Association between Glucagon-like Peptide-1 Receptor Agonists and the Risk of Glaucoma in Individuals with Type 2 Diabetes.

PURPOSE: To examine the association between glucagon-like peptide-1 receptor agonist (GLP-1RA) use and the development of glaucoma in individuals with type 2 diabetes. DESIGN: Nationwide, nested case-control study. PARTICIPANTS: From a nationwide cohort of 264 708 individuals, we identified 1737 incident glaucoma cases and matched them to 8685 glaucoma-free controls, all aged more than 21 years and treated with metformin and a second-line antihyperglycemic drug formulation, with no history of glaucoma, eye trauma, or eye surgery. METHODS: Cases were incidence-density-matched to 5 controls by birth year, sex, and date of second-line treatment initiation. MAIN OUTCOME MEASURES: Conditional logistic regression was used to calculate adjusted hazard ratios (HRs) with 95% confidence intervals (CIs) for glaucoma, defined by first-time diagnosis, first-time use of glaucoma-specific medication, or first-time glaucoma-specific surgical intervention. RESULTS: Compared with the reference group, who received treatments other than GLP-1RA, individuals who were exposed to GLP-1RA treatment exhibited a lower risk of incident glaucoma (HR, 0.81; CI, 0.70-0.94; P = 0.006). Prolonged treatment extending beyond 3 years lowered the risk even further (HR, 0.71; CI, 0.55-0.91; P = 0.007). Treatment with GLP-1RA for 0 to 1 year (HR, 0.89; CI, 0.70-1.14; P = 0.35) and 1 to 3 years (HR, 0.85; CI, 0.67-1.06; P = 0.15) was not significant. CONCLUSIONS: Exposure to GLP-1RA was associated with a lower risk of developing glaucoma compared with receiving other second-line antihyperglycemic medication. FINANCIAL DISCLOSURE(S): Proprietary or commercial disclosure may be found after the references.

Prodromal complaints and 30-day survival after emergency medical services-witnessed out-of-hospital cardiac arrest.

BACKGROUND: Out-of-hospital cardiac arrest (OHCA) is a frequent and lethal condition with a yearly incidence of approximately 5000 in Denmark. Thirty-day survival is associated with the patient's prodromal complaints prior to cardiac arrest. This paper examines the odds of 30-day survival dependent on the reported prodromal complaints among OHCAs witnessed by the emergency medical services (EMS). METHODS: EMS-witnessed OHCAs in the Capital Region of Denmark from 2016-2018 were included. Calls to the emergency number 1-1-2 and the medical helpline for out-of-hours were analyzed according to the Danish Index; data regarding the OHCA was collected from the Danish Cardiac Arrest Registry. We performed multiple logistic regression to calculate the odds ratio (OR) of 30-day survival with adjustment for sex and age. RESULTS: We identified 311 eligible OHCAs of which 79 (25.4%) survived. The most commonly reported complaints were dyspnea (n = 209, OR 0.79 [95% CI 0.46: 1.36]) and 'feeling generally unwell' (n = 185, OR 1.07 [95% CI 0.63: 1.81]). Chest pain (OR 9.16 [95% CI 5.09:16.9]) and heart palpitations (OR 3.15 [95% CI 1.07:9.46]) had the highest ORs, indicating favorable odds for 30-day survival, while unresponsiveness (OR 0.22 [95% CI 0.11:0.43]) and blue skin or lips (OR 0.30, 95% CI 0.09, 0.81) had the lowest, indicating lesser odds of 30-day survival. CONCLUSION: Experiencing chest pain or heart palpitations prior to EMS-witnessed OHCA was associated with higher 30-day survival. Conversely, complaints of unresponsiveness or having blue skin or lips implied reduced odds of 30-day survival.

Association between mortality and phone-line waiting time for non-urgent medical care: a Danish registry-based cohort study.

BACKGROUND AND IMPORTANCE: Telephone calls are often patients' first healthcare service contact, outcomes associated with waiting times are unknown. OBJECTIVES: Examine the association between waiting time to answer for a medical helpline and 1- and 30-day mortality. DESIGN, SETTING AND PARTICIPANTS: Registry-based cohort study using phone calls data (January 2014 to December 2018) to the Capital Region of Denmark's medical helpline. The service refers to hospital assessment/treatment, dispatches ambulances, or suggests self-care guidance. EXPOSURE: Waiting time was grouped into the following time intervals in accordance with political service targets for waiting time in the Capital Region: <30 s, 0:30-2:59, 3-9:59, and ≥10 min. OUTCOME MEASURES AND ANALYSIS: The association between time intervals and 1- and 30-day mortality per call was calculated using logistic regression with strata defined by age and sex. MAIN RESULTS: In total, 1 244 252 callers were included, phoning 3 956 243 times, and 78% of calls waited <10 min. Among callers, 30-day mortality was 1% (16 560 deaths). For calls by females aged 85-110 30-day mortality increased with longer waiting time, particularly within the first minute: 9.6% for waiting time <30 s, 10.8% between 30 s and 1 minute and 9.1% between 1 and 2 minutes. For calls by males aged 85-110 30-day mortality was 11.1%, 12.9% and 11.1%, respectively. Additionally, among calls with a Charlson score of 2 or higher, longer waiting times were likewise associated with increased mortality. For calls by females aged 85-110 30-day mortality was 11.6% for waiting time <30 s, 12.9% between 30 s and 1 minute and 11.2% between 1 and 2 minutes. For calls by males aged 85-110 30-day mortality was 12.7%, 14.1% and 12.6%, respectively. Fewer ambulances were dispatched with longer waiting times (4%/2%) with waiting times <30 s and >10 min. CONCLUSION: Longer waiting times for telephone contact to a medical helpline were associated with increased 1- and 30-day mortality within the first minute, especially among elderly or more comorbid callers.

Usefulness of Heat Map Explanations for Deep-Learning-Based Electrocardiogram Analysis.

Deep neural networks are complex machine learning models that have shown promising results in analyzing high-dimensional data such as those collected from medical examinations. Such models have the potential to provide fast and accurate medical diagnoses. However, the high complexity makes deep neural networks and their predictions difficult to understand. Providing model explanations can be a way of increasing the understanding of "black box" models and building trust. In this work, we applied transfer learning to develop a deep neural network to predict sex from electrocardiograms. Using the visual explanation method Grad-CAM, heat maps were generated from the model in order to understand how it makes predictions. To evaluate the usefulness of the heat maps and determine if the heat maps identified electrocardiogram features that could be recognized to discriminate sex, medical doctors provided feedback. Based on the feedback, we concluded that, in our setting, this mode of explainable artificial intelligence does not provide meaningful information to medical doctors and is not useful in the clinic. Our results indicate that improved explanation techniques that are tailored to medical data should be developed before deep neural networks can be applied in the clinic for diagnostic purposes.

"I just haven't experienced anything like this before": A qualitative exploration of callers' interpretation of experienced conditions in telephone consultations preceding a myocardial infarction.

OBJECTIVES: Callers with myocardial infarction presenting atypical symptoms in telephone consultations when calling out-of-hours medical services risk misrecognition. We investigated characteristics in callers' interpretation of experienced conditions through communication with call-takers. METHODS: Recording of calls resulting in not having an ambulance dispatched for 21 callers who contacted a non-emergency medical helpline, Copenhagen (Denmark), up to one week before they were diagnosed with myocardial infarction. Qualitative content analysis was applied. RESULTS: Awareness of illness, remedial actions and previous experiences contributed to callers' interpretation of the experienced condition. Unclear symptoms resulted in callers reacting to their interpretation by being unsure and worried. Negotiation of the interpretation was seen when callers tested the call-taker's interpretation of the condition and when either caller or call-taker suggested: "wait and see". CONCLUSION: Callers sought to interpret the experienced conditions but faced challenges when the conditions appeared unclear and did not correspond to the health system's understanding of symptoms associated with myocardial infarction. It affected the communicative interaction with the call-taker and influenced the call-taker's choice of response. PRACTICE IMPLICATIONS: Call-takers, as part of the decision-making process, could ask further questions about the caller's insecurity and worry. It might facilitate faster recognition of conditions warranting hospital referral.

Registered prodromal symptoms of out-of-hospital cardiac arrest among patients calling the medical helpline services.

Background Early identification of warning symptoms among out-of-hospital cardiac arrest (OHCA) patients remains challenging. Thus, we examined the registered prodromal symptoms of patients who called medical helpline services within 30-days before OHCA. Methods Patients unwitnessed by emergency medical services (EMS) aged ≥18 years during their OHCA were identified from the Danish Cardiac Arrest Registry (2014-2018) and linked to phone records from the 24-h emergency helpline (1-1-2) and out-of-hours medical helpline (1813-Medical Helpline) in Copenhagen before the arrest. The registered symptoms were categorized into chest pain; breathing problems; central nervous system (CNS)-related/unconsciousness; abdominal/back/urinary; psychiatric/addiction; infection/fever; trauma/exposure; and unspecified (diverse from the beforementioned categories). Analyses were divided by the time-period of calls (0-7 days/8-30 days preceding OHCA) and call type (1-1-2/1813-Medical Helpline). Results Of all OHCA patients, 18% (974/5442) called helpline services (males 56%, median age 76 years[Q1-Q3:65-84]). Among these, 816 had 1145 calls with registered symptoms. The most common symptom categories (except for unspecified, 33%) were breathing problems (17%), trauma/exposure (17%), CNS/unconsciousness (15%), abdominal/back/urinary (12%), and chest pain (9%). Most patients (61%) called 1813-Medical Helpline, especially for abdominal/back/urinary (17%). Patients calling 1-1-2 had breathing problems (24%) and CNS/unconsciousness (23%). Nearly half of the patients called within 7 days before their OHCA, and CNS/unconsciousness (19%) was the most registered. The unspecified category remained the most common during both time periods (32%;33%) and call type (24%;39%). Conclusions Among patients who called medical helplines services up to 30-days before their OHCA, besides symptoms being highly varied (unspecified (33%)), breathing problems (17%) were the most registered symptom-specific category.

Symptoms reported in calls to emergency medical services within 24 hours prior to out-of-hospital cardiac arrest.

AIM: There is limited evidence regarding prodromal symptoms of out-of-hospital cardiac arrest (OHCA). We aimed to describe patient characteristics, prodromal symptoms, and prognosis of patients contacting emergency medical services (EMS) within 24 hours before OHCA. METHODS: We identified all OHCA treated by Copenhagen EMS from 2016 through 2018 using the Danish Cardiac Arrest Registry and linked them to emergency calls. We included all pre-arrest calls by patients or bystanders if they were performed 1) within 24 hours before the OHCA call or 2) during the OHCA event for EMS-witnessed OHCA. Calls were reviewed by healthcare professionals using a survey guide. RESULTS: Among 4,071 patients, 481 patients (12 %) had 539 calls within 24 hours prior to OHCA (60 % male, median age 74 years of age). The patient spoke on the phone in 25 % of calls. The most common symptoms were breathing problems (59 %), confusion (23 %), unconsciousness (20 %), chest pain (20 %), and paleness (19 %). Patients with breathing problems compared to chest pain were more likely to be ≤ 75 years of age (55 % versus 35 %), less likely to be male (52 % versus 73 %), have shockable rhythm (10 % versus 38 %), receive bystander defibrillation (6 % versus 19 %) or EMS defibrillation (15 % versus 65 %), achieve return of spontaneous circulation (37 % versus 68 %) and survive 30 days following OHCA (10 % versus 50 %). CONCLUSION: More than 10% of patients with OHCA had a call to EMS within 24 hours before OHCA. The most common symptom was breathing problems which compared to chest pain had lower 30-day survival.

"Like a rainy weather inside of me": Qualitative content analysis of telephone consultations concerning back pain preceding out-of-hospital cardiac arrest.

INTRODUCTION: Cardiac arrest patients presenting with back pain are at risk of not receiving the appropriate help when calling emergency medical services. In telephone consultations regarding patients with back pain preceding an out-of-hospital cardiac arrest, we investigated how communication between caller and call-taker influenced the call-taker's interpretation of back pain descriptions and decision-making about choice of response. METHOD: The study was conducted using 20 recorded phone calls from 17 patients who contacted the Copenhagen Emergency Medical Services (Denmark) reporting back pain up to 24 hours before an out-of-hospital cardiac arrest. Qualitative content analysis was applied. RESULTS: Two main categories emerged: (1) reasons, including subcategories: reported conditions, descriptions of conditions, patient's interpretation of condition and patient's own remedial actions; and (2) considerations, including subcategories: assessment of the severity, call-taker's interpretation of the condition, arguments for chosen response and conditions not facilitating further communication by the call-taker. CONCLUSION: In telephone consultations regarding patients with back pain preceding an out-of-hospital cardiac arrest the communication was influenced by the communicative preconditions of the call-taker. Communication in consultations where ambulances were not dispatched was characterized by complex descriptions of symptoms not easily fitting into the health system's interpretations of conditions warranting an urgent response.

Household Exposure to Severe Acute Respiratory Syndrome Coronavirus 2 and Association With Coronavirus Disease 2019 Severity: A Danish Nationwide Cohort Study.

BACKGROUND: Households are high-risk settings for the transmission of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Severity of coronavirus disease 2019 (COVID-19) is likely associated with the infectious dose of SARS-CoV-2 exposure. We therefore aimed to assess the association between SARS-CoV-2 exposure within households and COVID-19 severity. METHODS: We performed a Danish, nationwide, register-based, cohort study including laboratory-confirmed SARS-CoV-2-infected individuals from 22 February 2020 to 6 October 2020. Household exposure to SARS-CoV-2 was defined as having 1 individual test positive for SARS-CoV-2 within the household. Cox proportional hazards models were used to estimate the association between "critical COVID-19" within and between households with and without secondary cases. RESULTS: From 15 063 multiperson households, 19 773 SARS-CoV-2-positive individuals were included; 11 632 were categorized as index cases without any secondary household cases; 3431 as index cases with secondary cases, that is, 22.8% of multiperson households; and 4710 as secondary cases. Critical COVID-19 occurred in 2.9% of index cases living with no secondary cases, 4.9% of index cases with secondary cases, and 1.3% of secondary cases. The adjusted hazard ratio for critical COVID-19 among index cases vs secondary cases within the same household was 2.50 (95% confidence interval [CI], 1.88-3.34), 2.27 (95% CI, 1.77-2.93) for index cases in households with no secondary cases vs secondary cases, and 1.1 (95% CI, .93-1.30) for index cases with secondary cases vs index cases without secondary cases. CONCLUSIONS: We found no increased hazard ratio of critical COVID-19 among household members of infected SARS-CoV-2 index cases.

Contacts With the Health Care System Before Out-of-Hospital Cardiac Arrest.

Background It remains challenging to identify patients at risk of out-of-hospital cardiac arrest (OHCA). We aimed to examine health care contacts in patients before OHCA compared with the general population that did not experience an OHCA. Methods and Results Patients with OHCA with a presumed cardiac cause were identified from the Danish Cardiac Arrest Registry (2001-2014) and their health care contacts (general practitioner [GP]/hospital) were examined up to 1 year before OHCA. In a case-control study (1:9), OHCA contacts were compared with an age- and sex-matched background population. Separately, patients with OHCA were examined by the contact type (GP/hospital/both/no contact) within 2 weeks before OHCA. We included 28 955 patients with OHCA. The weekly percentages of patient contacts with GP the year before OHCA were constant (25%) until 1 week before OHCA when they markedly increased (42%). Weekly percentages of patient contacts with hospitals the year before OHCA gradually increased during the last 6 months (3.5%-6.6%), peaking at the second week (6.8%) before OHCA; mostly attributable to cardiovascular diseases (21%). In comparison, there were fewer weekly contacts among controls with 13% for GP and 2% for hospital contacts (P<0.001). Within 2 weeks before OHCA, 57.8% of patients with OHCA had a health care contact, and these patients had more contacts with GP (odds ratio [OR], 3.17; 95% CI, 3.09-3.26) and hospital (OR, 2.32; 95% CI, 2.21-2.43) compared with controls. Conclusions The health care contacts of patients with OHCA nearly doubled leading up to the OHCA event, with more than half of patients having health care contacts within 2 weeks before arrest. This could have implications for future preventive strategies.

Impact of myocardial infarction symptom presentation on emergency response and survival.

AIMS: We examined associations between symptom presentation and chance of receiving an emergency dispatch and 30-day mortality among patients with acute myocardial infarction (MI). METHODS AND RESULTS: Copenhagen, Denmark has a 24-h non-emergency medical helpline and an emergency number 1-1-2 (equivalent to 9-1-1). Both services register symptoms/purpose of calls. Among patients with MI as either hospital diagnosis or cause of death within 72 h after a call, the primary symptom was categorized as chest pain, atypical symptoms (breathing problems, unclear problem, central nervous system symptoms, abdominal/back/urinary, other cardiac symptoms, and other atypical symptoms), unconsciousness, non-informative symptoms, and no recorded symptoms. We identified 4880 emergency and 3456 non-emergency calls from patients with MI. The most common symptom was chest pain (N = 5219) followed by breathing problems (N = 556). Among patients with chest pain, 95% (3337/3508) of emergency calls and 76% (1306/1711) of non-emergency calls received emergency dispatch. Mortality was 5% (163/3508) and 3% (49/1711) for emergency/non-emergency calls, respectively. For atypical symptoms 62% (554/900) and 17% (137/813) of emergency/non-emergency calls received emergency dispatch and mortality was 23% (206/900) and 15% (125/813). Among unconscious, patients 99%/100% received emergency dispatch and mortality was 71%/75% for emergency/non-emergency calls. Standardized 30-day mortality was 4.3% for chest pain and 15.6% for atypical symptoms, and associations between symptoms and emergency dispatch remained in subgroups of age and sex. CONCLUSION: Myocardial infarction patients presenting with atypical symptoms when calling for help have a reduced chance of receiving an emergency dispatch and increased 30-day mortality compared to MI patients with chest pain.

Symptom presentation of SARS-CoV-2-positive and negative patients: a nested case-control study among patients calling the emergency medical service and medical helpline.

OBJECTIVE: Currently effective symptom-based screening of patients suspected of COVID-19 is limited. We aimed to investigate age-related differences in symptom presentations of patients tested positive and negative for SARS-CoV-2. DESIGN: SETTING: Calls to the medical helpline (1-8-1-3) and emergency number (1-1-2) in Copenhagen, Denmark. At both medical services all calls are recorded. PARTICIPANTS: We included calls for patients who called for help/guidance at the medical helpline or emergency number prior to receiving a test for SARS-CoV-2 between April 1st and 20th 2020 (8423 patients). Among these calls, we randomly sampled recorded calls from 350 patients who later tested positive and 250 patients tested negative and registered symptoms described in the call. OUTCOME: RESULTS: After exclusions, 544 calls (312 SARS-CoV-2 positive and 232 negative) were included in the analysis. Fever and cough remained the two most common of COVID-19 symptoms across all age groups and approximately 42% of SARS-CoV-2 positive and 20% of negative presented with both fever and cough. Symptoms including nasal congestion, irritation/pain in throat, muscle/joint pain, loss of taste and smell, and headache were common symptoms of COVID-19 for patients younger than 60 years; whereas loss of appetite and feeling unwell were more commonly seen among patients over 60 years. Headache and loss of taste and smell were rare symptoms of COVID-19 among patients over 60 years. CONCLUSION: Our study identified age-related differences in symptom presentations of SARS-CoV-2-positive patients calling for help or medical advice. The specific symptoms of loss of smell or taste almost exclusively reported by patients younger than 60 years. Differences in symptom presentation across age groups must be considered when screening for COVID-19.

Rapid dispatch for out-of-hospital cardiac arrest is associated with improved survival.

AIM: As proxy for initiation of the first link in the Chain of Survival by the dispatcher, we aimed to investigate the effect of time to first dispatch on 30-day survival among patients with OHCA ultimately receiving the highest-level emergency medical response. METHODS: We linked data on all OHCA unwitnessed by emergency medical services (EMS) treated by Copenhagen EMS from 2016 through 2018 to corresponding emergency call records. Among patients receiving highest priority emergency response, we calculated time to dispatch as time from start of call to time of first dispatch. RESULTS: We included 3548 patients with OHCA. Of these, 94.1% received the highest priority response (median time to dispatch 0.84 min, 25th-75th percentile 0.58-1.24 min). Patients with time to dispatch within one minute compared to three or more minutes were more likely to receive bystander cardiopulmonary resuscitation (77.3 vs 54.2%), bystander defibrillation (11.5 vs 6.5%) and defibrillation by emergency medical services (24.1 vs 7.5%) and were 2.6-fold more likely to survive 30 days after the OHCA (P = 0.004). Results from multivariate logistic regression were similar: odds ratio (OR) of survival 0.83 per minute increase (95% confidence interval 0.70-1.00, P = 0.04). However, survival was similar between those who received highest priority response and those who did not: OR of survival 0.88 (95% confidence interval 0.53-1.46, P = 0.61). CONCLUSION: Rapid time to dispatch among patients with highest priority response was significantly associated with a higher probability of 30-day survival following OHCA.

National all-cause mortality during the COVID-19 pandemic: a Danish registry-based study.

Denmark implemented early widespread social distancing to reduce pressure on the healthcare system from the coronavirus disease 2019 (COVID-19) pandemic, with the aims to reduce mortality. Unintended consequences might be delays in treatment for other diseases and subsequent mortality. We examined national all-cause mortality comparing weeks 1-27 in 2020 and 2015-2019. This registry-based study used Danish national registry data until 5 July 2020. We examined all-cause mortality rates among all deaths recorded from 2015 to 2020 and among chronic conditions (cardiovascular (cardiac & circulatory), chronic pulmonary, chronic kidney disease, cancer, and diabetes), comparing each week in 2020 to weeks in 2015-2019. In 2020, there were 28,363 deaths in weeks 1-27 (30 December 2019-5 July 2020), the mean deaths in 2015-2019 were 28,630 deaths (standard deviation 784). Compared to previous years, the mortality rate in weeks 3-10 of 2020 was low, peaking in week 14 (17.6 per 100,000 persons in week 9, 19.9 per 100,000 in week 14). Comorbidity prevalence among deceased individuals was similar in 2020 and 2015-2019: 71.1% of all deceased had a prior cardiovascular diagnosis, 30.0% of all deceased had a prior cardiac diagnosis. There were 493 deaths with COVID-19 in weeks 11-27, (59.8% male), and 75.1% had a prior cardiovascular diagnosis. Weekly mortality rates for pre-existing chronic conditions peaked in week 14, and then declined. During the COVID-19 pandemic, due to timely lockdown measures, the mortality rate in Denmark has not increased compared to the mortality rates in the same period during 2015-2019.

Metformin monotherapy for adults with type 2 diabetes mellitus.

BACKGROUND: Worldwide, there is an increasing incidence of type 2 diabetes mellitus (T2DM). Metformin is still the recommended first-line glucose-lowering drug for people with T2DM. Despite this, the effects of metformin on patient-important outcomes are still not clarified. OBJECTIVES: To assess the effects of metformin monotherapy in adults with T2DM. SEARCH METHODS: We based our search on a systematic report from the Agency for Healthcare Research and Quality, and topped-up the search in CENTRAL, MEDLINE, Embase, WHO ICTRP, and ClinicalTrials.gov. Additionally, we searched the reference lists of included trials and systematic reviews, as well as health technology assessment reports and medical agencies. The date of the last search for all databases was 2 December 2019, except Embase (searched up 28 April 2017). SELECTION CRITERIA: We included randomised controlled trials (RCTs) with at least one year's duration comparing metformin monotherapy with no intervention, behaviour changing interventions or other glucose-lowering drugs in adults with T2DM. DATA COLLECTION AND ANALYSIS: Two review authors read all abstracts and full-text articles/records, assessed risk of bias, and extracted outcome data independently. We resolved discrepancies by involvement of a third review author. For meta-analyses we used a random-effects model with investigation of risk ratios (RRs) for dichotomous outcomes and mean differences (MDs) for continuous outcomes, using 95% confidence intervals (CIs) for effect estimates. We assessed the overall certainty of the evidence by using the GRADE instrument. MAIN RESULTS: We included 18 RCTs with multiple study arms (N = 10,680). The percentage of participants finishing the trials was approximately 58% in all groups. Treatment duration ranged from one to 10.7 years. We judged no trials to be at low risk of bias on all 'Risk of bias' domains. The main outcomes of interest were all-cause mortality, serious adverse events (SAEs), health-related quality of life (HRQoL), cardiovascular mortality (CVM), non-fatal myocardial infarction (NFMI), non-fatal stroke (NFS), and end-stage renal disease (ESRD). Two trials compared metformin (N = 370) with insulin (N = 454). Neither trial reported on all-cause mortality, SAE, CVM, NFMI, NFS or ESRD. One trial provided information on HRQoL but did not show a substantial difference between the interventions. Seven trials compared metformin with sulphonylureas. Four trials reported on all-cause mortality: in three trials no participant died, and in the remaining trial 31/1454 participants (2.1%) in the metformin group died compared with 31/1441 participants (2.2%) in the sulphonylurea group (very low-certainty evidence). Three trials reported on SAE: in two trials no SAE occurred (186 participants); in the other trial 331/1454 participants (22.8%) in the metformin group experienced a SAE compared with 308/1441 participants (21.4%) in the sulphonylurea group (very low-certainty evidence). Two trials reported on CVM: in one trial no CVM was observed and in the other trial 4/1441 participants (0.3%) in the metformin group died of cardiovascular reasons compared with 8/1447 participants (0.6%) in the sulphonylurea group (very low-certainty evidence). Three trials reported on NFMI: in two trials no NFMI occurred, and in the other trial 21/1454 participants (1.4%) in the metformin group experienced a NFMI compared with 15/1441 participants (1.0%) in the sulphonylurea group (very low-certainty evidence). One trial reported no NFS occurred (very low-certainty evidence). No trial reported on HRQoL or ESRD. Seven trials compared metformin with thiazolidinediones (very low-certainty evidence for all outcomes). Five trials reported on all-cause mortality: in two trials no participant died; the overall RR was 0.88, 95% CI 0.55 to 1.39; P = 0.57; 5 trials; 4402 participants). Four trials reported on SAE, the RR was 0,95, 95% CI 0.84 to 1.09; P = 0.49; 3208 participants. Four trials reported on CVM, the RR was 0.71, 95% CI 0.21 to 2.39; P = 0.58; 3211 participants. Three trial reported on NFMI: in two trials no NFMI occurred and in one trial 21/1454 participants (1.4%) in the metformin group experienced a NFMI compared with 25/1456 participants (1.7%) in the thiazolidinedione group. One trial reported no NFS occurred. No trial reported on HRQoL or ESRD. Three trials compared metformin with dipeptidyl peptidase-4 inhibitors (one trial each with saxagliptin, sitagliptin, vildagliptin with altogether 1977 participants). There was no substantial difference between the interventions for all-cause mortality, SAE, CVM, NFMI and NFS (very low-certainty evidence for all outcomes). One trial compared metformin with a glucagon-like peptide-1 analogue (very low-certainty evidence for all reported outcomes). There was no substantial difference between the interventions for all-cause mortality, CVM, NFMI and NFS. One or more SAEs were reported in 16/268 (6.0%) of the participants allocated to metformin compared with 35/539 (6.5%) of the participants allocated to a glucagon-like peptide-1 analogue. HRQoL or ESRD were not reported. One trial compared metformin with meglitinide and two trials compared metformin with no intervention. No deaths or SAEs occurred (very low-certainty evidence) no other patient-important outcomes were reported. No trial compared metformin with placebo or a behaviour changing interventions. Four ongoing trials with 5824 participants are likely to report one or more of our outcomes of interest and are estimated to be completed between 2018 and 2024. Furthermore, 24 trials with 2369 participants are awaiting assessment. AUTHORS' CONCLUSIONS: There is no clear evidence whether metformin monotherapy compared with no intervention, behaviour changing interventions or other glucose-lowering drugs influences patient-important outcomes.

Metformin and second- or third-generation sulphonylurea combination therapy for adults with type 2 diabetes mellitus.

BACKGROUND: The number of people with type 2 diabetes mellitus (T2DM) is increasing worldwide. The combination of metformin and sulphonylurea (M+S) is a widely used treatment. Whether M+S shows better or worse effects in comparison with other antidiabetic medications for people with T2DM is still controversial. OBJECTIVES: To assess the effects of metformin and sulphonylurea (second- or third-generation) combination therapy for adults with type 2 diabetes mellitus. SEARCH METHODS: We updated the search of a recent systematic review from the Agency for Healthcare Research and Quality (AHRQ). The updated search included CENTRAL, MEDLINE, Embase, ClinicalTrials.gov and WHO ICTRP. The date of the last search was March 2018. We searched manufacturers' websites and reference lists of included trials, systematic reviews, meta-analyses and health technology assessment reports. We asked investigators of the included trials for information about additional trials. SELECTION CRITERIA: We included randomised controlled trials (RCTs) randomising participants 18 years old or more with T2DM to M+S compared with metformin plus another glucose-lowering intervention or metformin monotherapy with a treatment duration of 52 weeks or more. DATA COLLECTION AND ANALYSIS: Two review authors read all abstracts and full-text articles and records, assessed risk of bias and extracted outcome data independently. We used a random-effects model to perform meta-analysis, and calculated risk ratios (RRs) for dichotomous outcomes and mean differences (MDs) for continuous outcomes, using 95% confidence intervals (CIs) for effect estimates. We assessed the certainty of the evidence using the GRADE instrument. MAIN RESULTS: We included 32 RCTs randomising 28,746 people. Treatment duration ranged between one to four years. We judged none of these trials as low risk of bias for all 'Risk of bias' domains. Most important events per person were all-cause and cardiovascular mortality, serious adverse events (SAE), non-fatal stroke (NFS), non-fatal myocardial infarction (MI) and microvascular complications. Most important comparisons were as follows:Five trials compared M+S (N = 1194) with metformin plus a glucagon-like peptide 1 analogue (N = 1675): all-cause mortality was 11/1057 (1%) versus 11/1537 (0.7%), risk ratio (RR) 1.15 (95% confidence interval (CI) 0.49 to 2.67); 3 trials; 2594 participants; low-certainty evidence; cardiovascular mortality 1/307 (0.3%) versus 1/302 (0.3%), low-certainty evidence; serious adverse events (SAE) 128/1057 (12.1%) versus 194/1537 (12.6%), RR 0.90 (95% CI 0.73 to 1.11); 3 trials; 2594 participants; very low-certainty evidence; non-fatal myocardial infarction (MI) 2/549 (0.4%) versus 6/1026 (0.6%), RR 0.57 (95% CI 0.12 to 2.82); 2 trials; 1575 participants; very low-certainty evidence.Nine trials compared M+S (N = 5414) with metformin plus a dipeptidyl-peptidase 4 inhibitor (N = 6346): all-cause mortality was 33/5387 (0.6%) versus 26/6307 (0.4%), RR 1.32 (95% CI 0.76 to 2.28); 9 trials; 11,694 participants; low-certainty evidence; cardiovascular mortality 11/2989 (0.4%) versus 9/3885 (0.2%), RR 1.54 (95% CI 0.63 to 3.79); 6 trials; 6874 participants; low-certainty evidence; SAE 735/5387 (13.6%) versus 779/6307 (12.4%), RR 1.07 (95% CI 0.97 to 1.18); 9 trials; 11,694 participants; very low-certainty evidence; NFS 14/2098 (0.7%) versus 8/2995 (0.3%), RR 2.21 (95% CI 0.74 to 6.58); 4 trials; 5093 participants; very low-certainty evidence; non-fatal MI 15/2989 (0.5%) versus 13/3885 (0.3%), RR 1.45 (95% CI 0.69 to 3.07); 6 trials; 6874 participants; very low-certainty evidence; one trial in 64 participants reported no microvascular complications were observed (very low-certainty evidence).Eleven trials compared M+S (N = 3626) with metformin plus a thiazolidinedione (N = 3685): all-cause mortality was 123/3300 (3.7%) versus 114/3354 (3.4%), RR 1.09 (95% CI 0.85 to 1.40); 6 trials; 6654 participants; low-certainty evidence; cardiovascular mortality 37/2946 (1.3%) versus 41/2994 (1.4%), RR 0.78 (95% CI 0.36 to 1.67); 4 trials; 5940 participants; low-certainty evidence; SAE 666/3300 (20.2%) versus 671/3354 (20%), RR 1.01 (95% CI 0.93 to 1.11); 6 trials; 6654 participants; very low-certainty evidence; NFS 20/1540 (1.3%) versus 16/1583 (1%), RR 1.29 (95% CI 0.67 to 2.47); P = 0.45; 2 trials; 3123 participants; very low-certainty evidence; non-fatal MI 25/1841 (1.4%) versus 21/1877 (1.1%), RR 1.21 (95% CI 0.68 to 2.14); P = 0.51; 3 trials; 3718 participants; very low-certainty evidence; three trials (3123 participants) reported no microvascular complications (very low-certainty evidence).Three trials compared M+S (N = 462) with metformin plus a glinide (N = 476): one person died in each intervention group (3 trials; 874 participants; low-certainty evidence); no cardiovascular mortality (2 trials; 446 participants; low-certainty evidence); SAE 34/424 (8%) versus 27/450 (6%), RR 1.68 (95% CI 0.54 to 5.21); P = 0.37; 3 trials; 874 participants; low-certainty evidence; no NFS (1 trial; 233 participants; very low-certainty evidence); non-fatal MI 2/215 (0.9%) participants in the M+S group; 2 trials; 446 participants; low-certainty evidence; no microvascular complications (1 trial; 233 participants; low-certainty evidence).Four trials compared M+S (N = 2109) with metformin plus a sodium-glucose co-transporter 2 inhibitor (N = 3032): all-cause mortality was 13/2107 (0.6%) versus 19/3027 (0.6%), RR 0.96 (95% CI 0.44 to 2.09); 4 trials; 5134 participants; very low-certainty evidence; cardiovascular mortality 4/1327 (0.3%) versus 6/2262 (0.3%), RR 1.22 (95% CI 0.33 to 4.41); 3 trials; 3589 participants; very low-certainty evidence; SAE 315/2107 (15.5%) versus 375/3027 (12.4%), RR 1.02 (95% CI 0.76 to 1.37); 4 trials; 5134 participants; very low-certainty evidence; NFS 3/919 (0.3%) versus 7/1856 (0.4%), RR 0.87 (95% CI 0.22 to 3.34); 2 trials; 2775 participants; very low-certainty evidence; non-fatal MI 7/890 (0.8%) versus 8/1374 (0.6%), RR 1.43 (95% CI 0.49 to 4.18; 2 trials); 2264 participants; very low-certainty evidence; amputation of lower extremity 1/437 (0.2%) versus 1/888 (0.1%); very low-certainty evidence.Trials reported more hypoglycaemic episodes with M+S combination compared to all other metformin-antidiabetic agent combinations. Results for M+S versus metformin monotherapy were inconclusive. There were no RCTs comparing M+S with metformin plus insulin. We identified nine ongoing trials and two trials are awaiting assessment. Together these trials will include approximately 16,631 participants. AUTHORS' CONCLUSIONS: There is inconclusive evidence whether M+S combination therapy compared with metformin plus another glucose-lowering intervention results in benefit or harm for most patient-important outcomes (mortality, SAEs, macrovascular and microvascular complications) with the exception of hypoglycaemia (more harm for M+S combination). No RCT reported on health-related quality of life.