Impact of COVID-19 pandemic on depression incidence and healthcare service use among patients with depression: an interrupted time-series analysis from a nine-year population-based study

Background: Most studies on the impact of COVID-19 pandemic on depression burden focused on the earlier pandemic phase specific to lockdowns, but the longer-term impact of pandemic is less well-studied. In this population-based cohort study, we examined the short-term and long-term impacts of COVID-19 on depression incidence and healthcare service use among patients with depression. Methods: Using the territory-wide electronic medical records in Hong Kong, we identified all patients aged 10 years with new diagnoses of depression from 2014 to 2022. We performed an interrupted time-series (ITS) analysis to examine changes in incidence of medically attended depression before and during the pandemic. We then divided all patients into nine cohorts based on year of depression incidence and studied their initial and ongoing service use patterns until the end of 2022. We applied generalized linear modelling to compare the rates of healthcare service use in the year of diagnosis between patients newly diagnosed before and during the pandemic. A separate ITS analysis explored the pandemic impact on the ongoing service use among prevalent patients with depression. Results: We found an immediate increase in depression incidence (RR=1.21, 95% CI:1.10-1.33, p<0.001) in the population after the pandemic began with non-significant slope change, suggesting a sustained effect until the end of 2022. Subgroup analysis showed that the increases in incidence were significant among adults and the older population, but not adolescents. Depression patients newly diagnosed during the pandemic used 11% fewer resources than the pre-pandemic patients in the first diagnosis year. Pre-existing depression patients also had an immediate decrease of 16% in overall all-cause service use since the pandemic, with a positive slope change indicating a gradual rebound over a three-year period. Conclusions: During the pandemic, service provision for depression was suboptimal in the face of increased demand generated by the increasing depression incidence during the COVID-19 pandemic. Our findings indicate the need to improve mental health resource planning preparedness for future public health crises

Projecting the 10-year costs of care and mortality burden of depression until 2032: a Markov modelling study developed from real-world data

Background Based on real-world data, we developed a 10-year prediction model to estimate the burden among patients with depression from the public healthcare system payer's perspective to inform early resource planning in Hong Kong. Methods We developed a Markov cohort model with yearly cycles specifically capturing the pathway of treatment-resistant depression (TRD) and comorbidity development along the disease course. Projected from 2023 to 2032, primary outcomes included costs of all-cause and psychiatric care, and secondary outcomes were all-cause deaths, years of life lived, and quality-adjusted life-years. Using the territory-wide electronic medical records, we identified 25,190 patients aged ≥10 years with newly diagnosed depression from 2014 to 2016 with follow-up until 2020 to observe the real-world time-to-event pattern, based on which costs and time-varying transition inputs were derived using negative binomial modelling and parametric survival analysis. We applied the model as both closed cohort, which studied a fixed cohort of incident patients in 2023, and open cohort, which introduced incident patients by year from 2014 to 2032. Utilities and annual new patients were from published sources. Findings With 9217 new patients in 2023, our closed cohort model projected the 10-year cumulative costs of all-cause and psychiatric care to reach US$309.0 million and US$58.3 million, respectively, with 899 deaths (case fatality rate: 9.8%) by 2032. In our open cohort model, 55,849–57,896 active prevalent cases would cost more than US$322.3 million and US$60.7 million, respectively, with more than 943 deaths annually from 2023 to 2032. Fewer than 20% of cases would live with TRD or comorbidities but contribute 31–54% of the costs. The greatest collective burden would occur in women aged above 40, but men aged above 65 and below 25 with medical history would have the highest costs per patient-year. The key cost drivers were relevant to the early disease stages. Interpretation A limited proportion of patients would develop TRD and comorbidities but contribute to a high proportion of costs, which necessitates appropriate attention and resource allocation. Our projection also demonstrates the application of real-world data to model long-term costs and mortality, which aid policymakers anticipate foreseeable burden and undertake budget planning to prepare for the care need in alternative scenarios

Impact of COVID-19 pandemic on depression incidence and healthcare service use among patients with depression: an interrupted time-series analysis from a 9-year population-based study

Background: Most studies on the impact of the COVID-19 pandemic on depression burden focused on the earlier pandemic phase specific to lockdowns, but the longer-term impact of the pandemic is less well-studied. In this population-based cohort study, we examined the short-term and long-term impacts of COVID-19 on depression incidence and healthcare service use among patients with depression. Methods: Using the territory-wide electronic medical records in Hong Kong, we identified all patients aged ≥ 10 years with new diagnoses of depression from 2014 to 2022. We performed an interrupted time-series (ITS) analysis to examine changes in incidence of medically attended depression before and during the pandemic. We then divided all patients into nine cohorts based on year of depression incidence and studied their initial and ongoing service use patterns until the end of 2022. We applied generalized linear modeling to compare the rates of healthcare service use in the year of diagnosis between patients newly diagnosed before and during the pandemic. A separate ITS analysis explored the pandemic impact on the ongoing service use among prevalent patients with depression. Results: We found an immediate increase in depression incidence (RR = 1.21, 95% CI: 1.10–1.33, p < 0.001) in the population after the pandemic began with non-significant slope change, suggesting a sustained effect until the end of 2022. Subgroup analysis showed that the increases in incidence were significant among adults and the older population, but not adolescents. Depression patients newly diagnosed during the pandemic used 11% fewer resources than the pre-pandemic patients in the first diagnosis year. Pre-existing depression patients also had an immediate decrease of 16% in overall all-cause service use since the pandemic, with a positive slope change indicating a gradual rebound over a 3-year period. Conclusions: During the pandemic, service provision for depression was suboptimal in the face of increased demand generated by the increasing depression incidence during the COVID-19 pandemic. Our findings indicate the need to improve mental health resource planning preparedness for future public health crises

Moment-to-moment dynamics between auditory verbal hallucinations and negative affect and the role of beliefs about voices

Background Negative affect (NA) has been suggested to be both an antecedent and a consequence of auditory verbal hallucinations (AVH). Furthermore, negative appraisals of voices have been theorized to contribute to the maintenance of AVH. Using the experience sampling method (ESM), this study examined the bi-directional relationship between NA and AVH, and the moderating effect of negative beliefs about voices. Methods Forty-seven patients diagnosed with schizophrenia spectrum disorders with frequent AVH completed a clinical interview, followed by ESM for 10 times a day over 6 days on an electronic device. Time-lagged analyses were conducted using multilevel regression modeling. Beliefs about voices were assessed at baseline. Results A total of 1654 data points were obtained. NA predicted an increase in AVH in the subsequent moment, and AVH predicted an increase in NA in the subsequent moment. Baseline beliefs about voices as malevolent and omnipotent significantly strengthened the association between NA and AVH within the same moment. In addition, the belief of omnipotence was associated with more hallucinatory experiences in the moment following NA. However, beliefs about voices were not associated directly with momentary levels of NA or AVH. Conclusions Experiences of NA and AVH drove each other, forming a feedback loop that maintained the voices. The associations between NA and AVH, either within the same moment or across moments, were exacerbated by negative beliefs about voices. Our results suggest that affect-improving interventions may stop the feedback loop and reduce AVH frequency

Establishing the functional connectivity of the frontotemporal network in pre-attentive change detection with Transcranial Magnetic Stimulation and event-related optical signal

Current theories of pre-attentive deviant detection postulate that before the Superior Temporal Cortex (STC) detects a change, the Inferior Frontal Cortex (IFC) engages in stimulus analysis, which is particularly critical for ambiguous deviations (e.g., deviant preceded by a short train of standards). These theories rest on the assumption that IFC and STC are functionally connected, which has only been supported by correlational brain imaging studies. We examined this functional connectivity assumption by applying Transcranial Magnetic Stimulation (TMS) to disrupt IFC function, while measuring the later STC mismatch response with the event-related optical signal (EROS). EROS can localize brain activity in both spatial and temporal dimensions via measurement of optical property changes associated with neuronal activity, and is inert to the electromagnetic interference produced by TMS. Specifically, the STC mismatch response at 120–180 ms elicited by a deviant preceded by a short standard train when IFC TMS was applied at 80 ms was compared with the STC mismatch responses in temporal control (TMS with 200 ms delay), spatial control (sham TMS at vertex), auditory control (TMS pulse noise only), and cognitive control (deviant preceded by a long standard train) conditions. The STC mismatch response to deviants preceded by the short train was abolished by TMS of the IFC at 80 ms, while the STC responses remained intact in all other control conditions. These results confirm the involvement of the IFC in the STC mismatch response and support a functional connection between IFC and STC

Association between cumulative exposure periods of flupentixol or any antipsychotics and risk of lung cancer

Abstract Background Preclinical evidence suggests that certain antipsychotic medications may inhibit the development of lung cancer. This study aims to investigate the association between incident lung cancer and different cumulative exposure periods of flupentixol or any antipsychotics. Methods Using electronic health records from the Hospital Authority in Hong Kong, this nested case-control study included case participants aged 18 years or older with newly diagnosed lung cancer after initiating antipsychotics between January 1, 2003, and August 31, 2022. Each case was matched to up to ten controls of the same sex and age, who were also antipsychotic users. Multivariable conditional logistic regression models were conducted to quantify the association between lung cancer and different cumulative exposure times of flupentixol (0–365 days [ref]; 366–1825 days; 1826+ days) and any antipsychotics (1–365 days [ref]; 366–1825 days; 1826+ days), separately. Results Here we show that among 6435 cases and 64,348 matched controls, 64.06% are males, and 52.98% are aged 65–84 years. Compared to patients with less than 365 days of exposure, those with 366–1825 days of exposure to flupentixol (OR = 0.65 [95% CI, 0.47–0.91]) and any antipsychotics (0.42 [0.38–0.45]) have a lower risk of lung cancer. A decreased risk is observed in patients who have 1826+ days of cumulative use of any antipsychotics (0.54 [0.47–0.60]). Conclusions A reduced risk of lung cancer is observed in patients with more than one year of exposure to flupentixol or any antipsychotics. Further research on the association between lung cancer and other antipsychotic agents is warranted