Automatic Acne Severity Grading with a Small and Imbalanced Data Set of Low-Resolution Images.

INTRODUCTION: Developing automatic acne vulgaris grading systems based on machine learning is an expensive endeavor in terms of data acquisition. A machine learning practitioner will need to gather high-resolution pictures from a considerable number of different patients, with a well-balanced distribution between acne severity grades and potentially very tedious labeling. We developed a deep learning model to grade acne severity with respect to the Investigator's Global Assessment (IGA) scale that can be trained on low-resolution images, with pictures from a small number of different patients, a strongly imbalanced severity grade distribution and minimal labeling. METHODS: A total of 1374 triplets of images (frontal and lateral views) from 391 different patients suffering from acne labeled with the IGA severity grade by an expert dermatologist were used to train and validate a deep learning model that predicts the IGA severity grade. RESULTS: On the test set we obtained 66.67% accuracy with an equivalent performance for all grades despite the highly imbalanced severity grade distribution of our database. Importantly, we obtained performance on par with more tedious methods in terms of data acquisition which have the same simple labeling as ours but require either a more balanced severity grade distribution or large numbers of high-resolution images. CONCLUSIONS: Our deep learning model demonstrated promising accuracy despite the limited data set on which it was trained, indicating its potential for further development both as an assistance tool for medical practitioners and as a way to provide patients with an immediately available and standardized acne grading tool. TRIAL REGISTRATION: chinadrugtrials.org.cn identifier CTR20211314.

A dose-response correlation between smoking and severity of acute pancreatitis: a propensity score-matched study.

Background: Acute pancreatitis, among the most prevalent gastrointestinal disorders, exhibits a continual rise in its incidence recent years. This study endeavor to explore the correlation between smoking exposure and the severity of acute pancreatitis (AP). Methods: Five hundred and eight patients diagnosed as acute pancreatitis (AP) were included in our data analysis. Patients were categorized based on their smoking pack-years into four groups: light, moderate, heavy, and non-smokers. Outcomes were classified as two: "mild acute pancreatitis (MAP)" and "moderately severe acute pancreatitis (MSAP) or severe acute pancreatitis (SAP)". We conducted propensity score matching (PSM) to adjust confounding factors and multivariable logistic regression analysis to determine adjusted odds ratios and 95% confidence intervals. Additionally, a dose-dependent association analysis between smoking exposure and the incidence rate of "MSAP or SAP" was performed. Results: Smokers exhibited a higher risk of "MSAP or SAP" compared to non-smokers, both before (17.1 vs. 54.9%, p < 0.001) and after (9.4 vs. 24.7%, p < 0.001) PSM. With an area under the ROC curve of 0.708, smoking showed a moderate level of predictive ability. Furthermore, propensity score matching analysis showed that patients who smoked compared to non-smokers had significantly higher risks of "MSAP or SAP" for light smoking (OR 3.76, 95% CI 1.40-10.07, p = 0.008), moderate smoking (OR 4.94, 95% CI 2.23-10.92, p < 0.001), and heavy smoking (OR 8.08, 95% CI 3.39-19.25, p < 0.001). Conclusion: Smoking is an independent risk factor that can raise the severity of pancreatitis. Moreover, the severity of acute pancreatitis escalates in tandem with the accumulation of pack-years of smoking.

A scoping review of scores or grading systems for pelvic venous disorders.

BACKGROUND: Pelvic venous disorders (PeVD) encompass a variety of conditions linked to chronic pelvic pain in women. However, PeVD remain underdiagnosed due to the absence of universally accepted diagnostic criteria. The complexity of PeVD classifications across specialties leads to delays in treatment. This scoping review aims to fill a gap in PeVD diagnosis and management by identifying all existing scoring or grading systems to lay the foundation for standardized clinical scoring tools for PeVD. METHODS: This scoping review was undertaken according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping reviews. Online databases were searched up to April 2023. Studies implementing a scoring or grading system for patients with confirmed or suspected PeVD were included. Scores or grading systems were classified into four main categories based on their use in the study: screening, diagnosis, measure of disease severity, and measure of response to treatment. RESULTS: Of the 2976 unique records identified, 82 were reviewed in full, and 20 were included in this study. The publication dates ranged from 1984 to 2023 (median, 2018; interquartile range, 2003-2022). A total of 21 scores and/or grading systems were identified. Of these 21 scores, 10 (47.6%) were clinical scores, and 10 (47.6%) were scores based on radiological findings; one study included a score that used both clinical and radiological findings. The identified scores were used in various settings. Of the 21 scores, 2 (9.52%) were used for screening in a tertiary care setting; 3 (14.3%) were used to establish the PeVD diagnosis; 8 (38.1%) were used to assess disease severity; and 8 (38.1%) were used as measures of response to treatment. Of the eight scores assessing disease severity, four (50.0%) assessed the degree of dilatation of pelvic veins and four (50%) assessed the severity of reflux. Only three of the scores were validated. CONCLUSIONS: This scoping review identified a range of scoring and grading systems for PeVD. We note a lack of a validated scoring system, both clinical and radiological, for screening and assessment of disease severity. This is an important first step in developing validated disease-specific scoring systems for patient screening, appropriate referral, assessment of symptom severity, and assessment of the response to treatment.

Evaluation of colitis induced by immune-checkpoint inhibitors therapy in melanoma patients by an overall grading scale.

BACKGROUND: Colitis was the third most common immune-related adverse effect in melanoma patients treated with immune-checkpoint inhibitor (ICI). With the limitation of real-world data in the UK population, this study was conducted in a UK hospital where a fresh colitis guidance was introduced to evaluate the overall grading (OG) to assess colitis severity and guide the treatment. AIMS: This study aimed to investigate colitis severity by Common Terminology Criteria for Adverse Events (CTCAE) grade and overall grade at time of presentation. Colitis treatment and outcome were evaluated to compare the impact of these two categories. METHODS: A single-center, retrospective observational study was performed in melanoma patient developing colitis symptoms. RESULTS: A total of 44 advanced melanoma patient with colitis symptoms were included. Median time to colitis onset was 67 days (range 4-890). Majority of patients developed G1/ G2 of CTCAE scale (70.4%) but moderate or severe overall grade (84.1%). There were 65.9% of patients treated with steroids, and 38.2% with infliximab and 4.5% with vedolizumab. The median time of colitis resolution was 28 days (range 0-282). Both treatment modality and time to resolution were associated with severity of colitis assessed by complete OG(p<0.0001) rather than CTCAE grading (p>0.05). CONCLUSIONS: This study provided a comprehensive description about ICI-induced colitis management in a single center of the UK. The more completed OG was proposed to stratify colitis patient and guide the investigation and treatment decision at presenting time, replacing the old CTCAE grading.

Navigating Nutritional Strategies: A Comprehensive Review of Early and Delayed Enteral Feeding in Acute Pancreatitis.

This review critically examines enteral feeding strategies in managing acute pancreatitis, focusing on the contrasting early and delayed initiation approaches. Acute pancreatitis, marked by pancreatic inflammation, poses complex challenges, and nutritional interventions are pivotal in patient outcomes. Early enteral feeding, initiated within 24-48 hours, is associated with positive outcomes such as shortened hospital stays and reduced complications. However, controversies persist, with studies questioning its universal benefits. Conversely, delayed enteral feeding, employing a cautious approach, gains prominence in high-risk and severe cases. The identification of high-risk patients becomes paramount in decision-making. Practical recommendations for clinicians advocate an individualized approach, considering the severity of pancreatitis and regular monitoring. As the landscape of acute pancreatitis management evolves, staying abreast of emerging guidelines is essential. This review aims to provide a comprehensive understanding of critical findings, offering practical insights to guide clinicians in navigating the complexities of enteral feeding decisions in acute pancreatitis.

Comparison of the patient-derived modified Japanese Orthopaedic Association scale and the European myelopathy score.

PURPOSE: To compare the patient-derived modified Japanese Orthopaedic Association (P-mJOA) scale with the European myelopathy score (EMS) for the assessment of patients with degenerative cervical myelopathy (DCM). METHODS: In this register-based cohort study with prospectively collected data, included patients were surgically treated for DCM and had reported both P-mJOA and EMS scores at baseline, 1-year follow-up, and/or 2-year follow-up to the Swedish Spine Register. P-mJOA and EMS scores were defined as severe (P-mJOA 0-11 and EMS 5-8), moderate (P-mJOA 12-14 and EMS 9-12), or mild (P-mJOA 15-18 and EMS 13-18). P-mJOA and EMS mean scores were compared, and agreement was evaluated with Spearman's rank correlation coefficient (ρ), the intraclass correlation coefficient (ICC), and kappa (κ) statistics. RESULTS: Included patients (n = 714, mean age 63.2 years, 42.2% female) completed 937 pairs of the P-mJOA and the EMS. The mean P-mJOA and EMS scores were 13.9 ± 3.0 and 14.5 ± 2.7, respectively (mean difference -0.61 [95% CI -0.72 to -0.51; p < 0.001]). Spearman's ρ was 0.84 (p < 0.001), and intra-rater agreement measured with ICC was 0.83 (p < 0.001). Agreement of severity level measured with unweighted and weighted κ was fair (κ = 0.22 [p < 0.001]; κ = 0.34 [p < 0.001], respectively). Severity levels were significantly higher using the P-mJOA (p < 0.001). CONCLUSION: The P-mJOA and the EMS had similar mean scores, and intra-rater agreement was high, whereas severity levels only demonstrated fair agreement. The EMS has a lower sensitivity for detecting severe myelopathy but shows an increasing agreement with the P-mJOA for milder disease severity. A larger interval to define severe myelopathy with the EMS is recommended.

Harmonizing the collection of solicited adverse events in prophylactic vaccine clinical trials.

INTRODUCTION: During the clinical development of a vaccine, study participants are monitored for the occurrence of adverse events (AEs) over a defined period post-vaccination to assess the safety of prophylactic vaccines. Among the safety data collected, a standard practice in prophylactic vaccine clinical trials involves collecting reactogenicity data through daily AE solicitation of pre-defined sets of symptoms (i.e. solicited AEs). AREAS COVERED: This paper aims to propose recommendations to improve and harmonize the collection of active AE solicitation in prophylactic vaccine clinical trials. EXPERT OPINION: We recommend using limited lists of solicited AEs adapted to the vaccine technology and target population. While the US Food and Drug Administration toxicity grading scale is commonly used in adolescents/adults, harmonizing grading criteria in infants/children would facilitate the comparison of vaccines' safety profiles. Solicited systemic AEs should not systematically be considered causally related to vaccination. Collection of solicited AEs should occur in cohorts of a maximum of 1,000 vaccinated participants, as larger cohort sizes do not improve substantially the precision of AE incidence. The incidence of daily solicited AEs should be compared with a control group for improved interpretations of their clinical relevance. These suggestions would improve the characterization of safety profiles of vaccines.

Knowledge assessment of a donor adverse reaction severity grading tool by the National Blood Donor Vigilance Programme of India.

BACKGROUND AND OBJECTIVES: The severity grading tool (SGT) was recently designed by the Association for Advancement of Blood and Biotherapies (AABB) to have more objectivity in severity assignment for an adverse donor reaction after blood donation. A study was performed in India to assess the knowledge (post-training) and determine the degree of agreement of the SGT between participating centres and the subject expert group. MATERIALS AND METHODS: This prospective cross-sectional survey-based study was conducted by the National Coordinating Centre (NCC) of the National Blood Donor Vigilance Programme (NBDVP) of India. Thirty-five real-world case scenarios, validated by seven national and two international experts, were sent to the participating centres, and their responses received (diagnosis and severity grade) were compared and analysed. RESULTS: A total of 50 blood centres participated in the study. The overall agreement between the participating centres and the expert group was 66.4%, with a fair Kendall's coefficient of concordance (W) of 0.271 (p-value < 0.05). The degree of agreement was observed to be more than 80% for 12 centres, 60%-80% for 27 centres and <60% for 11 centres. The overall degree/percentage of agreement for cases with single and multiple types of donor adverse reaction was 71.3% and 42.6%, respectively. CONCLUSION: The SGT will be an efficient mode to have uniform objective reporting of the adverse donor reactions and may be implemented in the NBDVP of India. This study also highlights the need for training of the blood centres on the basic definitions and categorization of the donor's adverse reaction.

[Cholangitis and cholecystitis: diagnostic criteria and management]. / Epeút- és epehólyag-gyulladás: diagnosztikus kritériumok és terápia.

In developed countries, diseases of the gallbladder and the biliary tract count as some of the most frequent gastrointestinal disorders. The inflammation of the gallbladder/biliary tree is a potentially severe, even lethal condition that requires rapid diagnosis and early multidisciplinary approach to be treated. Although the frequency of these diseases is high, the treatment is not unified in Hungary yet. The aim of the evidence-based recommendation is to clarify the diagnostic criteria and severity grading of these diseases and to highlight the indications and rules of proper application of the numerous available therapeutic interventions. The recent guideline is based on the consensus of the Board members of the Endoscopic Section of the Hungarian Gastroenterology Society in contribution with renown experts of surgery, infectology as well as interventional radiology and it counts as a clear and easy applicable guide during the all-day healthcare practice. Our guidelines are based on Tokyo guidelines established on the basis of the consensus reached in the International Consensus Meeting held in Tokyo which were revised in 2013 (TG13) and in 2018 (TG18). Orv Hetil. 2023; 164(20): 770-787.

Severity grading of dermatological emergencies based on comorbidities and systemic involvement: An observational study.

Dermatological emergency is defined as any urgent/immediate care. Dermatological conditions compromise about 5-8% of all cases presenting to the emergency department. A grading system can help dermatologist's and allied medical personnel to triage a patient accordingly. Currently no severity grading for dermatological emergencies is available. All patients seen in OPD for dermatological consultations requiring urgent interventions were included. Detailed history and clinical examination were done. Patients were assessed according to the onset, symptoms, distribution, examination, body surface area percentage and mucosal involvement. The severity was graded separately based on comorbidities and systemic involvement. Grade I was no comorbidity or systemic involvement. Grade II was 1 comorbidity or systemic involvement. Grade III was 2 comorbidities or systemic involvement. Grade IV was > 2 comorbidities or multiorgan involvement. Interesting emergency cases observed in Covid period were noted. There were 202 cases, the most common age group was 19-64 (69.8%). Male (49%) and females (51%) had equal preponderance. Most common emergency was acute urticaria with or without angioedema (25.24%). There were 113 (55.94%) inpatients and 89 (44.05%) were outpatients. Acute on chronic onset (34.5%), pain (41.6%), vesicles (30.1%), erosion (23.9%), ulcers (9.7%) and more than 50% body surface area involvement (64.6%) were seen more in admitted cases. Grade I was most common for both comorbidities and systemic involvement. However, grades II, III and IV were higher in admitted cases for both grading systems. The presence of comorbidities and systemic involvement increases the severity of dermatological emergency. Six patients had relapse. Seven patients had methotrexate toxicity. The proposed grading system based on comorbidities and systemic involvement helps to assess the severity of dermatological emergencies.

Multi-head deep learning framework for pulmonary disease detection and severity scoring with modified progressive learning.

Chest X-rays (CXR) are the most commonly used imaging methodology in radiology to diagnose pulmonary diseases with close to 2 billion CXRs taken every year. The recent upsurge of COVID-19 and its variants accompanied by pneumonia and tuberculosis can be fatal in some cases and lives could be saved through early detection and appropriate intervention for the advanced cases. Thus CXRs can be used for an automated severity grading of pulmonary diseases that can aid radiologists in making better and informed diagnoses. In this article, we propose a single framework for disease classification and severity scoring produced by segmenting the lungs into six regions. We present a modified progressive learning technique in which the amount of augmentations at each step is capped. Our base network in the framework is first trained using modified progressive learning and can then be tweaked for new data sets. Furthermore, the segmentation task makes use of an attention map generated within and by the network itself. This attention mechanism allows to achieve segmentation results that are on par with networks having an order of magnitude or more parameters. We also propose severity score grading for 4 thoracic diseases that can provide a single-digit score corresponding to the spread of opacity in different lung segments with the help of radiologists. The proposed framework is evaluated using the BRAX data set for segmentation and classification into six classes with severity grading for a subset of the classes. On the BRAX validation data set, we achieve F1 scores of 0.924 and 0.939 without and with fine-tuning, respectively. A mean matching score of 80.8% is obtained for severity score grading while an average area under receiver operating characteristic curve of 0.88 is achieved for classification.

Neurodegenerative diseases detection and grading using gait dynamics.

Detection of neurodegenerative diseases such as Parkinson's disease, Huntington's disease, Amyotrophic Lateral Sclerosis, and grading of these diseases' severity have high clinical significance. These tasks based on walking analysis stand out compared to other methods due to their simplicity and non-invasiveness. This study has emerged to realize an artificial intelligence-based disease detection and severity prediction system for neurodegenerative diseases using gait features obtained from gait signals. For the detection of the disease, the problem is divided into parts which are subgroups of 4 classes consisting of Parkinson's, Huntington's, Amyotrophic Lateral Sclerosis diseases, and the control group. In addition, the disease vs. control subgroup where all diseases are collected under a single label, the subgroups where each disease is separately against the control group. For disease severity grading, each disease was divided into subgroups and a solution was sought for the prediction problem mentioned by various machine and deep learning methods separately for each group. In this context, the resulting detection performance was measured by the metrics of Accuracy, F1 Score, Precision, and Recall while the resulting prediction performance was measured by the metrics such as R, R2, MAE, MedAE, MSE, and RMSE.

A Machine Learning-Based Severity Prediction Tool for the Michigan Neuropathy Screening Instrument.

Diabetic sensorimotor polyneuropathy (DSPN) is a serious long-term complication of diabetes, which may lead to foot ulceration and amputation. Among the screening tools for DSPN, the Michigan neuropathy screening instrument (MNSI) is frequently deployed, but it lacks a straightforward rating of severity. A DSPN severity grading system has been built and simulated for the MNSI, utilizing longitudinal data captured over 19 years from the Epidemiology of Diabetes Interventions and Complications (EDIC) trial. Machine learning algorithms were used to establish the MNSI factors and patient outcomes to characterise the features with the best ability to detect DSPN severity. A nomogram based on multivariable logistic regression was designed, developed and validated. The extra tree model was applied to identify the top seven ranked MNSI features that identified DSPN, namely vibration perception (R), 10-gm filament, previous diabetic neuropathy, vibration perception (L), presence of callus, deformities and fissure. The nomogram's area under the curve (AUC) was 0.9421 and 0.946 for the internal and external datasets, respectively. The probability of DSPN was predicted from the nomogram and a DSPN severity grading system for MNSI was created using the probability score. An independent dataset was used to validate the model's performance. The patients were divided into four different severity levels, i.e., absent, mild, moderate, and severe, with cut-off values of 10.50, 12.70 and 15.00 for a DSPN probability of less than 50, 75 and 100%, respectively. We provide an easy-to-use, straightforward and reproducible approach to determine prognosis in patients with DSPN.

Automatic Facial Palsy Diagnosis as a Classification Problem Using Regional Information Extracted from a Photograph.

The incapability to move the facial muscles is known as facial palsy, and it affects various abilities of the patient, for example, performing facial expressions. Recently, automatic approaches aiming to diagnose facial palsy using images and machine learning algorithms have emerged, focusing on providing an objective evaluation of the paralysis severity. This research proposes an approach to analyze and assess the lesion severity as a classification problem with three levels: healthy, slight, and strong palsy. The method explores the use of regional information, meaning that only certain areas of the face are of interest. Experiments carrying on multi-class classification tasks are performed using four different classifiers to validate a set of proposed hand-crafted features. After a set of experiments using this methodology on available image databases, great results are revealed (up to 95.61% of correct detection of palsy patients and 95.58% of correct assessment of the severity level). This perspective leads us to believe that the analysis of facial paralysis is possible with partial occlusions if face detection is accomplished and facial features are obtained adequately. The results also show that our methodology is suited to operate with other databases while attaining high performance, even though the image conditions are different and the participants do not perform equivalent facial expressions.

Impact of correcting the 2D PISA method on the quantification of functional tricuspid regurgitation severity.

AIMS: In functional tricuspid regurgitation (FTR) patients, tricuspid leaflet tethering and relatively low jet velocity could result in proximal flow geometry distortions that lead to underestimation of TR. Application of correction factors on two-dimensional (2D) proximal isovelocity surface area (PISA) equation may increase its reliability. This study sought to evaluate the impact of the corrected 2D PISA method in quantifying FTR severity. METHODS AND RESULTS: In 102 patients with FTR, we compared both conventional and corrected 2D PISA measurements of effective regurgitant orifice area [EROA vs. corrected (EROAc)] and regurgitant volume (RegVol vs. RegVolc) with those obtained by volumetric method (VM) using three-dimensional echocardiography (3DE), as reference. Both EROAc and RegVolc were larger than EROA (0.29 ± 0.26 vs. 0.22 ± 0.21 cm2; P < 0.001) and RegVol (24.5 ± 20 vs. 18.5 ± 14.25 mL; P < 0.001), respectively. Compared with VM, both EROAc and RegVolc resulted more accurate than EROA [bias = -0.04 cm2, limits of agreement (LOA) ± 0.02 cm2 vs. bias = -0.15 cm2, LOA ± 0.31 cm2] and RegVol (bias = -3.29 mL, LOA ± 2.19 mL vs. bias = -10.9 mL, LOA ± 13.5 mL). Using EROAc and RegVolc, 37% of patients were reclassified in higher grades of FTR severity. Corrected 2D PISA method led to a higher concordance of TR severity grade with the VM method (ĸ = 0.84 vs. ĸ = 0.33 for uncorrected PISA, P < 0.001). CONCLUSION: Compared with VM by 3DE, the conventional PISA underestimated FTR severity in about 50% of patients. Correction for TV leaflets tethering angle and lower velocity of FTR jet improved 2D PISA accuracy and reclassified more than one-third of the patients.

Interobserver agreement on the sonographic severity grading of shoulder impingement syndrome.

BACKGROUND: Shoulder impingement syndrome is the painful entrapment of the soft tissues between the acromion and the humeral head. The severity of shoulder impingement could be graded according to the limitation of shoulder joint moment. The reliability of sonographic findings in the grading of shoulder impingement severity grading is required to be evaluated by the consistency of findings between the observers. PURPOSE: To assess the interobserver agreement in the sonographic severity grading of shoulder impingement syndrome with the help of a ratio between acromion-to-greater tuberosity distance in the abduction and neutral arm position. MATERIAL AND METHODS: Patients were examined by two independent observers in the coronal approach with neutral arm position. Acromion-to-greater tuberosity distance was measured in abduction and neutral shoulder position. The ratios of the distances in the abduction and neutral position were calculated to grade the severity of shoulder impingement syndrome. RESULTS: A total of 78 shoulders were included in this study. A strong agreement was found for the grading of shoulder impingement severity grading between the two independent observers with Kappa value of 0.94. And correlation between the results of the two observers for the severity grading of shoulder impingement syndrome was significant at 0.01 level. CONCLUSION: Severity grading of the shoulder impingement syndrome was performed based on the ratio of acromion-to-greater tuberosity distance in abduction and neutral arm position. However, the sonographic findings were consistent and a strong interobserver agreement was seen in this sonographic severity grading.

Prognostic nutritional index: Is it associated with the prognosis of Crimean Congo hemorrhagic fever.

INTRODUCTION: The prognostic nutritional index (PNI) is calculated using total serum lymphocyte counts and albumin levels. We aimed to analyze the role of PNI in predicting intensive care unit (ICU) referral and mortality in patients with Crimean Congo hemorrhagic fever (CCHF). MATERIALS AND METHODS: Our target population was adult (age >18) patients who presented between March 2015 and October 2021 within 5 days of symptom emergence and were diagnosed with CCHF. The predictive value of PNI was analyzed by the receiver operating curve analysis. The patients were categorized based on the severity grading scores (SGS) as mild, moderate, and severe. The relationship between PNI and ICU referral and mortality was analyzed by logistic regression analysis. RESULTS: Overall, 115 patients with the diagnosis of CCHF were included. 13.9% (n = 16) of the patients were referred to ICU while 11.3% (n = 13) died. A comparison of the patients with different SGS grades revealed that they were significantly different regarding PNI (p < 0.001). There was a significant negative correlation between PNI and SGS (r = -0.662; p < 0.001). PNI had a PV regarding ICU referral and mortality ([area under the curve [AUC] = 0.723, 95% confidence interval [CI]: 0.609-0.836, p = 0.004 [AUC = 0.738, 95% CI: 0.613-0.863, p = 0.005]). The PNI threshold was 36.1 for ICU referral and mortality. The rates of female patients, hospitalization periods longer than 1 week, platelet apheresis replacement, diabetes mellitus, bleeding history, ICU admission, and mortality were significantly higher in patients with a PNI of lower than 36.1 (p < 0.05). CONCLUSION: PNI can predict ICU referral and mortality in patients admitted due to CCHF.

Incidence and Clinical Characteristics of Takotsubo Syndrome in Patients with Subarachnoid Hemorrhage.

Although takotsubo syndrome (TTS) has been reported in patients with subarachnoid hemorrhage (SAH), its incidence and relation to the severity of SAH are unknown.Of 319 consecutive patients with aneurysmal SAH, 245 patients who underwent both the ECG and echocardiography were analyzed.The incidence of TTS was 6.9% (22 patients (21 women), median age 68 years (range, 60-83) ). Regional wall motion abnormalities were present as apical (64%), mid-ventricular (9%), basal (4%) and focal (23%) forms. Heart failure was found in 10 patients (45%) but there was no cardiac death. Regarding SAH severity, 10 patients (45%) with TTS were in World Federation of Neurosurgical Societies classification grade V, as compared to 40 patients (18%) without TTS (P = 0.005). Seven patients (32%) with TTS died during hospitalization, as compared to 26 patients (12%) without TTS (P = 0.018). Four patients (18%) with TTS were estimated as independent at discharge, as compared to 100 patients (45%) without TTS (P = 0.013).The incidence of TTS in patients with SAH was estimated as 6.9% with significant predominance of women. The severity of SAH was significantly greater in patients with TTS than in those without TTS.