"Wearing-off" efficacy of CGRP monoclonal antibodies for migraine prevention: A meta-analysis of randomized controlled trials.

BACKGROUND: A new migraine prevention, CGRP monoclonal antibodies (mAbs), is injectable on a monthly or quarterly basis. In clinical practice, some patients reported that drug effectiveness does not last until the upcoming scheduled injection, a so-called "wearing-off" effect. We aimed to evaluate the wearing-off effect of the CGRP mAbs for migraine prevention in patients with different monthly migraine days. METHODS: We conducted a literature search for studies that reported migraine frequency after CGRP monoclonal antibody administration from MEDLINE, SCOPUS, Web of Science, and Cochrane Database from inception through February 2022. A meta-analysis, random-effects model was applied to assess the difference in migraine frequency between early and later weeks after medication to assess the presence of a wearing-off effect. Risk ratio was calculated to report the pooled treatment effect. RESULTS: Four studies were entered for the analysis, comprising 2409 patients in randomized controlled trials. There was no association between CGRP mAbs and wearing-off effect in patients with galcanezumab with a pooled risk ratio of 1.29 (95% CI 0.73 to 2.28) compared to placebo group. However, there was an association between galcanezumab and wearing-off effect in patients with chronic migraine with a pooled risk ratio of 1.91 (95% CI 1.11 to 3.28) compared to placebo group. CONCLUSION: In this meta-analysis, there was a wearing-off efficacy of galcanezumab but only in a small percentage of patients with chronic migraine in randomized controlled trials.

Immunogenicity of the third and fourth BNT162b2 mRNA COVID-19 boosters and factors associated with immune response in patients with SLE and rheumatoid arthritis.

OBJECTIVES: To evaluate the safety and immunogenicity of third and fourth BNT162b2 boosters in patients with SLE and rheumatoid arthritis (RA). METHODS: Patients with SLE and RA aged 18-65 years who completed a series of inactivated, adenoviral vector, or heterogenous adenoviral vector/mRNA vaccines for at least 28 days were enrolled. Immunogenicity assessment was done before and day 15 after each booster vaccination. The third BNT162b2 booster was administered on day 1. Patients with suboptimal humoral response to the third booster dose (antireceptor-binding domain (RBD) IgG on day 15 <2360 BAU/mL) were given a fourth BNT162b2 booster on day 22. RESULTS: Seventy-one patients with SLE and 29 patients with RA were enrolled. The third booster raised anti-RBD IgG by 15-fold, and patients with positive neutralising activity against the Omicron variant increased from 0% to 42%. Patients with positive cellular immune response also increased from 55% to 94%. High immunosuppressive load and initial inactivated vaccine were associated with lower anti-RBD IgG titre. Fifty-four patients had suboptimal humoral responses to the third booster and 28 received a fourth booster dose. Although anti-RBD IgG increased further by sevenfold, no significant change in neutralising activity against the Omicron variant was observed. There were two severe SLE flares that occurred shortly after the fourth booster dose. CONCLUSIONS: The third BNT162b2 booster significantly improved humoral and cellular immunogenicity in patients with SLE and RA. The benefit of a short-interval fourth booster in patients with suboptimal humoral response was unclear. TRIAL REGISTRATION NUMBER: TCTR20211220004.

Comparison of Immunogenicity and Safety of Inactivated, Adenovirus-Vectored, and Heterologous Adenovirus-Vectored/mRNA Vaccines in Patients with Systemic Lupus Erythematosus and Rheumatoid Arthritis: A Prospective Cohort Study.

Background: Impaired immune responses to COVID-19 vaccines have been observed in autoimmune rheumatic disease patients. Determining the most effective and safe vaccine regimen is critically needed in such a population. We aim to compare the immunogenicity and safety of three COVID-19 vaccine regimens in patients with systemic lupus erythematosus (SLE) and rheumatoid arthritis (RA). Methods: SLE and RA patients aged 18−65 years who received inactivated (CoronaVac or COVILO), adenovirus-vectored (AZD1222), or heterogeneous (AZD1222/BNT162b2) vaccines were enrolled. Humoral and cellular immune responses were assessed at day 28 after the second vaccination. This was performed using the serum binding antibody level against the receptor-binding domain of the SARS-CoV-2 spike protein (anti-RBD Ig) and IFNy-ELISpot assay (ELISpot), respectively. Reactogenicity was reviewed on day 7 following each vaccination. Disease activity was assessed before and on day 28 after the second vaccination. Results: The cohort consisted of 94 patients (64 SLE and 30 RA). Inactivated, AZD1222, and AZD1222/BNT162b2 vaccines were administered to 23, 43, and 28 patients, respectively. Anti-RBD titers were lowest in the inactivated vaccine group (2.84 AU/mL; 95% CI 0.96−8.44), followed by AZD1222 (233.7 AU/mL; 95% CI 99.0−505.5), and AZD1222/BNT162b2 (688.6 AU/mL; 95% CI 271−1745), p < 0.0001. After adjusting for relevant factors, the inactivated vaccine was associated with the lowest humoral response, while adenovirus-vectored/mRNA vaccine was the highest. The proportion of positive ELISpot test was also lowest in the inactivated vaccine group (27%), followed by the adenovirus-vectored vaccine (67%), and the adenovirus-vectored/mRNA vaccine (73%) (p = 0.03). All types of vaccine were well-tolerated. There was no flare of autoimmune disease post-vaccination. Conclusion: Adenovirus-vectored and adenovirus-vectored/mRNA vaccines elicited a stronger humoral and cellular immune response than inactivated vaccines, suggesting that they may be more suitable in SLE and RA patients receiving immunosuppressive therapy.

Immunogenicity, safety and reactogenicity of a heterogeneous booster following the CoronaVac inactivated SARS-CoV-2 vaccine in patients with SLE: a case series.

Since the COVID-19 pandemic, CoronaVac, an inactivated SARS-CoV-2 vaccine, has been widely deployed in several countries for emergency use. However, the immunogenicity of the inactivated vaccine was relatively lower when compared to other vaccine types and was even more attenuated in autoimmune patients with rheumatic disease. A third-dose SARS-CoV-2 vaccination in immunosuppressed population is recommended in order to improve immune response. However, the data were limited to those initially received mRNA or viral vector SARS-CoV-2 vaccine. Thus, we aimed to describe the safety, reactogenicity and immunogenicity of patients with systemic lupus erythematosus (SLE) who received a heterogenous booster SARS-CoV-2 vaccine following the initial CoronaVac inactivated vaccine series. Our findings support that the third booster dose of mRNA or viral vector vaccine following the inactivated vaccine is well tolerated and elicited a substantial humoral and cellular immune response in inactive patients with SLE having maintenance immunosuppressive therapy without interruption of immunosuppressive medications.

Conflicting Orders in Physician Orders for Life-Sustaining Treatment Forms.

BACKGROUND/OBJECTIVES: Many older persons with chronic illness use Physician Orders for Life-Sustaining Treatment (POLST) to document portable medical orders for emergency care. However, some POLSTs contain combinations of orders that do not translate into a cohesive care plan (eg, cardiopulmonary resuscitation [CPR] without intensive care, or intensive care without antibiotics). This study characterizes the prevalence and predictors of POLSTs with conflicting orders. DESIGN: Retrospective cohort study. SETTING: Large academic health system. PARTICIPANTS: A total of 3,123 POLST users with chronic life-limiting illness who died between 2010 and 2015 (mean age = 69.7 years). MEASUREMENTS: In a retrospective review of all POLSTs in participants' electronic health records, we describe the prevalence of POLSTs with conflicting orders for cardiac arrest and medical interventions, and use clustered logistic regression to evaluate potential predictors of conflicting orders. We also examine the prevalence of conflicts between POLST orders for antibiotics and artificial nutrition with orders for cardiac arrest or medical interventions. RESULTS: Among 3,924 complete POLSTs belonging to 3,123 decedents, 209 (5.3%) POLSTs contained orders to "attempt CPR" paired with orders for "limited interventions" or "comfort measures only"; 745/3169 (23.5%) POLSTs paired orders to restrict antibiotics with orders to deliver non-comfort-only care; and, 170/3098 (5.5%) POLSTs paired orders to withhold artificial nutrition with orders to deliver CPR or intensive care. Among POLSTs with orders to avoid intensive care, orders to attempt CPR were more likely to be present in POLSTs completed earlier in the patient's illness course (adjusted odds ratio = 1.27 per twofold increase in days from POLST to death; 95% confidence interval = 1.18-1.36; P < .001). CONCLUSION: Although most POLSTs are actionable by clinicians, 5% had conflicting orders for cardiac arrest and medical interventions, and 24% had one or more conflicts between orders for cardiac arrest, medical interventions, antibiotics, and artificial nutrition. These conflicting orders make implementation of POLST challenging for clinicians in acute care settings.

Deep learning for automated classification of tuberculosis-related chest X-Ray: dataset distribution shift limits diagnostic performance generalizability.

BACKGROUND: Machine learning has been an emerging tool for various aspects of infectious diseases including tuberculosis surveillance and detection. However, the World Health Organization (WHO) provided no recommendations on using computer-aided tuberculosis detection software because of a small number of studies, methodological limitations, and limited generalizability of the findings. METHODS: To quantify the generalizability of the machine-learning model, we developed a Deep Convolutional Neural Network (DCNN) model using a Tuberculosis (TB)-specific chest x-ray (CXR) dataset of one population (National Library of Medicine Shenzhen No.3 Hospital) and tested it with non-TB-specific CXR dataset of another population (National Institute of Health Clinical Centers). RESULTS: In the training and intramural test sets using the Shenzhen hospital database, the DCCN model exhibited an AUC of 0.9845 and 0.8502 for detecting TB, respectively. However, the AUC of the supervised DCNN model in the ChestX-ray8 dataset was dramatically dropped to 0.7054. Using the cut points at 0.90, which suggested 72% sensitivity and 82% specificity in the Shenzhen dataset, the final DCNN model estimated that 36.51% of abnormal radiographs in the ChestX-ray8 dataset were related to TB. CONCLUSION: A supervised deep learning model developed by using the training dataset from one population may not have the same diagnostic performance in another population. Conclusion: Technical specification of CXR images, disease severity distribution, dataset distribution shift, and overdiagnosis should be examined before implementation in other settings.

Association of Physician Orders for Life-Sustaining Treatment With ICU Admission Among Patients Hospitalized Near the End of Life.

Importance: Patients with chronic illness frequently use Physician Orders for Life-Sustaining Treatment (POLST) to document treatment limitations. Objectives: To evaluate the association between POLST order for medical interventions and intensive care unit (ICU) admission for patients hospitalized near the end of life. Design, Setting, and Participants: Retrospective cohort study of patients with POLSTs and with chronic illness who died between January 1, 2010, and December 31, 2017, and were hospitalized 6 months or less before death in a 2-hospital academic health care system. Exposures: POLST order for medical interventions ("comfort measures only" vs "limited additional interventions" vs "full treatment"), age, race/ethnicity, education, days from POLST completion to admission, histories of cancer or dementia, and admission for traumatic injury. Main Outcomes and Measures: The primary outcome was the association between POLST order and ICU admission during the last hospitalization of life; the secondary outcome was receipt of a composite of 4 life-sustaining treatments: mechanical ventilation, vasopressors, dialysis, and cardiopulmonary resuscitation. For evaluating factors associated with POLST-discordant care, the outcome was ICU admission contrary to POLST order for medical interventions during the last hospitalization of life. Results: Among 1818 decedents (mean age, 70.8 [SD, 14.7] years; 41% women), 401 (22%) had POLST orders for comfort measures only, 761 (42%) had orders for limited additional interventions, and 656 (36%) had orders for full treatment. ICU admissions occurred in 31% (95% CI, 26%-35%) of patients with comfort-only orders, 46% (95% CI, 42%-49%) with limited-interventions orders, and 62% (95% CI, 58%-66%) with full-treatment orders. One or more life-sustaining treatments were delivered to 14% (95% CI, 11%-17%) of patients with comfort-only orders and to 20% (95% CI, 17%-23%) of patients with limited-interventions orders. Compared with patients with full-treatment POLSTs, those with comfort-only and limited-interventions orders were significantly less likely to receive ICU admission (comfort only: 123/401 [31%] vs 406/656 [62%], aRR, 0.53 [95% CI, 0.45-0.62]; limited interventions: 349/761 [46%] vs 406/656 [62%], aRR, 0.79 [95% CI, 0.71-0.87]). Across patients with comfort-only and limited-interventions POLSTs, 38% (95% CI, 35%-40%) received POLST-discordant care. Patients with cancer were significantly less likely to receive POLST-discordant care than those without cancer (comfort only: 41/181 [23%] vs 80/220 [36%], aRR, 0.60 [95% CI, 0.43-0.85]; limited interventions: 100/321 [31%] vs 215/440 [49%], aRR, 0.63 [95% CI, 0.51-0.78]). Patients with dementia and comfort-only orders were significantly less likely to receive POLST-discordant care than those without dementia (23/111 [21%] vs 98/290 [34%], aRR, 0.44 [95% CI, 0.29-0.67]). Patients admitted for traumatic injury were significantly more likely to receive POLST-discordant care (comfort only: 29/64 [45%] vs 92/337 [27%], aRR, 1.52 [95% CI, 1.08-2.14]; limited interventions: 51/91 [56%] vs 264/670 [39%], aRR, 1.36 [95% CI, 1.09-1.68]). In patients with limited-interventions orders, older age was significantly associated with less POLST-discordant care (aRR, 0.93 per 10 years [95% CI, 0.88-1.00]). Conclusions and Relevance: Among patients with POLSTs and with chronic life-limiting illness who were hospitalized within 6 months of death, treatment-limiting POLSTs were significantly associated with lower rates of ICU admission compared with full-treatment POLSTs. However, 38% of patients with treatment-limiting POLSTs received intensive care that was potentially discordant with their POLST.

Temporal Trends Between 2010 and 2015 in Intensity of Care at End-of-Life for Patients With Chronic Illness: Influence of Age Under vs. Over 65 Years.

CONTEXT: Recent analyses of Medicare data show decreases over time in intensity of end-of-life care. Few studies exist regarding trends in intensity of end-of-life care for those under 65 years of age. OBJECTIVES: To examine recent temporal trends in place of death, and both hospital and intensive care unit (ICU) utilization, for age-stratified decedents with chronic, life-limiting diagnoses (<65 vs. ≥65 years) who received care in a large healthcare system. METHODS: Retrospective cohort using death certificates and electronic health records for 22,068 patients with chronic illnesses who died between 2010 and 2015. We examined utilization overall and stratified by age using multiple regression. RESULTS: The proportion of deaths at home did not change, but hospital admissions in the last 30 days of life decreased significantly from 2010 to 2015 (hospital b = -0.026; CI = -0.041, -0.012). ICU admissions in the last 30 days also declined over time for the full sample and for patients aged 65 years or older (overall b = -0.023; CI = -0.039, -0.007), but was not significant for younger decedents. Length of stay (LOS) did not decrease for those using the hospital or ICU. CONCLUSION: From 2010 to 2015, we observed a decrease in hospital admissions for all age groups and in ICU admissions for those over 65 years. As there were no changes in the proportion of patients with chronic illness who died at home nor in hospital or ICU LOS in the last 30 days, hospital and ICU admissions in the last 30 days may be a more responsive quality metric than site of death or LOS for palliative care interventions.

Using Electronic Health Records for Quality Measurement and Accountability in Care of the Seriously Ill: Opportunities and Challenges.

BACKGROUND: As our population ages and the burden of chronic illness rises, there is increasing need to implement quality metrics that measure and benchmark care of the seriously ill, including the delivery of both primary care and specialty palliative care. Such metrics can be used to drive quality improvement, value-based payment, and accountability for population-based outcomes. METHODS: In this article, we examine use of the electronic health record (EHR) as a tool to assess quality of serious illness care through narrative review and description of a palliative care quality metrics program in a large healthcare system. RESULTS: In the search for feasible, reliable, and valid palliative care quality metrics, the EHR is an attractive option for collecting quality data on large numbers of seriously ill patients. However, important challenges to using EHR data for quality improvement and accountability exist, including understanding the validity, reliability, and completeness of the data, as well as acknowledging the difference between care documented and care delivered. Challenges also include developing achievable metrics that are clearly linked to patient and family outcomes and addressing data interoperability across sites as well as EHR platforms and vendors. This article summarizes the strengths and weakness of the EHR as a data source for accountability of community- and population-based programs for serious illness, describes the implementation of EHR data in the palliative care quality metrics program at the University of Washington, and, based on that experience, discusses opportunities and challenges. Our palliative care metrics program was designed to serve as a resource for other healthcare systems. DISCUSSION: Although the EHR offers great promise for enhancing quality of care provided for the seriously ill, significant challenges remain to operationalizing this promise on a national scale and using EHR data for population-based quality and accountability.