Prognosis Of Patients Research Articles

Association between the stress-hyperglycemia ratio and all-cause mortality in community-dwelling populations: An analysis of the National Health and Nutrition Examination Survey (NHANES) 1999-2014.

Reportedly, the stress-hyperglycemia ratio (SHR) is closely associated with poor prognosis in patients with severe acute disease. However, the community-dwelling may also be in a state of stress due to environmental exposure. Our study aimed to explore the association between SHR and all-cause mortality in the community-dwelling population. A total of 18 480 participants were included out of 82 091 from the NHANES 1999-2014 survey. The Kaplan-Meier survival analyses were used to assess the disparities in survival rates based on SHR, and the log-rank test was employed to investigate the distinctions between groups. The multivariate Cox regression analysis and restricted cubic spline (RCS) analysis were performed to assess the association of SHR with all-cause mortality. A subgroup analysis was also conducted. A total of 3188 deaths occurred during a median follow-up period of 11.0 (7.7; 15.4) years. The highest risk for all-cause mortality was observed when SHR≤ 0.843 or SHR ≥0.986 (log-rank p < .001). After adjusting for the confounding factors, compared with subjects in the second SHR quartile (Q2), participants in the highest (Q4, adjusted hazard ratio [HR] 1.49, 95% confidence interval [CI] 1.28-1.73) and lowest quartiles (Q1, adjusted HR 1.37, 95% CI 1.16-1.60) have a higher probability of all-cause death. The RCS observed a dose-response U-shaped association between SHR and all-cause mortality. The U-shaped association between SHR and all-cause mortality was similar across subgroup analysis. The SHR was significantly associated with all-cause mortality in the community-dwelling population, and the relationship was U-shaped.

Prognostic value of body mass index for first-line chemoimmunotherapy combinations in advanced non-small cell lung cancer in Chinese population.

BackgroundFew studies have examined the correlation between body mass index (BMI) and effectiveness of first-line chemoimmunotherapy in patients with advanced non-small cell lung cancer (NSCLC); moreover, the conclusion remains elusive and no such studies have been conducted in the Chinese population. Our study aimed to validate the predictive significance of BMI in Chinese patients with advanced NSCLC receiving first-line chemoimmunotherapy combinations. MethodsData of patients with advanced NSCLC treated with first-line chemoimmunotherapy between June 2018 and February 2022 at three centers were retrieved retrospectively. The association between baseline BMI with progression-free survival (PFS) and overall survival (OS) was evaluated using the Kaplan–Meier method and Cox regression models. BMI was categorized according to the World Health Organization criteria. ResultsOf the included 805 patients, 5.3% were underweight, 63.4% had normal weight, 27.8% were overweight, and 3.5% were obese. Survival analysis showed that patients in the high BMI group had significantly better PFS (p=0.012) and OS (p=0.014) than those in the low BMI group. Further, patients in the overweight subgroup had better PFS (p=0.036) and OS (p=0.043) compared to the normal weight population. The results of Cox regression analysis confirmed the correlations between BMI and prognosis of advanced NSCLC patients receiving first-line chemoimmunotherapy combinations. ConclusionsBaseline BMI affected the clinical outcomes of first-line chemoimmunotherapy combinations in patients with advanced NSCLC, and was especially favorable for the overweight subgroup.

Sepsis epidemiology and prognosis in cancer patients: Preliminary results of a multicenter prospective observational study

Sepsis epidemiology and prognosis in cancer patients: Preliminary results of a multicenter prospective observational study

Predictive value of Piezo2 in BALF on the prognosis of ARDS patients

Predictive value of Piezo2 in BALF on the prognosis of ARDS patients

TMErisk score: a tumor microenvironment-based model for predicting prognosis and immunotherapy in patients with head and neck squamous cell carcinoma

Tumor microenvironment (TME) is closely associated with the progression and prognosis of head and neck squamous cell carcinoma (HNSCC). To investigate potential biomarkers for predicting therapeutic outcomes in HNSCC, we analyzed the immune and stromal status of HNSCC based on the genes associated with TME using the ESTIMATE algorithm. Immune and stromal genes were identified with differential gene expression and weighted gene co-expression network analysis (WGCNA). From these genes, 118 were initially selected through Cox univariate regression and then further input into least absolute shrinkage and selection operator (LASSO) regression analysis. As a result, 11 genes were screened out for the TME-related risk (TMErisk) score model which presented promising overall survival predictive potential. The TMErisk score was negatively associated with immune and stromal scores but positively associated with tumor purity. Individuals with high TMErisk scores exhibited decreased expression of most immune checkpoints and all human leukocyte antigen family genes, and reduced abundance of infiltrating immune cells. Divergent genes were mutated in HNSCC. In both high and low TMErisk score groups, the tumor protein P53 exhibited the highest mutation frequency. A higher TMErisk score was found to be associated with reduced overall survival probability and worse outcomes of immunotherapy. Therefore, the TMErisk score could serve as a valuable model for the outcome prediction of HNSCC in clinic.

LncRNA NEAT1 Promotes the Cancer Stem Cell-Like Properties of HCC by miR-128-3p/GP73 Axis

In this study, we investigated the role of long non-coding RNA NEAT1 in hepatocellular carcinoma (HCC) and its impact on liver cancer cell behavior, particularly their cancer stem cell (CSC)-like properties. We observed elevated NEAT1 levels in HCC cell lines and tissues, and this upregulation was associated with adverse clinical characteristics and poor prognosis in HCC patients. Through in vitro experiments, we found that silencing NEAT1 in HCC cells led to decreased cell proliferation, migration, invasion, and inhibited epithelial-mesenchymal transition (EMT) in Huh7 cells. Additionally, the unique surface markers of CSCs were downregulated upon NEAT1 knockdown. Further investigation revealed that NEAT1 regulates the expression of GP73 by directly binding to miR-128-3p, functioning as a competitive ceRNA to suppress miR-128-3p expression. Rescue experiments showed that inhibiting miR-128-3p expression reversed the effects of NEAT1 knockdown on HCC cell proliferation,migration, and invasion. In summary, our findings demonstrate that lncRNA NEAT1 plays a pivotal role in promoting HCC progression and enhancing CSC properties by upregulating GP7 through competitive binding to miR-128-3p. This insight into the underlying mechanism may have promising implications for the treatment of HCC.

Innovative Therapeutic Approaches in Congenital Myasthenic Syndromes.

To provide real-word clinical follow-up data on patients carrying variations of congenital myasthenic syndromes (CMS) and who respond to some innovative drugs. Patients recruited from the Neurology Department of the Mustapha Bacha university hospital in Algiers. Treated with innovative drugs, they were monitored and their clinical progress was evaluated on the basis of clinical arguments suggestive of CMSs, but also para clinical arguments (electromyography and genetic study). Six patients carrying different mutations in different genes of CMSs were studied. They had different pathophysiologic profiles (slow or fast channel syndromes, low expressor of receptor). Their therapeutic management was based on innovative drugs, normally indicated in other, non-neurological pathologies. Their outcome was toward a clear clinical improvement. This work relates the interest of proposing treatments (outside of Pyridostigmine) in the management of CMSs. These therapies can greatly modify the prognosis of patients suffering from this orphan disease. This study provides Class IV evidence that for patients with congenital myasthenic syndromes, some innovative treatments are effective.

Suppression of N-Glycosylation of Zinc Finger Protein 471 Affects Proliferation, Invasion, and Docetaxel Sensitivity of Tongue Squamous Cell Carcinoma via Regulation of c-Myc

Zinc finger protein 471 (ZNF471) is a member of the Krüppel-related domain zinc finger protein family, and has recently attracted attention because of its anti-cancer effects. N-glycosylation regulates expression and functions of the protein. This study aimed to investigate the effects of ZNF471 N-glycosylation on the proliferation, invasion, and docetaxel sensitivity of tongue squamous cell carcinoma (TSCC). It analyzed the expression, function, and prognostic significance of ZNF471 in TSCC using bioinformatics techniques such as gene differential expression analysis, univariate Cox regression analysis, functional enrichment analysis, and gene set enrichment analysis. Using site-specific mutagenesis, this study generated three mutant sites for ZNF471 N-glycosylation to determine the effect of N-glycosylation on ZNF471 protein levels and function. Quantitative real-time PCR, Western blot analysis, and immunohistochemistry tests confirmed the down-regulation of ZNF471 expression in TSCC. Low expression of ZNF471 is associated with poor prognosis of patients with TSCC. Overexpression of ZNF471 invitro retarded the proliferation of TSCC cells and suppressed cell invasion and migration ability. Asparagine 358 was identified as a N-glycosylation site of ZNF471. Suppressing N-glycosylation of ZNF471 enhanced the protein stability and promoted the translocation of protein to the cell nucleus. ZNF471 binding to c-Myc gene promoter suppressed oncogene c-Myc expression, thereby playing the anti-cancer effect and enhancing TSCC sensitivity to docetaxel. In all, N-glycosylation of ZNF471 affects the proliferation, invasion, and docetaxel sensitivity of TSCC via regulation of c-Myc.

The prognostic nutritional index as a predictor of efficacy and early recurrence for adjuvant transarterial chemoembolization in hepatocellular carcinoma.

Postoperative adjuvant transcatheter arterial chemoembolization (TACE) can prevent recurrence of hepatocellular carcinoma (HCC) in certain patients. This study aimed to identify the potential beneficiaries of adjuvant TACE. 477 patients who underwent curative resection for HCC were enrolled in this retrospectively cohort study. The trajectory of the prognostic nutritional index (PNI) during the perioperative period was fitted using a latent-class growth mixed model. The association between adjuvant TACE and recurrence-free survival in each PNI group was assessed using the Kaplan-Meier curve. Furthermore, Cox regression analysis was conducted to identify the risk factors for early recurrence after adjuvant TACE and develop a nomogram model. Patients in the PNI group III had a high risk of recurrence and could benefit from adjuvant TACE (P = 0.009). The prognostic prediction model for adjuvant TACE (PAT) incorporated eight variables (PNI, tumor size, tumor number, vascular invasion, sex, aspartate aminotransferase, gamma-glutamyl transferase, and degree of differentiation). Patients with PAT scores > 330 and 235-330 had significantly higher recurrence rates than those with PAT scores < 235 (P < 0.001). PNI may help guide the selection of adjuvant TACE beneficiaries. PAT demonstrated a high accuracy in predicting the prognosis of patients who underwent postoperative TACE.

A comparative analysis of convolutional neural networks for breast cancer prediction

Breast cancer continues to be a substantial worldwide health concern, affecting millions of individuals each year; this emphasizes the critical nature of early detection in order to enhance patient prognoses. The present study aims to assess the classification performance of three convolutional neural network (CNN) architectures-visual geometry group 19 (VGG19), AlexNet, and residual network 50 (ResNet50)-with respect to breast cancer detection in medical images. Thorough assessments, encompassing metrics such as accuracy, precision, recall, and F-score, were undertaken to evaluate the diagnostic performance of the models. ResNet50 consistently outperforms other models, as evidenced by its highest accuracy and F-score. The research highlights the significant importance of carefully choosing suitable architectures for medical image analysis, with a specific focus on the detection of breast cancer. In addition, it demonstrates the capacity of deep learning models, such as ResNet50, to improve the diagnosis of breast cancer with exceptional precision and sensitivity, which is critical for reducing the occurrence of false positives and negatives in clinical environments. In addition, computational efficiency is taken into account; AlexNet is recognized as the most efficient model, which is advantageous in environments with limited resources. This study advances medical image processing by demonstrating the potential of CNNs in the detection of breast cancer. The results of this study establish a fundamental basis for sub- sequent inquiries and suggest approaches to improve timely detection and treatment, which will ultimately be advantageous for both patients and healthcare professionals.

Pancreatic Injury Is Associated with Poor Prognosis in Severe Fever with Thrombocytopenia Syndrome.

Severe fever with thrombocytopenia syndrome (SFTS) is an emerging infectious disease. Previous studies have primarily focused on the epidemiological and clinical characteristics of patients with SFTS, whereas pancreatic injury has received little attention. This study investigated the effects of pancreatic injury on the prognosis of patients with SFTS. A total of 156 patients diagnosed with SFTS between April 2016 and April 2022 were included in the analysis. Multivariate logistic regression analysis showed that pancreatic injury (odds ratio [OR] = 3.754, 95% confidence interval [CI]: 1.361-79.036, P = 0.024) and neurological symptoms (OR = 18.648, 95% CI: 4.921-70.668, P < 0.001) were independent risk factors for mortality. The receiver operating characteristic curve indicated that serum pancreatic enzymes were predictive of progression to death in patients with SFTS. The area under the curve (AUC) for amylase was 0.711, with an optimal cutoff value of 95.5 U/L, sensitivity of 96.4%, and specificity of 35.9%. Lipase had an AUC of 0.754, an optimal cutoff value of 354.75 U/L, sensitivity of 75%, and specificity of 67.2%. Thus, pancreatic injury was associated with a poor prognosis of SFTS and can be used as an important reference for SFTS determination and prognostic assessment.

Biological profile of secondary hyperparathyroidism in chronic renal failure patients

Secondary hyperparathyroidism (SHPT) is a common complication of chronic kidney disease, especially in hemodialysis patients. It is characterized by overproduction of parathyroid hormone in response to chronic deterioration of renal function. The aim of this retrospective study was to determine the average time to develop secondary hyperparathyroidism, analyze the initial phosphocalcic profiles, and evaluate the evolution of these profiles in hemodialysis patients, following the recommendations of the KDOQI 2003 and KDIGO 2009 groups. The study included 134 hemodialysis patients from two private dialysis centers. Data were collected from patients' medical records and analyzed using SPSS software. The results showed that the average time to develop secondary hyperparathyroidism was 3.15 years according to KDOQI recommendations and 4.64 years according to KDIGO recommendations based on parathyroid hormone levels. The initial assessment revealed an imbalance in phosphocalcic metabolism in approximately 20.1% to 22.5% of patients, a proportion that increased to 27.5% during follow-up, according to both sets of recommendations. In conclusion, secondary hyperparathyroidism is an inevitable complication of chronic kidney disease, affecting the vital and functional prognosis of hemodialysis patients. Diagnosis primarily relies on parathyroid hormone levels, associated with phosphocalcemia, vitamin D, and PAL analyses. Treatment aims mainly to maintain blood levels of calcium, phosphorus, and vitamin D within recommended limits and to reduce parathyroid response to phosphocalcic disturbances.

Characteristics of COVID-19 patients with coronary artery disease comorbidity

Coronavirus disease 2019 (COVID-19) is an infectious respiratory disease which is caused by the SARS-CoV-2 virus. Coronary heart disease is a disease caused by plaque build-up in artery walls which supply blood to the heart and other body parts. Coronary heart disease is amongst the most severe COVID-19 comorbidities. Objective: To determine the patient profile of COVID-19 patients with coronary heart disease comorbidity Methods: Literature study with a systematic review that uses previous research as a reference to generate conclusions. Results: Based on the 24 journals used in this literature review, 11 journals discuss the topic of age, 9 journals discuss the topic of gender, and 8 journals discuss the topic of the prognosis of COVID-19 patients with coronary heart disease comorbidity. Conclusion: The mean age of COVID-19 patients with coronary heart disease comorbidity is 63,4 years old. The gender in this case is 64,7% males dan 34,3% females. The rates for prognosis are 47,6% of patients need to go to the ICU, 32,8% of patients died, 51,75% of patients recovered and 36,5% of patients need further treatment.

Paradoxical tuberculous reaction to anti-tnfα discontinuation: a complex case of miliary tuberculosis and macrophagic activation syndrome with hepatic manifestations

Tuberculosis reactivation during anti-TNF-alpha therapy paradoxically worsened following reconstitution of pathogen-specific immune responses after cessation of TNFα antagonist treatment and initiation of anti-bacillary therapy. We report the case of a 46-year-old woman who was prescribed a tumor necrosis factor blocker (anti-TNF) for a relapse of Behçet's disease. The patient developed pulmonary miliary tuberculosis following the reactivation of latent tuberculosis, despite a normal pre-therapeutic work-up. Discontinuation of anti-TNF and initiation of anti-bacillary drugs triggered a paradoxical tubercular reaction (PTR). The diagnosis of paradoxical reaction to anti-tuberculosis drugs was evoked by the clinical and biological deterioration and the appearance of miliary cerebral tuberculosis and cerebral venous thrombosis after a period of clinical improvement. Although this phenomenon has been documented, it represents a major challenge for clinicians. The peculiarity of this case lies in its association with a macrophagic activation syndrome (MAS) with hepatic involvement, retained on clinical-biological and histological criteria. The overlap between MAS and PTR makes it difficult to diagnose these two entities with certainty. The patient responded favorably to moderate-dose systemic corticosteroid therapy with progressive degression, and the reintroduction of anti-tuberculosis drugs.This work aims to highlight the importance of close monitoring of TB patients on anti-TNFα therapy for early diagnosis and management of complications to improve the prognosis of these complex patients.

Artificial intelligence and machine learning for early cancer prediction and response

Worldwide, cancer claims more lives than any other disease. Although cancer detection, prognosis, and treatment have all advanced, one major obstacle is the lack of personalized, data-driven care. Artificial intelligence (AI), used to forecast and automate numerous malignancies, has emerged as a viable solution for increasing healthcare accuracy and patient outcomes. Artificial intelligence applications in cancer include risk evaluation, early detection, patient prognosis prediction, and treatment selection based on comprehensive data. Machine learning (ML), a form of artificial intelligence that allows computers to learn from training data, is very successful in predicting breast, brain, lung, liver, and prostate cancers. Indeed, AI and machine learning have outperformed physicians in predicting cancer. These technologies can potentially enhance the diagnosis, prediction, and quality of life of patients with a wide range of disorders, not just cancer. As a result, it is critical to enhance existing AI and ML technologies and create new programs to help patients. This article discusses the use of AI and machine learning algorithms in cancer prediction, including its present uses, future possibilities, and limitations.

Predict the effect of the number of positive preoperative serum tumor markers on the surgical method and prognosis of intrahepatic cholangiocarcinoma patients based on mediation analysis

Objectives: To investigate the effect of the number of positive preoperative serological tumor markers on the surgical approach and prognosis of patients with intrahepatic cholangiocarcinoma. Methods: This is a retrospective case-series study. Data from 548 patients with intrahepatic cholangiocarcinoma after radical resection from October 2010 to April 2019 were retrospectively collected in 10 hospitals of China. There were 277 males and 271 females with an age of (57.8±10.2)years(range:23 to 84 years). Four hundred and twenty-six patients(77.7%) had at least one positive preoperative serum tumor marker. The data collection included the results of 4 preoperative serological tumor markers,other preoperative indicators(5 prodromal symptoms, 6 medical history,8 preoperative serological indicators,5 preoperative imaging indicators,and 14 preoperative pathological examination indicators),baseline data (gender and age),surgical methods,and prognostic follow-up data. Four preoperative results of serologic tumor marker and surgical procedure were converted into categorical variables. The number of positive preoperative serum tumor markers was used as the treatment variable,the surgical method was used as the mediating variable,and the survival time was used as the outcome variable. Univariate and multivariate analysis were used to screen for other preoperative indicators which were independent factors that influenced the surgical procedure and the prognosis of patients as covariates to analyze the mediating effect. Results: Of the 548 patients included in the study, 176 patients (32.1%) underwent partial hepatectomy,151 patients(27.5%) underwent hemihepatectomy, and 221 patients(40.3%) underwent partial hepatectomy or hemihepatectomy combined with other treatments. The results of the univariate and multivariate analysis showed that the number of positive serum tumor markers,intrahepatic bile duct dilatation,portal vein invasion,pathological differentiation,pathological type,vascular invasion,T stage,N stage and maximum tumor diameter were independent factors influencing the surgical procedure(all P<0.05). Intrahepatic bile duct dilatation,pathological differentiation and T stage were independent prognostic factors for patients with intrahepatic cholangiocarcinoma(all P<0.05). Intrahepatic bile duct dilatation,differentiation and T stage were included as covariates in the mediation effect model. The results showed that the number of positive serum tumor markers before surgery had a negative predictive effect on the survival time of patients with intrahepatic cholangiocarcinoma (β=-0.092, P=0.039),and had a positive predictive effect on the surgical method (β=0.244,P<0.01). The number of positive serum tumor markers had a negative predictive effect on the survival time of patients with intrahepatic cholangiocarcinoma (β=-0.151, P=0.002). Direct and indirect effects accounted for 71.3% and 28.7% of total effects,respectively. Conclusions: The higher the positive number of preoperative tumor markers,the worse the prognosis of patients with intrahepatic cholangiocarcinoma. The number of positive cells not only directly affects the prognosis of patients,but also indirectly affects the prognosis of patients by affecting the surgical method.

Impact of chemotherapy delay on long-term prognosis of laparoscopic radical surgery for locally advanced gastric cancer: a pooled analysis of four randomized controlled trials.

Adjuvant chemotherapy following curative surgery for locally advanced gastric cancer (AGC) significantly improves long-term patient prognosis. However, delayed chemotherapy (DC), in which patients are unable to receive timely treatment, is a common phenomenon in clinical practice for various reasons. This study aimed to investigate the impact of DC on the prognosis of patients with stage II-III locally AGC and explore the associated risk factors. Data from four prospective studies were included in the pooled analysis. The planned chemotherapy (PC) group was defined as the time interval between surgery and the first chemotherapy ≤ 49 d, while the DC group was defined as the time interval between surgery and chemotherapy > 49 d. The prognosis, recurrence, and risk factors were compared, and a nomogram for predicting DC was established. In total, 596 patients were included, of whom 531 (89.1%) had PC and 65 (10.9%) had DC. Survival analysis revealed that the 5-year overall survival (OS) and disease-free survival (DFS) were significantly lower in the DC group than those in the PC group (log-rank P < 0.001). Cox univariable and multivariable analyses showed that DC was an independent risk factor for OS and DFS in stage II-III patients (P < 0.05). Based on the significant factors for DC, a prediction model was established that had a good fit, high accuracy (AUC = 0.780), and clinical applicability in both the training and validation sets. Delayed chemotherapy after gastrectomy is associated with poor long-term prognosis in patients with locally advanced stage II-III GC disease. But standardized, full-cycle adjuvant chemotherapy after surgery may play a remedial role, and can to a certain extent compensate the poor effects caused by delayed chemotherapy.

HVEM in acute lymphocytic leukemia facilitates tumour immune escape by inhibiting CD8+ T cell function.

Leukaemia remains a major contributor to global mortality, representing a significant health risk for a substantial number of cancer patients. Despite notable advancements in the field, existing treatments frequently exhibit limited efficacy or recurrence. Here, we explored the potential of abolishing HVEM (herpes virus entry mediator, TNFRSF14) expression in tumours as an effective approach to treat acute lymphoblastic leukaemia (ALL) and prevent its recurrence. The clinical correlations between HVEM and leukaemia were revealed by public data analysis. HVEM knockout (KO) murine T cell lymphoblastic leukaemia cell line EL4 were generated using CRISPR-Cas9 technology, and syngeneic subcutaneous tumour models were established to investigate the in vivo function of HVEM. Immunohistochemistry (IHC), RNA-seq and flow cytometry were used to analyse the tumour immune microenvironment (TIME) and tumour draining lymph nodes (dLNs). Immune functions were investigated by depletion of immune subsets in vivo and T cell functional assays in vitro. The HVEM mutant EL4 cell lines were constructed to investigate the functional domain responsible for immune escape. According to public databases, HVEM is highly expressed in patients with ALL and acute myeloid leukemia (AML) and is negatively correlated with patient prognosis. Genetic deletion of HVEM in EL4 cells markedly inhibited tumour progression and prolonged the survival of tumour-bearing mice. Our experiments proved that HVEM exerted its immunosuppressive effect by inhibiting antitumour function of CD8+ T cell through CRD1 domain both in vivo and in vitro. Additionally, we identified a combination therapy capable of completely eradicating ALL tumours, which induces immune memory toward tumour protection. Our study reveals the potential mechanisms by which HVEM facilitates ALL progression, and highlights HVEM as a promising target for clinical applications in relapsed ALL therapy.

Emerging pharmacotherapy trends in preventing and managing oral mucositis induced by chemoradiotherapy and targeted agents.

The introduction of targeted therapy and immunotherapy has tremendously changed the clinical outcomes and prognosis of cancer patients. Despite innovative pharmacological therapies and improved radiotherapy (RT) techniques, patients continue to suffer from side effects, of which oral mucositis (OM) is still the most impactful, especially for quality of life. We provide an overview of current advances in cancer pharmacotherapy and RT, in relation to their potential to cause OM, and of the less explored and more recent literature reports related to the best management of OM. We have analyzed natural/antioxidant agents, probiotics, mucosal protectants and healing coadjuvants, pharmacotherapies, immunomodulatory and anticancer agents, photobiomodulation and the impact of technology. The discovery of more precise pathophysiologic mechanisms of CT and RT-induced OM has outlined that OM has a multifactorial origin, including direct effects, oxidative damage, upregulation of immunologic factors, and effects on oral flora. A persistent upregulated immune response, associated with factors related to patients' characteristics, may contribute to more severe and long-lasting OM. The goal is strategies to conjugate individual patient, disease, and therapy-related factors to guide OM prevention or treatment. Despite further high-quality research is warranted, the issue of prevention is paramount in future strategies.

Reframing acute kidney injury as a pathophysiological continuum of disrupted renal excretory function.

Surrogate measures of glomerular filtration rate (GFR) continue to serve as pivotal determinants of the incidence, severity, and management of acute kidney injury (AKI), as well as the primary reference point underpinning knowledge of its pathophysiology. However, several clinically important deficits in aspects of renal excretory function during AKI other than GFR decline, including acid-base regulation, electrolyte and water balance, and urinary concentrating capacity, can evade detection when diagnostic criteria are built around purely GFR-based assessments. The use of putative markers of tubular injury to detect "sub-clinical" AKI has been proposed to expand the definition and diagnostic criteria for AKI, but their diagnostic performance is curtailed by ambiguity with respect to their biological meaning and context specificity. Efforts to devise new holistic assessments of overall renal functional compromise in AKI would foster the capacity to better personalize patient care by replacing biomarker threshold-based diagnostic criteria with a shift to assessment of compromise along a pathophysiological continuum. The term AKI refers to a syndrome of sudden renal deterioration, the severity of which is classified by precise diagnostic criteria that have unquestionable utility in patient management as well as blatant limitations. Particularly, the absence of an explicit pathophysiological definition of AKI curtails further scientific development and clinical handling, entrapping the field within its present narrow GFR-based view. A refreshed approach based on a more holistic consideration of renal functional impairment in AKI as the basis for a new diagnostic concept that reaches beyond the boundaries imposed by the current GFR threshold-based classification of AKI, capturing broader aspects of pathogenesis, could enhance AKI prevention strategies and improve AKI patient outcome and prognosis.