External validation of six COVID-19 prognostic models for predicting mortality risk in older populations in a hospital, primary care, and nursing home setting.

OBJECTIVES: To systematically evaluate the performance of COVID-19 prognostic models and scores for mortality risk in older populations across three health-care settings: hospitals, primary care, and nursing homes. STUDY DESIGN AND SETTING: This retrospective external validation study included 14,092 older individuals of ≥70 years of age with a clinical or polymerase chain reaction-confirmed COVID-19 diagnosis from March 2020 to December 2020. The six validation cohorts include three hospital-based (CliniCo, COVID-OLD, COVID-PREDICT), two primary care-based (Julius General Practitioners Network/Academisch network huisartsgeneeskunde/Network of Academic general Practitioners, PHARMO), and one nursing home cohort (YSIS) in the Netherlands. Based on a living systematic review of COVID-19 prediction models using Prediction model Risk Of Bias ASsessment Tool for quality and risk of bias assessment and considering predictor availability in validation cohorts, we selected six prognostic models predicting mortality risk in adults with COVID-19 infection (GAL-COVID-19 mortality, 4C Mortality Score, National Early Warning Score 2-extended model, Xie model, Wang clinical model, and CURB65 score). All six prognostic models were validated in the hospital cohorts and the GAL-COVID-19 mortality model was validated in all three healthcare settings. The primary outcome was in-hospital mortality for hospitals and 28-day mortality for primary care and nursing home settings. Model performance was evaluated in each validation cohort separately in terms of discrimination, calibration, and decision curves. An intercept update was performed in models indicating miscalibration followed by predictive performance re-evaluation. MAIN OUTCOME MEASURE: In-hospital mortality for hospitals and 28-day mortality for primary care and nursing home setting. RESULTS: All six prognostic models performed poorly and showed miscalibration in the older population cohorts. In the hospital settings, model performance ranged from calibration-in-the-large -1.45 to 7.46, calibration slopes 0.24-0.81, and C-statistic 0.55-0.71 with 4C Mortality Score performing as the most discriminative and well-calibrated model. Performance across health-care settings was similar for the GAL-COVID-19 model, with a calibration-in-the-large in the range of -2.35 to -0.15 indicating overestimation, calibration slopes of 0.24-0.81 indicating signs of overfitting, and C-statistic of 0.55-0.71. CONCLUSION: Our results show that most prognostic models for predicting mortality risk performed poorly in the older population with COVID-19, in each health-care setting: hospital, primary care, and nursing home settings. Insights into factors influencing predictive model performance in the older population are needed for pandemic preparedness and reliable prognostication of health-related outcomes in this demographic.

Predicting direct healthcare costs of general practitioner-guided care in patients with musculoskeletal complaints.

ABSTRACT: Information on healthcare utilization and costs of general practitioner (GP)-guided care in patients with musculoskeletal complaints is important for keeping healthcare affordable and accessible. A registry-based study was performed to describe healthcare utilization and costs of GP-guided care in patients with musculoskeletal complaints and to predict having higher direct healthcare costs. Healthcare costs of GP-guided care included all healthcare resources used by patients due to a musculoskeletal condition in 2018. Data were extracted from the database with a 1-year follow-up and descriptively analyzed. A general linear model was developed to predict having higher direct healthcare costs. In total, 403,719 patients were included, of whom 92% only received a single consultation. The number of referrals varied across the different types of complaints. Total annual direct healthcare costs amounted to €39,180,531, of which a key cost driver was referrals. Primary care consultations accounted for the largest part of referral-related costs. For all musculoskeletal conditions combined, the mean annual direct healthcare cost per patient was €97 (SEM = €0.18). Older age, being a woman, low socioeconomic status, spine complaints, high number of musculoskeletal diagnoses, and a high comorbidity score were predictive of having higher direct healthcare costs and explained 0.7% of the variance. This study showed that mean annual direct healthcare costs of GP-guided care in patients with musculoskeletal conditions were relatively low and did not differ considerably across conditions. The predictive model explained a negligible part of the variance in costs. Thus, it is unclear which factors do predict high direct healthcare costs in this population.

A study protocol of external validation of eight COVID-19 prognostic models for predicting mortality risk in older populations in a hospital, primary care, and nursing home setting.

BACKGROUND: The COVID-19 pandemic has a large impact worldwide and is known to particularly affect the older population. This paper outlines the protocol for external validation of prognostic models predicting mortality risk after presentation with COVID-19 in the older population. These prognostic models were originally developed in an adult population and will be validated in an older population (≥ 70 years of age) in three healthcare settings: the hospital setting, the primary care setting, and the nursing home setting. METHODS: Based on a living systematic review of COVID-19 prediction models, we identified eight prognostic models predicting the risk of mortality in adults with a COVID-19 infection (five COVID-19 specific models: GAL-COVID-19 mortality, 4C Mortality Score, NEWS2 + model, Xie model, and Wang clinical model and three pre-existing prognostic scores: APACHE-II, CURB65, SOFA). These eight models will be validated in six different cohorts of the Dutch older population (three hospital cohorts, two primary care cohorts, and a nursing home cohort). All prognostic models will be validated in a hospital setting while the GAL-COVID-19 mortality model will be validated in hospital, primary care, and nursing home settings. The study will include individuals ≥ 70 years of age with a highly suspected or PCR-confirmed COVID-19 infection from March 2020 to December 2020 (and up to December 2021 in a sensitivity analysis). The predictive performance will be evaluated in terms of discrimination, calibration, and decision curves for each of the prognostic models in each cohort individually. For prognostic models with indications of miscalibration, an intercept update will be performed after which predictive performance will be re-evaluated. DISCUSSION: Insight into the performance of existing prognostic models in one of the most vulnerable populations clarifies the extent to which tailoring of COVID-19 prognostic models is needed when models are applied to the older population. Such insight will be important for possible future waves of the COVID-19 pandemic or future pandemics.

Effectiveness of COVID-19 Vaccines in Adults with Diabetes Mellitus: A Systematic Review.

Persons with diabetes mellitus may have an increased risk of severe illness or death from COVID-19 compared to persons without diabetes. Prior studies indicate that immune response and thus vaccine effectiveness might be lower in persons with diabetes. We aimed to systematically review the effectiveness of COVID-19 vaccines in adults with diabetes. Pubmed, Embase, Web of Science and Cochrane Library were searched for studies that evaluated the effectiveness of COVID-19 vaccines in adults with diabetes, published before 4 March 2022. Risk of bias in the included studies was evaluated using the ROBINS-I tool. At least two reviewers conducted the study selection, data extraction, and risk of bias assessment independently. After screening of 2196 studies, a total of 17 articles were included. Six different COVID-19 vaccines (Ad5-nCoV-S, AZD1222, BNT162b2, CoronaVac, JNJ-78436735, and mRNA-1273) were included in the synthesis. Vaccine effectiveness was reported for SARS-CoV-2 infection, symptomatic COVID-19, hospitalization, and death, and ranged from 24 to 96% in persons with diabetes, and from 33 to 97% in total study populations; effectiveness was generally lower for persons with diabetes. Odds ratios for breakthrough infection or severe COVID-19 ranged from 1.03 to 2.41 in vaccinated persons with diabetes compared to persons without diabetes. Even though the included studies were very heterogeneous, results from the synthesis indicate that effectiveness of COVID-19 vaccines might be lower in persons with diabetes. More research is needed on the comparison of vaccine effectiveness between persons with and without diabetes, and the effectiveness of repeat COVID-19 vaccinations.

Multidisciplinary management of auto-immune ocular diseases in adult patients by ophthalmologists and rheumatologists.

PURPOSE: Management of chronic vision threatening auto-immune ocular diseases (AIOD, e.g. uveitis, scleritis) can be challenging. Guidelines recommend a multidisciplinary approach (MDA) with ophthalmologists and rheumatologists, to enhance the recognition of systemic diseases and guide the use of immunosuppressives. However, the indications and results of such an approach have not yet been studied. METHODS: A monocentre, retrospective chart review of all patients treated in a MDA between ophthalmologists and rheumatologists, in a Dutch tertiary center. The collaboration was twofold: a combined multidisciplinary team meeting every 2 weeks, and an ophthalmology-dedicated rheumatology outpatient clinic. Primary endpoints of this descriptive study were as follows: indications for MDA, new diagnoses of systemic auto-immune diseases and changes in systemic immunosuppression and prednisone dosages. RESULTS: In total, 157 adults (mean age 46 years, 57% female, median disease duration 19 months) were included, mainly with uveitis (74%) and scleritis (12%). Multidisciplinary approach (MDA)-indications included diagnostic workup (32%), treatment support (44%), diagnostic-and-treatment support (10%) and side effects (8%). A systemic disease was newly diagnosed in eight and already present in 34 patients. At baseline, 54 patients used oral prednisone at >7.5 mg/day. Non-corticoid immunosuppressives, mostly methotrexate, were started in 41% of the patients. During follow-up, systemic prednisone was lowered to ≤7.5 mg/day in 68% of the patients. CONCLUSION: This evaluation of an MDA-programme in the management of AIOD demonstrated its added value. Mainly, it addressed the high demand for support in managing systemic immunosuppression, resulting in significant corticosteroid tapering. In addition, it resulted in the recognition of underlying systemic diseases.