Effectiveness and safety of prehospital analgesia with nalbuphine and paracetamol versus morphine by paramedics - an observational study.

BACKGROUND: Despite the development of various analgesic concepts, prehospital oligoanalgesia remains very common. The present work examines prehospital analgesia by paramedics using morphine vs. nalbuphine + paracetamol. METHODS: Patients with out-of-hospital-analgesia performed by paramedics from the emergency medical services of the districts of Fulda (morphine) and Gütersloh (nalbuphine + paracetamol) were evaluated with regards to pain intensity at the beginning and the end of prehospital treatment using the Numeric-Rating-Scale for pain (NRS), sex, age, and complications. The primary endpoint was achievement of adequate analgesia, defined as NRS < 4 at hospital handover, depending on the analgesics administered (nalbuphine + paracetamol vs. morphine). Pain intensity before and after receiving analgesia using the NRS, sex, age and complications were also monitored. RESULTS: A total of 1,808 patients who received out-of-hospital-analgesia were evaluated (nalbuphine + paracetamol: 1,635 (90.4%), NRS-initial: 8.0 ± 1.4, NRS-at-handover: 3.7 ± 2.0; morphine: 173(9.6%), NRS-initial: 8.5 ± 1.1, NRS-at-handover: 5.1 ± 2.0). Factors influencing the difference in NRS were: initial pain intensity on the NRS (regression coefficient (RK): 0.7276, 95%CI: 0.6602-0.7950, p < 0.001), therapy with morphine vs. nalbuphine + paracetamol (RK: -1.2594, 95%CI: -1.5770 - -0.9418, p < 0.001) and traumatic vs. non-traumatic causes of pain (RK: -0.2952, 95%CI: -0.4879 - -0.1024, p = 0.002). Therapy with morphine (n = 34 (19.6%)) compared to nalbuphine + paracetamol (n = 796 (48.7%)) (odds ratio (OR): 0.274, 95%CI: 0.185-0.405, p < 0.001) and the initial NRS score (OR:0.827, 95%CI: 0.771-0.887, p < 0.001) reduced the odds of having an NRS < 4 at hospital handover. Complications occurred with morphine in n = 10 (5.8%) and with nalbuphine + paracetamol in n = 35 (2.1%) cases. Risk factors for complications were analgesia with morphine (OR: 2.690, 95%CI: 1.287-5.621, p = 0.008), female sex (OR: 2.024, 95%CI: 1.040-3.937, p = 0.0379), as well as age (OR: 1.018, 95%CI: 1.003-1.034, p = 0.02). CONCLUSIONS: Compared to morphine, prehospital analgesia with nalbuphine + paracetamol yields favourable effects in terms of analgesic effectiveness and a lower rate of complications and should therefore be considered in future recommendations for prehospital analgesia.

Prehospital anesthesia in postcardiac arrest patients: a multicenter retrospective cohort study.

BACKGROUND: Currently, the data regarding the impact of prehospital postcardiac arrest anesthesia on target hemodynamic and ventilatory parameters of early postresuscitation care and recommendations on its implementation are rare. The present study examines the incidence and impact of prehospital postcardiac arrest anesthesia on hemodynamic and ventilatory target parameters of postresuscitation care. METHODS: In this multicentre observational study between 2019 and 2021 unconscious adult patients after out-of-hospital-cardiac arrest with the presence of a return-of-spontaneous circulation until hospital admission were included. Primary endpoint was the application of postarrest anesthesia. Secondary endpoints included the medication group used, predisposing factors to its implementation, and its influence on achieving target parameters of postresuscitation care (systolic blood pressure: ≥ 100 mmHg, etCO2:35-45 mmHg, SpO2: 94-98%) at hospital handover. RESULTS: During the study period 2,335 out-of-hospital resuscitations out of 391,305 prehospital emergency operations (incidence: 0.58%; 95% CI 0.54-0.63) were observed with a return of spontaneous circulation to hospital admission in 706 patients (30.7%; 95% CI 28.8-32.6; female: 34.3%; age:68.3 ± 14.2 years). Postcardiac arrest anesthesia was performed in 482 patients (68.3%; 95% CI 64.7-71.7) with application of hypnotics in 93.4% (n = 451), analgesics in 53.7% (n = 259) and relaxants in 45.6% (n = 220). Factors influencing postcardiac arrest sedation were emergency care by an anesthetist (odds ratio: 2.10; 95% CI 1.34-3.30; P < 0.001) and treatment-free interval ≤ 5 min (odds ratio: 1.59; 95% CI 1.01-2.49; P = 0.04). Although there was no evidence of the impact of performing postcardiac arrest anesthesia on achieving a systolic blood pressure ≥ 100 mmHg at the end of operation (odds ratio: 1.14; 95% CI 0.78-1.68; P = 0.48), patients with postcardiac arrest anesthesia were significantly more likely to achieve the recommended ventilation (odds ratio: 1.59; 95% CI 1.06-2.40; P = 0.02) and oxygenation (odds ratio:1.56; 95% CI 1.04-2.35; P = 0.03) targets. Comparing the substance groups, the use of hypnotics significantly more often enabled the target values for etCO2 to be reached alone (odds ratio:2.79; 95% CI 1.04-7.50; P = 0.04) as well as in combination with a systolic blood pressure ≥ 100 mmHg (odds ratio:4.42; 95% CI 1.03-19.01; P = 0.04). CONCLUSIONS: Postcardiac arrest anesthesia in out-of-hospital cardiac arrest is associated with early achievement of respiratory target parameters in prehospital postresuscitation care without evidence of more frequent hemodynamic complications.

Effects of COVID-19 on a mature citizen first responder system in the German district of Gütersloh: an observational study.

BACKGROUND: The aim of this study was to examine the impact of COVID-19 on the response rate of community-first-responders (CFR) and other out-of-hospital-cardiac-arrest (OHCA) outcomes using the smartphone-first-responder-system (SFRS) "Mobile Retter." METHODS: All adult non-traumatic OHCA in the district of Gütersloh between 01.01.2018-31.12.2021 were included. Periods of interest were 1) prior to the first COVID-19-lockdown; to 2) both lockdowns; and 3) the time in between, as well as after the COVID-19-lockdowns (pre-COVID-19, COVID-19-lockdown and COVID-19-pandemic respectively). The primary outcome was the CFR response rate defined as proportion of CFR alerts that were accepted by a CFR and in which at least one CFR arrived on scene of the emergency out of all CFR alerts. Secondary outcomes included the rate of CFR alerts, defined as proportion of OHCA to which CFR were summoned by the emergency medical dispatcher, as well as the rate of return-of-spontaneous-circulation (ROSC) and rate of survival until hospital discharge. We also examined the incidence COVID-19-infection of CFR in context of the SFRS. RESULTS: A total of 1064 OHCA-patients (mean age: 71.4±14.5 years; female: 33.8%) were included in the study (Pre-COVID-19: 539; COVID-19-lockdown: 109; COVID-19-pandemic: 416). The response rate was 64.0% (pre-COVID-19: 58.7%; COVID-19-lockdown: 63.5%; COVID-19-pandemic: 71.8%, P=0.002 vs. pre-COVID-19). The alert rate was 52.7% (pre-COVID-19: 56.2%; COVID-19-lockdown: 47.7%, P=0.04 vs. Pre-COVID-19; COVID-19-Pandemic: 49.5%, P=0.02 vs. pre-COVID-19). The ROSC-rate was 40.4% (pre-COVID-19: 41.0%; COVID-19-lockdown: 33.9%; COVID-19-pandemic: 41.4%) and hospital discharge rate 31.2% (Pre-COVID-19: 33.0%; COVID-19-lockdown: 36.8%; COVID-19-pandemic: 28.7%). The use of CFR was associated with favorable effects in terms of hospital admission (odds ratio [OR]: 0.654 (CI95: 0.444-0.963), P=0.03), hospital discharge (OR: 2.343 (CI95: 1.002-5.475), P=0.04). None of the CFR became infected with COVID-19. CONCLUSIONS: "Mobile-Retter" was associated with high response rates, improved outcome in OHCA patients and no COVID-19-infections of CFR during the COVID-19-pandemic and -lockdowns.

A parametric additive hazard model for time-to-event analysis.

BACKGROUND: In recent years, the use of non- and semi-parametric models which estimate hazard ratios for analysing time-to-event outcomes is continuously criticized in terms of interpretation, technical implementation, and flexibility. Hazard ratios in particular are critically discussed for their misleading interpretation as relative risks and their non-collapsibility. Additive hazard models do not have these drawbacks but are rarely used because they assume a non- or semi-parametric additive hazard which renders computation and interpretation complicated. METHODS: As a remedy, we propose a new parametric additive hazard model that allows results to be reported on the original time rather than on the hazard scale. Being an essentially parametric model, survival, hazard and probability density functions are directly available. Parameter estimation is straightforward by maximizing the log-likelihood function. RESULTS: Applying the model to different parametric distributions in a simulation study and in an exemplary application using data from a study investigating medical care to lung cancer patients, we show that the approach works well in practice. CONCLUSIONS: Our proposed parametric additive hazard model can serve as a powerful tool to analyze time-to-event outcomes due to its simple interpretation, flexibility and facilitated parameter estimation.

Association of plasma proteomics with incident coronary heart disease in individuals with and without type 2 diabetes: results from the population-based KORA study.

BACKGROUND: Coronary heart disease (CHD) is a major global health concern, especially among individuals with type 2 diabetes (T2D). Given the crucial role of proteins in various biological processes, this study aimed to elucidate the aetiological role and predictive performance of protein biomarkers on incident CHD in individuals with and without T2D. METHODS: The discovery cohort included 1492 participants from the Cooperative Health Research in the Region of Augsburg (KORA) S4 study with 147 incident CHD cases (45 vs. 102 cases in the group with T2D and without T2D, respectively) during 15.6 years of follow-up. The validation cohort included 888 participants from the KORA-Age1 study with 70 incident CHD cases (19 vs. 51 cases in the group with T2D and without T2D, respectively) during 6.9 years of follow-up. We measured 233 plasma proteins related to cardiovascular disease and inflammation using proximity extension assay technology. Associations of proteins with incident CHD were assessed using Cox regression and Mendelian randomization (MR) analysis. Predictive models were developed using priority-Lasso and were evaluated on top of Framingham risk score variables using the C-index, category-free net reclassification index (cfNRI), and relative integrated discrimination improvement (IDI). RESULTS: We identified two proteins associated with incident CHD in individuals with and 29 in those without baseline T2D, respectively. Six of these proteins are novel candidates for incident CHD. MR suggested a potential causal role for hepatocyte growth factor in CHD development. The developed four-protein-enriched model for individuals with baseline T2D (ΔC-index: 0.017; cfNRI: 0.253; IDI: 0.051) and the 12-protein-enriched model for individuals without baseline T2D (ΔC-index: 0.054; cfNRI: 0.462; IDI: 0.024) consistently improved CHD prediction in the discovery cohort, while in the validation cohort, significant improvements were only observed for selected performance measures (with T2D: cfNRI: 0.633; without T2D: ΔC-index: 0.038; cfNRI: 0.465). CONCLUSIONS: This study identified novel protein biomarkers associated with incident CHD in individuals with and without T2D and reaffirmed previously reported protein candidates. These findings enhance our understanding of CHD pathophysiology and provide potential targets for prevention and treatment.

Estimation of mortality rate ratios for chronic conditions with misclassification of disease status at death.

Estimation of mortality rates and mortality rate ratios (MRR) of diseased and non-diseased individuals is a core metric of disease impact used in chronic disease epidemiology. Estimation of mortality rates is often conducted through retrospective linkage of information from nationwide surveys such as the National Health Interview Survey (NHIS) and death registries. These surveys usually collect information on disease status during only one study visit. This infrequency leads to missing disease information (with right censored survival times) for deceased individuals who were disease-free at study participation, and a possibly biased estimation of the MRR because of possible undetected disease onset after study participation. This occurrence is called "misclassification of disease status at death (MicDaD)" and it is a potentially common source of bias in epidemiologic studies. In this study, we conducted a simulation analysis with a high and a low incidence setting to assess the extent of MicDaD-bias in the estimated mortality. For the simulated populations, MRR for diseased and non-diseased individuals with and without MicDaD were calculated and compared. Magnitude of MicDaD-bias depends on and is driven by the incidence of the chronic disease under consideration; our analysis revealed a noticeable shift towards underestimation for high incidences when MicDaD is present. Impact of MicDaD was smaller for lower incidence (but associated with greater uncertainty in the estimation of MRR in general). Further research can consider the amount of missing information and potential influencers such as duration and risk factors of the disease.

Midazolam for Post-Arrest Sedation in Pre-Hospital Emergency Care­a Multicenter Propensity Score Analysis.

BACKGROUND: An out-of-hospital cardiac arrest (OHCA) with return of spontaneous circulation (ROSC) may need to be treated with airway management, emergency ventilation, invasive interventions, and post-arrest sedation. We investigated the influence of the use of midazolam for post-arrest sedation on achieving post-resuscitation care targets and the associated risk of hemodynamic complications. METHODS: All emergency rescue missions of the Dresden, Gütersloh, and Lippe medical rescue services in the years 2019-2021 were reviewed to identify adult patients who had OHCA, unconsciousness, and sustained ROSC with spontaneous circulation until arrival at the hospital; the findings were supplemented with data from the German Resuscitation Registry. Patients who received midazolam (alone or in combination with other anesthetic agents) for post-arrest sedation were compared with those who did not. The endpoints were the regaining of a systolic blood pressure ≥ 100 mmHg, end-tidal pCO2 35-45 mmHg, and oxygen saturation (SpO2) 94-98%. A propensity score analysis was used to adjust for age, sex, and variables potentially affecting hemodynamic status or the targets for oxygenation and ventilation. RESULTS: There were 2335 cases of OHCA among 391 305 emergency rescue missions. 571 patients had ROSC before arrival in the hospital (24.5%; female, 33.6%; age, 68 ± 14 years). Of the 395 among them (69.2%) who were treated with post-arrest sedation, 249 (63.0%) received midazolam. Patients who received midazolam reached the guideline-recommended targets for oxygenation, ventilation, and blood pressure more frequently than those who were not sedated: the respective odds ratios and 95% confidence intervals were 2.00 [1.20; 3.34], 1.57 [0.99; 2.48], and 1.41 [0.89; 2.21]. CONCLUSION: The pre-hospital administration of midazolam leads to more frequent pre-hospital attainment of the oxygenation and ventilation targets in post-resuscitation care, without any evidence of an elevated risk of hemodynamic complications.

Prolonged mHealth-Based Arrhythmia Monitoring in Patients With Hypertrophic Cardiomyopathy (HCM-PATCH): Protocol for a Single-Center Cohort Study.

BACKGROUND: Patients with hypertrophic cardiomyopathy (HCM) are at increased risk of sudden cardiac death (SCD) due to ventricular arrhythmias and other arrhythmias. Screening for arrhythmias is mandatory to assess the individual SCD risk, but long-term electrocardiography (ECG) is rarely performed in routine clinical practice. Intensified monitoring may increase the detection rate of ventricular arrhythmias and identify more patients with an increased SCD risk who are potential candidates for the primary prophylactic implantation of an implantable cardioverter-defibrillator. To date, reliable data on the clinical benefit of prolonged arrhythmia monitoring in patients with HCM are rare. OBJECTIVE: This prospective study aims to measure the prevalence of ventricular arrhythmias in patients with HCM observed by mobile health (mHealth)-based continuous rhythm monitoring over 14 days compared to standard practice (a 24- and 48-h long-term ECG). The frequency of ventricular arrhythmias in this 14-day period is compared with the frequency in the first 24 or 48 hours for the same patient (intraindividual comparison). METHODS: Following the sample size calculation, 34 patients with a low or intermediate risk for SCD, assessed by the HCM Risk-SCD calculator, will need to be recruited in this single-center cohort study between June 2023 and February 2024. All patients will receive an ECG patch that records their heart activity over 14 days. In addition, cardiac magnetic resonance imaging and genetic testing data will be integrated into risk stratification. All patients will be asked to complete questionnaires about their symptoms; previous therapy; family history; and, at the end of the study, their experience with the ECG patch-based monitoring. RESULTS: The Hypertrophic Cardiomyopathy: Clinical Impact of a Prolonged mHealth-Based Arrhythmia Monitoring by Single-Channel ECG (HCM-PATCH) study investigates the prevalence of nonsustained ventricular tachycardia (ie, ≥3 consecutive ventricular beats at a rate of 120 beats per minute, lasting for <30 seconds) in low- to intermediate-risk patients with HCM (according to the HCM Risk-SCD calculator) with additional mHealth-based prolonged rhythm monitoring. The study was funded by third-party funding from the Department of Cardiology and Intensive Care Medicine, University Hospital Ostwestfalen-Lippe of Bielefeld University in June 2023 and approved by the institutional review board in May 2023. Data collection began in June 2023, and we plan to end the study in February 2024. Of the 34 patients, 26 have been recruited. Data analysis has not yet taken place. Publication of the results is planned for the fall of 2024. CONCLUSIONS: Prolonged mHealth-based rhythm monitoring could lead to differences in the prevalence of arrhythmias compared to 24- and 48-hour long-term ECGs. This may lead to improved identification of patients at high risk and trigger therapeutic interventions that may provide better protection from SCD or atrial fibrillation-related complications such as embolic stroke. TRIAL REGISTRATION: Deutsches Register Klinischer Studien DRKS00032144; https://tinyurl.com/498bkrx8. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/52035.

Effectiveness and safety of prehospital analgesia including nalbuphine and paracetamol by paramedics: an observational study.

BACKGROUND: The aim of this study was to examine the effectiveness and safety of prehospital analgesia with nalbuphine and/or paracetamol by paramedics. METHODS: In this retrospective trial, following the implementation of a standard-operating-procedure for pain requiring treatment as defined as a score ≥4 on the 0-10 Numeric Rating Scale for pain, all emergency operations in the district of Gütersloh between January 1, 2020, and June 30, 2022, with analgesic administration by paramedics in patients ≥18 years were included in the study. Analgesic agents employed by the paramedics included nalbuphine and/or paracetamol, butylscopolamine for abdominal colic, and esketamine in case of failure of the other analgesics. The primary endpoint was the patients' rating of their pain on the Numeric Rating Scale at the end of the operation. Additional covariates included sex, cause of pain, analgesics used, Numeric Rating Scale at beginning and analgesic-associated complications (reduced level of consciousness, hypotension, desaturation, a- or bradypnea). RESULTS: A total of 1931 emergency operations (female: N.=1039 [53.8%]) with pain requiring treatment (non-traumatic cause: N.=1106 [57.3%]; initial Numeric Rating Scale: 8.0±1.4). Analgesics applied were nalbuphine + paracetamol (50.6%), paracetamol (38.7%), butylscopolamine (13.4%), nalbuphine (7.7%), and esketamine (4.9%). Mean pain reduction was 4.3±2.3 (nalbuphine + paracetamol: 5.0±2.1; nalbuphine: 4.7±2.3) and paracetamol: 3.3±2.2, respectively. Factors influencing a change in the Numeric Rating Scale were trauma (regression-coefficient: -0.308, 95% CI: -0.496 - -0.119, P=0.0014 vs. non-trauma; nalbuphine [yes vs. no]: regression-coefficient 0.684, 95% CI 0.0774-1.291, P=0.03; nalbuphine + paracetamol: regression-coefficient 0.763, 95% CI 0.227-1.299, P=0.005). At the end of the operation, 49.7% had a Numeric Rating Scale <4, 34.3% had a Numeric Rating Scale 4-5, and 16.0% had a Numeric Rating Scale ≥6. Factors influencing a Numeric Rating Scale <4 at end of use were trauma vs. non-trauma: odds ratio 0.788, 95% CI 0.649-0.957, P=0.02. The Numeric Rating Scale at beginning reported: odds ratios 0.754, 95% CI 0.700-0.812, P<0.0001. Analgesic-associated complications were not observed. CONCLUSIONS: Prehospital analgesia by paramedics with nalbuphine as monotherapy or in combination with paracetamol allows for sufficient analgesia without the occurrence of complications.

Explanted Skull Flaps after Decompressive Hemicraniectomy Demonstrate Relevant Bone Avitality-Is Their Reimplantation Worth the Risk?

BACKGROUND: Reimplantations of autologous skull flaps after decompressive hemicraniectomies (DHs) are associated with high rates of postoperative bone flap resorption (BFR). We histologically assessed the cell viability of explanted bone flaps in certain periods of time after DH, in order to conclude whether precursors of BRF may be developed during their storage. METHODS: Skull bone flaps explanted during a DH between 2019 and 2020 were stored in a freezer at either -23 °C or -80 °C. After their thawing process, the skulls were collected. Parameters of bone metabolism, namely PTH1 and OPG, were analyzed via immunohistochemistry. H&E stain was used to assess the degree of avital bone tissue, whereas the repeated assays were performed after 6 months. RESULTS: A total of 17 stored skull flaps (8 at -23 °C; 9 at -80 °C) were analyzed. The duration of cryopreservation varied between 2 and 17 months. A relevant degree of bone avitality was observed in all skull flaps, which significantly increased at the repeated evaluation after 6 months (p < 0.001). Preservation at -23 °C (p = 0.006) as well as longer storage times (p < 0.001) were identified as prognostic factors for higher rates of bone avitality in a linear mixed regression model. CONCLUSIONS: Our novel finding shows a clear benefit from storage at -80° C, which should be carefully considered for the future management and storage of explanted skull flaps. Our analysis also further revealed a significant degree of bone avitality, a potential precursor of BFR, in skull flaps stored for several weeks. To this end, we should reconsider whether the reimplantation of autologous skull flaps instead of synthetic skull flaps is still justified.

Associations of plasma proteomics with type 2 diabetes and related traits: results from the longitudinal KORA S4/F4/FF4 Study.

AIMS/HYPOTHESIS: This study aimed to elucidate the aetiological role of plasma proteins in glucose metabolism and type 2 diabetes development. METHODS: We measured 233 proteins at baseline in 1653 participants from the Cooperative Health Research in the Region of Augsburg (KORA) S4 cohort study (median follow-up time: 13.5 years). We used logistic regression in the cross-sectional analysis (n=1300), and Cox regression accounting for interval-censored data in the longitudinal analysis (n=1143). We further applied two-level growth models to investigate associations with repeatedly measured traits (fasting glucose, 2 h glucose, fasting insulin, HOMA-B, HOMA-IR, HbA1c), and two-sample Mendelian randomisation analysis to investigate causal associations. Moreover, we built prediction models using priority-Lasso on top of Framingham-Offspring Risk Score components and evaluated the prediction accuracy through AUC. RESULTS: We identified 14, 24 and four proteins associated with prevalent prediabetes (i.e. impaired glucose tolerance and/or impaired fasting glucose), prevalent newly diagnosed type 2 diabetes and incident type 2 diabetes, respectively (28 overlapping proteins). Of these, IL-17D, IL-18 receptor 1, carbonic anhydrase-5A, IL-1 receptor type 2 (IL-1RT2) and matrix extracellular phosphoglycoprotein were novel candidates. IGF binding protein 2 (IGFBP2), lipoprotein lipase (LPL) and paraoxonase 3 (PON3) were inversely associated while fibroblast growth factor 21 was positively associated with incident type 2 diabetes. LPL was longitudinally linked with change in glucose-related traits, while IGFBP2 and PON3 were linked with changes in both insulin- and glucose-related traits. Mendelian randomisation analysis suggested causal effects of LPL on type 2 diabetes and fasting insulin. The simultaneous addition of 12 priority-Lasso-selected biomarkers (IGFBP2, IL-18, IL-17D, complement component C1q receptor, V-set and immunoglobulin domain-containing protein 2, IL-1RT2, LPL, CUB domain-containing protein 1, vascular endothelial growth factor D, PON3, C-C motif chemokine 4 and tartrate-resistant acid phosphatase type 5) significantly improved the predictive performance (ΔAUC 0.0219; 95% CI 0.0052, 0.0624). CONCLUSIONS/INTERPRETATION: We identified new candidates involved in the development of derangements in glucose metabolism and type 2 diabetes and confirmed previously reported proteins. Our findings underscore the importance of proteins in the pathogenesis of type 2 diabetes and the identified putative proteins can function as potential pharmacological targets for diabetes treatment and prevention.

How amenable is type 2 diabetes treatment for precision diabetology? A meta-regression of glycaemic control data from 174 randomised trials.

AIMS/HYPOTHESIS: There are two prerequisites for the precision medicine approach to be beneficial for treated individuals. First, there must be treatment heterogeneity; second, in the case of treatment heterogeneity, we need to detect clinical predictors to identify people who would benefit from one treatment more than from others. There is an established meta-regression approach to assess these two prerequisites that relies on measuring the variability of a clinical outcome after treatment in placebo-controlled randomised trials. Our aim was to apply this approach to the treatment of type 2 diabetes. METHODS: We performed a meta-regression analysis using information from 174 placebo-controlled randomised trials with 178 placebo and 272 verum (i.e. active treatment) arms including 86,940 participants with respect to the variability of glycaemic control as assessed by HbA1c after treatment and its potential predictors. RESULTS: The adjusted difference in log(SD) values between the verum and placebo arms was 0.037 (95% CI: 0.004, 0.069). That is, we found a small increase in the variability of HbA1c values after treatment in the verum arms. In addition, one potentially relevant predictor for explaining this increase, drug class, was observed, and GLP-1 receptor agonists yielded the largest differences in log(SD) values. CONCLUSIONS/INTERPRETATION: The potential of the precision medicine approach in the treatment of type 2 diabetes is modest at best, at least with regard to an improvement in glycaemic control. Our finding of a larger variability after treatment with GLP-1 receptor agonists in individuals with poor glycaemic control should be replicated and/or validated with other clinical outcomes and with different study designs. FUNDING: The research reported here received no specific grant from any funding agency in the public, commercial or not-for-profit sectors. DATA AVAILABILITY: Two datasets (one for the log[SD] and one for the baseline-corrected log[SD]) to reproduce the analyses from this paper are available on https://zenodo.org/record/7956635 .

Virus variant-specific clinical performance of a SARS-CoV-2 rapid antigen test with focus on Omicron variants of concern.

OBJECTIVES: Antigen rapid diagnostic tests (Ag-RDTs) play an important role in the diagnosis of SARS-CoV-2. They are easier, quicker, and less expensive than the 'reference standard' RT-PCR and therefore widely in use. Reliable clinical data with respect to Ag-RDT performance in SARS-CoV-2 Omicron variants of concern (VOCs) are limited. Consequently, the objective of this study was to determine the impact different VOCs-especially Omicron-have on the clinical performance of an Ag-RDT. METHODS: We compared the clinical performance of the Sofia SARS-CoV-2 Ag-RDT to RT-PCR in a real-world, single-centre study in a clinical point-of-care setting in patients admitted to a large hospital via the emergency department from 2 November 2020 to 4 September 2022. RESULTS: Among 38 434 Ag-RDT/RT-PCR tandems taken, 1528 yielded a SARS-CoV-2 positive RT-PCR test result, with a prevalence of 4.0% (95% CI, 3.8-4.2). Overall sensitivity of the Ag-RDT was 63.7% (95% CI, 61.3-66.1) and overall specificity was 99.6% (95% CI, 99.5-99.6). Ag-RDT sensitivity was dependent on viral load (VL), because the sensitivity increased to 93.2% (95% CI, 91.5-94.6) in samples with a VL > 106 SARS-CoV-2 copies/mL. Furthermore, the Ag-RDT was more sensitive in men, and older patients. Variant-dependent sensitivity assessment showed that the sensitivity was significantly lower in Omicron-VOC (64.1%; 95% CI, 60.5-67.6) compared with SARS-CoV-2 wild-type samples (70.0%; 95% CI, 59,8-78,6) (binomial test; p value < 0.001). Analysing the limits of detection showed a 27 times higher 95% limit of detection for the Omicron-VOC BA.5 compared with the SARS-CoV-2 wild-type. DISCUSSION: Ag-RDT sensitivity for detection of patients with lower VLs and with Omicron-VOC is reduced, limiting the effectiveness of Ag-RDTs. However, Ag-RDTs are still an unreplaceable tool for widely available, quick, and inexpensive point-of-care SARS-CoV-2 diagnostics.

Future number of people with diagnosed type 1 diabetes in Germany until 2040: an analysis based on claims data.

INTRODUCTION: We aim to project the number of people with diagnosed type 1 diabetes in Germany between 2010 and 2040. RESEARCH DESIGN AND METHODS: We first estimate the age-specific and sex-specific incidence and prevalence of type 1 diabetes in Germany in 2010 using data from 65 million insurees of the German statutory health insurance. Then, we use the illness-death model to project the prevalence of type 1 diabetes until 2040. We alter the incidence and mortality underlying the illness-death model in several scenarios to explore the impact of possible temporal trends on the number of people with type 1 diabetes. RESULTS: Applying the prevalence from 2010 to the official population projections of Germany's Federal Statistical Office yields a total number of 252 000 people with type 1 diabetes in Germany in 2040 (+1% compared with 2010). Incorporating different annual trends of the incidence and mortality in the projection model results in a future number of people with type 1 diabetes between 292 000 (+18%) and 327 000 (+32%). CONCLUSIONS: For the first time in Germany, we provide estimates for the incidence, prevalence, and number of people with diagnosed type 1 diabetes for the whole German population between 2010 and 2040. The relative increase of the people with type 1 diabetes ranges from 1% to 32% in 2040 compared with 2010. The projected results are mainly influenced by temporal trends in the incidence. Ignoring these trends, that is, applying a constant prevalence to population projections, probably underestimates future chronic disease numbers.

Age-specific incidence of need for long-term care for men and women in Germany 2015: Cross-sectional study comprising 82 million people.

Background: With the growing number of older people, the number of people in need of long-term care is increasing, too. Official statistics only report on the age-specific prevalence of long-term care. Therefore, there is no data on the age- and sex-specific incidence of the need for care at the population level for Germany available. Methods: Analytical relationships between age-specific prevalence, incidence rate, remission rate, all-cause mortality, and mortality rate ratio are used to estimate the age-specific incidence of long-term care among men and women in 2015. The data is based on the official prevalence data from the nursing care statistics for the years 2011 to 2019 and official mortality rates from the Federal Statistical Office. For Germany, there is no data on the mortality rate ratio of people with and without a need for care, which is why we use two extreme scenarios that were obtained in a systematic literature search to estimate the incidence. Results: The age-specific incidence is about 1 per 1000 person-years (PY) in men and women at the age of 50 and increases exponentially up to the age of 90. Up to about the age of 60, men have a higher incidence rate than women. Thereafter, women have a higher incidence. At the age of 90, women and men have an incidence rate of 145 to 200 and 94 to 153 per 1000 PY, respectively, depending on the scenario. Conclusion: We estimated the age-specific incidence of the need for long-term care for women and men in Germany for the first time. We observed a strong increase, leading to a huge number of people in need of long-term care in higher age groups. It is to be expected that this will result in an increased economic burden and a further increased need for nursing and medical staff.

Estimating incidence of type 1 and type 2 diabetes using prevalence data: the SEARCH for Diabetes in Youth study.

BACKGROUND: Incidence is one of the most important epidemiologic indices in surveillance. However, determining incidence is complex and requires time-consuming cohort studies or registries with date of diagnosis. Estimating incidence from prevalence using mathematical relationships may facilitate surveillance efforts. The aim of this study was to examine whether a partial differential equation (PDE) can be used to estimate diabetes incidence from prevalence in youth. METHODS: We used age-, sex-, and race/ethnicity-specific estimates of prevalence in 2001 and 2009 as reported in the SEARCH for Diabetes in Youth study. Using these data, a PDE was applied to estimate the average incidence rates of type 1 and type 2 diabetes for the period between 2001 and 2009. Estimates were compared to annual incidence rates observed in SEARCH. Precision of the estimates was evaluated using 95% bootstrap confidence intervals. RESULTS: Despite the long period between prevalence measures, the estimated average incidence rates mirror the average of the observed annual incidence rates. Absolute values of the age-standardized sex- and type-specific mean relative errors are below 8%. CONCLUSIONS: Incidence of diabetes can be accurately estimated from prevalence. Since only cross-sectional prevalence data is required, employing this methodology in future studies may result in considerable cost savings.

Spatio-Temporal Trends in the Incidence of Type 2 Diabetes in Germany.

BACKGROUND: There are no data on recent trends in the incidence rate of type 2 diabetes (T2D) in Germany. The aim of this study was to determine the sex-, age-, and region-specific trends in the T2D incidence rate between 2014 and 2019. METHODS: Based on nationwide data from statutorily insured persons in Germany, negative binomial regression models were used to analyze age- and sex-specific trends in the T2D incidence rate. Age- and sex-adjusted trends were calculated for 401 administrative districts using a Bayesian spatio-temporal regression model. RESULTS: During the period concerned, approximately 450 000 new cases of T2D were observed each year among some 63 million persons. Taking all age groups together, the incidence rate decreased in both women and men, from 6.9 (95% confidence interval [6.7; 7.0]) and 8.4 [8.2; 8.6] respectively per 1000 persons in 2014 to 6.1 [5.9; 6.3] and 7.7 [7.5; 8.0] per 1000 persons in 2019. This corresponds to an annual reduction of 2.4% [1.5; 3.2] for women and 1.7% [0.8; 2.5] for men. The incidence rate increased in the age group 20-39 years. The age- and sex-adjusted incidence rate decreased in almost all districts, although regional differences persisted. CONCLUSION: The T2D incidence rate should be closely monitored to see whether the decreasing trend continues. One must not forget that the prevalence can rise despite decreasing incidence. For this reason, the findings do not necessarily mean a decrease in the disease burden of T2D and the associated demand on healthcare resources.

Projections of Type 1 and Type 2 Diabetes Burden in the U.S. Population Aged <20 Years Through 2060: The SEARCH for Diabetes in Youth Study.

OBJECTIVE: To project the prevalence and number of youths with diabetes and trends in racial and ethnic disparities in the U.S. through 2060. RESEARCH DESIGN AND METHODS: Based on a mathematical model and data from the SEARCH for Diabetes in Youth study for calendar years 2002-2017, we projected the future prevalence of type 1 and type 2 diabetes among youth aged <20 years while considering different scenarios of future trends in incidence. RESULTS: The number of youths with diabetes will increase from 213,000 (95% CI 209,000; 218,000) (type 1 diabetes 185,000, type 2 diabetes 28,000) in 2017 to 239,000 (95% CI 209,000; 282,000) (type 1 diabetes 191,000, type 2 diabetes 48,000) in 2060 if the incidence remains constant as observed in 2017. Corresponding relative increases were 3% (95% CI -9%; 21%) for type 1 diabetes and 69% (95% CI 43%; 109%) for type 2 diabetes. Assuming that increasing trends in incidence observed between 2002 and 2017 continue, the projected number of youths with diabetes will be 526,000 (95% CI 335,000; 893,000) (type 1 diabetes 306,000, type 2 diabetes 220,000). Corresponding relative increases would be 65% (95% CI 12%; 158%) for type 1 diabetes and 673% (95% CI 362%; 1,341%) for type 2 diabetes. In both scenarios, substantial widening of racial and ethnic disparities in type 2 diabetes prevalence are expected, with the highest prevalence among non-Hispanic Black youth. CONCLUSIONS: The number of youths with diabetes in the U.S. is likely to substantially increase in future decades, which emphasizes the need for prevention to attenuate this trend.

Epidemiological measures for assessing the dynamics of the SARS-CoV-2-outbreak: Simulation study about bias by incomplete case-detection.

During the SARS-CoV-2 outbreak, several epidemiological measures, such as cumulative case-counts (CCC), incidence rates, effective reproduction numbers (Reff) and doubling times, have been used to inform the general public and to justify interventions such as lockdown. It has been very likely that not all infectious people have been identified during the course of the epidemic, which lead to incomplete case-detection. We compare CCC, incidence rates, Reff and doubling times in the presence of incomplete case-detection. For this, an infection-age-structured SIR model is used to simulate a SARS-CoV-2 outbreak followed by a lockdown in a hypothetical population. Different scenarios about temporal variations in case-detection are applied to the four measures during outbreak and lockdown. The biases resulting from incomplete case-detection on the four measures are compared in terms of relative errors. CCC is most prone to bias by incomplete case-detection in all of our settings. Reff is the least biased measure. The possibly biased CCC may lead to erroneous conclusions in cross-country comparisons. With a view to future reporting about this or other epidemics, we recommend including and placing an emphasis on Reff in those epidemiological measures used for informing the general public and policy makers.