Dynamic prediction of mortality in COVID-19 patients in the intensive care unit: A retrospective multi-center cohort study.

Background: The COVID-19 pandemic continues to overwhelm intensive care units (ICUs) worldwide, and improved prediction of mortality among COVID-19 patients could assist decision making in the ICU setting. In this work, we report on the development and validation of a dynamic mortality model specifically for critically ill COVID-19 patients and discuss its potential utility in the ICU. Methods: We collected electronic medical record (EMR) data from 3222 ICU admissions with a COVID-19 infection from 25 different ICUs in the Netherlands. We extracted daily observations of each patient and fitted both a linear (logistic regression) and non-linear (random forest) model to predict mortality within 24 h from the moment of prediction. Isotonic regression was used to re-calibrate the predictions of the fitted models. We evaluated the models in a leave-one-ICU-out (LOIO) cross-validation procedure. Results: The logistic regression and random forest model yielded an area under the receiver operating characteristic curve of 0.87 [0.85; 0.88] and 0.86 [0.84; 0.88], respectively. The recalibrated model predictions showed a calibration intercept of -0.04 [-0.12; 0.04] and slope of 0.90 [0.85; 0.95] for logistic regression model and a calibration intercept of -0.19 [-0.27; -0.10] and slope of 0.89 [0.84; 0.94] for the random forest model. Discussion: We presented a model for dynamic mortality prediction, specifically for critically ill COVID-19 patients, which predicts near-term mortality rather than in-ICU mortality. The potential clinical utility of dynamic mortality models such as benchmarking, improving resource allocation and informing family members, as well as the development of models with more causal structure, should be topics for future research.

Distribution of care expenditures for men and women with type 2 diabetes treated in primary care in the Netherlands: a case-control study (ZODIAC-59).

OBJECTIVE: This study aims to provide insight into the distribution of care expenditures for patients with type 2 diabetes mellitus (T2DM)- across multiple healthcare service categories and medical specialties-who receive diabetes care in the primary care setting. DESIGN: Observational, matched case-control study. SETTING: In the Netherlands, T2DM-specific care is mainly provided in the primary care setting. However, many patients with T2DM also use secondary care for complications and comorbidities, either related or unrelated to their diabetes. PARTICIPANTS: Patients with T2DM receiving diabetes care in primary care and participating in the Dutch Zwolle Outpatient Diabetes project Integrating Available Care cohort in the year 2011 were matched to persons without T2DM. Matching (1:2 ratio) was performed based on age, gender and socioeconomic status. Clinical data were combined with an all-payer claims database from 2011. RESULTS: In total, 43 775 patients with T2DM were identified of whom 37 240 could be matched with 74 480 controls. Total secondary care expenditures were €94 705 814, with a total annual median expenditure per patient of €2133 (1161 to 3340) for men and €2,535 (1374 to 5105) for women. The largest share of expenditures was on medication (26%), followed by secondary care (23%) and primary care services related (23%) to T2DM. The five most expensive specialties were: cardiology, surgery, internal medicine, orthopaedics and ophthalmology. Care expenditures for T2DM patients were twofold higher than those for persons without T2DM. Healthcare expenditures showed a skewed distribution, indicating that a small part of the studied population is responsible for a considerable part of the costs. CONCLUSIONS: Expenditures among primary care treated T2DM patients are higher than non-diabetic matched controls. Medication is the largest share of T2DM care expenditures. The present study provides insights into healthcare expenditures for T2DM; this may enable more efficient healthcare planning and reimbursement.

Uptake and Effects of the e-Vita Personal Health Record with Self-Management Support and Coaching, for Type 2 Diabetes Patients Treated in Primary Care.

We studied the use, uptake, and effects of e-Vita, a personal health record, with self-management support and personalized asynchronized coaching, for type 2 diabetes patients treated in primary care. Patients were invited by their practice nurse to join the study aimed at testing use and effects of a personal health record. Patients were followed up for 6 months. Uptake and usage were monitored using log data. Outcomes were self-reported diabetes self-care, diabetes-related distress, and emotional wellbeing. Patients' health status was collected from their medical chart. 132 patients agreed to participate in the study of which less than half (46.1%) did not return to the personal health record after 1st login. Only 5 patients used the self-management support program within the personal health record, 3 of whom asked a coach for feedback. Low use of the personal health record was registered. No statistical significant differences on any of the outcome measures were found between baseline and 6 month follow-up. This study showed minimal impact of implementing a personal health record including self-management support in primary diabetes care. Successful adoption of web-based platforms, as ongoing patient centered care, is hard to achieve without additional strategies aimed at enhancing patient motivation and engaging professionals.

Intraperitoneal versus subcutaneous insulin therapy in the treatment of type 1 diabetes mellitus.

BACKGROUND: Continuous intraperitoneal insulin infusion (CIPII), a last-resort type 1 diabetes mellitus (T1DM) treatment, has only been investigated in small or controlled studies. We aimed to investigate glycaemia and quality of life (QoL) with CIPII versus subcutaneous (SC) insulin therapy during usual T1DM care. METHODS: A prospective, observational case-control study. CIPII-treated cases were matched to SC controls. The primary endpoint was a non-inferiority assessment (pre-defined margin of -5.5 mmol÷mol) of the baseline adjusted difference in HbA1c between groups during a 26-week follow-up. Secondary outcomes included QoL, clinical and biochemical measurements. RESULTS: In total, 183 patients were analysed (CIPII n = 39 and SC n = 144). The HbA1c difference between treatment groups was -3.0 mmol÷mol (95% CI -5.0, -1.0), being lower in the SC group. Patients using SC insulin therapy spent less percentage of time in hyperglycaemia (-9.3% (95% CI -15.8, -2.8)) and more in euglycaemia (6.9% (95% CI 1.2, 12.5) as compared with CIPII-treated patients. Besides a 3.6 U÷l (95% CI 1.2, 6.0) lower concentration of alanine aminotransferase with CIPII, no biochemical and clinical differences were present. Most QoL scores were lower at baseline among CIPII-treated patients. However, besides lower health status, there were no differences in the baseline-adjusted general and diabetes-specific QoL and treatment satisfaction. CONCLUSION: Although patients using CIPII had a higher glycaemic profile compared with patients using SC insulin therapy, the HbA1c difference was non-inferior. Overall, health status was lower among CIPII-treated patients, although diabetes-specific QoL and treatment satisfaction was similar to subcutaneously treated patients.