Data-driven optimization of version 9 American Joint Committee on Cancer staging system for anal cancer.

INTRODUCTION: The American Joint Committee on Cancer (AJCC) staging system undergoes periodic revisions to maintain contemporary survival outcomes related to stage. Recently, the AJCC has developed a novel, systematic approach incorporating survival data to refine stage groupings. The objective of this study was to demonstrate data-driven optimization of the version 9 AJCC staging system for anal cancer assessed through a defined validation approach. METHODS: The National Cancer Database was queried for patients diagnosed with anal cancer in 2012 through 2017. Kaplan-Meier methods analyzed 5-year survival by individual clinical T category, N category, M category, and overall stage. Cox proportional hazards models validated overall survival of the revised TNM stage groupings. RESULTS: Overall, 24,328 cases of anal cancer were included. Evaluation of the 8th edition AJCC stage groups demonstrated a lack of hierarchical prognostic order. Survival at 5 years for stage I was 84.4%, 77.4% for stage IIA, and 63.7% for stage IIB; however, stage IIIA disease demonstrated a 73.0% survival, followed by 58.4% for stage IIIB, 59.9% for stage IIIC, and 22.5% for stage IV (p <.001). Thus, stage IIB was redefined as T1-2N1M0, whereas Stage IIIA was redefined as T3N0-1M0. Reevaluation of 5-year survival based on data-informed stage groupings now demonstrates hierarchical prognostic order and validated via Cox proportional hazards models. CONCLUSION: The 8th edition AJCC survival data demonstrated a lack of hierarchical prognostic order and informed revised stage groupings in the version 9 AJCC staging system for anal cancer. Thus, a validated data-driven optimization approach can be implemented for staging revisions across all disease sites moving forward.

Quantitative evaluation of lesion response heterogeneity for superior prognostication of clinical outcome.

PURPOSE: Standardized reporting of treatment response in oncology patients has traditionally relied on methods like RECIST, PERCIST and Deauville score. These endpoints assess only a few lesions, potentially overlooking the response heterogeneity of all disease. This study hypothesizes that comprehensive spatial-temporal evaluation of all individual lesions is necessary for superior prognostication of clinical outcome. METHODS: [18F]FDG PET/CT scans from 241 patients (127 diffuse large B-cell lymphoma (DLBCL) and 114 non-small cell lung cancer (NSCLC)) were retrospectively obtained at baseline and either during chemotherapy or post-chemoradiotherapy. An automated TRAQinform IQ software (AIQ Solutions) analyzed the images, performing quantification of change in regions of interest suspicious of cancer (lesion-ROI). Multivariable Cox proportional hazards (CoxPH) models were trained to predict overall survival (OS) with varied sets of quantitative features and lesion-ROI, compared by bootstrapping with C-index and t-tests. The best-fit model was compared to automated versions of previously established methods like RECIST, PERCIST and Deauville score. RESULTS: Multivariable CoxPH models demonstrated superior prognostic power when trained with features quantifying response heterogeneity in all individual lesion-ROI in DLBCL (C-index = 0.84, p < 0.001) and NSCLC (C-index = 0.71, p < 0.001). Prognostic power significantly deteriorated (p < 0.001) when using subsets of lesion-ROI (C-index = 0.78 and 0.67 for DLBCL and NSCLC, respectively) or excluding response heterogeneity (C-index = 0.67 and 0.70). RECIST, PERCIST, and Deauville score could not significantly associate with OS (C-index < 0.65 and p > 0.1), performing significantly worse than the multivariable models (p < 0.001). CONCLUSIONS: Quantitative evaluation of response heterogeneity of all individual lesions is necessary for the superior prognostication of clinical outcome.

Outcomes after intervention for enteral nutrition in patients with amyotrophic lateral sclerosis in multidisciplinary clinics.

INTRODUCTION/AIMS: Patients with amyotrophic lateral sclerosis (ALS) are susceptible to malnutrition, with appropriate management of nutritional interventions an active area of investigation. We sought to determine the impact of gastrostomy tube placement in ALS patients, exploring the correlation between forced vital capacity (FVC), malnutrition, and perioperative complications. METHODS: A retrospective review was performed of clinically diagnosed ALS patients treated at two multidisciplinary clinics (University of Kansas, University of Nebraska) from January 2009 to September 2020 who were referred for gastrostomy. Data collected included demographics, disease characteristics, and key gastrostomy related dates/outcomes. RESULTS: Two hundred thirty-nine patients were included with a median age of 65 years and median of 589 days from symptom onset to gastrostomy (interquartile range, 404-943). The population was predominantly Non-Hispanic White with bulbar-onset ALS. 30-day mortality was 4% and 30-day morbidity was 13%. Weight loss, body mass index, and predicted FVC at placement showed no increased 30-day morbidity or mortality association. Bulbar-onset ALS patients exhibited higher overall mortality postplacement than limb onset (odds ratio: 1.85, 95% confidence interval: 1.03-3.33). There was a 5% incidence of symptoms suggestive of refeeding syndrome. DISCUSSION: Rates of major/minor complications and 30-day mortality related to gastrostomy placement in our population were similar compared with prior studies in ALS. The lack of difference in outcomes based on FVC at procedure may suggest this is not predictive of outcome, or perhaps, high-quality perioperative respiratory management. Alternative reasons may account for the increased morbidity and mortality of gastrostomy placement in the ALS population.

The impact of macro- and micro-steatosis on the outcomes of patients who undergo liver transplant: Analysis of the UNOS-STAR database.

BACKGROUND AND AIMS: The presence of steatosis in a donor liver and its relation to post-transplantation outcomes are not well defined. This study evaluates the effect of the presence and severity of micro- and macro-steatosis of a donor graft on post-transplantation outcomes. METHODS: The UNOS-STAR registry (2005-2019) was used to select patients who received a liver transplant graft with hepatic steatosis. The study cohort was stratified by the presence of macro- or micro-vesicular steatosis, and further stratified by histologic grade of steatosis. The primary endpoints of all-cause mortality and graft failure were compared using sequential Cox regression analysis. Analysis of specific causes of mortality was further performed. RESULTS: There were 9184 with no macro-steatosis (control), 150 with grade 3 macro-steatosis, 822 with grade 2 macro-steatosis and 12 585 with grade 1 macro-steatosis. There were 10 320 without micro-steatosis (control), 478 with grade 3 micro-steatosis, 1539 with grade 2 micro-steatosis and 10 404 with grade 1 micro-steatosis. There was no significant difference in all-cause mortality or graft failure among recipients who received a donor organ with any evidence of macro- or micro-steatosis, compared to those receiving non-steatotic grafts. There was increased mortality due to cardiac arrest among recipients of a grade 2 macro-steatosis donor organ. CONCLUSION: This study shows no significant difference in all-cause mortality or graft failure among recipients who received a donor liver with any degree of micro- or macro-steatosis. Further analysis identified increased mortality due to specific aetiologies among recipients receiving donor organs with varying grades of macro- and micro-steatosis.

Prognostic value of early EEG abnormalities in severe stroke patients requiring mechanical ventilation: a pre-planned analysis of the SPICE prospective multicenter study.

INTRODUCTION: Prognostication of outcome in severe stroke patients necessitating invasive mechanical ventilation poses significant challenges. The objective of this study was to assess the prognostic significance and prevalence of early electroencephalogram (EEG) abnormalities in adult stroke patients receiving mechanical ventilation. METHODS: This study is a pre-planned ancillary investigation within the prospective multicenter SPICE cohort study (2017-2019), conducted in 33 intensive care units (ICUs) in the Paris area, France. We included adult stroke patients requiring invasive mechanical ventilation, who underwent at least one intermittent EEG examination during their ICU stay. The primary endpoint was the functional neurological outcome at one year, determined using the modified Rankin scale (mRS), and dichotomized as unfavorable (mRS 4-6, indicating severe disability or death) or favorable (mRS 0-3). Multivariable regression analyses were employed to identify EEG abnormalities associated with functional outcomes. RESULTS: Of the 364 patients enrolled in the SPICE study, 153 patients (49 ischemic strokes, 52 intracranial hemorrhages, and 52 subarachnoid hemorrhages) underwent at least one EEG at a median time of 4 (interquartile range 2-7) days post-stroke. Rates of diffuse slowing (70% vs. 63%, p = 0.37), focal slowing (38% vs. 32%, p = 0.15), periodic discharges (2.3% vs. 3.7%, p = 0.9), and electrographic seizures (4.5% vs. 3.7%, p = 0.4) were comparable between patients with unfavorable and favorable outcomes. Following adjustment for potential confounders, an unreactive EEG background to auditory and pain stimulations (OR 6.02, 95% CI 2.27-15.99) was independently associated with unfavorable outcomes. An unreactive EEG predicted unfavorable outcome with a specificity of 48% (95% CI 40-56), sensitivity of 79% (95% CI 72-85), and positive predictive value (PPV) of 74% (95% CI 67-81). Conversely, a benign EEG (defined as continuous and reactive background activity without seizure, periodic discharges, triphasic waves, or burst suppression) predicted favorable outcome with a specificity of 89% (95% CI 84-94), and a sensitivity of 37% (95% CI 30-45). CONCLUSION: The absence of EEG reactivity independently predicts unfavorable outcomes at one year in severe stroke patients requiring mechanical ventilation in the ICU, although its prognostic value remains limited. Conversely, a benign EEG pattern was associated with a favorable outcome.

Plasma glial fibrillary acidic protein and tau: predictors of neurological outcome after cardiac arrest.

BACKGROUND: The purpose was to evaluate glial fibrillary acidic protein (GFAP) and total-tau in plasma as predictors of poor neurological outcome after out-of-hospital (OHCA) and in-hospital cardiac arrest (IHCA), including comparisons with neurofilament light (NFL) and neuron-specific enolase (NSE). METHODS: Retrospective multicentre observational study of patients admitted to an intensive care unit (ICU) in three hospitals in Sweden 2014-2018. Blood samples were collected at ICU admission, 12 h, and 48 h post-cardiac arrest. Poor neurological outcome was defined as Cerebral Performance Category 3-5 at 2-6 months after cardiac arrest. Plasma samples were retrospectively analysed for GFAP, tau, and NFL. Serum NSE was analysed in clinical care. Prognostic performances were tested with the area under the receiver operating characteristics curve (AUC). RESULTS: Of the 428 included patients, 328 were OHCA, and 100 were IHCA. At ICU admission, 12 h and 48 h post-cardiac arrest, GFAP predicted neurological outcome after OHCA with AUC (95% CI) 0.76 (0.70-0.82), 0.86 (0.81-0.90) and 0.91 (0.87-0.96), and after IHCA with AUC (95% CI) 0.77 (0.66-0.87), 0.83 (0.74-0.92) and 0.83 (0.71-0.95). At the same time points, tau predicted outcome after OHCA with AUC (95% CI) 0.72 (0.66-0.79), 0.75 (0.69-0.81), and 0.93 (0.89-0.96) and after IHCA with AUC (95% CI) 0.61 (0.49-0.74), 0.68 (0.56-0.79), and 0.77 (0.65-0.90). Adding the change in biomarker levels between time points did not improve predictive accuracy compared to the last time point. In a subset of patients, GFAP at 12 h and 48 h, as well as tau at 48 h, offered similar predictive value as NSE at 48 h (the earliest time point NSE is recommended in guidelines) after both OHCA and IHCA. The predictive performance of NFL was similar or superior to GFAP and tau at all time points after OHCA and IHCA. CONCLUSION: GFAP and tau are promising biomarkers for neuroprognostication, with the highest predictive performance at 48 h after OHCA, but not superior to NFL. The predictive ability of GFAP may be sufficiently high for clinical use at 12 h after cardiac arrest.

Prognostication for surgically treated papillary renal cell carcinoma: which model is the optimal choice?

Tweetable abstract Surgically treated papillary renal cell carcinoma shows distinct prognosis and needs specific prognostic models for counseling, follow-up and high-risk patient identification. Our goal is to summarize and compare currently recommended models.

Factors related to accurate clinicians' prediction of survival: an international multicenter study in East Asia.

PURPOSE: Recent guidelines for prognostic evaluation recommend clinicians' prediction of survival (CPS) for survival prediction in patients with advanced cancer. However, CPS is often inaccurate and optimistic. Studies on factors associated with overestimation or underestimation of CPS are limited. We aimed to investigate the factors associated with the overestimation and underestimation of CPS in patients with far-advanced cancer. METHODS: The current study was a secondary analysis of an international multicenter prospective cohort study, which enrolled newly admitted patients with advanced cancer in palliative care units (PCUs) in Japan, Korea, and Taiwan from 2017 to 2018. We obtained the temporal CPS at enrollment and performed multivariate logistic regression analysis to identify the factors associated with "underestimation (less than 33% of actual survival)" and "overestimation (more than 33% of actual survival)." RESULTS: A total of 2571 patients were assessed and admitted in 37 PCUs between January 2017 and September 2018. Older age (adjusted odds ratio [aOR] 1.01; 95% confidence interval [CI] 1.01-1.02; P < 0.01) and reduced oral intake (aOR 0.68; 95% CI 0.51-0.89; P < 0.01) were identified as significant factors associated with underestimation. Dyspnea (aOR 1.28; 95% CI 1.06-1.54; P = 0.01) and hyperactive delirium (aOR 1.34; 95% CI 1.05-1.72; P = 0.02) were identified as significant factors associated with overestimation. CONCLUSION: Older age was related to underestimation, while dyspnea and hyperactive delirium were related to overestimation of CPS for patients with weeks of survival. However, reduced oral intake was less likely to lead to underestimation.

Impact of Automated Prognostication on Traumatic Brain Injury Care: A Focus Group Study.

BACKGROUND: Prognosticating outcomes for traumatic brain injury (TBI) patients is challenging due to the required specialized skills and variability among clinicians. Recent attempts to standardize TBI prognosis have leveraged machine learning (ML) methodologies. This study evaluates the necessity and influence of ML-assisted TBI prognostication through healthcare professionals' perspectives via focus group discussions. METHODS: Two virtual focus groups included ten key TBI care stakeholders (one neurosurgeon, two emergency clinicians, one internist, two radiologists, one registered nurse, two researchers in ML and healthcare and one patient representative). They answered six open-ended questions about their perceptions and potential ML use in TBI prognostication. Transcribed focus group discussions were thematically analyzed using qualitative data analysis software. RESULTS: The study captured diverse perceptions and interests in TBI prognostication across clinical specialties. Notably, certain clinicians who currently do not prognosticate expressed an interest in doing so independently provided they had access to ML support. Concerns included ML's accuracy and the need for proficient ML researchers in clinical settings. The consensus suggested using ML as a secondary consultation tool and promoting collaboration with internal or external research resources. Participants believed ML prognostication could enhance disposition planning and standardize care regardless of clinician expertise or injury severity. There was no evidence of perceived bias or interference during the discussions. CONCLUSION: Our findings revealed an overall positive attitude toward ML-based prognostication. Despite raising multiple concerns, the focus group discussions were particularly valuable in underscoring the potential of ML in democratizing and standardizing TBI prognosis practices.

'How long do you think?' Unresponsive dying patients in a specialist palliative care service: A consecutive cohort study.

BACKGROUND: Predicting length of time to death once the person is unresponsive and deemed to be dying remains uncertain. Knowing approximately how many hours or days dying loved ones have left is crucial for families and clinicians to guide decision-making and plan end-of-life care. AIM: To determine the length of time between becoming unresponsive and death, and whether age, gender, diagnosis or location-of-care predicted length of time to death. DESIGN: Retrospective cohort study. Time from allocation of an Australia-modified Karnofsky Performance Status (AKPS) 10 to death was analysed using descriptive narrative. Interval-censored survival analysis was used to determine the duration of patient's final phase of life, taking into account variation across age, gender, diagnosis and location of death. SETTING/PARTICIPANTS: A total of 786 patients, 18 years of age or over, who received specialist palliative care: as hospice in-patients, in the community and in aged care homes, between January 1st and October 31st, 2022. RESULTS: The time to death after a change to AKPS 10 is 2 days (n = 382; mean = 2.1; median = 1). Having adjusted for age, cancer, gender, the standard deviation of AKPS for the 7-day period prior to death, the likelihood of death within 2 days is 47%, with 84% of patients dying within 4 days. CONCLUSION: This study provides valuable new knowledge to support clinicians' confidence when responding to the 'how long' question and can inform decision-making at end-of-life. Further research using the AKPS could provide greater certainty for answering 'how long' questions across the illness trajectory.

Post Cardiac Arrest Care in the Cardiac Intensive Care Unit.

PURPOSE OF REVIEW: Cardiac arrests constitute a leading cause of mortality in the adult population and cardiologists are often tasked with the management of patients following cardiac arrest either as a consultant or primary provider in the cardiac intensive care unit. Familiarity with evidence-based practice for post-cardiac arrest care is a requisite for optimizing outcomes in this highly morbid group. This review will highlight important concepts necessary to managing these patients. RECENT FINDINGS: Emerging evidence has further elucidated optimal care of post-arrest patients including timing for routine coronary angiography, utility of therapeutic hypothermia, permissive hypercapnia, and empiric aspiration pneumonia treatment. The complicated state of multi-organ failure following cardiac arrest needs to be carefully optimized by the clinician to prevent further neurologic injury and promote systemic recovery. Future studies should be aimed at understanding if these findings extend to specific patient populations, especially those at the highest risk for poor outcomes.

Guidelines for Neuroprognostication in Critically Ill Adults with Moderate-Severe Traumatic Brain Injury.

BACKGROUND: Moderate-severe traumatic brain injury (msTBI) carries high morbidity and mortality worldwide. Accurate neuroprognostication is essential in guiding clinical decisions, including patient triage and transition to comfort measures. Here we provide recommendations regarding the reliability of major clinical predictors and prediction models commonly used in msTBI neuroprognostication, guiding clinicians in counseling surrogate decision-makers. METHODS: Using the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) methodology, we conducted a systematic narrative review of the most clinically relevant predictors and prediction models cited in the literature. The review involved framing specific population/intervention/comparator/outcome/timing/setting (PICOTS) questions and employing stringent full-text screening criteria to examine the literature, focusing on four GRADE criteria: quality of evidence, desirability of outcomes, values and preferences, and resource use. Moreover, good practice recommendations addressing the key principles of neuroprognostication were drafted. RESULTS: After screening 8125 articles, 41 met our eligibility criteria. Ten clinical variables and nine grading scales were selected. Many articles varied in defining "poor" functional outcomes. For consistency, we treated "poor" as "unfavorable". Although many clinical variables are associated with poor outcome in msTBI, only the presence of bilateral pupillary nonreactivity on admission, conditional on accurate assessment without confounding from medications or injuries, was deemed moderately reliable for counseling surrogates regarding 6-month functional outcomes or in-hospital mortality. In terms of prediction models, the Corticosteroid Randomization After Significant Head Injury (CRASH)-basic, CRASH-CT (CRASH-basic extended by computed tomography features), International Mission for Prognosis and Analysis of Clinical Trials in TBI (IMPACT)-core, IMPACT-extended, and IMPACT-lab models were recommended as moderately reliable in predicting 14-day to 6-month mortality and functional outcomes at 6 months and beyond. When using "moderately reliable" predictors or prediction models, the clinician must acknowledge "substantial" uncertainty in the prognosis. CONCLUSIONS: These guidelines provide recommendations to clinicians on the formal reliability of individual predictors and prediction models of poor outcome when counseling surrogates of patients with msTBI and suggest broad principles of neuroprognostication.

Cerebrospinal Creatine Kinase BB Isoenzyme: A Biomarker for Predicting Outcome After Cardiac Arrest.

BACKGROUND: Cerebrospinal fluid creatine kinase BB isoenzyme (CSF CK-BB) after cardiac arrest (CA) has been shown to have a high positive predictive value for poor neurological outcome, but it has not been evaluated in the setting of targeted temperature management (TTM) and modern CA care. We aimed to evaluate CSF CK-BB as a prognostic biomarker after CA. METHODS: We performed a retrospective cohort study of patients with CA admitted between 2010 and 2020 to a three-hospital health system who remained comatose and had CSF CK-BB assayed between 36 and 84 h after CA. We examined the proportion of patients at hospital discharge who achieved favorable or intermediate neurological outcome, defined as Cerebral Performance Category score of 1-3, compared with those with poor outcome (Cerebral Performance Category score 4-5) for various CSF CK-BB thresholds. We also evaluated additive value of bilateral absence of somatosensory evoked potentials (SSEPs). RESULTS: Among 214 eligible patients, the mean age was 54.7 ± 4.8 years, 72% of patients were male, 33% were nonwhite, 17% had shockable rhythm, 90% were out-of-hospital CA, and 83% received TTM. A total of 19 (9%) awakened. CSF CK-BB ≥ 230 U/L predicted a poor outcome at hospital discharge, with a specificity of 100% (95% confidence interval [CI] 82-100%) and sensitivity of 69% (95% CI 62-76%). When combined with bilaterally absent N20 response on SSEP, specificity remained 100% while sensitivity increased to 80% (95% CI 73-85%). Discordant CK-BB and SSEP findings were seen in 13 (9%) patients. CONCLUSIONS: Cerebrospinal fluid creatine kinase BB isoenzyme levels accurately predicted poor neurological outcome among CA survivors treated with TTM. The CSF CK-BB cutoff of 230 U/L optimizes sensitivity to 69% while maintaining a specificity of 100%. CSF CK-BB could be a useful addition to multimodal neurological prognostication after CA.

How Has the Total Hip Arthroplasty Patient Population Changed? A Ten-Year Analysis of Total Hip Arthroplasty Patients From 2013 to 2022: A Retrospective, Single-Center Study.

BACKGROUND: Over the past decades, utilization of total hip arthroplasty (THA) has steadily increased. Understanding the demographic trends of THA patients can assist in projecting access to care. This study sought to assess the temporal trends in THA patient baseline characteristics and socioeconomic factors. METHODS: We retrospectively analyzed 16,296 patients who underwent primary elective THA from January 1, 2013, to December 31, 2022. Demographic data, including age, sex, race, body mass index (BMI), Charlson comorbidity index, insurance, and socioeconomic status, as determined by median income by patients' zip code, were collected. The trends of these data were analyzed using the Mann-Kendall test. RESULTS: Over the past decade at our institution, patient age (2013: 62.1 years to 2022: 65.1 years, P = .001), BMI (2013: 29.0 to 2022: 29.5, P = .020), and mean Charlson comorbidity index (2013: 2.4 to 2022: 3.1, P = .001) increased. The proportion of Medicare patients increased from 48.4% in 2013 to 54.9% in 2022 (P = .001). The proportion of African American patients among the THA population increased from 11.3% in 2013 to 13.0% in 2022 (P = .012). Over this period, 90-day readmission and 1-year revision rates did not significantly change (2013: 4.8 and 3.0% to 2022: 3.4 and 1.4%, P = .107 and P = .136, respectively). The proportion of operations using robotic devices also significantly increased (2013: 0% to 2022: 19.1%; P < .001). CONCLUSIONS: In the past decade, the average age, BMI, and comorbidity burden of THA patients have significantly increased, suggesting improved access to care for these populations. Similarly, there have been improvements in access to care for African American patients. Along with these changes in patient demographics, we found no change in 90-day readmission or 1-year revision rates. Continued characterization of the THA patient population is vital to understanding this demographic shift and educating future strategies and improvements in patient care.

The Evolving Role of Genomic Testing in Early Breast Cancer: Implications for Diagnosis, Prognosis, and Therapy.

Multigene prognostic genomic assays have become indispensable in managing early breast cancer (EBC), offering crucial information for risk stratification and guiding adjuvant treatment strategies in conjunction with traditional clinicopathological parameters. The American Society of Clinical Oncology (ASCO) guidelines endorse these assays, though some clinical contexts still lack definitive recommendations. The dynamic landscape of EBC management demands further refinement and optimization of genomic assays to streamline their incorporation into clinical practice. The breast cancer community is poised at the brink of transformative advances in enhancing the clinical utility of genomic assays, aiming to significantly improve the precision and effectiveness of both diagnosis and treatment for women with EBC. This article methodically examines the testing methodologies, clinical validity and utility, costs, diagnostic frameworks, and methodologies of the established genomic tests, including the Oncotype Dx Breast Recurrence Score®, MammaPrint, Prosigna®, EndoPredict®, and Breast Cancer Index (BCI). Among these tests, Prosigna and EndoPredict® have at present been validated only on a prognostic level, while Oncotype Dx, MammaPrint, and BCI hold both a prognostic and predictive role. Oncologists and pathologists engaged in the management of EBC will find in this review a thorough comparison of available genomic assays, as well as strategies to optimize the utilization of the information derived from them.

Synergizing Survival: Uniting Acute Gastrointestinal Injury Grade and Disease Severity Scores in Critical Care Prognostication.

How to cite this article: Patnaik RK, Karan N. Synergizing Survival: Uniting Acute Gastrointestinal Injury Grade and Disease Severity Scores in Critical Care Prognostication. Indian J Crit Care Med 2024;28(6):529-530.

[The characteristics of medical technical task working out as a factor of successful implementation of project of public-private partnership in health care].

The application of mathematical modeling approaches based on factual demand of the population of territories in setting of medical and technical tasks makes it possible to significantly optimize costs of construction and equipping primary health care objects. This is confirmed by both corresponding calculations and results of analysis. This operation is oriented both on structural divisions of regional executive authorities responsible for setting of medical and technical tasks, and on investment companies implementing projects in health care.

Clinical features, haemodynamics, and outcomes of heart failure with preserved ejection fraction in coarctation of aorta.

AIMS: There are similarities in the pathogenesis of cardiac remodelling and dysfunction in heart failure with preserved ejection fraction (HFpEF) and coarctation of aorta (COA). We hypothesized that clinical HFpEF would be highly prevalent in adults with COA, and that the presence of HFpEF would increase the risk of mortality in this population. The aim of this study was to define the clinical features, haemodynamics, and prognostic implications of HFpEF in COA. METHODS AND RESULTS: Consecutive adults with repaired COA that underwent right heart catheterization were identified retrospectively. HFpEF was defined as heart failure symptoms (exertional dyspnoea or fatigue), preserved left ventricular ejection fraction ≥50%, and pulmonary artery wedge pressure at rest >15 mmHg. Of 99 COA patients, 32 (32%) had HFpEF. The correlates of HFpEF were obesity (adjusted odds ratio [OR] 4.15, 95% confidence interval [CI] 1.31-13.2), atrial fibrillation (adjusted OR 3.13, 95% CI 1.00-10.7), total arterial compliance index (adjusted OR 0.12, 95% CI 0.06-0.41 per 1 ml/mmHg*m2), and pulmonary artery compliance index (adjusted OR 0.36, 95% CI 0.15-0.56 per 1 ml/mmHg*m2). Of 99 patients, 24 (24%) died and 5 (5%) underwent heart transplant. The 10-year cumulative incidence of death/transplant was higher in COA patients with HFpEF compared with patients without HFpEF (39% vs. 12%, p = 0.001). The presence of HFpEF was associated with increased risk of death/transplant (adjusted hazard ratio 1.68, 95% CI 1.16-3.11). CONCLUSIONS: Heart failure with preserved ejection fraction is common in adults with COA and is associated with greater risk of death/transplant, emphasizing a pressing need for interventions to prevent and treat HFpEF in COA.

A locally optimised machine learning approach to early prognostication of long-term neurological outcomes after out-of-hospital cardiac arrest.

Background: Out-of-hospital cardiac arrest (OHCA) represents a major burden for society and health care, with an average incidence in adults of 67 to 170 cases per 100,000 person-years in Europe and in-hospital survival rates of less than 10%. Patients and practitioners would benefit from a prognostication tool for long-term good neurological outcomes. Objective: We aim to develop a machine learning (ML) pipeline on a local database to classify patients according to their neurological outcomes and identify prognostic features. Methods: We collected clinical and biological data consecutively from 595 patients who presented OHCA and were routed to a single regional cardiac arrest centre in the south of France. We applied recursive feature elimination and ML analyses to identify the main features associated with a good neurological outcome, defined as a Cerebral Performance Category score less than or equal to 2 at six months post-OHCA. Results: We identified 12 variables 24 h after admission, capable of predicting a six-month good neurological outcome. The best model (extreme gradient boosting) achieved an AUC of 0.96 and an accuracy of 0.92 in the test cohort. Conclusion: We demonstrated that it is possible to build accurate, locally optimised prediction and prognostication scores using datasets of limited size and breadth. We proposed and shared a generic machine-learning pipeline which allows external teams to replicate the approach locally.