Early Categorization Research Articles

Early diagnosis of oral cancer - A narrative review

Oral cancer (OC) is a common malignancy in Asian countries. Early diagnosis is crucial because of its high mortality rate. Patients and physicians both contribute to the delay in oral cancer diagnosis. Improved knowledge of the disease, its risk factors and symptoms would have a positive influence upon the early diagnosis. Majority of the risk factors such as alcohol consumption, tobacco, betel nut, viral infections, chronic irritation and inflammation if identified timely can mostly avoid the cancer. Prevention and anticipation of diagnosis begin with identification of potentially malignant lesions of the oral mucosa and local conditions promoting chronic inflammation. Each lesion needs to be identified quickly and given the proper care. The clinical recognition and evaluation of oral mucosal lesions can detect up to 99% of oral cancers/ pre-malignancies. The World Health Organization states that a biopsy is required for any suspicious lesion that does not go away after two weeks of local causes of irritation have been identified and removed. Surgical biopsy is the gold standard for diagnosis of oral cancer. However oral brush biopsy, toluidine blue vital staining, auto-fluorescence imaging, and other non-invasive techniques have been created and researched to aid physicians in the diagnostic process. Currently, artificial intelligence is a key component in the early detection of oral malignancies. Present review was written to highlight various factors resulting in delayed diagnosis of oral cancer as well as to discuss different non-invasive techniques that can easily be used in early categorization of oral pre-malignant and malignant lesions. Keywords: Oral cancer, Early diagnosis, Noninvasive techniques, Salivary biomarkers, Biopsy, Artificial intelligence.

An optimized support vector machine for lung cancer classification system

IntroductionLung cancer is one of the main causes of the rising death rate among the expanding population. For patients with lung cancer to have a higher chance of survival and fewer deaths, early categorization is essential. The goal of thisresearch is to enhance machine learning to increase the precision and quality of lung cancer classification.MethodsThe dataset was obtained from an open-source database and was utilized for testing and training. The suggested system used a CT scan picture as its input image, and it underwent a variety of image processing operations, including segmentation, contrast enhancement, and feature extraction.ResultsThe training process produces a chameleon swarm-based supportvector machine that can identify between benign, malignant, and normal nodules.ConclusionThe performance of the system is evaluated in terms of false-positive rate (FPR), sensitivity, specificity, recognition time and recognition accuracy.

Role of 99mTc-sestamibi Scintimammography in Predicting Response to Neoadjuvant Chemotherapy in Locally Advanced Breast Cancer: A Prospective Study.

Neoadjuvant chemotherapy (NACT) is the first line of management for locally advanced breast cancer (LABC). However, chemoresistance is prevalent in 18%-50% of the cases. One of the important and most studied causes of chemoresistance is P-glycoprotein (Pgp) expression. 99mTc-sestamibi scintimammography may serve as a useful imaging tool to predict Pgp expression, thereby response to NACT. The aim was to study the role of 99mTc-sestamibi scintimammography in predicting response to NACT in treatment-naive, biopsy-proven LABC patients. 99mTc-sestamibi scintimammography (early and delayed images) was performed on a total of 34 patients. Eight patients were lost to follow-up, and only 26 (25 females and 1 male) patients were available for final analysis, with a mean age of 49.7 ± 10.7 years. 99mTc-sestamibi washout rate (WOR) (%) and T/B buildup were calculated. Pre-NACT and Post-NACT tumor sizes were measured clinically, and a % decrease in tumor size was calculated. The WOR and T/B buildup values were correlated with the % decrease in tumor size. We found a statistically significant negative correlation between WOR (%) and % decrease in tumor size and a statistically significant positive correlation between T/B buildup and % decrease in tumor size. Furthermore, we found a positive correlation between the early T/B ratio and the Ki-67 index (P = 0.22). Early categorization of responders and nonresponders can help in optimal therapy planning. 99mTc-sestamibi scintimammography can serve as an imaging marker for Pgp expression, thereby predicting clinical response to NACT in LABC patients. Further studies with larger sample sizes are warranted to consolidate the above findings.

Neutrosophic-CNN-based image and text fusion for multimodal classification

Recent advances in technology and devices have caused a data explosion on the Internet and on our home PCs. This data is predominantly obtained in various modalities (text, image, video, etc.) and is essential for e-commerce websites. The products on these websites have both images and descriptions in text form, making them multimodal in nature. Earlier categorization and information retrieval methods focused mostly on a single modality. This study employs multimodal data for classification using neutrosophic fuzzy sets for uncertainty management for information retrieval tasks. This effort utilizes image and text data and, inspired by past techniques of embedding text over an image, attempts to classify the images using neutrosophic classification algorithms. For classification tasks, Neutrosophic Convolutional Neural Networks (NCNNs) are used to learn feature representations of the produced images. We demonstrate how a pipeline based on NCNN can be utilized to learn representations of the innovative fusion method. Traditional convolutional neural networks are vulnerable to unknown noisy conditions in the test phase, and as a result, their performance for the classification of noisy data declines. Comparing our method against individual sources on two large-scale multi-modal categorization datasets yielded good results. In addition, we have compared our method to two well-known multi-modal fusion methodologies, namely early fusion and late fusion.

CAN KI-67 PREDICT MALIGNANT AND PRE-MALIGNANT ORAL LESION? : AN EXPERIENCE IN A TERTIARY CARE HOSPITAL IN THE CENTRAL INDIA.

Background: Oral cancer ranks the sixth commonest cancer worldwide and the third most common cancer in India. Ki67 index has been suggested to play an important role in early diagnosis and prognosis of potentially malignant disorders. This study aims to understand prognostic role of Ki 67 expression in different categories of oral mucosal neoplastic lesions in Central India, where tobacco chewing is endemic. This could help in early categorization and effective management of patients. Aims: To study the Ki67 expression in terms of Index of Positivity and Intensity score in oral mucosal neoplastic lesions. Setting and Design: Department of Pathology, Tertiary Care Hospital Observational & Prospective study Methods & Material: The expression of Ki-67was studied in parafn- embedded tissue sections of histopathology proven pre- malignant and malignant lesions of oral cavity in ninety four cases. Results: Association of Ki67 Expression Intensity score with the type of lesion was found to be signicant in premalignant and malignant lesions predominantly (p= <0.001).Similarly, Ki67 Index of positivity score was highly statistically signicant (p= <0.001) in association with the type of lesion. Conclusions: the expression of Ki-67 correlates well with the disease progression from dysplasia to carcinoma of the oral cavity. It is therefore a marker of malignant transformation and carcinogenesis in oral premalignant lesions and in future it may serve as a prognostic tool in the early detection of malignancy

Early categorization of social affordances during the visual encoding of bodily stimuli

Interpersonal interactions rely on various communication channels, both verbal and non-verbal, through which information regarding one's intentions and emotions are perceived. Here, we investigated the neural correlates underlying the visual processing of hand postures conveying social affordances (i.e., hand-shaking), compared to control stimuli such as hands performing non-social actions (i.e., grasping) or showing no movement at all. Combining univariate and multivariate analysis on electroencephalography (EEG) data, our results indicate that occipito-temporal electrodes show early differential processing of stimuli conveying social information compared to non-social ones. First, the amplitude of the Early Posterior Negativity (EPN, an Event-Related Potential related to the perception of body parts) is modulated differently during the perception of social and non-social content carried by hands. Moreover, our multivariate classification analysis (MultiVariate Pattern Analysis - MVPA) expanded the univariate results by revealing early (<200 ms) categorization of social affordances over occipito-parietal sites. In conclusion, we provide new evidence suggesting that the encoding of socially relevant hand gestures is categorized in the early stages of visual processing.

Severe COVID-19 among Admitted COVID-19 Patients in a Tertiary Care Centre: A Descriptive Cross-sectional Study.

Severe COVID-19 patients experience elevated levels of serologic indicators of inflammation which can alter blood cell lineages and cause lymphopenia. The objective of this study was to find out the prevalence of severe COVID-19 among admitted COVID-19 patients in a tertiary care centre. A descriptive cross-sectional study was conducted in a tertiary care centre from 22 June 2021 to 30 September 2021 after obtaining ethical approval from the Institutional Review Committee (Reference number: IRC-PA-146/2077-78). Confirmed COVID-19 patients by reverse transcriptase polymerase chain reaction and admitted in the COVID block during the study period were included and those who were discharged on request or referred or unavailable blood tests were excluded. A convenience sampling method was used. Point estimate and 95% Confidence Interval were calculated. Among 72 admitted COVID-19 patients, 63 (87.5%) (79.86-95.14, 95% Confidence Interval) patients had severe disease. The mean neutrophil to lymphocyte ratio and mean lymphocyte to C-reactive protein ratio were 11.60±8.15 and 25.55±20.96 respectively. The prevalence of severe COVID-19 was higher than in other studies done in similar settings. We suggest clinical parameter-based early categorisation of COVID-19 cases to utilize limited resources during the pandemic. COVID-19; c-reactive protein; lymphocytes; severe acute respiratory syndrome coronavirus.

ISC-DL: DL For Diagnosis of Ischemic Stroke

Stroke is still the world's second biggest cause of mortality.It is one of the illnesses that artificial intelligence (AI) can detect.Early detection of an acute stroke is crucial for commencingprompt treatments and reducing morbidity and death. Imagingtechniques such as (CT) Computed Tomography and (MRI)Magnetic Resonance Imaging can identify it, however, they takelonger and have worse accuracy than AI. Artificial intelligencealgorithms are particularly adapted to the rapid decision-makingrequired in the management of big vessel occlusive strokes.Through early categorization by CT and MRI, AI can assist inidentifying kinds of strokes such as ischemic and hemorrhagicstrokes. With the help of AI, doctors can quickly analyze a patient'sbrain scan and receive results in minutes. Imaging is also importantsince professionals may evaluate amounts of data and detect anyindicators of a possible stroke. AI enhances the quality of (CT) and(MRI) scans, yielding more than 90% accuracy and improvingpatient care. The AI detection time of a brain stroke is now 5minutes. We will discuss the use of AI in stroke imaging and how toimprove (CT) and (MRI) quality in this study.

On Disharmony in Batch Normalization and Dropout Methods for Early Categorization of Alzheimer’s Disease

Alzheimer’s disease (AD) is a global health issue that predominantly affects older people. It affects one’s daily activities by modifying neural networks in the brain. AD is categorized by the death of neurons, the creation of amyloid plaques, and the development of neurofibrillary tangles. In clinical settings, an early diagnosis of AD is critical to limit the problems associated with it and can be accomplished using neuroimaging modalities, such as magnetic resonance imaging (MRI) and positron emission tomography (PET). Deep learning (DL) techniques are widely used in computer vision and related disciplines for various tasks such as classification, segmentation, detection, etc. CNN is a sort of DL architecture, which is normally useful to categorize and extract data in the spatial and frequency domains for image-based applications. Batch normalization and dropout are commonly deployed elements of modern CNN architectures. Due to the internal covariance shift between batch normalization and dropout, the models perform sub-optimally under diverse scenarios. This study looks at the influence of disharmony between batch normalization and dropout techniques on the early diagnosis of AD. We looked at three different scenarios: (1) no dropout but batch normalization, (2) a single dropout layer in the network right before the softmax layer, and (3) a convolutional layer between a dropout layer and a batch normalization layer. We investigated three binaries: mild cognitive impairment (MCI) vs. normal control (NC), AD vs. NC, AD vs. MCI, one multiclass AD vs. NC vs. MCI classification problem using PET modality, as well as one binary AD vs. NC classification problem using MRI modality. In comparison to using a large value of dropout, our findings suggest that using little or none at all leads to better-performing designs.

MicroRNAs as Potential Diagnostic New Biomarkers in Diagnosis of Sepsis in Pediatric Patients.

Sepsis is one of the most common causes of multiorgan failure. Sepsis requires the presence of infection with a resultant systemic inflammatory state. Organ dysfunction occurs from the combination of the two processes. Sepsis is the main cause of mortality at intensive care units, with 30-50% mortality rate for all septic episodes. MicroRNA (miRNA) profile data could be beneficial as a specific diagnostic biomarker for sepsis and systemic inflammatory response syndrome (SIRS). Expression of miRNAs -122, -181b, -223 and -146a levels were assayed by quantitative real time polymerase chain reaction (qRT-PCR) in a prospective case control study, where forty septic cases were compared to 40 healthy controls of matched age and gender. miRNAs -122 and -181b were significantly upregulated during early septic conditions, indicating that they could be sensitive and specific biomarkers for diagnosing sepsis. miRNA-223 and miRNA-146a could also represent highly specific and sensitive diagnostic biomarkers, as they were found to be significantly down-regulated. Serum levels of miRNA-223 could be used to predict poor prognosis with 70% sensitivity and 75% specificity, whereas the other three miRNAs could not predict prognosis. Our study shows that all tested miRNAs can be used for early detection of sepsis, with miRNA-223 being predictive of mortality, hence preventing multi-organ failure and reducing mortality, and predicting poor outcomes, thereby assisting in early categorization of ICU patients for rapid appropriate treatment and medico legal aspects.

Paediatric inflammatory multisystem syndrome - temporally associated with SARS-CoV-2 (PIMS-TS) - a German single centre real-life evaluation of the Swiss and UK consensus statements.

In the absence of randomised trials for paediatric multisystem inflammatory syndrome temporally associated with SARS-CoV2 (PIMS-TS), optimal management of PIMS-TS-patients remains somewhat uncertain. We aimed to evaluate the practicability of consensus diagnostic/therapeutic pathways in a real-life German hospital setting. All children treated for PIMS-TS (February to November, 2021) at the Childrens' Hospital Kassel were analysed retrospectively. Patients were treated according to local PIMS-TS standardised operating procedure based on the Swiss and UK consensus statements. Eleven patients treated for PIMS-TS were included in this study (female:male = 2.1:1). According to the categories of the Swiss and UK consensus statements, 36% were uncomplicated hyperinflammation, 36% Kawasaki-like and 27% shock-like disease. Local estimated incidence was 0.92/1000 Covid-19 cases in children aged 4-15 years. Significant inter-group differences in laboratory parameters were found: BNP was highest in shock-like presentation compared to Kawasaki-like and uncomplicated hyperinflammation (median 954 (668-1491) versus 213 (173-934) versus 80 (5-257) ng/l, p = 0.02), whereas troponin was highest in Kawasaki-like, followed by shock-like presentation and uncomplicated hyperinflammation (median 34.7 (27.5-58.4) versus 19.1 (14.1-23.4) versus 1.9 (1.9-16.4) ng/l, p = 0.02). Patients with shock-like presentation needed circulatory resuscitation in the paediatric ICU. All patients received standardised operating procedure-based therapy and were discharged home after a medium of 7.4 days. The Swiss and UK consensus statements on the management of PIMS-TS proved very valuable in a real-life clinical setting, facilitated early categorisation, and initiation of specific therapy, possibly improving the outcome. Additional randomised trials are necessary to further improve the management of PIMS-TS.

Role of hemogram-derived ratios in predicting intensive care unit admission in COVID-19 patients: a multicenter study

PurposeAs hyperinflammation is recognized as a driver of severe COVID-19 disease, checking markers of inflammation is gaining more attention. Our study aimed to evaluate the utility of cost-effective hemogram-derived ratios in predicting intensive care unit (ICU) admission in COVID-19 patients. MethodsThis multicenter retrospective study included hospitalized COVID-19 patients from four dedicated COVID-19 hospitals in Sylhet, Bangladesh. Data on demographics, clinical characteristics, laboratory parameters and survival outcomes were analyzed. Logistic regression analysis was used to identify the significance of each hemogram-derived ratio in predicting ICU admission. ResultsOf 442 included patients, 98 (22.17%) required ICU admission. At the time of admission, patients requiring ICU had a higher neutrophil count and lower lymphocyte and platelet counts than patients not requiring ICU. Peripheral capillary oxygen saturation at admission was significantly lower in those who subsequently required ICU admission. Neutrophil-to-lymphocyte ratio, derived neutrophil-to-lymphocyte ratio, neutrophil-to-platelet ratio, and systemic immune-inflammation index were significant predictors of ICU admission. ConclusionHemogram-derived ratios can be an effective tool in facilitating the early categorization of at-risk patients, enabling timely measures to be taken early in the disease course.

How to manage traumatic brain injury without invasive monitoring?

Severe traumatic brain injury (TBI) is an extremely serious health problem, especially in low-middle income countries (LMICs). The prevalence of severe TBI continues to increase in LMICs. Major limitations in the chain of care for TBI patients are common in LMICs including suboptimal or nonexistent prehospital care, overburdened emergency services, lack of trained human resources and limited availability of ICUs. Basic neuromonitoring, such as intracranial pressure, are unavailable or underutilized and advanced techniques are not available. Attention to fundamental principles of TBI care in LMICs, including early categorization, prevention and treatment of secondary insults, use of low-cost technology for evaluation of intracranial bleeding and neuromonitoring, and emphasis on education of human resources and multidisciplinary work, are particularly important in LMICs. Institutional collaborations between high-income and LMICs have developed evidence focused on available resources. Accordingly, an expert group have proposed consensus recommendations for centers without availability of invasive brain monitoring. Severe TBI is very prevalent in LMIC and neuromonitoring is often not available in these environments. When intracranial pressure monitors are not available, careful attention to changes on clinical examination, serial imaging and noninvasive monitoring techniques can help recognize intracranial hypertension and effectively guide treatment decisions.

Association of Glycosylated hemoglobin with Radiological severity, Systemic inflammation and Hypercoagulability in COVID -19 patients in a hospital from Central India: A Monocentric Retrospective Observational study

Background: COVID-19 is currently the most common cause of morbidity and mortality worldwide. Diabetes is also one of the most common causes of morbidity and associated complications. Identification of prognostic markers like glycated hemoglobin can help early categorization of patients and their better management.&#x0D; Aims and Objectives: To determine if Glycated Hemoglobin (HbA1c) levels are associated with radiological severity of COVID -19 disease, thereby predict prognosis in COVID -19 patients. Its association with D dimer andIL-6 was also evaluated to assess hypercoagulability and systemic inflammation in these patients.&#x0D; Materials and Methods: A monocentric retrospective observational study was conducted during admission period from August 1, 2020- October 31, 2020. HbA1c levels of 188 patients who tested positive for COVID-19 in a dedicated COVID-19 tertiary care center (L.N. Medical college and J.K. Hospital, Bhopal) were determined. They were divided into 2 groups: A (HbA1c level ≤6.5 %), B (HbA1c level &gt;6.5 %). Severity of disease in terms of lung involvement in HRCT Chest was recorded. Their SpO2 and oxygen requirement at admission was also recorded. Among laboratory investigations, D dimer, IL6 Levels were obtained.&#x0D; Results: Out of 188 COVID-19 positive patients included in our study, there were 132 men, 56 women. Median age of patients was 66 years. Mean HbA1c level was 7.2%. Of these, 87 had normal HBA1C and 101 had raised HBA1C &gt;6.5%. Oxygen was required in 58 patients with raised HbA1c (RR of 2.782, p value&lt;0.0001), of which 42 patients had severe lung involvement (RR of 2.498, p value=0.0003). 20 (22.9%) patients with normal HbA1c required oxygen on admission, out of which 11 (12.6%) patients had severe lung involvement. Those who had higher HbA1c levels, had higher chances of severe lung involvement (&gt;50%) in radiological evaluation (RR 2.783, p-value 0.0003, Positive Likelihood ratio: 2.78, 95% CI: 1.60 to 4.83, 85% specificity).Significant increase in D dimer was seen in 77 (76.2%) patients with raised HbA1c compared to 40 patients (45.9%) with normal HbA1c(RR-1.6582, p-value 0.0001). No significant relation between HbA1c levels with IL-6 was found.&#x0D; Conclusion: Patients with raised HBA1C contracting COVID-19 have more severe inflammation and greater lung involvement, higher chances of oxygen requirement and are associated with higher risk of hypercoagulability. HbA1C will not only help identify hyperglycemia but also help assess severity of disease (both clinically and radiologically), systemic inflammation, hypercoagulability, thereby helps in predicting prognosis, managing patients and hasten recovery.

Children’s Ethno-National Flag Categories in Three Divided Societies

Abstract Flags are conceptual representations that can prime nationalism and allegiance to one’s group. Investigating children’s understanding of conflict-related ethno-national flags in divided societies sheds light on the development of national categories. We explored the development of children’s awareness of, and preferences for, ethno-national flags in Northern Ireland, Kosovo, and the Republic of North Macedonia. Children displayed early categorization of, and ingroup preferences for, ethno-national flags. By middle-childhood, children’s conflict-related social categories shaped systematic predictions about other’s group-based preferences for flags. Children of minority-status groups demonstrated more accurate flag categorization and were more likely to accurately infer others’ flag preferences. While most Balkan children preferred divided versus integrated ethno-national symbols, children in the Albanian majority group in Kosovo demonstrated preferences for the new supra-ethnic national flag. We discuss the implications of children’s ethno-national flag categories on developing conceptualizations of nationality and the potential for shared national symbols to promote peace.

A Systematic Framework for Olfactory Bulb Signal Transformations.

We describe an integrated theory of olfactory systems operation that incorporates experimental findings across scales, stages, and methods of analysis into a common framework. In particular, we consider the multiple stages of olfactory signal processing as a collective system, in which each stage samples selectively from its antecedents. We propose that, following the signal conditioning operations of the nasal epithelium and glomerular-layer circuitry, the plastic external plexiform layer of the olfactory bulb effects a process of category learning—the basis for extracting meaningful, quasi-discrete odor representations from the metric space of undifferentiated olfactory quality. Moreover, this early categorization process also resolves the foundational problem of how odors of interest can be recognized in the presence of strong competitive interference from simultaneously encountered background odorants. This problem is fundamentally constraining on early-stage olfactory encoding strategies and must be resolved if these strategies and their underlying mechanisms are to be understood. Multiscale general theories of olfactory systems operation are essential in order to leverage the analytical advantages of engineered approaches together with our expanding capacity to interrogate biological systems.

Focused ultrasonography for septic shock resuscitation.

Severe sepsis with septic shock is the most common cause of death among critically ill patients. Mortality has decreased substantially over the last decade but recent data has shown that opportunities remain for the improvement of early and targeted therapy. This review discusses published data regarding the role of focused ultrasonography in septic shock resuscitation. Early categorization of the cardiovascular phenotypes with echocardiography can be crucial for timely diagnosis and targeted therapy of patients with septic shock. In the last few years, markers of volume status and volume responsiveness have been investigated, serving as valuable tools for targeting volume therapy in the care of both spontaneously breathing and mechanically ventilated patients. In tandem, investigators have highlighted findings of extravascular volume with ultrasonographic evaluation to compliment de-escalation of resuscitation efforts when appropriate. Furthermore, special attention has been given to resuscitation efforts of patients in septic shock with right ventricular failure. Severe sepsis with septic shock is an insidious disease process that continues to take lives. In more recent years, data have emerged suggesting the utility of bedside ultrasonography for early cardiovascular categorization, goal directed resuscitation, and appropriate cardiovascular support based on its changing phenotypes.

0098 The Role of Sleep in Novel Category Learning in Infancy

Abstract Introduction A growing body of research suggests that sleep has an important role in consolidating newly learnt information and generalising this knowledge to novel instances (e.g. Djonlagic et al., 2009). The effects of sleep on early categorisation abilities haven’t been investigated so far and thus the aim of this study is to examine the role of sleep in formation of category representations. Two experiments were conducted. Experiment 1 set out to determine 4-months-old infants’ ability to form novel visual categories when category formation test immediately followed learning. Experiment 2 investigated the impact of sleep on category consolidation by testing category formation after a 2 hours delay. Methods Both experiments employed eye-tracking familiarisation-novelty-preference paradigm. In Experiment 1, infants were familiarised with a set of exemplars from a novel category. Immediately after the familiarisation phase, infants’ category formation was tested and their looking references were used as an index of category learning. Experiment 2 tested consolidation of the newly acquired categories by introducing a delay between the familiarisation and the test phase. Half of the participants took a nap during the delay, whereas the other half remained awake. Polysomnography was recorded using a standard PSG protocol. Sleep stages were scored according to the AASM guidelines, and sleep spindles were detected using an adapted algorithm for children. Results Results of the Experiment 1 revealed that infants were able to learn novel visual categories when category formation was tested immediately after learning suggesting therefore that infants are able to extract relevant information and generalise to novel instances. Preliminary results of Experiment 2 (data analysis ongoing) suggested that infants who napped performed better than infants who stayed awake. Conclusion The present study suggests that infants are able to rapidly form novel categories, and that consolidation of this knowledge is shaped by the activity following learning. Support N/A

A Clinician's Approach to Peripheral Neuropathy.

Peripheral neuropathies are a group of disorders that affect the peripheral nervous system, for which hundreds of etiologies have been identified. This article presents a stepwise approach to the evaluation and workup of peripheral neuropathy, which starts with a detailed history of symptoms, family and occupational history, and a neurological as well as general physical exam. Pattern recognition of various neuropathies can help to build a differential diagnosis based on the presentation. Such patterns include acute versus chronic, primary demyelinating versus axonal, hereditary versus acquired, asymmetric versus symmetric, presence of facial palsies, sensory or motor predominant, and presence of prominent autonomic symptoms. Early categorization of the type of neuropathy can help focus the workup for peripheral neuropathy. Nerve conduction studies and electromyography (NCS/EMG) is the primary diagnostic tool in the evaluation of patients with large-fiber polyneuropathy. One of the most important roles of NCS/EMG is to help categorize polyneuropathy as primary axonal versus primary demyelinating. The finding of a primary demyelinating polyneuropathy narrows the differential diagnosis of polyneuropathy dramatically and increases the chances of finding a treatable etiology. Laboratory workup includes serum studies and potentially cerebrospinal fluid, genetic studies, immunological markers, and fat pad biopsy for select patients. Skin biopsy may be used to assess intraepidermal nerve fiber density if small-fiber neuropathy is suspected, and nerve biopsy may be useful in select cases. In recent years, magnetic resonance imaging and neuromuscular ultrasound have also shown promise in the evaluation of peripheral neuropathy. Identification of the etiology of neuropathy is crucial and often time-sensitive, as an increasing number of causes are now reversible or treatable.

Prematurity, a significant predictor for worse outcome in viral bronchiolitis: a comparative study in infancy

BackgroundThe rate of admissions to hospital with bronchiolitis has increased over the past years. The reasons for this are likely to be multifactorial including improved survival of preterm infants.AimTo assess the severity of viral bronchiolitis in preterm compared to term infants admitted at a tertiary hospital in Cairo, Egypt, based on the outcome.Patients and methodsThis prospective study was conducted throughout a 3-year period from September 2011 to October 2014. It included 153 infants, 74 healthy preterm, and 79 healthy term infants admitted with clinical diagnosis of bronchiolitis at a tertiary hospital in Cairo, Egypt. Bronchiolitis severity score (BSS) was recorded, and nasopharyngeal swabs were obtained from each patient at the time of presentation. Viruses were identified using reverse transcription polymerase chain reaction (RT-PCR). The clinical course and patient’s outcome were recorded.ResultsThis study recorded a significantly more severe BSS for preterm compared to term infants. The preterm group had an increased mean length of hospital stay and oxygen therapy and was more likely to need intensive care unit admission and mechanical ventilation (MV) compared to the term group. The mean (± SD) BSS for infections with h-MPV, RSV, and para-influenza 3 was more significantly severe in preterm compared to term infants. Bacterial co-infection was significantly correlated with severity scoring in both groups.ConclusionPrematurity significantly affects the severity of bronchiolitis, and this underscores the importance of early categorization as a high-risk group on their first visit. The physician should be aware that their illness runs a more severe course, even if they have no underlying disorders.