Medical management of neurogenic bladder in patients with spina bifida: A scoping review.

INTRODUCTION: Neurogenic bladder is a common source of morbidity in patients with spina bifida and can cause renal damage. Medical management may include imaging, urodynamic studies (UDS), laboratory testing, clean intermittent catheterization (CIC), and medication. There is ongoing debate regarding the optimal management regimen. Approaches are described by two paradigms: proactive and expectant management. In a proactive approach, invasive interventions like CIC and UDS are initiated before the onset of renal abnormalities. In expectant management, UDS, CIC, and medications are started after abnormalities are identified. In this scoping review, we aim to comprehensively review existing literature on outcomes of proactive and expectant management of neurogenic bladder in patients with spina bifida. METHODS: We searched multiple databases and screened articles for inclusion using PRISMA-ScR guidelines. Included studies reported clinical outcomes of any aspect of proactive or expectant neurogenic bladder management in patients with spina bifida. RESULTS: Ultimately, 74 articles were included for review including 67 cohort studies, 4 cross-sectional studies, 2 sequential cohort studies, and 1 randomized control trial. Eleven studies directly compared management strategies. There was substantial heterogeneity in study designs, management protocols, and reported outcomes. Most studies addressed multiple simultaneous aspects of management without specifically analyzing individual aspects. However, some commented on individual aspects of management including UDS (13), CIC (32), imaging (7), and medication (5). Although there was no consensus about optimal management, all direct comparisons of paradigms supported a proactive approach. CONCLUSION: Our review identified a broad body of literature about optimal management of neurogenic bladder. Existing studies vary greatly in terms of treatment protocols, measured outcomes, and management recommendations. Overall, studies that directly compare management are scarce but favor proactive management. Given the implications on clinical outcomes, it is crucial to focus future work on directly comparing management strategies and isolating the effects of different individual management elements.

Predicting postoperative complications in pediatric surgery: A novel pediatric comorbidity index.

INTRODUCTION/BACKGROUND: Comorbidity-driven surgical risk assessment is essential for informed patient counseling, risk-stratification, and outcomes-based health-services research. Existing mortality-focused comorbidity indices have had mixed success at risk-adjustment in children. OBJECTIVE: To develop a new comorbidity-driven multispecialty surgical risk index predicting 30-day postoperative complications in children. STUDY DESIGN: This retrospective cohort study investigated children undergoing surgical procedures across seven specialties in 2014-2015 using the MarketScan® Research databases. The risk index was derived separately for ambulatory and inpatient surgery patients using logistic regression with backward selection. The performance of the novel index in discriminating postoperative complications vis-à-vis three existing comorbidity indices was compared using bootstrapping and area under the receiver operating characteristics curves (AUC). RESULTS: We identified 190,629 ambulatory and 22,633 inpatient patients. The novel index had the best performance for discriminating postoperative complications for inpatients (AUC 0.76, 95% confidence interval [CI] 0.75-0.77) relative to the Charlson Comorbidity Index (CCI, 0.56, 95% CI 0.56-0.57), Van Walraven Index (VWI, 0.60, 95% CI 0.60-0.61), and Rhee Score (RS, 0.69, 95% CI 0.68-0.70). In the ambulatory cohort, the novel index outperformed all three existing indices, though none demonstrated excellent discriminatory ability for complications (novel score 0.68, 95% CI 0.67-0.68; CCI 0.53, 95% CI 0.52-0.53; VWI 0.53, 95% CI 0.52-0.53; RS 0.50, 95% CI 0.49-0.50). DISCUSSION: In both inpatient and ambulatory pediatric settings, our novel comorbidity index demonstrated better performance at predicting postoperative complications than three widely used alternatives. This index will be useful for research and may be adaptable to clinical settings to identify high-risk patients and facilitate perioperative planning. CONCLUSION: We developed a novel pediatric comorbidity index with better performance at predicting postoperative complications than three widely used alternatives.

Financial toxicity among individuals with spina bifida and their families: A qualitative study and conceptual model.

INTRODUCTION: Spina bifida is the most common permanently disabling birth defect in the United States and requires lifelong, multi-specialty care. The cost of such care has the potential to result in financial toxicity - the 'objective financial burden' and 'subjective financial distress' which can negatively impact clinical outcomes. While this concept has been extensively studied in other areas of medicine, particularly oncology, financial toxicity has not yet been examined in pediatric urology or in individuals with spina bifida and their families/caregivers. OBJECTIVE: To qualitatively explore the presence of financial toxicity in individuals with spina bifida and their caregivers with the objective of identifying themes and creating a conceptual model. MATERIALS AND METHODS: We conducted semi-structured interviews with individuals with spina bifida and/or their caregivers with the aim of eliciting information regarding financial distress associated with spina bifida care. Interviews were transcribed and qualitative thematic analysis was performed to identify recurring themes. These insights were used to create a conceptual model of financial toxicity among individuals with spina bifida. RESULTS: A total of 14 interviews were conducted (total of 6 patients and 13 parents/caregivers). Average patient age was 17.9 years. Five dominant themes were identified: 1) resources (insurance type, community support, etc.), 2) direct costs (copays, deductibles, travel expenses, etc.), 3) indirect costs (lost work time, hindered career advancement, resource navigation burden, etc.), 4) coping (work adjustments, decreased spending, etc.), and 5) affect (lack of control, uncertainty, worry, etc.). These insights were used to create a conceptual model. DISCUSSION: This is the first study to explore financial toxicity in spina bifida and establish a conceptual model. Our findings are corroborated by prior spina bifida literature and are closely mirrored by studies in cancer patients. Given that financial toxicity is associated with negative outcomes in other medical domains, the impact of financial toxicity on health outcomes among individuals with spina bifida warrants further study, particularly in instrument development to better understand and quantify financial toxicity in this group. CONCLUSION: Financial toxicity is a concern among individuals with spina bifida and their caregivers. This concept will need to be investigated further in order to develop validated measurement tools, identify solutions, and provide optimal care; our conceptual model will help guide these future investigations.

Combining adult with pediatric patient data to develop a clinical decision support tool intended for children: leveraging machine learning to model heterogeneity.

BACKGROUND: Clinical decision support (CDS) tools built using adult data do not typically perform well for children. We explored how best to leverage adult data to improve the performance of such tools. This study assesses whether it is better to build CDS tools for children using data from children alone or to use combined data from both adults and children. METHODS: Retrospective cohort using data from 2017 to 2020. Participants include all individuals (adults and children) receiving an elective surgery at a large academic medical center that provides adult and pediatric services. We predicted need for mechanical ventilation or admission to the intensive care unit (ICU). Predictor variables included demographic, clinical, and service utilization factors known prior to surgery. We compared predictive models built using machine learning to regression-based methods that used a pediatric or combined adult-pediatric cohort. We compared model performance based on Area Under the Receiver Operator Characteristic. RESULTS: While we found that adults and children have different risk factors, machine learning methods are able to appropriately model the underlying heterogeneity of each population and produce equally accurate predictive models whether using data only from pediatric patients or combined data from both children and adults. Results from regression-based methods were improved by the use of pediatric-specific data. CONCLUSIONS: CDS tools for children can successfully use combined data from adults and children if the model accounts for underlying heterogeneity, as in machine learning models.

Machine Learning for Urodynamic Detection of Detrusor Overactivity.

OBJECTIVE: To develop a machine learning algorithm that identifies detrusor overactivity (DO) in Urodynamic Studies (UDS) in the spina bifida population. UDS plays a key role in assessment of neurogenic bladder in patients with spina bifida. Due to significant variability in individual interpretations of UDS data, there is a need to standardize UDS interpretation. MATERIALS AND METHODS: Patients who underwent UDS at a single pediatric urology clinic between May 2012 and September 2020 were included. UDS files were analyzed in both time and frequency domains, varying inclusion of vesical, abdominal, and detrusor pressure channels. A machine learning pipeline was constructed using data windowing, dimensionality reduction, and support vector machines. Models were designed to detect clinician identified detrusor overactivity. RESULTS: Data were extracted from 805 UDS testing files from 546 unique patients. The generated models achieved good performance metrics in detecting DO agreement with the clinician, in both time- and frequency-based approaches. Incorporation of multiple channels and data windowing improved performance. The time-based model with all 3 channels had the highest area under the curve (AUC) (91.9 ± 1.3%; sensitivity: 84.2 ± 3.8%; specificity: 86.4 ± 1.3%). The 3-channel frequency-based model had the highest specificity (AUC: 90.5 ± 1.9%; sensitivity: 68.3 ± 5.3%; specificity: 92.9 ± 1.1%). CONCLUSION: We developed a promising proof-of-concept machine learning pipeline that identifies DO in UDS. Machine-learning-based predictive modeling algorithms may be employed to standardize UDS interpretation and could potentially augment shared decision-making and improve patient care.

Patient Narratives as a Teaching Tool: A Pilot Study of First-Year Medical Students and Patient Educators Affected by Intellectual/Developmental Disabilities.

PROBLEM: People with intellectual and developmental disabilities (IDD) face complex biopsychosocial challenges and are medically underserved. This is in part due to insufficient resources and supports but can also be attributed to a lack of adequate physician training in addressing the unique needs of this population. INTERVENTION: This study aimed to introduce 1st-year medical students to the IDD population using a blended educational experience that included video narratives of and direct interactions with people affected by IDD. The goal of this intervention was to promote person-centered attitudes and communication among early medical trainees. CONTEXT: The study recruited 27 first-year medical students and randomly assigned each to 1 of 2 groups. The control group received an introductory video lecture about IDD healthcare, followed by a quiz. The narrative group received the same lecture, followed by reflective discussion of videos featuring people living with IDD sharing their perspectives and stories. All students then participated in 4 simulated clinical encounters with patient educators (PEs) who have lived experiences of IDD. Focus groups were conducted with students following the simulated encounters to explore their experiences and perceptions of this blended learning activity. Moreover, secondary quantitative data were collected to assess students' performance in the clinical encounters, along with self-reports of comfort, confidence, and competence of interacting with people with IDD (pre- and postparticipation). OUTCOME: All students thought that the blended educational experience was valuable and enjoyable, commenting on the importance of adaptable language and engagement of people with IDD, as well as the merits of reflecting on patient narratives. Students also discussed feelings of discomfort stemming from a lack of knowledge and previous exposure to IDD and how this discomfort might motivate them to learn more and develop their skills further. In addition, descriptive analyses revealed that students in the narrative group showed greater self-rated measures of comfort, confidence, and competence compared to control; they also had higher mean performance scores across all PE interview stations. LESSONS LEARNED: PEs add a powerful real-life dimension to communication skills teaching and have been shown to be a valuable educational modality. Moreover, exposure to and reflection on video-based patient narratives are useful ways of teaching medical students about patients' lived experiences and promoting person-centered communication, both within and beyond IDD.

Temperature sensitivity of the pyloric neuromuscular system and its modulation by dopamine.

We report here the effects of temperature on the p1 neuromuscular system of the stomatogastric system of the lobster (Panulirus interruptus). Muscle force generation, in response to both the spontaneously rhythmic in vitro pyloric network neural activity and direct, controlled motor nerve stimulation, dramatically decreased as temperature increased, sufficiently that stomach movements would very unlikely be maintained at warm temperatures. However, animals fed in warm tanks showed statistically identical food digestion to those in cold tanks. Applying dopamine, a circulating hormone in crustacea, increased muscle force production at all temperatures and abolished neuromuscular system temperature dependence. Modulation may thus exist not only to increase the diversity of produced behaviors, but also to maintain individual behaviors when environmental conditions (such as temperature) vary.

High-resolution computed tomography of lobster (Panulirus interruptus) stomach.

We used micro computed tomography to produce a high-resolution density image of the lobster (Panulirus interruptus) stomach and identified on this image the previously defined stomach ossicles. These data are the first coordinate-based, three-dimensional description of the stomach and are a necessary first step for developing biomechanical models of it. They are also interesting for several reasons in their own right. First, the ossicles showed large shape and density variations. These data suggest that different ossicles may serve different functions, with some acting as force-delivering levers, some as spring-like elements, and some as wall-like elements that resist internal stomach pressure or function as two-dimensional force-delivering plates. Second, large intra-ossicle density variations were present in individual ossicles, reminiscent of I-beams, oval bicycle frames, and similar mass-minimizing structural elements, suggesting that evolution has minimized ossicle mass and identifying which ossicle regions are most likely important in force delivery. Third, joints appeared to be either continuous density interconnections without distinct separations between the ossicles or 'floating' joints in which the ends of the two ossicles were separated by relatively large distances spanned by connective tissue. In these latter joints, although the distance between ossicle ends is likely maintained at a relatively constant value, a wide range of ossicle angles would thus be theoretically possible. Notably absent are close-apposition, morphologically specialized joints such as hinge or ball-and-socket joints.

Slow conductances could underlie intrinsic phase-maintaining properties of isolated lobster (Panulirus interruptus) pyloric neurons.

The rhythmic pyloric network of the lobster stomatogastric system approximately maintains phase (that is, the burst durations and durations between the bursts of its neurons change proportionally) when network cycle period is altered by current injection into the network pacemaker (Hooper, 1997a,b). When isolated from the network and driven by rhythmic hyperpolarizing current pulses, the delay to firing after each pulse of at least one network neuron type [pyloric (PY)] varies in a phase-maintaining manner when cycle period is varied (Hooper, 1998). These variations require PY neurons to have intrinsic mechanisms that respond to changes in neuron activity on time scales at least as long as 2 s. Slowly activating and deactivating conductances could provide such a mechanism. We tested this possibility by building models containing various slow conductances. This work showed that such conductances could indeed support intrinsic phase maintenance, and we show here results for one such conductance, a slow potassium conductance. These conductances supported phase maintenance because their mean activation level changed, hence altering neuron postinhibition firing delay, when the rhythmic input to the neuron changed. Switching the sign of the dependence of slow-conductance activation and deactivation on membrane potential resulted in neuron delays switching to change in an anti-phase-maintaining manner. These data suggest that slow conductances or similar slow processes such as changes in intracellular Ca(2+) concentration could underlie phase maintenance in pyloric network neurons.

Pyloric neuron morphology in the stomatogastric ganglion of the lobster, Panulirus interruptus.

The pyloric network of decapod crustaceans has been intensively studied electrophysiologically in the infraorders Astacidea, Brachyura, and Palinura. The morphology of some or all pyloric neurons has been well described in Astacidea and Brachyura, but less so in Palinura. Given the large evolutionary distance between these three groups, and the large amount of electrophysiology that has been performed in palinuroid species, it is important to fill this gap. We describe here the gross morphology of all six pyloric neuron types in a palinuroid, P. interruptus. All pyloric neurons had complicated, extended dendritic trees that filled the majority of the neuropil, with most small diameter processes present in a shell near the surface of the ganglion. Certain neuron types showed modest preferences for somata location in the ganglion, but these differences were too weak to use as identifying characteristics. Quantitative measurements of secondary branch number, maximum branch order, total process length, and neuron somata diameter were also, in general, insufficient to distinguish among the neurons, although AB and LP neuron somata diameters differed from those of the other types. One neuron type (VD) had a distinctive neurite branching pattern consisting of a small initial branch followed shortly by a bifurcation of the main neurite. The processes arising from these two branches occupied largely non-overlapping neuropil. Electrophysiological recordings showed that each major branch had its own spike initiation zone and that, although the zones fired correlated spikes, they generated spikes independently. VD neurons in the other infraorders have similar morphologies, suggesting that having two arbors is important for the function of this neuron. These data are similar to those previously obtained in Brachyura and Astacidea. It thus appears that, despite their long evolutionary separation, neuron morphology in these three infraorders has not greatly diverged.

Invertebrate muscles: thin and thick filament structure; molecular basis of contraction and its regulation, catch and asynchronous muscle.

This is the second in a series of canonical reviews on invertebrate muscle. We cover here thin and thick filament structure, the molecular basis of force generation and its regulation, and two special properties of some invertebrate muscle, catch and asynchronous muscle. Invertebrate thin filaments resemble vertebrate thin filaments, although helix structure and tropomyosin arrangement show small differences. Invertebrate thick filaments, alternatively, are very different from vertebrate striated thick filaments and show great variation within invertebrates. Part of this diversity stems from variation in paramyosin content, which is greatly increased in very large diameter invertebrate thick filaments. Other of it arises from relatively small changes in filament backbone structure, which results in filaments with grossly similar myosin head placements (rotating crowns of heads every 14.5 nm) but large changes in detail (distances between heads in azimuthal registration varying from three to thousands of crowns). The lever arm basis of force generation is common to both vertebrates and invertebrates, and in some invertebrates this process is understood on the near atomic level. Invertebrate actomyosin is both thin (tropomyosin:troponin) and thick (primarily via direct Ca(++) binding to myosin) filament regulated, and most invertebrate muscles are dually regulated. These mechanisms are well understood on the molecular level, but the behavioral utility of dual regulation is less so. The phosphorylation state of the thick filament associated giant protein, twitchin, has been recently shown to be the molecular basis of catch. The molecular basis of the stretch activation underlying asynchronous muscle activity, however, remains unresolved.

Using complicated, wide dynamic range driving to develop models of single neurons in single recording sessions.

Neuron models are typically built by measuring individually, for each membrane conductance, its parameters (e.g., half-maximal voltages) and maximal conductance value (g(max)). However, neurons have extended morphologies with nonuniform conductance distributions, whereas models generally contain at most a few compartments. Both the original conductance measurements and the models therefore unavoidably contain error due to the electrical filtering of neurons and the differential placement of conductances on them. Model parameters (typically g(max) values) are therefore generally altered by hand or brute force to match model and neuron activity. We propose an alternative method in which complicated, rapidly changing driving input is used to optimize model parameters. This method also ensures that neuron and model dynamics match across a wide dynamic range, a test not performed in most modeling. We tested this concept using leech heartbeat and generic tonically firing models and lobster stomatogastric and generic bursting models as targets and g(max) values as optimized parameters. In all four cases optimization solutions excellently matched target activity. Complicated, wide dynamic range driving thus appears to be an excellent method to characterize neuron properties in detail and to build highly accurate models. In these completely defined targets, the method found each target's 8-13 g(max) values with high accuracy, and may therefore also provide an alternative, functionally based method of defining neuron g(max) values. The method uses only standard experimental and computational techniques, could be easily extended to optimize conductance parameters other than g(max), and should be readily applicable to real neurons.

Nanostructured biosensors built by layer-by-layer electrostatic assembly of enzyme-coated single-walled carbon nanotubes and redox polymers.

In this study, we describe the construction of glucose biosensors based on an electrostatic layer-by-layer (LBL) technique. Gold electrodes were initially functionalized with negatively charged 11-mercaptoundecanoic acid followed by alternate immersion in solutions of a positively charged redox polymer, poly[(vinylpyridine)Os(bipyridyl)2Cl(2+/3+)], and a negatively charged enzyme, glucose oxidase (GOX), or a GOX solution containing single-walled carbon nanotubes (SWNTs). The LBL assembly of the multilayer films were characterized by UV-vis spectroscopy, ellipsometry, and cyclic voltammetry, while characterization of the single-walled nanotubes was performed with transmission electron microscopy, Raman spectroscopy, thermogravimetric analysis, and X-ray photoelectron spectroscopy. When the GOX solution contained single-walled carbon nanotubes (GOX-SWNTs), the oxidation peak currents during cyclic voltammetry increased 1.4-4.0 times, as compared to films without SWNTs. Similarly the glucose electro-oxidation current also increased (6-17 times) when SWNTs were present. By varying the number of multilayers, the sensitivity of the sensors could be controlled.

A computational role for slow conductances: single-neuron models that measure duration.

Humans effortlessly interpret speech and music, whose patterns can contain sound durations up to thousands of milliseconds. How nervous systems measure such long durations is unclear. We show here that model neurons containing physiological slow conductances are 'naturally' sensitive to duration, replicate known duration-sensitive neurons and can be 'tuned' to respond to a wide range of specific durations. In addition, these models reproduce several other properties of duration-sensitive neurons not selected for in model construction. These data, and the widespread presence of slow conductances in nervous systems, suggest that slow conductances might play a major role in duration measurement.