp to the bacterial and toxic aspect of VPAHPND as a disease.
•VPAHPND-responsive immune genes of Litopenaeus vannamei haemocyte were reported.•Among the identified genes, LvALF specifically responded to purified toxin challenge.•LvALF knockdown significantly increased shrimp mortalities during VPAHPND toxin challenge.•Molecular docking suggests that the LPS-binding domain of LvALF takes part in VPAHPND toxin neutralization.
There has been no severity evaluation model for pediatric patients with hemophagocytic lymphohistiocytosis (HLH) that uses readily available parameters. This study aimed to develop a novel model for ...predicting the early mortality risk in pediatric patients with HLH using easily obtained parameters whatever etiologic subtype. Patients from one center were divided into training and validation sets for model derivation. The developed model was validated using an independent validation cohort from the second center. The prediction model with nomogram was developed based on logistic regression. The model performance underwent internal and external evaluation and validation using the area under the receiver operating characteristic curve (AUC), calibration curve with 1000 bootstrap resampling, and decision curve analysis (DCA). Model performance was compared with the most prevalent severity evaluation scores, including the PELOD-2, P-MODS, and pSOFA scores. The prediction model included nine variables: glutamic-pyruvic transaminase, albumin, globulin, myohemoglobin, creatine kinase, serum potassium, procalcitonin, serum ferritin, and interval between onset and diagnosis. The AUC of the model for predicting the 28-day mortality was 0.933 and 0.932 in the training and validation sets, respectively. The AUC values of the HScore, PELOD-2, P-MODS and pSOFA were 0.815, 0.745, 0.659 and 0.788, respectively. The DCA of the 28-day mortality prediction exhibited a greater net benefit than the HScore, PELOD-2, P-MODS and pSOFA. Subgroup analyses demonstrated good model performance across HLH subtypes. The novel mortality prediction model in this study can contribute to the rapid assessment of early mortality risk after diagnosis with readily available parameters.
In June 2017, mass mortalities were reported at whiteleg shrimp Penaeus vannamei farms in Texas, USA. PCR testing for OIE-listed and non-listed pathogens detected the pirA and pirB toxin genes ...associated with acute hepatopancreatic necrosis disease (AHPND). DNA sequence analyses of cloned pirA and pirB genes showed them to be identical to those detected in other AHPND-causing Vibrio sp. Amplicons generated using PCR tests targeted to the toxR gene showed the Pir toxin genes to be associated with a V. parahaemolyticus type more similar to a genotype found in Mexico compared to that found in Asia. Histology detected masses of bacteria and hemocytic infiltrations as well as extensive necrosis and sloughing of epithelial cells in hepatopancreatic tubules pathognomonic of AHPND. The data support AHPND as the cause of the mortalities. Given that US companies produce shrimp broodstock for farms in Asia and Latin America, the further spread of AHPND in the USA needs to be prevented to avoid serious economic consequences to these industries.
•Early mortality after radical RT/CRT in HNSCC patients is often not cancer-related.•An early non-cancer risk prediction model was developed.•After internal validation, the AUC was 0.74 and ...calibration was good.•Pneumonia was estimated to be the cause of death in 32% of early non-cancer deaths.•The provided risk estimates can help select patients for supportive interventions.
In patients with head and neck squamous cell carcinoma (HNSCC), curative-intent radiotherapy (RT) and chemoradiotherapy (CRT) are associated with substantial acute morbidity and 5–10% of patients die within 180 days of treatment initiation. Most of these early deaths occur without HNSCC recurrence or progression and may therefore be preventable to some extent. We developed a prediction tool to estimate the risk of non-HNSCC mortality occurring within the first 180 days followingRT/CRT initiation.
Patients with HNSCC treated with RT/CRT, including postoperative RT/CRT, at Rigshospitalet or Herlev Hospitals between 2010–2017 were identified in the Danish Head and Neck Cancer Group (DAHANCA) database. Predictor variables included age, stage, performance status, tumor subsite including p16 status, comorbidity, postoperative status, smoking and pre-treatment albumin levels. The 180-day non-HNSCCmortality risk was estimated by combining cause-specific Cox regression models.
We included 2209 patients. The 180-day non-HNSCCmortality rate was 4.4% and almostone third (31.6%) of non-HNSCCdeathswere caused by pneumonia.After internal model validation, the area under the receiver operating curve was 0.74 (95% CI: 0.66–0.81) and calibration was good for risk predictions ranging from 0% to 20%.
We developed a prediction tool to estimate the 180-day non-HNSCC mortality risk. This tool can be used to select high-risk patients for supportive interventions aiming to improve survival rates, and is availablefor interactive use at https://emriskpred.shinyapps.io/EMNED_App/.
PDF
