Methylation profiling in the contemporary management of meningioma.

BACKGROUND: The last decade has seen major international research efforts focus on better understanding disease heterogeneity in meningioma. Multiple molecular platforms have generated significant biological and clinical utility, and there is a need to translate these findings into routine clinical practice. Here we review the role of DNA methylation profiling in meningioma and advocate for its widespread adoption. METHODS: We review modern DNA methylation-based classification and outcome prediction tools in meningioma. Biological classifiers, which were constructed agnostic to outcome using unsupervised approaches, outcome predictors, and liquid biopsy models are discussed in detail. RESULTS: DNA methylation has been used for biological classification and outcome in meningioma with considerable success. Several groups have proposed novel molecular classification systems which share similar features with one another and outperform WHO grade in their ability to predict outcome and explain subgroup-specific biological processes. In addition, recent studies have suggested a role for methylation-based liquid-biopsy in meningioma, which represents an exciting avenue for further exploration. CONCLUSIONS: DNA methylation profiling has been revolutionary in meningioma. There is a need for widespread adoption of these approaches to personalize care and inform clinical trial design.

Machine learning and brain-computer interface approaches in prognosis and individualized care strategies for individuals with amyotrophic lateral sclerosis: A systematic review.

Amyotrophic lateral sclerosis (ALS) characterized by progressive degeneration of motor neurons is a debilitating disease, posing substantial challenges in both prognosis and daily life assistance. However, with the advancement of machine learning (ML) which is renowned for tackling many real-world settings, it can offer unprecedented opportunities in prognostic studies and facilitate individuals with ALS in motor-imagery tasks. ML models, such as random forests (RF), have emerged as the most common and effective algorithms for predicting disease progression and survival time in ALS. The findings revealed that RF models had an excellent predictive performance for ALS, with a testing R2 of 0.524 and minimal treatment effects of 0.0717 for patient survival time. Despite significant limitations in sample size, with a maximum of 18 participants, which may not adequately reflect the population diversity being studied, ML approaches have been effectively applied to ALS datasets, and numerous prognostic models have been tested using neuroimaging data, longitudinal datasets, and core clinical variables. In many literatures, the constraints of ML models are seldom explicitly enunciated. Therefore, the main objective of this research is to provide a review of the most significant studies on the usage of ML models for analyzing ALS. This review covers a variation of ML algorithms involved in applications in ALS prognosis besides, leveraging ML to improve the efficacy of brain-computer interfaces (BCIs) for ALS individuals in later stages with restricted voluntary muscular control. The key future advances in individualized care and ALS prognosis may include the advancement of more personalized care aids that enable real-time input and ongoing validation of ML in diverse healthcare contexts.

The Pupillary Light-Off Reflex in Acute Disorders of Consciousness.

BACKGROUND: In intensive care patients with disorders of consciousness, the pupillary light reflex is a measure of pupillary parasympathetic function. By contrast, the pupillary light-off reflex leads to pupil dilation in response to an abrupt change from light to darkness ("light-off") and reflects combined parasympathetic and sympathetic pupillary function. To our knowledge, this reflex has not been systematically investigated in patients with disorders of consciousness. We hypothesized that the pupillary light-off reflex correlates with consciousness levels after acute brain injury. METHODS: From November 2022 to March 2023, we enrolled 100 study participants: 25 clinically unresponsive (coma or unresponsive wakefulness syndrome) and 25 clinically low-responsive (minimally conscious state or better) patients from the intensive care units of a tertiary referral center, and 50 age-matched and sex-matched healthy controls. Exclusion criteria were active or chronic eye disease. We used automated pupillometry to assess the pupillary light-off reflex and the pupillary light reflex of both eyes under scotopic conditions in all study participants. RESULTS: The pupillary light-off reflex was strongly correlated with consciousness levels (r = 0.62, p < 0.001), the increase in pupillary diameters being smallest in unresponsive patients (mean ± standard deviation 20% ± 21%), followed by low-responsive patients (mean ± standard deviation 47% ± 26%) and healthy controls (mean ± standard deviation 67% ± 17%; p < 0.001). Similar yet less pronounced patterns were observed for the pupillary light reflex. Twenty-one of 25 (84%) unresponsive patients had preserved pupillary light reflexes, but only seven (28%) had fully preserved pupillary light-off reflexes (p < 0.0001). Of these 7 patients, five (71%) regained awareness. CONCLUSIONS: The pupillary light-off reflex may be more sensitive to consciousness levels than the pupillary light reflex. The clinical implications of this finding seem worthy of further investigation, particularly regarding possible benefits for neuromonitoring and prognostication after brain injury.

Angiogenesis and multiple myeloma: Exploring prognostic potential of adrenomedullin.

BACKGROUND: Adrenomedullin (AM) is a multifunctional peptide which under basal conditions mainly regulates vasodilation and maintains vascular integrity but is also implicated in the pathogenesis of several malignancies, including multiple myeloma (MM). It has been shown that adrenomedullin is expressed by human myeloma cell lines and that it enhances MM-driven angiogenesis. However, the clinical impact of AM remains unknown. MATERIALS AND METHODS: On that basis, we enrolled 32 newly diagnosed multiple myeloma patients (NDMM) and studied the potential of AM as a prognostic biomarker. RESULTS: We report that elevated levels of AM trend with suboptimal treatment response and inferior survival of NDMM patients.

Proceedings of the 2024 Transplant AI Symposium.

With recent advancements in deep learning (DL) techniques, the use of artificial intelligence (AI) has become increasingly prevalent in all fields. Currently valued at 9.01 billion USD, it is a rapidly growing market, projected to increase by 40% per annum. There has been great interest in how AI could transform the practice of medicine, with the potential to improve all healthcare spheres from workflow management, accessibility, and cost efficiency to enhanced diagnostics with improved prognostic accuracy, allowing the practice of precision medicine. The applicability of AI is particularly promising for transplant medicine, in which it can help navigate the complex interplay of a myriad of variables and improve patient care. However, caution must be exercised when developing DL models, ensuring they are trained with large, reliable, and diverse datasets to minimize bias and increase generalizability. There must be transparency in the methodology and extensive validation of the model, including randomized controlled trials to demonstrate performance and cultivate trust among physicians and patients. Furthermore, there is a need to regulate this rapidly evolving field, with updated policies for the governance of AI-based technologies. Taking this in consideration, we summarize the latest transplant AI developments from the Ajmera Transplant Center's inaugural symposium.

Prognostic significance of paramagnetic rim lesions in multiple sclerosis: A systematic review.

The diagnostic potential of paramagnetic rim lesions (PRLs) has been previously established; however, the prognostic significance of these lesions has not previously been consistently described. This study aimed to establish the prognostic role of PRLs in MS with respect to the Expanded Disability Status Scale (EDSS) and rates of disability progression. Databases of PubMed, EMBASE, Scopus and reference lists of selected articles were searched up to 29/04/2023. The review was conducted in accordance with PRISMA guidelines and was registered prospectively on PROSPERO (CRD42023422052). 7 studies were included in the final review. All of the eligible studies found that patients with PRLs tend to have higher baseline EDSS scores. Longitudinal assessments revealed greater EDSS progression in patients with PRLs over time in most studies. However, the effect of location of PRLs within the central nervous system were not assessed across the studies. Only one study investigated progression independent of relapse activity (PIRA) and showed that this clinical entity occurred in a greater proportion in patients with PRLs. This review supports PRLs as a predictor of EDSS progression. This measure has widespread applicability, however further multicentre studies are needed. Future research should explore the impact of PRLs on silent disability, PIRA, take into account different MS phenotypes and the topography of PRLs in prognosis.

Cardiac arrest centres for patients with non-traumatic cardiac arrest: A systematic review.

INTRODUCTION: Regionalisation and organised pathways of care using specialist centre hospitals can improve outcomes for critically ill patients. Cardiac arrest centre hospitals (CAC) may optimise the delivery of post-resuscitation care. The International Liaison Committee on Resuscitation (ILCOR) has called for a review of the current evidence base. AIM: This systematic review aimed to assess the effect of cardiac arrest centres for patients with non-traumatic cardiac arrest. METHODS: Articles were included if they met the prospectively registered (PROSPERO) inclusion criteria. These followed the PICOST framework for ILCOR systematic reviews. A strict definition for a CAC was used, reflecting current position statements and clinical practice. MEDLINE, Embase and the Cochrane Library were searched using pre-determined criteria from inception to 31 December 2023. Risk of bias was assessed using Cochrane's Risk of Bias tool and ROBINS-I. The certainty of evidence for each outcome was assessed using the GRADE approach. Substantial heterogeneity precluded meta-analysis and a narrative synthesis with visualisation of effect estimates in forest plots was performed. RESULTS: Sixteen studies met eligibility criteria, including data on over 145,000 patients. One was a randomised controlled trial (RCT) at low risk of bias and the remainder were observational studies, all at moderate or serious risk of bias. All studies included adults with out-of-hospital cardiac arrest. One study used initial shockable rhythm as an inclusion criterion and most studies (n = 12) included patients regardless of prehospital ROSC status. Two studies, including the RCT, excluded patients with ST elevation. Survival to hospital discharge with a favourable neurological outcome was reported by 11 studies and favoured CAC care in all observational studies, but the RCT showed no difference. Survival to 30 days with a favourable neurological outcome was reported by two observational studies and favoured CAC care in both. Survival to hospital discharge was reported by 13 observational studies and generally favoured CAC care. Survival to 30 days was reported by two studies, where the observational study favoured CAC care, but the RCT showed no difference. CONCLUSION: This review supports a weak recommendation that adults with out-of-hospital cardiac arrest are cared for at CACs based on very low certainty of evidence. Randomised evidence has not confirmed the benefits of CACs found in observational studies, however this RCT was a single trial in a very specific setting and a population without ST elevation on post-ROSC ECG. The role of CACs in shockable and non-shockable subgroups, direct versus secondary transfer, as well as the impact of increased transport time and bypassing local hospitals remains unclear.

High frequency oscillations may improve somatosensory evoked potential detection of good outcomes in disorders of consciousness secondary to acute neurologic injury.

BACKGROUND: Somatosensory evoked potentials (SEPs) are highly specific predictors of poor prognosis in hypoxic-ischemic coma when cortical responses (N20s) are absent. However, bilateral N20 presence is nonspecific for good outcomes. High-frequency oscillations (HFOs) in the SEP waveform predict neurologic recovery in animals, but clinical applications are poorly understood. We sought to develop a clinical measure of HFOs to potentially improve detection of good outcomes in coma. MATERIALS AND METHODS: We collected SEP waveform data from all comatose inpatients (GCS<=8) who underwent neurologic prognostication from 2020 to 2022 at Johns Hopkins Hospital. We developed a novel measure - HFO evoked to spontaneous ratios (HFO-ESRs) - and applied this to those patients with bilaterally present N20s using both standard univariate classification and cubic kernal vector machine (SVM) models to predict the last documented in-hospital Glasgow Coma Scale (GCS) prior to discharge or death. RESULTS: Of 58 total patients, 34 (58.6%) had bilaterally present N20s. Of these, 14 had final GCS>=9, and 20 had final GCS<=8. Mean age was 52 (+/- 17) years, 20.1% female. Etiologies of coma were primarily global hypoxic-ischemic brain injury (79.4%), intracranial hemorrhage (11.8%), and traumatic brain injury (2.9%). In univariate classification, the addition of averaged HFO-ESRs to bilaterally present N20s predicted final GCS>=9 with 68% specificity. The SVM model further improved specificity to 85%. CONCLUSIONS: In this pilot investigation, we developed a novel clinical measure of SEP HFOs. Incorporation of this measure may improve the specificity of the SEP to predict in-hospital GCS outcomes in coma, but requires further validation in specific neurologic injuries and with longitudinal outcomes.

The Usefulness of the CHA2DS2-VASc Score to Predict Outcomes in Patients with Infective Endocarditis.

Introduction: Despite diagnostic and therapeutic advances, infective endocarditis (IE) is still associated with high mortality rates. Currently, there are no good prognostic tools for the risk assessment of patients with IE. The CHA2DS2-VASc score, used to estimate the risk of ischemic stroke in patients with non-valvular atrial fibrillation (AF), has been shown to be a powerful predictor of stroke and death in patients without known AF associated with other cardiovascular conditions. Objective: We aimed to evaluate the usefulness of the CHA2DS2-VASc score as a prognostic tool in a population of patients with IE. Methods: The Rabin Medical Center Endocarditis Team (RMCET) registry is a retrospective cohort of all patients evaluated at our center due to acute or sub-acute bacterial endocarditis. The CHA2DS2-VASc score was extracted for all patients. All-cause mortality was depicted for all patients. Results: The cohort included 330 patients with a mean age of 65.2 ± 14.7 years (70% men). During a median follow-up of 24 months [IQR 4.7-48.6], 121 (36.7%) patients died. The median CHA2DS2-VASc score was 3, and any score above 2 was associated with increased overall mortality (50.8% vs. 19.9%, p < 0.001). A multivariate model incorporating important confounders not included in the CHA2DS2-VASc model showed consistent results with a risk increase of 121% for the higher CHA2DS2-VASc score groups (HR 2.21 [CI 1.12-4.39], p = 0.023). Conclusions: IE currently has no good risk stratification models for clinical practice. The CHA2DS2-VASc score might serve as a simple and available tool to stratify risk among patients with IE.

Early point-of-care echocardiography as a predictive factor for absence of return of spontaneous circulatory in out-of-hospital cardiac arrests: A multicentre observational study.

INTRODUCTION: Early assessment of the prognosis of a patient in cardiac arrest during cardiopulmonary resuscitation is highly challenging. This study aims to evaluate the predictive outcome value of early point-of-care ultrasound (POCUS) in out-of-hospital settings. METHODS: This observational, prospective, multicentre study's primary endpoint was the positive predictive value (PPV) of POCUS cardiac standstill within the first 12 min of advanced life support (ALS) initiation in determining the absence of return of spontaneous circulation (ROSC). A multivariate logistic regression model was constructed with adjustments for known predictive variables typically used in termination of resuscitation (TOR) rules. RESULTS: A total of 293 patients were analysed, with a mean age of 66.6 ± 14.6 years, and a majority were men (75.8%). POCUS was performed on average 7.9 ± 2.6 min after ALS initiation. Among patients with cardiac standstill (72.4%), 16.0% achieved ROSC compared with 48.2% in those with visible cardiac motions. The PPV of early POCUS cardiac standstill for the absence of ROSC was 84.0%, 95% CI [78.3-88.6]. In multivariable analysis, only POCUS cardiac standstill (adjusted odds ratio [aOR] 3.89, 95% CI [1.86-8.17]) and end-tidal CO2 (ETCO2) value ≤37 mmHg (aOR 4.27, 95% CI [2.21-8.25]) were associated with the absence of ROSC. CONCLUSION: Early POCUS cardiac standstill during CPR for out-of-hospital cardiac arrest was a reliable predictor of the absence of ROSC. However, its presence alone was not sufficient to determine the termination of resuscitation efforts. TRIAL REGISTRATION: ClinicalTrials.gov Identifier: NCT03494153. Registered March 29, 2018.

Prognostic performance of gray-white matter ratio in adult out-of-hospital cardiac arrest patients after receiving extracorporeal cardiopulmonary resuscitation.

BACKGROUND: Gray-to-white matter ratio (GWR), measured by computed tomography (CT), is commonly used to predict poor neurological outcomes after out-of-hospital cardiac arrest (OHCA). The prognostic performance of GWR in OHCA patients receiving extracorporeal cardiopulmonary resuscitation (ECPR) is not known. METHODS: This study is a secondary analysis of data from the SAVE-J II registry, a retrospective, multicenter study. Participants were divided into four groups according to average GWR (aGWR) values ranging from 1.00 to 1.39, separated by 0.1 intervals. The aGWR values were calculated for bilateral basal ganglia, centrum semiovale, and high convexity obtained by head CT within 24 h after ECPR. Primary outcome was poor neurological outcomes at 30-day. RESULTS: In total, 1,146 OHCA patients treated with ECPR were included in our analysis. Overall, participants with lower aGWR more likely had poor neurological outcomes, aGWR 1.00-1.09 (94.6%), aGWR 1.10-1-19 (87.8%), aGWR 1.20-1.29 (78.5%), and aGWR 1.30-1.39 (70.3%). Multivariable logistic regression showed that lower aGWR was associated with poor neurological outcome at 30-day, aGWR 1.30-1.39: reference, aGWR 1.00-1.09: adjusted odds ratio (aOR) 10.01 (95% confidence interval (CI) [3.58-27.99]), aGWR 1.10-1.19: aOR 4.83 (95% CI [2.31-10.12]), aGWR 1.20-1.29: aOR 2.16 (95% CI [1.02-4.55]). Receiver operating characteristic curve analysis revealed that the prognostic performance of aGWR had an area under the curve of 0.628, 95% CI [0.59-0.66]). The aGWR threshold of 1.005 for predicting poor neurological outcome reached 100% specificity with 0.1% sensitivity. CONCLUSION: Early neuro-prognostication depending on GWR may not be sufficient after ECPR and requires a multimodal approach.

[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.

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.

Importance of risk assessment, endoscopic hemostasis, and recent advancements in the management of acute non-variceal upper gastrointestinal bleeding.

Acute non-variceal upper gastrointestinal bleeding (ANVUGIB) is a common medical emergency in clinical practice. While the incidence has significantly reduced, the mortality rates have not undergone a similar reduction in the last few decades, thus presenting a significant challenge. This editorial outlines the key causes and risk factors of ANVUGIB and explores the current standards and recent updates in risk assessment scoring systems for predicting mortality and endoscopic treatments for achieving hemostasis. Since ANUVGIB predominantly affects the elderly population, the impact of comorbidities may be responsible for the poor outcomes. A thorough drug history is important due to the increasing use of antiplatelet agents and anticoagulants in the elderly. Early risk stratification plays a crucial role in deciding the line of management and predicting mortality. Emerging scoring systems such as the ABC (age, blood tests, co-morbidities) score show promise in predicting mortality and guiding clinical decisions. While conventional endoscopic therapies remain cornerstone approaches, novel techniques like hemostatic powders and over-the-scope clips offer promising alternatives, particularly in cases refractory to traditional modalities. By integrating validated scoring systems and leveraging novel therapeutic modalities, clinicians can enhance patient care and mitigate the substantial morbidity and mortality associated with ANVUGIB.

Prognosticating accelerated deterioration in skeletally mature adolescent idiopathic scoliosis curves of 40-50° using uniplanar radiographic measures of axial rotation.

PURPOSE: The management of adolescent idiopathic scoliosis (AIS) curves between 40 and 50° is controversial. Here, we investigated the prognostic significance of simple radiographic rotational parameters to identify curves of this magnitude with accelerated deterioration following skeletal maturity. METHODS: Seventy-three patients were identified with AIS and Cobb angles of the major curve between 40 and 50° at skeletal maturity. We defined fast progressive curves as those increasing by ≥ 2° per year after skeletal maturity. From the apical vertebra of the major curve upon presentation and skeletal maturity, we determined the modified Nash-Moe index (×100), and from thoracic major curves, the Rib Index. T tests were performed to compare fast-progressive curves with those that deteriorated by < 2° per year. Receiver operator characteristic (ROC) curves were plotted to establish optimal cutoffs, sensitivity, and specificity measures for rotational parameters. RESULTS: The average duration of follow-up post was 11.8 ± 7.3 years. Thirteen out of seventy-three patients were fast progressors. The modified Nash-Moe index was similar between groups at presentation (p = 0.477) but significantly higher in fast progressors than non-fast progressors at maturity for major thoracic curves (25.40 ± 6.60 vs. 19.20 ± 4.40, p < 0.001). Rib Index values were also higher among fast progressors at skeletal maturity (2.50 ± 0.90 vs. 1.80 ± 0.60, p = 0.026). An ROC curve for a modified Nash-Moe index of 0.235 for thoracic curves achieved an area under the curve (AUC) of 0.76 for discriminating fast progressors. A threshold of 1.915 for Rib Index at maturity achieved an AUC of 0.72 for discriminating fast progressors. In combining both rotational parameters, an AUC of 0.81 was achieved. CONCLUSION: These simple rotational parameters may be useful to predict fast progression in 40-50° AIS curves following skeletal maturity indicated for early fusion, but further validation upon larger cohorts and non-thoracic major curves is required.

Prognostic Implication of Ventricular Volumetry in Early Brain Computed Tomography after Cardiac Arrest.

Brain swelling after cardiac arrest may affect brain ventricular volume. This study aimed to investigate the prognostic implications of ventricular volume on early thin-slice brain computed tomography (CT) after cardiac arrest. We measured the gray-to-white matter ratio (GWR) and the characteristics and volumes of the lateral, third, and fourth ventricles. The primary outcome was a poor 6-month neurological outcome. Of the 166 patients, 115 had a poor outcome. The fourth ventricle was significantly smaller in the poor outcome group (0.58 cm3 [95% CI, 0.43-0.80]) than in the good outcome group (0.74 cm3 [95% CI, 0.68-0.99], p < 0.001). Ventricular characteristics and other ventricular volumes did not differ between outcome groups. The area under the curve for the fourth ventricular volume was 0.68, comparable to 0.69 for GWR. Lower GWR (<1.09) and lower fourth ventricular volume (<0.41 cm3) predicted poor outcomes with 100% specificity and sensitivities of 8.7% (95% CI, 4.2-15.4) and 20.9% (95% CI, 13.9-29.4), respectively. Combining these measures improved the sensitivity to 25.2% (95% CI, 17.6-34.2). After adjusting for covariates, the fourth ventricular volume was independently associated with neurologic outcome. A marked decrease in fourth ventricular volume, with concomitant hypoattenuation on CT scans, more accurately predicted outcomes.

The transformative potential of artificial intelligence in solid organ transplantation.

Solid organ transplantation confronts numerous challenges ranging from donor organ shortage to post-transplant complications. Here, we provide an overview of the latest attempts to address some of these challenges using artificial intelligence (AI). We delve into the application of machine learning in pretransplant evaluation, predicting transplant rejection, and post-operative patient outcomes. By providing a comprehensive overview of AI's current impact, this review aims to inform clinicians, researchers, and policy-makers about the transformative power of AI in enhancing solid organ transplantation and facilitating personalized medicine in transplant care.

Functional Improvement at One Year in Fibrotic Interstitial Lung Diseases-Prognostic Value of Baseline Biomarkers and Anti-Inflammatory Therapies.

BACKGROUND: The clinical spectrum of fibrotic interstitial lung diseases (ILDs) is highly heterogeneous. We aimed to evaluate the prognostic value of widely available baseline biomarkers for the improvement of lung function in patients with fibrotic ILDs. METHODS: This registry-based study included 142 patients with fibrotic ILDs as defined by the presence of reticulation, traction bronchiectasis or honeycombing on initial high-resolution computed tomography (HRCT). Functional improvement at 1 year was defined as a relative increase of 5% in forced vital capacity (FVC) or of 10% in diffusion capacity for carbon monoxide (DLCO). The prognostic value of baseline biomarkers was evaluated for all patients and the subgroup with anti-inflammatory treatment. RESULTS: At one year, 44 patients showed improvement while 73 showed disease progression. Multivariate analyses found prognostic significance for age < 60 years (OR 5.4; 95%CI 1.9-15.4; p = 0.002), lactate dehydrogenase (LDH) >250 U/L (OR 2.5; 95%CI 1.1-5.8; p = 0.043) and blood monocyte count < 0.8 G/L (OR 3.5; 95%CI 1.1-11.3; p = 0.034). In 84 patients undergoing anti-inflammatory treatment, multivariate analysis revealed age < 60 years (OR 8.5 (95%CI 2.1-33.4; p = 0.002) as the only significant variable. CONCLUSION: Younger age, a higher LDH and lower blood monocyte count predicted functional improvement in fibrotic ILD patients, while in those treated with anti-inflammatory drugs, only age had significant implications.

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.

[Research Progress on Predictive Biomarkers of Immunotherapy Efficacy
in Non-small Cell Lung Cancer].

Lung cancer is one of the most common malignant tumors in the world, of which non-small cell lung cancer (NSCLC) is the majority. The emergence of immune checkpoint inhibitors (ICIs) has greatly changed the treatment strategy of NSCLC and improved the prognosis of patients. However, in reality, only a small number of patients can achieve long-term benefit. Therefore, the identification of reliable predictive biomarkers is essential for the selection of treatment modalities. With the development of molecular biology and genome sequencing technology in recent years, as well as the in-depth understanding of tumor and its host immune microenvironment, research on biomarkers has emerged in an endless stream. This review focuses on the predictive biomarkers of immunotherapy efficacy in NSCLC, in order to provide some guidance for precision immunotherapy.
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