Phylogeny, morphology, and behavior of the new ciliate species Stentor stipatus

The study of evolution at the cellular level traditionally has focused on the evolution of metabolic pathways, endomembrane systems, and genomes, but there has been increasing interest in evolution of more complex cellular structures and behaviors, particularly in the eukaryotes. Ciliates have major advantages for such studies due to their easily visible surface patterning and their dramatic and complex behaviors that can be easily analyzed. Among the ciliates, the genus Stentor epitomizes the features that are useful for studying evolution: they are widespread in freshwater environments, easy to visualize because of their large size, and capable of complex behaviors such as learning, decision-making, and phototaxis. Here, we introduce the discovery of a new species within this genus: Stentor stipatus , so named for their distinctive dark brown aggregates. We present morphological, phylogenetic, ecological, and behavioral characterizations of these cells. The S. stipatus clade has a bootstrap value of 93 and is phylogenetically distinct from S. amethystinus , the closest related species which shares a sequence similarity of 98.9%. S. stipatus is capable of phototaxis and can also habituate more quickly than S. coeruleus , the Stentor species in which most habituation studies have previously been conducted. These findings expand our understanding of Stentor species diversity, natural history, and demonstrate common principles of complex behavior that are present in single-celled organisms.

Early onset metastatic colorectal cancer in Australia

BACKGROUND

Colorectal cancer (CRC) incidence and mortality rates have been increasing among young patients (YP), for uncertain reasons. It is unclear whether YP have a distinct tumor biology or merit a different treatment approach to older patients (OP).

METHODS

We reviewed prospectively collected data from consecutive patients with metastatic CRC (MCRC) enrolled in the multi-site Treatment of Recurrent and Advanced Colorectal Cancer (TRACC) Australian registry. Clinicopathological features, treatment and survival outcomes were compared between YP (<50 years) and OP (≥50 years).

RESULTS

Of 3692 patients diagnosed August 2009 - March 2023, 14 % (513) were YP. YP were more likely than OP to be female (52% vs. 40 %, P < 0.0001), have ECOG performance status 0-1 (94% vs. 81 %, P < 0.0001), to have a left-sided primary (72% vs. 63 %, P = 0.0008) and to have fewer comorbidities (90% vs. 60 % Charleston score 0, P < 0.0001). There were no differences in the available molecular status, which was more complete in YP. YP were more likely to have de novo metastatic disease (71% vs. 57 %, P < 0.0001). YP were more likely to undergo curative hepatic resection (27% vs. 17 %, P < 0.0001), to receive any chemotherapy (93% vs. 78 % (P < 0.0001), and to receive 3+ lines of chemotherapy (30% vs. 24 % (P < 0.0034)). Median first-line progression free survival (10.2 versus 10.6 months) was similar for YP vs OP, but overall survival (32.1 versus 25.4 months, HR = 0.745, P < 0.0001) was longer in YP.

CONCLUSION

Known prognostic variables mostly favored YP versus OP with newly diagnosed mCRC, who were also more heavily treated. Consistent with this, overall survival outcomes were improved. This data does not support that CRC in YP represent a distinct subset of mCRC patients, or that a modified treatment approach is warranted.

Screening, brief intervention, and referral to treatment for tobacco consumption, alcohol misuse, and physical inactivity: an equity-informed rapid review

OBJECTIVE

This rapid review systematically synthesizes evidence of the effectiveness of the Screening, Brief Intervention, and Referral (SBIR/T) approach for tobacco use, alcohol misuse, and physical inactivity.

STUDY DESIGN

This was a rapid review.

METHODS

We searched primary studies between 2012 and 2022 in seven electronic databases. The search strategy used concepts related to alcohol-related disorders, intoxication, cigarette, nicotine, physical activity, exercise, sedentary, screening, therapy, and referral. We reviewed both title/abstract and full-text using a priori set inclusion and exclusion criteria to identify the eligible studies. We appraised study quality, extracted data, and summarized the characteristics of the included studies. We applied health equity lenses in the synthesis.

RESULTS

Of the 44 included studies, most focused on alcohol misuse. SBIR/T improved patients' attitudes toward alcohol behavior change, improved readiness and referral initiation for change, and effectively reduced alcohol consumption. Few studies pertained to smoking and physical inactivity. Most studies on smoking demonstrated effectiveness pertaining to patients' acceptance of referral recommendations, improved readiness and attempts to quitting smoking, and reduced or cessation of smoking. Findings were mixed about the effectiveness of SBIR/T in improving physical activity. Minimal studies exist on the impacts of SBIR/T for these three risk factors on healthcare resource use or costs. Studies considering diverse population characteristics in the design and effectiveness assessment of the SBIR/T intervention are lacking.

CONCLUSIONS

More research on the impacts of SBIR/T on tobacco use, alcohol misuse, and physical inactivity is required to inform the planning and delivery of SBIR/T for general and disadvantaged populations.

Structure guided mutagenesis of Henipavirus Receptor Binding Proteins reveals molecular determinants of receptor usage and antibody binding epitopes

Nipah virus (NiV) is a highly lethal, zoonotic henipavirus (HNV) that causes respiratory and neurological signs and symptoms in humans. Similar to other paramyxoviruses, HNVs mediate entry into host cells through the concerted actions of two surface glycoproteins: a receptor binding protein (RBP) that mediates attachment and a fusion glycoprotein (F) that triggers fusion in an RBP-dependent manner. NiV uses ephrin-B2 (EFNB2) and ephrin-B3 (EFNB3) as entry receptors. Ghana virus (GhV), a novel HNV identified in a Ghanaian bat, use EFNB2 but not EFNB3. In this study, we employ a structure-informed approach to identify receptor interfacing residues and systematically introduce GhV-RBP residues into a NiV-RBP backbone to uncover the molecular determinants of EFNB3 usage. We reveal two regions that severely impair EFNB3 binding by NiV-RBP and EFNB3-mediated entry by NiV pseudotyped viral particles. Further analyses uncovered two point mutations (NiVN557SGhV and NiVY581TGhV) pivotal for this phenotype. Moreover, we identify NiV interaction with Y120 of EFNB3 as important for usage of this receptor. Beyond these EFNB3-related findings, we reveal two domains that restrict GhV binding of EFNB2, identify the HNV-head as an immunodominant target for polyclonal and monoclonal antibodies, and describe putative epitopes for GhV and NiV-specific monoclonal antibodies. Cumulatively, the work presented here generates useful reagents and tools that shed insight to residues important for NiV usage of EFNB3, reveals regions critical for GhV binding of EFNB2, and describes putative HNV antibody binding epitopes.

Integrating a Tool to Automatically Determine Necessity of Online Adaptive Replanning

PURPOSE/OBJECTIVE(S)

As online adaptive replanning (OLAR) is labor-intensive and time-consuming, it's desirable to determine when OLAR is necessary before OLAR is initiated. We have previously reported a novel method to automatically determine the necessity of OLAR using machine leaning algorithms based on the structural similarity maps (SSIM) and wavelet texture maps (WMT) extracted from the daily MRI during MR-guided adaptive radiation therapy (MRgART). This study aims to integrate this method into a commercial software platform that has been used during our routine MRgART.

MATERIALS/METHODS

The method of automatically determining the necessity of OLAR based on daily MRI was implemented and integrated into the software platform through a specifically developed workflow. The obtained workflow was tested using 25 daily MRI sets acquired from 5 patients with pancreatic cancer in the following procedure: 1) rigidly registering the daily and reference MRIs, 2) identifying the region enclosed by the 50-100% iso-dose surfaces on the daily MRI by transferring the iso-dose surfaces from the reference to the daily MRIs, 3) launching our in-house codes to calculate significant changes in textures extracted from SSIM and WMT maps, 4) inputting the feature values into the pre-trained classifier models for SSIM and WMT, and 5) outputting results considering the WMT based prediction as the primary indicator and the SSIM-based as the secondary (validation) indicator on whether OLAR is needed for the daily MRI.

RESULTS

The execution of the developed workflow was fast and can be used to streamline the process. It provides the ability to scroll through the images for better decision making while providing quantitative prediction within 30-38 seconds. Eighty percent of the daily MRIs required OLAR. The SSIM map displayed was able to successfully captured the areas of similarity between the reference and daily MRIs and the WMT prediction agreed with the prediction class.

CONCLUSION

The integration of the prediction method for automatically determining the necessity of OLAR based on two independent machine learning classifiers into a commercially available software is feasible and can be used to streamline the process of MRgART. With larger verification studies, this workflow-based tool may be developed into a generalized tool that assist in OLAR using different platforms.

Uncertainty in phosphorus fluxes and budgets across the U.S. long-term agroecosystem research network

Phosphorus (P) budgets can be useful tools for understanding nutrient cycling and quantifying the effectiveness of nutrient management planning and policies; however, uncertainties in agricultural nutrient budgets are not often quantitatively assessed. The objective of this study was to evaluate uncertainty in P fluxes (fertilizer/manure application, atmospheric deposition, irrigation, crop removal, surface runoff, leachate) and the propagation of these uncertainties to annual P budgets. Data from 56 cropping systems in the P-FLUX database, which spans diverse rotations and landscapes across the U.S. and Canada, were evaluated. Results showed that across cropping systems, average annual P budget was 22.4 kg P ha^-1 (range = -32.7 to 340.6 kg P ha^-1 ), with an average uncertainty of 13.1 kg P ha^-1 (range = 1.0 to 87.1 kg P ha^-1 ). Fertilizer/manure application and crop removal were the largest P fluxes across cropping systems and, as a result, accounted for the largest fraction of uncertainty in annual budgets (61 and 37%, respectively). Remaining fluxes individually accounted for <2% of the budget uncertainty. Uncertainties were large enough that determining whether P was increasing, decreasing, or not changing was inconclusive in 39% of the budgets evaluated. Findings indicate that more careful and/or direct measurements of inputs, outputs, and stocks are needed. Recommendations for minimizing uncertainty in P budgets based on the results of the study were developed. Quantifying, communicating, and constraining uncertainty in budgets among production systems and multiple geographies is critical for engaging stakeholders, developing local and national strategies for P reduction, and informing policy. This article is protected by copyright. All rights reserved.

Initial phase establishment of an in vitro method for developmental neurotoxicity test using Ki-67 in human neural progenitor cells

Building a precise alternative neurotoxicological test is of great importance to respond to societal and ethical requirements. In this study, a new developmental neurotoxicity test (DNT) was established with the human neural progenitor cell line. ReNcell CX cells were exposed to neurotoxic chemicals (aphidicolin, hydroxyurea, cytosine arabinoside, 5-fluorouracil, and ochratoxin A) or non-neurotoxic chemicals (sodium gluconate, sodium bicarbonate, penicillin G, and saccharin). Propidium iodide (PI) was used to evaluate cell viability. BrdU and Ki-76 were employed to determine cell proliferation. Based on the cell viability and proliferation, mathematical models were built by linear discriminant analysis. Furthermore, the neurotoxic-considered chemicals inhibited cell cycle progression at the protein level, supporting the biomolecular rationale for the predictive model. Overall, these results show that the new test method can be used to determine the potential developmental neurotoxicants or new drug candidates.

Integrating EM and Patch-seq data: Synaptic connectivity and target specificity of predicted Sst transcriptomic types

Neural circuit function is shaped both by the cell types that comprise the circuit and the connections between those cell types ¹ . Neural cell types have previously been defined by morphology ^{2, 3} , electrophysiology ^{4, 5} , transcriptomic expression ^6-8 , connectivity ^9-13 , or even a combination of such modalities ^14-16 . More recently, the Patch-seq technique has enabled the characterization of morphology (M), electrophysiology (E), and transcriptomic (T) properties from individual cells ^17-20 . Using this technique, these properties were integrated to define 28, inhibitory multimodal, MET-types in mouse primary visual cortex ²¹ . It is unknown how these MET-types connect within the broader cortical circuitry however. Here we show that we can predict the MET-type identity of inhibitory cells within a large-scale electron microscopy (EM) dataset and these MET-types have distinct ultrastructural features and synapse connectivity patterns. We found that EM Martinotti cells, a well defined morphological cell type ^{22, 23} known to be Somatostatin positive (Sst+) ^{24, 25} , were successfully predicted to belong to Sst+ MET-types. Each identified MET-type had distinct axon myelination patterns and synapsed onto specific excitatory targets. Our results demonstrate that morphological features can be used to link cell type identities across imaging modalities, which enables further comparison of connectivity in relation to transcriptomic or electrophysiological properties. Furthermore, our results show that MET-types have distinct connectivity patterns, supporting the use of MET-types and connectivity to meaningfully define cell types.

The Factors and Relationships Influencing Forest Hiking Exercise Characteristics after COVID-19 Occurrence: At Seoul Metropolitan Area and in Hikers' 20s and 30s

The growing interest and usage of green space during the pandemic relates to why greenery increases enjoyment of daily life and alleviates troubles arising from infectious periods. However, it is necessary to understand what reactions to the degree of COVID-19's spread were expressed in hiking exercise characteristics (hiking frequency, actual movement distance, average speed, total exercise time). To understand the progress of forest usage behavior during the pandemic, we analyzed factors influencing hiking exercise characteristics and relationships between those factors and hiking exercise characteristics. Hiking record data were obtained (2019-2020) from the workout app "Tranggle" pertaining to hikers in their 20s and 30s who visited the 13 mountains in the Seoul Metropolitan Area most frequently. The differences in hiking exercise characteristics (2019 data subtracted from 2020) were linked with factor data that could be related to them, including the degree of COVID-19's spread (Rt). To explore relationships between hiking exercise characteristics and factors, we developed four models with a linear mixed model. We found that Rt, week, weekdays/weekends, and PM10 contributed to explaining the hiking exercise characteristics' differences. As a result of this analysis, the degree of COVID-19's spread (Rt) affected hiking frequency; the week affected hiking frequency and actual movement distance; weekdays or weekends affected hiking frequency, actual movement distance, average speed, and total exercise time; and PM10 affected hiking frequency. These findings indicate that hiking was an alternative way for those looking for a new strategy to replace lost opportunities for physical activity. Therefore, we conclude that it is necessary to induce the usage of green space so that many people can take advantage of the functions and benefits of greenery, which stood out during the pandemic era.

Stent expansion evaluated by optical coherence tomography and subsequent outcomes

Background

Regarding stent expansion indexes, previous optical coherence tomography (OCT) studies have shown minimal stent area (MSA) to be most predictive of adverse events.

Purpose

We sought to evaluate the impact of various stent expansion indexes by post-stent OCT on long-term clinical outcomes, and hence to find OCT-defined optimal stent expansion criteria.

Methods

Of the patients registered in the Yonsei OCT registry, a total of 1071 patients with 1123 native coronary artery lesions treated with new-generation drug-eluting stents under the OCT guidance and analyzable final post-stent OCT were included. Stent expansion indexes and different suboptimal stent expansion criteria were evaluated for their association with device-oriented clinical endpoints (DoCE) including cardiac death, target vessel-related myocardial infarction (TVMI) or stent thrombosis, and target lesion revascularization. Major safety events (MSE) included cardiac death, TVMI or stent thrombosis.

Results

The median follow-up period was 40.6 (interquartile range 22.0–50.0) months. As a continuous variable, MSA, adaptive volumetric stent expansion (stent volume/adaptive reference lumen volume) and overall volumetric stent expansion (stent volume/post-stent lumen volume) were significantly predictive of DoCE. As a categorical criteria, MSA &lt;5.0 mm2 (hazard ratio [HR] 3.80; 95% confidence interval [CI] 1.53–9.45), MSA/distal reference lumen area &lt;90% (HR 2.13; 95% CI 1.10–4.14), and overall volumetric stent expansion ≥96.6% (HR 2.38; 95% CI 1.09–5.22) were independently associated with DoCE after adjusting for confounders, and a total malapposition volume ≥7.0 mm3 (HR 3.38; 95% CI 1.05–10.93) was linked to MSE.

Conclusions

This OCT study highlights that sufficient stent expansion to achieve adequate absolute MSA and relative MSA by distal reference lumen area and alleviate significant malapposition is important to improve clinical outcome, but overall stent overexpansion may have deleterious effect.

Funding Acknowledgement

Type of funding sources: None.

Atrial fibrillation detection in ambulatory patients using a smart ring powered by deep learning analysis of continuous photoplethysmography monitoring

Background

Atrial fibrillation (AF) detection could be effective with photoplethysmography (PPG) signal monitoring by a wearable device.

Purpose

We aimed to validate the performance of AF detection among ambulatory patients who underwent electrical cardioversion for AF using a smart ring capable of continuous PPG monitoring and deep learning analysis.

Methods

In this prospective single-arm study, participants who underwent successful electrical cardioversion for AF were enrolled. The participants equipped a smart ring (CardioTracker, Sky Labs Inc., Seongnam, Republic of Korea) after the electrical cardioversion. The smart ring then continuously monitored PPG over 14 days to detect AF recurrence. The smart ring alarmed AF episodes based on deep learning analysis of PPG. The participants were asked to measure at least three daily ECGs using the smart ring to validate AF recurrence detected by PPG. All ECG snapshots were recorded along with lead I and saved with simultaneous PPG. ECG data were examined by the three cardiologists independently (SK, SRL, and EKC). The monitoring time, analyzable proportions of monitored signals, detection rates of AF episodes, and the diagnostic performance of PPG-based deep learning were evaluated. At the end of the monitoring, a survey on the use of the smart ring was performed.

Results

A total of 35 participants (mean age 58.9 years, male 74.3%) were enrolled. Figure 1 illustrates an example of PPG monitoring and PPG-ECG snapshots by the smart ring. The study participation period was a median of 14 days and the wearing time of the smart ring was a median of 9.2 days (IQR 7.1–11.5 days). Signal artifacts during daily activity decreased the analyzable proportions of monitored PPG by 68.5%. Irregular pulse episodes were detected by the smart ring in 29 (82.9%) participants after a median of 1 day from the cardioversion (Figure 2). A total of 2532 PPG-ECG snapshots were acquired and 1623 (64.1%) were interpretable by both the cardiologists (using ECG) and the deep learning analysis (using PPG). Comparing PPG by simultaneous ECG, the performance of AF detection by the smart ring was 98.7% for sensitivity, 97.8% for specificity, 2.2% for false positives, and 1.3% for false negatives (Figure 2). After using the smart ring, 76.9% of the participants responded that they had no discomfort in using the smart ring in daily activity and another 76.9% responded that it was helpful to monitor their disease.

Conclusion

Despite the signal artifacts during daily activity, AF detection with PPG monitoring by a smart ring could be effective for AF screening among ambulatory patients.

Funding Acknowledgement

Type of funding sources: Private company. Main funding source(s): This work was supported by Sky Labs Inc, Seongnam, Republic of Korea, and by the grant No. 0320202040 from the Seoul National University Hospital Research Fund.

POS0763 A MULTIMODAL MAGNETIC RESONANCE IMAGING STUDY OF COGNITIVE FUNCTION IN SYSTEMIC LUPUS ERYTHEMATOSUS: A MACHINE LEARNING APPROACH

Background

Systemic lupus erythematosus (SLE) is a multisystem autoimmune disorder that can affect the central nervous system. Cognitive dysfuncion is the most common neuropsyhiatric event in SLE patients, yet it is also one of the hardest to diagnose.

Objectives

To investigate if multimodal imaging to assess anatomical magnetic resonance imaging (MRI) abnormalities in the brains of SLE patients can predict cognitive function.

Methods

Subjects underwent voxel-based morphometry (VBM), magnetization transfer imaging (MTI), and dynamic contrast-enhanced (DCE) MRI. Automated Neuropsychological Assessment Metrics (ANAM) was used to assess cognitive function in this cross-sectional study and the primary measure was the total throughput score (TTS). TTS is the total of the throughput scores for each of the 8 ANAM subtests: (i) code substitution learning (CSL); (ii) code substitution immediate (CSI); (iii) code substitution delayed (CSD); (iv) spatial processing (SP); (v) matching to sample (MSP); (vi) running memory continuous performance test (CPT); (vii) mathematical processing (MTH) and (viii) memory search (MS). Olfactory assessment was done using the University of Pennsylvania Smell Identification Test. We used a machine learning-based model (i.e. GLMnet) to predict TTS. Subjects with active SLE disease or above 40 years old were excluded.

Results

Thirty SLE patients [26 female, 32.0 (26.8-37.0) years] without clinically overt neuropsychiatric manifestations and 10 healthy controls (HCs) [9 females, 27.0 (23.0-31.5) years] were enrolled in this study. Both groups had comparable cognitive and olfactory functions. No significant differences were observed in VBM, MTR, olfactory blub and tract (OBT) volume in SLE patients compared to HCs. We observed increased blood-brain barrier (BBB) permeability parameters (Ktrans and PS) in several regions of SLE patients. DCE-MRI perfusion parameters such as perfusion (F) and vp but not permeability measures were associated with TTS. In particular, F right amygdala correlated with TTS in SLE patients (r = 0.636, FDR p < 0.05) (Table 1). Using GLMnet, we trained a multimodal MRI model comprising of VBM, MTR, DCE-MRI and OBT volume parameters to predict TTS in SLE patients (r = 0.998, p < 0.0005) (Figure 1).

Figure 1.

Machine learning-based models to predict cognitive function.

Table 1.

Correlation between ANAM tests with perfusion (F) in SLE patients, ranked in descending order of statistical significance for TTS.

VariableTTSCSLCSICSDSPMSPCPTMTHMSF right amygdala0.636‡*0.520‡0.3370.437†0.559‡0.3230.633‡0.412†0.598‡F left entorhinal0.504‡0.422†0.3660.416†0.3050.1850.530‡0.1860.416†F left amygdale0.495‡0.400†0.1890.378†0.3300.2370.491‡0.376†0.449†F choroid0.469†0.384†0.2160.413†0.458†0.2020.456†0.3400.406†plexusF right rostal anterior cingulate0.453†0.3010.1180.2960.393†0.2140.547‡0.420†0.383†F right entorhinal0.448†0.368†0.2320.3120.376†0.1560.438†0.2710.407†F cerebellum white matter0.427†0.3580.2010.370†0.2730.0780.449†0.2900.297F left hippocampus0.427†0.3550.1340.390†0.3560.2030.511‡0.3360.332F brain stem0.407†0.2980.1380.2750.2940.1530.478‡0.3080.369†F right insula0.407†0.3080.0740.3000.3240.1760.437†0.3230.347F left parietal0.400†0.2630.0920.2540.2940.2240.487‡0.2740.332F ventricles0.396†0.3030.0830.3210.370†0.1920.477‡0.2860.361F right temporal0.395†0.2800.1130.2810.2880.1670.477‡0.3220.331F right hippocampus0.395†0.3070.0770.3250.3560.1900.486‡0.3570.339F right parietal0.376†0.2490.0820.2740.2830.1390.460†0.2550.311F right parahippocampal gyrus0.375†0.3530.1190.3020.3410.2410.3530.2080.273

† p < 0.05, ‡ p < 0.01, *FDR p < 0.05

Conclusion

These findings suggest that the BBB may be affected early in the course of cognitive dysfunction, even preceding detectable changes in other MRI sequences and machine learning algorithms can be used to predict TTS measures, even in asymptomatic SLE patients.

References

Nil.

Disclosure of Interests

Sen Hee Tay: None declared, Mary Stephenson: None declared, Nur Azizah Allameen: None declared, Sriram Narayanan: None declared, Bernett Lee: None declared, Anselm Mak Speakers bureau: JnJ Apr 2019 and GSK Jan 2022, Grant/research support from: GSK - The Supported Studies Programme

P-FLUX: A phosphorus budget dataset spanning diverse agricultural production systems in the United States and Canada

Quantifying spatial and temporal fluxes of phosphorus (P) within and among agricultural production systems is critical for sustaining agricultural production while minimizing environmental impacts. To better understand P fluxes in agricultural landscapes, P-FLUX, a detailed and harmonized dataset of P inputs, outputs, and budgets, as well as estimated uncertainties for each P flux and budget, was developed. Data were collected from 24 research sites and 61 production systems through the Long-term Agroecosystem Research (LTAR) network and partner organizations spanning 22 U.S. states and 2 Canadian provinces. The objectives of this paper are to (a) present and provide a description of the P-FLUX dataset, (b) provide summary analyses of the agricultural production systems included in the dataset and the variability in P inputs and outputs across systems, and (c) provide details for accessing the dataset, dataset limitations, and an example of future use. P-FLUX includes information on select site characteristics (area, soil series), crop rotation, P inputs (P application rate, source, timing, placement, P in irrigation water, atmospheric deposition), P outputs (crop removal, hydrologic losses), P budgets (agronomic budget, overall budget), uncertainties associated with each flux and budget, and data sources. Phosphorus fluxes and budgets vary across agricultural production systems and are useful resources to improve P use efficiency and develop management strategies to mitigate environmental impacts of agricultural systems. P-FLUX is available for download through the USDA Ag Data Commons (https://doi.org/10.15482/USDA.ADC/1523365).

Multidisciplinary aerodigestive program at a children's hospital: A protocol for a prospective observational study

BACKGROUND

Children with complex chronic multisystemic diseases frequently require care from multiple pediatric subspecialists. The aerodigestive program is a multidisciplinary program that diagnoses and treats pediatric patients with complex multi-systematic problems affecting airway, breathing, feeding, swallowing, or growth. The aim of this study is to present the protocol of the aerodigestive program of a children's hospital.

METHODS AND DESIGN

This study is a prospective study to evaluate and compare the overall improvement of patients' objective and subjective conditions before and after the AeroDigestive Team (ADT) program. Among children from 1 month to 18 years of age, patients with complex problems of the airway, breathing, feeding, swallowing, or growth meeting at least two parameters of the inclusion criteria were enrolled. The overall process included referral based on the inclusion criteria, enrollment of ADT program with informed consents, interview and questionnaire for assessing patients' medical condition, prescheduling appointment, multi-specialists' evaluation, monthly team meetings, wrap-up discussion with the patients and family, therapeutic intervention, and follow-up at 6 months with the assessment of outcome measures. The outcome was evaluated objectively and subjectively. The objective outcome measure was divided into surgical or medical intervention, assessment of changes in medical condition, and follow-up study. Both caregiver interviews and questionnaires using a scoring system were used as subjective outcome measures before and after the ADT program. Children were scheduled to be followed-up at 6 months after the interventions or ADT meeting.

DISCUSSION

The aerodigestive program is expected to provide comprehensive and multidisciplinary management of children with complex airway and digestive tract disorders.