Titration Algorithm Research Articles

Optimizing Inspire Hypoglossal Nerve Stimulator Settings in Pediatric Obstructive Sleep Apnea.

Hypoglossal nerve stimulation (HGNS) is an effective therapy for carefully selected pediatric patients with Down syndrome (DS) and obstructive sleep apnea (OSA), but optimization of device settings has been focused on stimulation settings. The potential benefits of sensing lead setting optimization have not been investigated. We describe a series of three cases of HGNS in children with DS where optimization of both the stimulation lead and sensing lead settings, as well as utilization of drug-induced sleep endoscopy (DISE), when indicated, was more effective than stimulation lead optimization alone. Using our novel titration algorithm, among the three identified pediatric patients with DS in whom HGNS initially failed to reduce the apnea-hypopnea index (AHI), two patients in whom sleep studies were characterized as hypopnea-dominant were assigned to advanced titration (optimization of stimulation settings and sensing lead settings). The third patient, with an obstructive apnea-dominant sleep study, was referred for interrogated DISE. Advanced titration included adjustment of both stimulation settings and sensing lead settings. Application of the advanced titration algorithm, tailored to obstructive apnea- versus hypopnea-dominant sleep patterns, resulted in approximately 50% or greater reduction in AHI in all three patients. "Normal to mild OSA" AHI (AHI <5) was achieved in two patients. A novel diagnostic and therapeutic titration algorithm for the Inspire HGNS system significantly reduced AHI in three pediatric patients with DS and OSA who had failed to respond to the standard device titration that focused solely on stimulation settings. 4 Laryngoscope, 2024.

Titration of anti-IL-5 biologics in severe asthma: an open-label randomised controlled trial (the OPTIMAL study).

Anti-interleukin (IL)-5 biologics effectively reduce exacerbations and the need for maintenance oral corticosteroids (mOCS) in severe eosinophilic asthma. However, it is unknown how long anti-IL-5 treatment should be continued. Data from clinical trials indicate a gradual but variable loss of control after treatment cessation. In this pilot study of titration, we evaluated a dose-titration algorithm in patients who had achieved clinical control on an anti-IL-5 biologic. In this open-label randomised controlled trial conducted over 52 weeks, patients with clinical control (no exacerbations or mOCS) on anti-IL-5 treatment were randomised to continue with unchanged intervals or have dosing intervals adjusted according to a titration algorithm that gradually extended dosing intervals and reduced them again at signs of loss of disease control. The OPTIMAL algorithm was designed to down-titrate dosing until signs of loss of control, to enable assessment of the longest dosing interval possible. Among 73 patients enrolled, 37 patients were randomised to the OPTIMAL titration arm; 78% of patients tolerated down-titration of treatment. Compared to the control arm, the OPTIMAL arm tended to have more exacerbations during the study (32% versus 17%; p=0.13). There were no severe adverse events related to titration, and lung function and symptoms scores remained stable and comparable in both study arms throughout. This study serves as a proof of concept for titration of anti-IL-5 biologics in patients with severe asthma with clinical control on treatment, and the OPTIMAL algorithm provides a potential framework for individualising dosing intervals in the future.

Summary of clinical investigation plan for The DIATEC trial: in-hospital diabetes management by a diabetes team and continuous glucose monitoring or point of care glucose testing – a randomised controlled trial

BackgroundWorldwide, up to 20 % of hospitalised patients have diabetes mellitus. In-hospital dysglycaemia increases patient mortality, morbidity, and length of hospital stay. Improved in-hospital diabetes management strategies are needed. The DIATEC trial investigates the effects of an in-hospital diabetes team and operational insulin titration algorithms based on either continuous glucose monitoring (CGM) data or standard point-of-care (POC) glucose testing.MethodsThis is a two-armed, two-site, prospective randomised open-label blinded endpoint (PROBE) trial. We recruit non-critically ill hospitalised general medical and orthopaedic patients with type 2 diabetes treated with basal, prandial, and correctional insulin (N = 166).In both arms, patients are monitored by POC glucose testing and diabetes management is done by ward nurses guided by in-hospital diabetes teams. In one of the arms, patients are monitored in addition to POC glucose testing by telemetric CGM viewed by the in-hospital diabetes teams only. The in-hospital diabetes teams have operational algorithms to titrate insulin in both arms. Outcomes are in-hospital glycaemic and clinical outcomes.DiscussionThe DIATEC trial will show the glycaemic and clinical effects of in-hospital CGM handled by in-hospital diabetes teams with access to operational insulin titration algorithms in non-critically ill patients with type 2 diabetes. The DIATEC trial seeks to identify which hospitalised patients will benefit from CGM and in-hospital diabetes teams compared to POC glucose testing. This is essential information to optimise the use of healthcare resources before broadly implementing in-hospital CGM and diabetes teams.Trial registrationProspectively registered at ClinicalTrials.gov with identification number NCT05803473 on March 27th 2023.

Smart Algorithms for Efficient Insulin Therapy Initiation in Individuals With Type 2 Diabetes: An in Silico Study.

Insulin-naive subjects with type 2 diabetes (T2D) start basal insulin titration from a low initial insulin dose (IID), which is adjusted weekly or twice per week based on fasting plasma glucose (FPG) measurement as recommended by the American Diabetes Association (ADA). The procedure to reach the optimal insulin dose (OID) is time-consuming, especially in subjects with high insulin needs (HIN). The aim of this study is to provide a fast and effective, but still safe, insulin titration algorithm in insulin-naive T2D subjects with HIN. To do that, we in silico cloned 300 subjects, matching a real population of insulin-naive T2D and used a logistic regression model to classify them as subjects with HIN or subjects with low insulin needs (LIN). Then, we applied to the subjects with HIN both a more aggressive insulin dose initiation (SMART-IID) and two newly developed titration algorithms (continuous glucose monitoring [CGM]-BASED and SMART-CGM-BASED) in which CGM was used to guide the decision-making process. The new titration algorithm applied to HIN-classified individuals guaranteed a faster reaching of OID, with significant improvements in time in range (TIR) and reduction in time above range (TAR) in the first months of the trial, without any clinically significant increase in the risk of hypoglycemia. Smart basal insulin titration algorithms enable insulin-naive T2D individuals to achieve OID and improve their glycemic control faster than standard guidelines, without jeopardizing patient safety.

Comparison of Efficacy and Adherence of Patient-Preferred (1 Unit Daily) and ADA/EASD Guideline-Recommended (2 Units Every 3 Days) Basal Insulin Titration Algorithms: Multicenter, Randomized, Clinical Study.

Insulin titration often faces inertia, hindering glycemic control. A patient-centered approach empowers patients to overcome this inertia. This study aims to compare the effectiveness of patient-preferred and guideline-recommended self-titration algorithms in achieving glycemic targets and improving adherence. Outpatients with type 2 diabetes (T2D) who did not respond to oral antihyperglycemic drugs (OAD) were assessed. They were randomly assigned to patient-preferred and guideline-recommended groups. In the patient-preferred group, individuals selected an algorithm to self-adjust their insulin glargine dosage by 2 units every 3 days if the mean fasting blood glucose (FBG) over the past 3 consecutive days was ≥7.0 mmol/L, or by 1 unit daily if the FBG on the same day was ≥7.0 mmol/L. In the guideline-recommended group, insulin glargine was titrated by 2 units every 3 days if the mean FBG over the past 3 consecutive days was ≥7.0 mmol/L. The FBG target was set below <7.0 mmol/L. Thirty-nine participants in the patient-preferred group and 42 in the guideline-recommended group completed the study. The cumulative rates of achieving the FBG target in the patient-preferred group compared to the guideline-recommended group were 69.2% vs 54.8% (χ²=1.792, p=0.181) in week 1, 89.7% vs 73.8% (χ²=3.403, p = 0.065) in week 2, 94.9% vs 76.2% (χ²=17.638, p=0.000) in week 3, and 100.0% vs 88.1% (χ²=4.405, p=0.036) in week 4. Adherence rates were significantly higher in the patient-preferred group (97.4%, 37/38) compared to the guideline-recommended group (66.7%, 28/42) (χ²=12.688, p=0.000). Insulin glargine dosage at FBG target achievement was 21.2±4.3 U in the patient-preferred group and 18.8±6.7 U in the guideline-recommended group (t=1.888, p=0.063). Hypoglycemia was reported in 1 patient in the guideline-recommended group, with no instances in the patient-preferred group. The patient-preferred self-titration algorithm demonstrates a higher rate of reaching glucose targets and improved adherence. ChiCTR2100050805.

Lung- and diaphragm-protective strategies in acute respiratory failure: an in silico trial

BackgroundLung- and diaphragm-protective (LDP) ventilation may prevent diaphragm atrophy and patient self-inflicted lung injury in acute respiratory failure, but feasibility is uncertain. The objectives of this study were to estimate the proportion of patients achieving LDP targets in different modes of ventilation, and to identify predictors of need for extracorporeal carbon dioxide removal (ECCO2R) to achieve LDP targets.MethodsAn in silico clinical trial was conducted using a previously published mathematical model of patient–ventilator interaction in a simulated patient population (n = 5000) with clinically relevant physiological characteristics. Ventilation and sedation were titrated according to a pre-defined algorithm in pressure support ventilation (PSV) and proportional assist ventilation (PAV+) modes, with or without adjunctive ECCO2R, and using ECCO2R alone (without ventilation or sedation). Random forest modelling was employed to identify patient-level factors associated with achieving targets.ResultsAfter titration, the proportion of patients achieving targets was lower in PAV+ vs. PSV (37% vs. 43%, odds ratio 0.78, 95% CI 0.73–0.85). Adjunctive ECCO2R substantially increased the probability of achieving targets in both PSV and PAV+ (85% vs. 84%). ECCO2R alone without ventilation or sedation achieved LDP targets in 9%. The main determinants of success without ECCO2R were lung compliance, ventilatory ratio, and strong ion difference. In silico trial results corresponded closely with the results obtained in a clinical trial of the LDP titration algorithm (n = 30).ConclusionsIn this in silico trial, many patients required ECCO2R in combination with mechanical ventilation and sedation to achieve LDP targets. ECCO2R increased the probability of achieving LDP targets in patients with intermediate degrees of derangement in elastance and ventilatory ratio.

On the Validity of Constant pH Simulations.

Constant pH (cpH) simulations are now a standard tool for investigating charge regulation in coarse-grained models of polyelectrolytes and colloidal systems. Originally developed for studying solutions with implicit ions, extending this method to systems with explicit ions or solvents presents several challenges. Ensuring proper charge neutrality within the simulation cell requires performing titration moves in sync with the insertion or deletion of ions, a crucial aspect often overlooked in the literature. Contrary to the prevailing views, cpH simulations are inherently grand-canonical, meaning that the controlled pH is that of the reservoir. The presence of the Donnan potential between the implicit reservoir and the simulation cell introduces significant differences between titration curves calculated for open and closed systems; the pH of an isolated (closed) system is different from the pH of the reservoir for the same protonation state of the polyelectrolyte. To underscore this point, in this paper, we will compare the titration curves calculated using the usual cpH algorithm with those from the exact canonical simulation algorithm. In the latter case, titration moves adhere to the correct detailed balance condition, and pH is calculated using the recently introduced surface Widom insertion algorithm. Our findings reveal a very significant difference between the titration isotherms obtained using the standard cpH algorithm and the canonical titration algorithm, emphasizing the importance of using the correct simulation approach when studying charge regulation of polyelectrolytes, proteins, and colloidal particles.

Short- and Long-Term Effects on Glucose Control of Nonadherence to Insulin Therapy in People With Type 2 Diabetes An In Silico Study.

Strict adherence to multiple daily insulin (MDI) therapy is a cornerstone for the achievement of good glucose control in people with advanced type 2 diabetes (T2D). Here, we aim to in silico assess glucose control in T2D subjects with poor adherence to MDI therapy. We tuned the Padova T2D Simulator, originally describing early-stage T2D physiology, around advanced T2D people. One hundred in silico advanced T2D subjects were generated and equipped with optimal MDI therapy: specifically, basal and bolus insulin amounts and injection times were individualized for each subject by applying titration algorithms that iteratively update insulin dose based on glucose deviation from its target. Then, the effect of nonadhering to MDI therapy was assessed using standard glucose control metrics calculated in two 6-month 3-meal/day in silico scenarios: in Scenario 1, subjects received the optimal basal and prandial insulin bolus at each meal; in Scenario 2, subjects received optimal basal insulin and randomly delayed or skipped the prandial insulin bolus in 3 lunches during working days and 1 dinner during weekends. A statistically significant degradation was found in all glucose control outcome metrics in Scenario 2 versus Scenario 1: e.g., percent time above 180 mg/dL increased by 22.2% and glucose management index by 0.2%. Impaired adherence to MDI therapy in T2D leads to glucose control deteriorations in both short and long terms. Interestingly, short-term hyperglycemia seems being contrasted by residual endogenous insulin secretion, which statistically increased by 3-fold after delayed/skipped insulin boluses compared with optimal ones.

A Data-Driven Framework for Clinical Decision Support Systems in Positive Airway Pressure and Oxygen Titration

Background: Current obstructive sleep apnea treatment relies on manual PAP titration, but it has limitations. Complex interactions during titration and variations in SpO2 data accuracy pose challenges. Patients with co-occurring chronic hypercapnia may require precise oxygen titration. To address these issues, we propose a Clinical Decision Support System using Markov decision processes. Methods: This study, compliant with data protection laws, focused on adults with OSA-induced hypoxemia utilizing supplemental oxygen and CPAP/BiPAP therapy. PAP titration, conducted over one night, involved vigilant monitoring of vital signs and physiological parameters. Adjustments to CPAP pressure, potential BiLevel transitions, and supplemental oxygen were precisely guided by patient metrics. Markov decision processes outlined three treatment actions for disorder management, incorporating expert medical insights. Results: In our study involving 14 OSA patients (average age: 63 years, 27% females, BMI 41 kg m−2), significant improvements were observed in key health parameters after manual titration. The initial AHI of 61.8 events per hour significantly decreased to an average of 18.0 events per hour after PAP and oxygen titration (p &lt; 0.0001), indicating a substantial reduction in sleep-disordered breathing severity. Concurrently, SpO2 levels increased significantly from an average of 79.7% before titration to 89.1% after titration (p &lt; 0.0003). Pearson correlation coefficients demonstrated aggravation of hypercapnia in 50% of patients (N = 5) with initial pCO2 &lt; 55 mmHg during the increase in CPAP pressure. However, transitioning to BiPAP exhibited a reduction in pCO2 levels, showcasing its efficacy in addressing hypercapnia. Simultaneously, BiPAP therapy correlated with a substantial increase in SpO2, underscoring its positive impact on oxygenation in OSA patients. Markov Decision Process analysis demonstrated realistic patient behavior during stable night conditions, emphasizing minimal apnea and good toleration to high CPAP pressure. Conclusions: The development of a framework for Markov decision processes of PAP and oxygen titration algorithms holds promise for providing algorithms for improving pCO2 and SpO2 values. While challenges remain, including the need for high-quality data, the potential benefits in terms of patient management and care optimization are substantial, and this approach represents an exciting frontier in the realm of telemedicine and respiratory healthcare.

Efficacy and safety of basal-bolus insulin at 1:1.5 ratio compared to 1:1 ratio using a weight-based initiation and titration (WIT2) algorithm in hospitalized patients with type 2 Diabetes: a multicenter, randomized, clinical study

BackgroundMost studies initiated basal-bolus insulin in a ratio of 1:1 and titrated based on glucose. This study aimed to investigate the effectiveness and safety of a weight-based and ratio of 1:1.5 basal-bolus insulin using an algorithm for both initiation and titration in hospitalized patients with type 2 diabetes (T2D).MethodsHospitalized patients with T2D were randomly assigned to two groups in equal numbers to receive 1:1.5 and 1:1 ratios of basal-bolus insulin using a weight-based algorithm for both initiation and titration. The primary outcome was the time taken to reach the fasting blood glucose (FBG) target and 2-h postprandial blood glucose (2hBG) targets after three meals. The secondary outcome included insulin dosage to achieve glycemic control and the incidence of hypoglycemia during hospitalization.Results250 patients were screened between October 2021 and June 2022, 220 were randomly grouped, and 182 completed the trial (89 in the 1:1.5 and 93 in the 1:1 groups). The time taken to reach FBG targets was comparable between the two groups (3.4 ± 1.7 vs. 3.0 ± 1.3 days, p = 0.137) within about 3 days. The 2hBG after three meals was shorter in the 1:1.5 group than in the 1:1group (2.9 ± 1.5 vs. 3.4 ± 1.4 days, p = 0.015 for breakfast, 3.0 ± 1.6 vs. 3.6 ± 1.4 days, p = 0.005 for lunch, and 3.1 ± 2.1 vs. 4.0 ± 1.5 days, p = 0.002 for dinner). No significant difference in insulin dosages was found between the two groups at the end of the study. The incidence of hypoglycemia was similar in both groups.ConclusionsWe demonstrated that fixed dose-ratio basal-bolus insulin at 1:1.5 calculated using a weight-based initiation and titration algorithm was simple, as effective, and safe as ratio at 1:1 in managing T2D in hospitalized patients.Trial Registration ChiCTR 2,100,050,963. Date of registration: September 8, 2021.

Study protocol: glycaemic outcomes in people with type 2 diabetes initiating continuous glucose monitoring: the 2GO-CGM study

PurposeImproving glycaemic control in type 2 diabetes (T2D) is essential to reducing social and health-economic burden of diabetes-related complications. Continuous glucose monitoring (CGM) has been established as beneficial in improving glycaemic control and reducing hypoglycaemia in people with type 1 diabetes, however data in T2D is limited. This study has been designed to assess the effect of initiating real-time CGM (rtCGM) on glycaemic control in a high-risk population of adults with T2D. Secondary objectives are to assess the cost-effectiveness and safety of rtCGM, and the effects of rtCGM on diet/lifestyle and the burden of diabetic complications, including cardiovascular risk.MethodsThis multicentre randomised controlled trial (RCT) will be conducted at three sites in New Zealand (Waikato, Christchurch and Dunedin). Eighty adults with T2D on insulin with suboptimal glycaemic control (HbA1c > 8.0% or 64 mmol/mol) will be randomised 1:1 to rtCGM or routine care with self-monitoring of blood glucose levels (SMBG) for three months. This intervention phase will be followed by a three-month continuation phase where SMBG group crossover to use rtCGM. Participants will then be invited to join the extension phase with continued use of rtCGM for a further 12 months. During the extension phase, both groups will independently titrate their insulin under the remote supervision of prescribing diabetes nurse specialists following an insulin titration algorithm. The primary outcome of the study is time in target glucose range (3.9–10 mmol/L or 70–180 mg/dL; TIR). Secondary outcomes include CGM metrics as per consensus statement recommendations, and HbA1c. Additional planned analyses include cardiovascular risk profile, incremental cost-effectiveness analyses, dietary patterns, and qualitative analyses.Trial registration numberThe trial was registered with the Australian New Zealand Clinical Trials Registry (ACTRN12621000889853) on 8 July 2021 and the World Health Organisation International Clinical Trial Registry Platform (Universal Trial Number U1111–1264-5822).

Adaptive Balloon Weaning Algorithm With Automated REBOA Facilitates Proximal Homeostasis During Reperfusion in a Swine Hemorrhagic Shock Model

Restoration of distal blood flow is critical to successfully salvage patients with resuscitative endovascular balloon occlusion of the aorta (REBOA). Yet, ideal methods for REBOA deflation to restore flow and simultaneously avoid proximal hypotension, remain undefined. Adaptive balloon titration algorithms to guide deflation may prevent large hemodynamic fluctuations during weaning. We hypothesize that automated REBOA weaning can both augment proximal hemodynamics and avoid hypotension during resuscitation in a swine model of hemorrhagic shock. Fifteen swine underwent 30% controlled hemorrhage followed by 30 minutes of zone 1 REBOA. Next, the REBOA was deflated with an automated syringe running an adaptive algorithm that prioritized proximal mean arterial blood pressure (pMAP) of >62.5 mm Hg during transfusion of shed blood. Upon post hoc analysis, animal pMAP responses (hypertensive [HTN] vs normotensive [NORM]) and the discovery of low volume distal flow during the intended complete REBOA allowed us to identify two distinct cohorts. The performance of the adaptive weaning algorithm was compared between the groups. The two cohorts (HTN, n = 5; NORM, n = 10) differed in pMAP (P = .001) and distal flow (P = .001) during REBOA. During the wean phase, cohorts were similar in pMAP, time with carotid flow within 90% of baseline, and time above the pMAP threshold of 62.5 mm Hg (P = .20, P = .59, and P = .95, respectively) despite the weaning algorithm permitting 14.5 mL/kg more distal aortic flow for the HTN cohort (P = .001). Automated REBOA weaning is feasible and maintains consistent hemodynamics across various physiological profiles. Automated endovascular devices that can interpret and adapt to a range of hemodynamic physiology will soon facilitate precision resuscitation for patients requiring endovascular aortic occlusion. These findings highlight the need for adaptive control to overcome variability in hemodynamics and differences in resuscitation intensity across clinical contexts.

Basal insulin titration algorithms in patients with type 2 diabetes: the simplest is the best (?)

Basal insulin is the first and main component of insulin therapy in patients with type 2 diabetes mellitus (T2DM). Based on the shortcomings of human NPH insulin and the advantages provided by long-acting basal insulin analogues, they are recommended for priority use in patients with T2DM. The leading factor in the success of insulin therapy is titration of its dose with the achievement of the target range of glycemia. Data from clinical trials and real clinical practice indicate that simpler dose titration algorithms ensure better achievement of glycemic goals with a lower risk of hypoglycemia. In addition, simple dose titration algorithms are better accepted by patients and increase satisfaction with treatment. The leading societies of diabetologists ADA/EASD and AACE/ACE recommend the use of simple dose titration algorithms. Recent clinical trials on the effectiveness of the insulin glargine dose titration based on the INSIGHT algorithm, which, unlike the traditional options for changing the dose 1–2 times a week, involves a daily correction of the insulin glargine dose by 1 Unit, have proven its effectiveness and safety. Most patients prefer this type of insulin dose titration. The same titration algorithm can be used for a fixed combination of glargine with lixisenatide, which was also confirmed by the results of clinical trials. In general, simplified options for correcting the basal insulin dose have demonstrated their effectiveness and allow increasing the percentage of patients who manage to achieve the glycemic goal without increasing the risk of hypoglycemia. When prescribing basal insulin, physician must determine the target range of glycemia, demonstrate the titration algorithm that is acceptable for each insulin and which a patient will use to achieve the glycemic goal.

Altruism and Patience in Choices between Financial Losses – Experimental Findings

In this empirical study (n = 102), the authors set out to investigate the relation between altruism (measured with the use of individual social discounting rates) and patience (measured with the use of delays) under the conditions of financial losses. Thanks to the titration algorithm by Holt et al. (2003), and the Area Under the Curve indicator by Myerson et al. (2001), the study could apply discounting procedures to assess the altruism and patience of individuals. It was found that altruism and patience can be but do not have to be positively correlated in the domain of economic losses. It turns out that the occurrence of a positive correlation between altruism and patience (as often reported in the behavioural economics literature devoted to economic gains) depends on the temporal structure of the discounting task (temporal context of choice). When both the loss for the decision maker and another person from the social distance scale is delayed (shifted in time), positive correlations between altruism and patience are not observed. The latter finding is novel and nuances the behavioural economics knowledge on the relation between altruism and patience in economic choices.

Time for Using Machine Learning for Dose Guidance in Titration of People With Type 2 Diabetes? A Systematic Review of Basal Insulin Dose Guidance.

Real-world studies of people with type 2 diabetes (T2D) have shown insufficient dose adjustment during basal insulin titration in clinical practice leading to suboptimal treatment. Thus, 60% of people with T2D treated with insulin do not reach glycemic targets. This emphasizes a need for methods supporting efficient and individualized basal insulin titration of people with T2D. However, no systematic review of basal insulin dose guidance for people with T2D has been found. To provide an overview of basal insulin dose guidance methods that support titration of people with T2D and categorize these methods by characteristics, effect, and user experience. The review was conducted according to the Preferred Reporting Items for Systematic Review and Meta-Analysis (PRISMA) guidelines. Studies about basal insulin dose guidance, including adults with T2D on basal insulin analogs published before September 7, 2022, were included. Joanna Briggs Institute critical appraisal checklists were applied to assess risk of bias. In total, 35 studies were included, and three categories of dose guidance were identified: paper-based titration algorithms, telehealth solutions, and mathematical models. Heterogeneous reporting of glycemic outcomes challenged comparison of effect between the three categories. Few studies assessed user experience. Studies mainly used titration algorithms to titrate basal insulin as telehealth or in paper format, except for studies using mathematical models. A numerically larger proportion of participants seemed to reach target using telehealth solutions compared to paper-based titration algorithms. Exploring capabilities of machine learning may provide insights that could pioneer future research while focusing on holistic development.

Abstract 15142: Consistent Improvement in Utilization of Guideline Directed Medical Therapy Race for Traditionally Underserved Populations Using a Remote Intervention

Background: Heart failure (HF) disproportionately affects populations traditionally underserved in medicine. Remote healthcare delivery expands the reach of health care systems and providers, however some fear new models may pose challenges to equitable health care delivery. By building a remote HF clinic we aimed to increase equitable access to guideline-directed medical therapy (GDMT) optimization for HF. Methods: Patients with HF and a left ventricular ejection fraction &lt; 40% were identified by health record screening. Patients’ cardiologist was approached to participate in the remote intervention (RI) program, and those who declined their patient’s involvement served as a reference ‘usual care’ (UC) group. HF medications in the RI group were adjusted by pharmacists and patient navigators according to a GDMT titration algorithm. We examined differences in the efficacy of the intervention by race and separately by area deprivation index (ADI) - a validated method of stratifying neighborhood-level health determinants (higher scores indicate fewer resources). Results: Of 1131 eligible patients, 196 completed the 3-month follow-up in the RI group. The RI group included 16.8% Black individuals, 59.2% of patients in the low (1-5) ADI category and 29.6% in the high (6-10) ADI category. The UC group included 831 patients: 9.9% Black individuals, 54.0% in the low ADI category and 25.6% in the high ADI category. When compared to Black patients in UC, Black patients who participated in the RI program saw more medication titrations and rates of reaching target dosage for both ACE/ARB/ARNI &amp; beta-blockers (BB). When compared across ADI, the RI group had increased rates of ACE/ARB/ARNI &amp; BB titration and target dose achieved in the low and high ADI categories compared the UC group (Figure 1). Conclusion: A remote HF program was able to improve utilization of GDMT regardless of race and ADI. This care model may improve access to HF care for traditionally underserved populations.

Prone positioning may increase lung overdistension in COVID-19-induced ARDS

Real-time effects of changing body position and positive end-expiratory pressure (PEEP) on regional lung overdistension and collapse in individual patients remain largely unknown and not timely monitored. The aim of this study was to individualize PEEP in supine and prone body positions seeking to reduce lung collapse and overdistension in mechanically ventilated patients with coronavirus disease (COVID-19)-induced acute respiratory distress syndrome (ARDS). We hypothesized that prone positioning with bedside titrated PEEP would provide attenuation of both overdistension and collapse. In this prospective observational study, patients with COVID-19-induced ARDS under mechanical ventilation were included. We used electrical impedance tomography (EIT) with decremental PEEP titration algorithm (PEEPEIT-titration), which provides information on regional lung overdistension and collapse, along with global respiratory system compliance, to individualize PEEP and body position. PEEPEIT-titration in supine position followed by PEEPEIT-titration in prone position were performed. Immediately before each PEEPEIT-titration, the same lung recruitment maneuver was performed: 2 min of PEEP 24 cmH2O and driving pressure of 15 cmH2O. Forty-two PEEPEIT-titration were performed in ten patients (21 pairs supine and prone positions). We have found larger % of overdistension along the PEEP titration in prone than supine position (P = 0.042). A larger % of collapse along the PEEP titration was found in supine than prone position (P = 0.037). A smaller respiratory system compliance was found in prone than supine position (P < 0.0005). In patients with COVID-19-induced ARDS, prone body position, when compared with supine body position, decreased lung collapse at low PEEP levels, but increased lung overdistension at PEEP levels greater than 10 cm H2O.Trial registration number: NCT04460859.

Patient-led rapid titration of basal insulin in gestational diabetes is associated with improved glycaemic control and lower birthweight.

AimsElevated fasting blood glucose in gestational diabetes (GDM) is a key predictor of high birthweight babies and adverse pregnancy outcomes but is hard to treat. We implemented a simple, patient‐led, insulin dose titration algorithm aiming to improve fasting glycaemic control in GDM.MethodsIn women with GDM, initiating basal insulin, we recommended a daily four‐unit dose increase after every fasting glucose value ≥5.0 mmol/mol (90 mg/dl). This approach augmented our pre‐existing intensive (weekly) specialist nursing input. Using a before‐and‐after retrospective observational study design, we examined insulin doses and glucose values at 36 weeks gestation and maternal and neonatal outcomes in 105 women completing pregnancy before and 93 women after the intervention.ResultsThe baseline characteristics of women in the before and after groups were the same. Women initiated on insulin after implementation (n = 30 before, n = 43 after) achieved substantially higher doses at 36 weeks (53 vs. 36 units/day; 0.56 vs. 0.37 units/kg/day; p = 0.027). 36‐week mean fasting glucose was lower in those on insulin after implementation (4.6 vs. 5.1 mmol/L [83 vs. 92 mg/dl]; p = 0.031). Birthweight was significantly reduced (birthweight Z‐scores 0.34 vs. 0.92; p = 0.005). There was no significant difference in macrosomia (after; 2% vs. before; 17% p = 0.078) or caesarean sections (after; 33% vs. before; 47%; p = 0.116). No women experienced severe hypoglycaemia. There were no outcome differences before versus after intervention in women not treated with insulin.ConclusionsPatient‐led daily insulin titration in gestational diabetes leads to higher insulin dose use lower fasting glucose and is associated with lower birthweight without causing significant hypoglycaemia.

In gestational diabetes, patient‐led insulin titration is rapidly effective, safe and is associated with reduced birthweight

AbstractBackground: Elevated fasting glucose in gestational diabetes (GDM) is the strongest predictor of adverse pregnancy outcomes but is difficult to treat. We assessed the effectiveness, safety, and patient acceptability of a simple patient‐led insulin dose titration algorithm in GDM, targeting rapid reduction in fasting glucose.Methods: Once initiated on basal insulin, women were asked to increase their dose by 4 units daily, following every fasting glucose ≥5.0mmol/L. We evaluated pregnancy outcomes, rates of hypoglycaemia and time taken to achieve target readings (&lt;5.3mmol/L) before and after this practice change. We undertook patient interviews and questionnaires to capture the patient perspective.Results: Insulin was commenced at a median 30+4 weeks with fasting glucose control (defined as the first of three consecutive readings &lt;5.3mmol/L) achieved after a median 4 days (IQR: 1–11) and maintained throughout pregnancy with further patient‐led titrations. Hypoglycaemia was uncommon; 1.7% of all fasting glucose readings were &lt;3.5mmol/L and 0.3% were &lt;3.0mmol/L. No patients experienced hypoglycaemia requiring assistance. At delivery, patient‐led titration achieved higher final insulin doses (53 vs 36 units/day; p=0.027), improved fasting glucose (4.6 vs 5.1mmol/L; p=0.031), and significantly lower birthweight (Z‐scores 0.34 vs 0.92; p=0.005) compared to our previous routine practice. Women liked the intervention and having increased responsibility for their own management.Conclusions: In GDM significant reduction in birthweight is achieved with patient‐led insulin dose titration. Following insulin initiation glycaemic control is achieved rapidly and maintained without detrimental hypoglycaemia. Copyright © 2022 John Wiley &amp; Sons.

Comparing a daily versus weekly titration algorithm in people with type 2 diabetes switching from basal insulin to iGlarLixi in the LixiLan ONE CAN randomized trial.

AimTo compare the efficacy and safety of a simple daily titration algorithm compared with a weekly dose adjustment of iGlarLixi in people with type 2 diabetes.Materials and MethodsLixiLan ONE CAN (NCT03767543), a randomized, 26‐week, open‐label, multicentre phase 3 trial conducted in Canada, involved 265 people with type 2 diabetes and an HbA1c of ≥7.5% to ≤ 10.5% or less (≥58 to ≤91 mmol/mol) on basal insulin for 6 months or longer. Participants were randomized 1:1 with instructions to self‐titrate iGlarLixi daily (1 unit/day) or once weekly (2 or 4 units/week) to a common target fasting plasma glucose of 4.4 to 5.6 mmol/L (79 to 101 mg/dl). The primary objective was to show non‐inferiority of the daily versus weekly titration algorithm.ResultsAt 26 weeks, daily titration of iGlarLixi was not inferior to a weekly titration for both the prespecified primary endpoint of change in HbA1c from baseline (least square [LS] mean change: −1.24% vs. −0.92%, respectively; LS mean difference: 0.32%; 95% CI [0.07, 0.57]; P < .0001) and for the secondary endpoint of change in weight from baseline (LS mean change: −0.22 vs. +0.81 kg, respectively; LS mean difference: 1.03 kg; 95% CI [0.01, 2.06]; P < .0001). Indeed, for both the primary and secondary outcome, the daily titration of iGlarLixi was superior. There were no statistically significant differences in hypoglycaemia incidence between the two titration strategies during the 26‐week study.ConclusionA daily titration algorithm for switching basal insulin to iGlarLixi was shown to be non‐inferior and superior for glycaemic control and weight compared with weekly titration.