Pediatric Distraction Methods for the Perioperative Period

Abstract Most pediatric patients will experience anxiety to some degree during the perioperative period. Unrecognized and untreated anxiety can lead to complications during induction of anesthesia and may manifest as maladaptive behaviors that can last up to 6 months postoperatively. Multiple modalities are typically utilized to provide the greatest amount of anxiety relief with minimal side effects. Nonpharmacological methods of distraction have been proven effective when used in combination with pharmacological agents, as well as when used alone. The goal of this project was to create and present an educational resource tool regarding pharmacological and nonpharmacological distraction methods for pediatric patients during the perioperative period. Following a brief educational presentation, participants were asked to complete an anonymous and voluntary 10-question survey to evaluate the value and efficacy of the resource tool. Overall, participants expressed an increase in knowledge and preparation in caring for pediatric patients after the presentation. Approximately one-third of the participants were not aware of the negative effects of untreated anxiety, further demonstrating a need for education on this topic. Increasing staff education at the host facility, as well as providing a variety of recommendations for distraction techniques, will better equip anesthesia providers to tailor distraction interventions to individual patient needs, resulting in a more pleasant operative experience for the entire family unit

The Stories behind the Struggle: A Closer Look at First Experiences with Opioid Misuse

The opioid crisis is a national public health emergency. Over 47,000 people in the U.S. died of opioid overdoses in 2017. Improving our knowledge about how people first come to misuse opioids can help to inform prevention and treatment interventions. This research brief shows that opioid misuse most often begins before age 25, most people obtain the opioids they misuse from friends and family rather than a health care provider, and experimenting and coping with life stressors are the most common motivations for starting opioid misuse

The Stories behind the Struggle: A Closer Look at First Experiences with Opioid Misuse

The opioid crisis is a national public health emergency. Over 47,000 people in the U.S. died of opioid overdoses in 2017. Improving our knowledge about how people first come to misuse opioids can help to inform prevention and treatment interventions. This research brief shows that opioid misuse most often begins before age 25, most people obtain the opioids they misuse from friends and family rather than a health care provider, and experimenting and coping with life stressors are the most common motivations for starting opioid misuse

Follistatin, a Novel Biomarker for Malignant Gliomas

Molecular biomarkers are commonly used for the management of several types of malignant tumours in routine clinical practice. However, this is not the case for malignant gliomas. Cytokines and Angiogenesis factors are potential candidates due to their intrinsic role in tumourigenesis. Pre- and post-operative serum from 36 malignant glioma patients and 36 controls was analysed using the Bio-Plex Pro Angiogenesis and Cytokines Assay (Bio-Rad, USA). Amongst the molecules tested, the serum concentration of follistatin was significantly higher in patients than in controls. Moreover, the serum concentration of follistatin of the patients postoperatively was significantly reduced compared to that preoperatively. Factors such as age and gender did not affect the concentrations of follistatin measured in the serum of patients pre- and post-operatively as well as healthy controls. This is the first report of follistatin as potential biomarker for the detection of malignant gliomas

Social and spatial networks: Kinship distance and dwelling unit proximity in rural Thailand

We address a long hypothesized relationship between the proximity of individuals' dwelling units and their kinship association. Better understanding this relationship is important because of its implications for contact and association among members of a society. In this paper, we use a unique dataset from Nang Rong, Thailand which contains dwelling unit locations (GPS) and saturated kinship networks of all individuals living in 51 agricultural villages. After presenting arguments for a relationship between individuals’ dwelling unit locations and their kinship relations as well as the particulars of our case study, we introduce the data and describe our analytic approach. We analyze how kinship - considered as both a system linking collections of individuals in an extended kinship network and as dyadic links between pairs of individuals -patterns the proximity of dwelling units in rural villages. The results show that in general, extended kin live closer to one another than do unrelated individuals. Further, the degree of relatedness between kin correlates with the distance between their dwelling units. Close kin are more likely to co-reside, a fact which drives much of the relationship between kinship relatedness and dwelling unit proximity within villages. There is nevertheless suggestive evidence of a relationship between kinship association and dwelling unit proximity among kin who do not live together

Spectrochemical differentiation of meningioma tumours based on attenuated total reflection Fourier-transform infrared (ATR-FTIR) spectroscopy

Meningiomas are the commonest types of tumours in the central nervous system (CNS). It is a benign type of tumour divided into three WHO grades (I, II and III) associated with tumour growth rate and likelihood of recurrence, where surgical outcomes and patient treatments are dependent on the meningioma grade and histological subtype. The development of alternative approaches based on attenuated total reflection Fourier-transform infrared (ATR-FTIR) spectroscopy could aid meningioma grade determination and its biospectrochemical profiling in an automated fashion. Herein, ATR-FTIR in combination with chemometric techniques is employed to distinguish grade I, grade II and grade I meningiomas that re-occurred. Ninety-nine patients were investigated in this study where their formalin-fixed paraffin-embedded (FFPE) brain tissue samples were analysed by ATR-FTIR spectroscopy. Subsequent classification was performed via principal component analysis plus linear discriminant analysis (PCA-LDA) and partial least squares plus discriminant analysis (PLS-DA). PLS-DA gave the best results where grade I and grade II meningiomas were discriminated with 79% accuracy, 80% sensitivity and 73% specificity, while grade I versus grade I recurrence and grade II versus grade I recurrence were discriminated with 94% accuracy (94% sensitivity and specificity) and 97% accuracy (97% sensitivity and 100% specificity), respectively. Several wavenumbers were identified as possible biomarkers towards tumour differentiation. The majority of these were associated with lipids, protein, DNA/RNA and carbohydrate alterations. These findings demonstrate the potential of ATR-FTIR spectroscopy towards meningioma grade discrimination as a fast, low-cost, non-destructive and sensitive tool for clinical settings. Graphical abstract Attenuated total reflection Fourier-transform infrared (ATR-FTIR) spectroscopy was used to discriminate meningioma WHO grade I, grade II and grade I recurrence tumours

Combining random forest and 2D correlation analysis to identify serum spectral signatures for neuro-oncology

Fourier transform infrared (FTIR) spectroscopy has long been established as an analytical tech- nique for the measurement of vibrational modes of molecular systems. More recently, FTIR has been used for the analysis of biofluids with the aim of becoming a tool to aid diagnosis. For the clinician, this represents a convenient, fast, non-subjective option for the study of biofluids and the diagnosis of disease states. The patient also benefits from this method, as the procedure for the collection of serum is much less invasive and stressful than traditional biopsy. This is especially true of patients in whom brain cancer is suspected. A brain biopsy carries a degree of morbidity and mortality and on occasion may even be inconclusive. We therefore present a method for the diagnosis of brain cancer from serum samples using FTIR and machine learning techniques. The scope of the study involved 433 patients from whom were collected 9 spectra each in the range 600-4000 cm−1. To begin development of the novel method, various pre-processing steps were investigated and ranked in terms of final accuracy of the diagnosis. Random Forest machine learning was utilised as a classifier to separate patients into cancer or non-cancer categories based upon the intensities of wavenumbers present in their spectra. Generalised 2D correlational analysis was then employed to further augment the machine learning, and also to establish spec- tral features important for the distinction between cancer and non-cancer serum samples. Using these methods, sensitivities of up to 92.8% and specificities of up to 91.5% were possible. Fur- thermore, ratiometrics were also investigated in order to establish any correlations present in the dataset. We show a rapid, computationally light, accurate, statistically robust methodology for the identification of spectral features present in differing disease states. With current advances in IR technology, such as the development of rapid discrete frequency collection, this approach is import to allow future clinical translation and enables IR to achieve its potential

Stratifying Brain Tumour Histological Sub-Types: The Application of ATR-FTIR Serum Spectroscopy in Secondary Care

Patients living with brain tumours have the highest average years of life lost of any cancer, ultimately reducing average life expectancy by 20 years. Diagnosis depends on brain imaging and most often confirmatory tissue biopsy for histology. The majority of patients experience non-specific symptoms, such as headache, and may be reviewed in primary care on multiple occasions before diagnosis is made. Sixty-two per cent of patients are diagnosed on brain imaging performed when they deteriorate and present to the emergency department. Histological diagnosis from invasive surgical biopsy is necessary prior to definitive treatment, because imaging techniques alone have difficulty in distinguishing between several types of brain cancer. However, surgery itself does not necessarily control tumour growth, and risks morbidity for the patient. Due to their similar features on brain scans, glioblastoma, primary central nervous system lymphoma and brain metastases have been known to cause radiological confusion. Non-invasive tests that support stratification of tumour subtype would enhance early personalisation of treatment selection and reduce the delay and risks associated with surgery for many patients. Techniques involving vibrational spectroscopy, such as attenuated total reflection Fourier transform infrared (ATR-FTIR) spectroscopy, have previously demonstrated analytical capabilities for cancer diagnostics. In this study, infrared spectra from 641 blood serum samples obtained from brain cancer and control patients have been collected. Firstly, we highlight the capability of ATR-FTIR to distinguish between healthy controls and brain cancer at sensitivities and specificities above 90%, before defining subtle differences in protein secondary structures between patient groups through Amide I deconvolution. We successfully differentiate several types of brain lesions (glioblastoma, meningioma, primary central nervous system lymphoma and metastasis) with balanced accuracies >80%. A reliable blood serum test capable of stratifying brain tumours in secondary care could potentially avoid surgery and speed up the time to definitive therapy, which would be of great value for both neurologists and patients

Introducing discrete frequency infrared technology for high-throughput biofluid screening

Accurate early diagnosis is critical to patient survival, management and quality of life. Biofluids are key to early diagnosis due to their ease of collection and intimate involvement in human function. Large-scale mid-IR imaging of dried fluid deposits offers a high-throughput molecular analysis paradigm for the biomedical laboratory. The exciting advent of tuneable quantum cascade lasers allows for the collection of discrete frequency infrared data enabling clinically relevant timescales. By scanning targeted frequencies spectral quality, reproducibility and diagnostic potential can be maintained while significantly reducing acquisition time and processing requirements, sampling 16 serum spots with 0.6, 5.1 and 15% relative standard deviation (RSD) for 199, 14 and 9 discrete frequencies respectively. We use this reproducible methodology to show proof of concept rapid diagnostics; 40 unique dried liquid biopsies from brain, breast, lung and skin cancer patients were classified in 2.4 cumulative seconds against 10 non-cancer controls with accuracies of up to 90%