A Randomized Evaluation of MoodFX, a Patient-Centred e-Health Tool to Support Outcome Measurement for Depression: Une évaluation randomisée de MoodFX, un outil de santé en ligne centré sur le patient pour soutenir la mesure du résultat dans la dépression

BACKGROUND

e-Health tools using validated questionnaires to assess outcomes may facilitate measurement-based care for psychiatric disorders. MoodFX was created as a free online symptom tracker to support patients for outcome measurement in their depression treatment. We conducted a pilot randomized evaluation to examine its usability, and clinical utility.

METHODS

Patients presenting with a major depressive episode (within a major depressive or bipolar disorder) were randomly assigned to receive either MoodFX or a health information website as the intervention and control condition, respectively, with follow-up assessment surveys conducted online at baseline, 8 weeks and 6 months. The primary usability outcomes included the percentage of patients with self-reported use of MoodFX 3 or more times during follow up (indicating minimally adequate usage) and usability measures based on the System Usability Scale (SUS). Secondary clinical outcomes included the Quick Inventory of Depressive Symptomatology, Self-Rated (QIDS-SR) and Patient Health Questionnaire (PHQ-9).

RESULTS

Forty-nine participants were randomized (24 to MoodFX and 25 to the control condition). Of the 23 participants randomized to MoodFX who completed the user survey, 18 (78%) used MoodFX 3 or more times over the 6 months of the study. The mean SUS score of 72.7 (65th-69th percentile) represents good usability. Compared to the control group, the MoodFX group had significantly better improvement on QIDS-SR and PHQ-9 scores, with large effect sizes and higher response rates at 6 months. There were no differences between conditions on other secondary outcomes such as functioning and quality of life.

CONCLUSION

MoodFX demonstrated good usability and was associated with reduction in depressive symptoms. This pilot study supports the use of digital tools in depression treatment.

Predicting which patients with cancer will see a psychiatrist or counsellor from their initial oncology consultation document using natural language processing

BACKGROUND

Patients with cancer often have unmet psychosocial needs. Early detection of who requires referral to a counsellor or psychiatrist may improve their care. This work used natural language processing to predict which patients will see a counsellor or psychiatrist from a patient's initial oncology consultation document. We believe this is the first use of artificial intelligence to predict psychiatric outcomes from non-psychiatric medical documents.

METHODS

This retrospective prognostic study used data from 47,625 patients at BC Cancer. We analyzed initial oncology consultation documents using traditional and neural language models to predict whether patients would see a counsellor or psychiatrist in the 12 months following their initial oncology consultation.

RESULTS

Here, we show our best models achieved a balanced accuracy (receiver-operating-characteristic area-under-curve) of 73.1% (0.824) for predicting seeing a psychiatrist, and 71.0% (0.784) for seeing a counsellor. Different words and phrases are important for predicting each outcome.

CONCLUSION

These results suggest natural language processing can be used to predict psychosocial needs of patients with cancer from their initial oncology consultation document. Future research could extend this work to predict the psychosocial needs of medical patients in other settings.

Evidence of factors influencing delays in the diagnosis and treatment of bipolar disorder in adolescents and young adults. Protocol for a systematic scoping review

BACKGROUND

Bipolar Disorder (BD) is a complex psychiatric condition that typically manifests during late adolescence and early adulthood. Over the past two decades, international studies have reported that BD often goes unrecognized and untreated for several years, which can lead to negative clinical and functional outcomes. However, the components of delay in the diagnosis and treatment of BD and various factors influencing those components have not been systematically explored.

OBJECTIVES

The scoping review described in this protocol aims to map the existing literature on potential factors that influence delays in the treatment of BD in adolescents and young adults, in order to identify the knowledge gaps and future research and policy priorities.

METHODS

This protocol for a systematic scoping review will be reported using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guideline (PRISMA-ScR). We will search the electronic databases of MEDLINE (OVID), EMBASE, PsycINFO and CINAHL for peer-reviewed primary research articles published in academic journals. Grey literature will not be explored due to resource limitations. A conceptual framework based on the Model of Pathways to Treatment by Scott and colleagues was used as a foundation for our search and extraction strategy to ensure all components of delay and potential factors influencing each component are explored. Two independent reviewers will screen the references retrieved by the literature search and select relevant studies based on our inclusion criteria. The data from included studies will be synthesized into a narrative summary, and implications for future research, practice and policy will be discussed.

DISCUSSION

To the best of our knowledge, this will be the first scoping review to explore the potential factors that influence delays in the treatment of BD in adolescents and young adults. We intend to disseminate the review results through academic conferences and publication in a peer-reviewed journal.

Machine Learning Prediction of Quality of Life Improvement During Antidepressant Treatment of Patients With Major Depressive Disorder: A STAR*D and CAN-BIND-1 Report

Background: Quality of life (QoL) is an important patient-centric outcome to evaluate in treatment of major depressive disorder (MDD). This work sought to investigate the performance of several machine learning methods to predict a return to normative QoL in patients with MDD after antidepressant treatment.

Methods: Several binary classification algorithms were trained on data from the first 2 weeks of the Sequenced Treatment Alternatives to Relieve Depression (STAR*D) study (n = 651, conducted from 2001 to 2006) to predict week 9 normative QoL (score ≥ 67, based on a community normative sample, on the Quality of Life Enjoyment and Satisfaction Questionnaire-Short Form [Q-LES-Q-SF]) after treatment with citalopram. Internal validation was performed using a STAR*D holdout dataset, and external validation was performed using the Canadian Biomarker Integration Network in Depression-1 (CAN-BIND-1) dataset (n = 175, study conducted from 2012 to 2017) after treatment with escitalopram. Feature importance was calculated using SHapley Additive exPlanations (SHAP).

Results: Random Forest performed most consistently on internal and external validation, with balanced accuracy (area under the receiver operator curve) of 71% (0.81) on the STAR*D dataset and 69% (0.75) on the CAN-BIND-1 dataset. Random Forest Classifiers trained on Q-LES-Q-SF and Quick Inventory of Depressive Symptomatology-Self-Rated variables had similar performance on both internal and external validation. Important predictive variables came from psychological, physical, and socioeconomic domains.

Conclusions: Machine learning can predict normative QoL after antidepressant treatment with similar performance to that of prior work predicting depressive symptom response and remission. These results suggest that QoL outcomes in MDD patients can be predicted with simple patient-rated measures and provide a foundation to further improve performance and demonstrate clinical utility.

Trial Registration: ClinicalTrials.gov identifiers NCT00021528 and NCT01655706.

Response trajectories during escitalopram treatment of patients with major depressive disorder

Depression is a leading global cause of disability, yet about half of patients do not respond to initial antidepressant treatment. This treatment difficulty may be in part due to the heterogeneity of depression and corresponding response to treatment. Unsupervised machine learning allows underlying patterns to be uncovered, and can be used to understand this heterogeneity by finding groups of patients with similar response trajectories. Prior studies attempting this have clustered patients using a narrow range of data primarily from depression scales. In this work, we used unsupervised machine learning to cluster patients receiving escitalopram therapy using a wide variety of subjective and objective clinical features from the first eight weeks of the Canadian Biomarker Integration Network in Depression-1 trial. We investigated how these clusters responded to treatment by comparing changes in symptoms and symptom categories, and by using Principal Component Analysis (PCA). Our algorithm found three clusters, which broadly represented non-responders, responders, and remitters. Most categories of features followed this response pattern except for objective cognitive features. Using PCA with our clusters, we found that subjective mood state/anhedonia is the core feature of response with escitalopram, but there exists other distinct patterns of response around neurovegetative symptoms, activation, and cognition.

Reduction in Substance-Related Composite Harm Scores Through Street Soccer

Introduction Street soccer makes the sport accessible to people affected by homelessness or precarious housing. There is overwhelming evidence that exercise improves physical and mental health. In addition, sport facilitates positive peer pressure that leads to beneficial life changes. Method To examine participants' accounts of the effects of street soccer in a sample of socially disadvantaged players from Western Canada, we collected 73 cross-sectional self-reports of life changes via a questionnaire. The questionnaire included questions on social, mental, and physical health, including substance use. This allowed the calculation of a modified composite harm score. Results Participants reported improved physical (46% of participants) and mental (43% of participants) health, reduced cigarette (50% of smokers), alcohol (45% of users), cannabis (42% of users), and other non-prescribed drug use, increased number of friends (88% of participants), improved housing (60% of participants), increased income (19% of participants), increased community medical supports (40% of participants), and decreased conflicts with police (47% of those with prior recent conflict). Perceived reductions in substance use were supported by significant changes in composite harm score. Conclusion Street soccer appears to promote improved physical, mental, and social health among people affected by homelessness or precarious housing, with reduction in substance use likely to be a key factor. This work builds upon past qualitative research showing the benefits of street soccer and supports future research which may help elucidate the mechanisms by which street soccer has beneficial effects.

Predicting the Survival of Patients With Cancer From Their Initial Oncology Consultation Document Using Natural Language Processing

IMPORTANCE

Predicting short- and long-term survival of patients with cancer may improve their care. Prior predictive models either use data with limited availability or predict the outcome of only 1 type of cancer.

OBJECTIVE

To investigate whether natural language processing can predict survival of patients with general cancer from a patient's initial oncologist consultation document.

DESIGN, SETTING, AND PARTICIPANTS

This retrospective prognostic study used data from 47 625 of 59 800 patients who started cancer care at any of the 6 BC Cancer sites located in the province of British Columbia between April 1, 2011, and December 31, 2016. Mortality data were updated until April 6, 2022, and data were analyzed from update until September 30, 2022. All patients with a medical or radiation oncologist consultation document generated within 180 days of diagnosis were included; patients seen for multiple cancers were excluded.

EXPOSURES

Initial oncologist consultation documents were analyzed using traditional and neural language models.

MAIN OUTCOMES AND MEASURES

The primary outcome was the performance of the predictive models, including balanced accuracy and receiver operating characteristics area under the curve (AUC). The secondary outcome was investigating what words the models used.

RESULTS

Of the 47 625 patients in the sample, 25 428 (53.4%) were female and 22 197 (46.6%) were male, with a mean (SD) age of 64.9 (13.7) years. A total of 41 447 patients (87.0%) survived 6 months, 31 143 (65.4%) survived 36 months, and 27 880 (58.5%) survived 60 months, calculated from their initial oncologist consultation. The best models achieved a balanced accuracy of 0.856 (AUC, 0.928) for predicting 6-month survival, 0.842 (AUC, 0.918) for 36-month survival, and 0.837 (AUC, 0.918) for 60-month survival, on a holdout test set. Differences in what words were important for predicting 6- vs 60-month survival were found.

CONCLUSIONS AND RELEVANCE

These findings suggest that models performed comparably with or better than previous models predicting cancer survival and that they may be able to predict survival using readily available data without focusing on 1 cancer type.

A Conserved Residue Cluster That Governs Kinetics of ATP-dependent Gating of Kir6.2 Potassium Channels

ATP-sensitive potassium (KATP) channels are heteromultimeric complexes of an inwardly rectifying Kir channel (Kir6.x) and sulfonylurea receptors. Their regulation by intracellular ATP and ADP generates electrical signals in response to changes in cellular metabolism. We investigated channel elements that control the kinetics of ATP-dependent regulation of KATP (Kir6.2 + SUR1) channels using rapid concentration jumps. WT Kir6.2 channels re-open after rapid washout of ATP with a time constant of ∼60 ms. Extending similar kinetic measurements to numerous mutants revealed fairly modest effects on gating kinetics despite significant changes in ATP sensitivity and open probability. However, we identified a pair of highly conserved neighboring amino acids (Trp-68 and Lys-170) that control the rate of channel opening and inhibition in response to ATP. Paradoxically, mutations of Trp-68 or Lys-170 markedly slow the kinetics of channel opening (500 and 700 ms for W68L and K170N, respectively), while increasing channel open probability. Examining the functional effects of these residues using φ value analysis revealed a steep negative slope. This finding implies that these residues play a role in lowering the transition state energy barrier between open and closed channel states. Using unnatural amino acid incorporation, we demonstrate the requirement for a planar amino acid at Kir6.2 position 68 for normal channel gating, which is potentially necessary to localize the ϵ-amine of Lys-170 in the phosphatidylinositol 4,5-bisphosphate-binding site. Overall, our findings identify a discrete pair of highly conserved residues with an essential role for controlling gating kinetics of Kir channels.

A novel mechanism for fine-tuning open-state stability in a voltage-gated potassium channel

Voltage-gated potassium channels elicit membrane hyperpolarization through voltage-sensor domains that regulate the conductive status of the pore domain. To better understand the inherent basis for the open-closed equilibrium in these channels, we undertook an atomistic scan using synthetic fluorinated derivatives of aromatic residues previously implicated in the gating of Shaker potassium channels. Here we show that stepwise dispersion of the negative electrostatic surface potential of only one site, Phe481, stabilizes the channel open state. Furthermore, these data suggest that this apparent stabilization is the consequence of the amelioration of an inherently repulsive open-state interaction between the partial negative charge on the face of Phe481 and a highly co-evolved acidic side chain, Glu395, and this interaction is potentially modulated through the Tyr485 hydroxyl. We propose that the intrinsic open-state destabilization via aromatic repulsion represents a new mechanism by which ion channels, and likely other proteins, fine-tune conformational equilibria.

Voltage-gated potassium channels cycle between closed and open states through poorly-defined transitions. Pless and colleagues incorporate artificial amino acids into Shaker potassium channels and find that that the negative electrostatic surface potential of Phe481, destabilizes the channel open state.

Efficacy of Germination Stimulants of Sclerotia of Sclerotium cepivorum for Management of White Rot of Garlic

The ability of soil-applied garlic powder and diallyl disulfide to stimulate germination of sclerotia of Sclerotium cepivorum, the cause of white rot of onion and garlic, was evaluated in four field trials. Because sclerotia germinate in response to exudation of specific volatile sulfides and thiols from allium roots, sulfides applied to the ground in the absence of an allium crop cause death of the sclerotia after they germinate and exhaust nutrient reserves. In this study, garlic powder and a synthetic garlic oil, diallyl disulfide, were incorporated into the soil in commercial fields naturally infested with S. cepivorum. Methyl bromide was included as a chemical control. Within 3 months after treatment, over 90% of the sclerotia died in the plots treated with the germinationstimulants, which was similar to the reduction of viable sclerotia achieved with an application of methyl bromide. The degree of sclerotial mortality in plots treated with garlic powder at 112 kg/ha or more was almost equal to that achieved by diallyl disulfide at 0.5 ml/m² or methyl bromide at 448 kg/ha. Despite the efficacy of the stimulants and methyl bromide to reduce populations of sclerotia, the pathogen caused substantial root rot and yield losses in subsequent garlic crops planted about a year after soil treatment. However, germination stimulants have utility because the reduction of the vast majority of sclerotia in a field reduces the risk of spread of the pathogen to neighboring fields.

Survival and Persistence of Alternaria dauci in Carrot Cropping Systems

Alternaria dauci was recovered in California from carrot crop residue and from volunteer carrot plants in fallow carrot fields. The fungus was not recovered from common weeds surrounding fallow fields. To evaluate further the survival of A. dauci on carrot crop residue, infected carrot leaf tissue was placed in fields or in soil in greenhouse pots, and recovered over time. In California, A. dauci was recovered from infected leaf tissue in both fallow and irrigated fields for as long as 1 year. In Florida, A. dauci was recovered from infected leaf tissue in fallow fields for up to 30 weeks. In greenhouse experiments, A. dauci was recovered from infected leaf tissue for as long as 1 year in dry soil, but only up to 30 weeks in soil that was watered weekly. To determine the infectivity of A. dauci borne on carrot crop residue, infected carrot crops were incorporated into organic and mineral field soils, and soil samples were collected over time. Carrot seed were planted in collected soil, and seedling infection by A. dauci was recorded. Seedling infection was detected up to 13 and 14 weeks after crop incorporation in organic and mineral soil, respectively. Seedling infection was detected for up to 5 weeks in soil that remained dry compared with 3 weeks in flooded soil.

First Report of Xanthomonas Leaf Blight of Onion in California

In 2000 and 2001, severe leaf blight of fresh market onions occurred in several fields in the Antelope Valley of California, a high desert area located in northern Los Angeles County. In at least two fields, 70% of the canopy was affected, which resulted in an estimated yield reduction of over 50%. Both organically and conventionally grown onions were affected. Symptoms included numerous small chlorotic lesions that appeared first on older leaves. Lesions were often surrounded by water-soaked margins. As the season progressed, the lesions became elongated and necrotic. Entire leaf blades were often killed. The disease never progressed into the bulbs, but bulbs of infected plants never grew to full size. Yellow mucoid bacterial colonies were recovered on yeast extractdextrose-CaCO₃ agar from symptomatic tissue. All isolates were gram-negative rods with single polar flagella. Two representative isolates were identified as Xanthomonas campestris based on their carbon utilization profile (similarity index of 0.784 and 0.850; Biolog, Hayward, CA), fatty acid profile (similarity index of 0.588; MIS-TSBA, version 4.10, MIDI Inc., Newark, DE), and 16S-23S intergenic spacer DNA sequences (98% sequence identify with strains of X. campestris). In greenhouse pathogenicity tests, eight white globe onion plants were inoculated with a bacterial suspension (10⁶ CFU/ml) of each of the two isolates. Plants were inoculated by spraying the suspension on leaves lightly injured by rubbing with Carborundum or puncturing with needles dipped in the suspension. Controls were inoculated with water. All plants inoculated with the bacteria developed symptoms in 6 days. The bacterium was reisolated from all inoculated plants and confirmed as Xanthomonas. The trial was conducted twice. To our knowledge, this is the first report of Xanthomonas leaf blight of onion in California. In the United States, the disease has been reported in Texas and Colorado (1,2). References: 1. T. Isakeit et al. Plant Dis. 84:201, 2000. 2. H. F. Schwartz and K. Otto. Plant Dis. 84:922, 2000.

Influence of Soil Saturation and Temperature on Erwinia chrysanthemi Soft Rot of Carrot

In 1998, soft rot caused by Erwinia chrysanthemi resulted in an estimated loss of 1,800 tons of carrots in California. The disease appeared to be related to unusually high temperatures and excessive irrigation. To determine the optimum conditions for development of soft rot under controlled conditions, pots of carrots inoculated with E. chrysanthemi were saturated with water and incubated at 20, 25, 30, or 35°C. Plants were harvested and examined for disease 12, 24, 36, 48, 72, and 96 h after inoculation. Negligible disease occurred after 12 h. Disease severity and incidence increased with increasing temperature and duration of saturation from 24 to 96 h. In a second experiment, carrot disks were inoculated with three isolates each of E. chrysanthemi and E. carotovora subsp. carotovora and incubated at 15, 20, 25, 30, and 35°C. After 48 h, the disks were washed to remove rotted tissue and reweighed. Neither bacterium reduced carrot disk weight at 15°C. In general, moderate weight reduction occurred at 20 and 25°C. The greatest degree of soft rot was caused by E. chrysanthemi at 30 and 35°C. E. carotovora subsp. carotovora isolates were relatively less virulent than E. chrysanthemi at 30°C and none of the E. carotovora subsp. carotovora isolates reduced carrot disk weight at 35°C. This is the first report of E. chrysanthemi causing soft rot of carrot in California. Based on these results, growers should limit the length of time carrot roots are exposed to saturated soil, especially at high soil temperatures.

Influence of Gibberellic Acid on Carrot Growth and Severity of Alternaria Leaf Blight

Applications of gibberellic acid (GA) to carrot foliage consistently reduced the percentage of leaf area affected by Alternaria dauci compared with nontreated plants. The degree of leaf blight reduction with two applications of GA was similar to that achieved with four applications of the fungicide iprodione. At the rates examined (GA at 2.5 to 250 mg/liter), foliage dry weights were generally increased by GA. Although root weight was significantly reduced by rates of 250 mg/liter, applications of lower rates (40 mg/liter or less) reduced leaf blight severity without affecting root quality. Applications of GA usually resulted in plants with longer leaves, wider petioles, and a more upright growth habit. In one trial, leaf length and petiole diameter increased linearly with increasing rates (20, 30, and 40 mg/liter). When applied twice at 30 mg/liter, GA did not affect cuticle, epidermal, or leaf thickness. In general, the initial timing of two applications of 20 to 40 mg/liter (4, 6, or 8 weeks after plant emergence) did not influence the effects of GA. However, in one trial, there was a greater incidence of core separation from the root cortex when 40 mg/liter was applied initially at 4 weeks. GA at 30 mg/liter slightly but significantly decreased inner root color in one of two trials.

Influence of Crop Rotation on the Incidence of Pythium- and Rhizoctonia-Induced Carrot Root Dieback

The influence of various crop rotations on population densities of Pythium spp. and Rhizoctonia solani, subsequent carrot yields, and incidence of carrot root dieback was investigated. Carrots followed crops of alfalfa, barley, carrots, cotton, onions, or fallowed soil in two independent trials. Populations of Pythium spp. were greater following alfalfa and barley than other crops in one of the 2 years of the study. Populations of R. solani were generally greater following alfalfa and cotton than other crops in each of the 2 years of the study. In 1 year, yields of marketable carrots were reduced following the alfalfa crop; no other cropping pattern influenced carrot yields. The incidence of root dieback, which resulted in mature carrots with misshapen or multiple taproots, was generally greater following alfalfa and barley than other crops in one trial, and greater following alfalfa and cotton in the other trial.

Benefits of Cotton Seed Treatments for the Control of Seedling Diseases in Relation to Inoculum Densities of Pythium Species and Rhizoctonia solani

Twenty-five field trials conducted over a 3-year period in five San Joaquin Valley counties included the following treatments: nontreated cotton seed; seed treated with myclobutanil for the control of Rhizoctonia solani-induced damping-off; seed treated with metalaxyl for the control of Pythium-induced damping-off; and seed treated with a combination of the two fungicides. The following parameters were measured: soil populations of Pythium spp. and R. solani at planting, soil temperature at planting, air temperatures for 5 days after planting, soil particle analysis, EC, calcium, pH, organic matter, and plant stands from each treatment. In 1993 and 1994, myclobutanil and the combination of the two fungicides resulted in improved stands in 15 of 18 fields. Metalaxyl did not increase stands in any field in 1993 to 1994. In 1995, the combination of fungicides increased stands relative to the nontreated seeds and was more effective in increasing stands than myclobutanil or metalaxyl alone. Pythium populations were much greater in 1995 than in 1993 to 1994 and may explain the increase in plant stands with the combination of fungicides and metalaxyl alone. Covariate analysis of the data indicated no relationship between stand increases from fungicide seed treatment and any of the soil parameters measured. Heat units following planting were not limiting and had no effect on stands. Populations of pathogens were not related to benefits of fungicides, with the exception of a negative correlation between stand increases from seed treatment with myclobutanil and Pythium populations. Apparently, seed protected with a fungicide active against R. solani were more susceptible to infection by Pythium spp. In general, the fungicide seed treatment active against R. solani increased stands of the cultivar Maxxa regardless of soil type and pathogen populations. Increased stands from the metalaxyl treatment occurred in 1 of the 3 years of the study.