Machine learning approach to predict body weight in adults.

Background: Obesity is an established risk factor for non-communicable diseases such as type 2 diabetes mellitus, hypertension and cardiovascular disease. Thus, weight control is a key factor in the prevention of non-communicable diseases. A simple and quick method to predict weight change over a few years could be helpful for weight management in clinical settings. Methods: We examined the ability of a machine learning model that we constructed to predict changes in future body weight over 3 years using big data. Input in the machine learning model were three-year data on 50,000 Japanese persons (32,977 men) aged 19-91 years who underwent annual health examinations. The predictive formulas that used heterogeneous mixture learning technology (HMLT) to predict body weight in the subsequent 3 years were validated for 5,000 persons. The root mean square error (RMSE) was used to evaluate accuracy compared with multiple regression. Results: The machine learning model utilizing HMLT automatically generated five predictive formulas. The influence of lifestyle on body weight was found to be large in people with a high body mass index (BMI) at baseline (BMI ≥29.93 kg/m2) and in young people (<24 years) with a low BMI (BMI <23.44 kg/m2). The RMSE was 1.914 in the validation set which reflects ability comparable to that of the multiple regression model of 1.890 (p = 0.323). Conclusion: The HMLT-based machine learning model could successfully predict weight change over 3 years. Our model could automatically identify groups whose lifestyle profoundly impacted weight loss and factors the influenced body weight change in individuals. Although this model must be validated in other populations, including other ethnic groups, before being widely implemented in global clinical settings, results suggested that this machine learning model could contribute to individualized weight management.

Combined effects of blood pressure and glycemic status on risk of heart failure: a population-based study.

AIMS: To investigate the combined effects of blood pressure (BP) and glycemic status on the risk of heart failure. METHODS: Examined was a Japanese claims database from 2008 to 2019 on 589 621 individuals. Cox proportional hazards model identified the incidence of heart failure among five levels of SBP/DBP according to glucose status. RESULTS: Mean follow-up period was 5.6 years. The incidence of heart failure per 1000 person-years in the normoglycemia, borderline glycemia, and diabetes groups were 0.10, 0.18, and 0.80, respectively. In normoglycemia, a linear trend was observed between both SBP and DBP categories and hazard ratios for heart failure ( P for linearity <0.001). In borderline glycemia, J-shaped association was observed between DBP categories and hazard ratios, although the liner trend was significant ( P  < 0.001). In diabetes, the linear trend for the relationship between DBP categories and hazard ratios was not significant ( P  = 0.09) and the J-shaped association in relation to the hazard ratios was observed between SBP categories and heart failure risk. In the lowest SBP category (i.e. SBP < 120 mmHg), patients with diabetes had more than five-fold heart failure risk [hazard ratio (95% confidence interval), 5.10 (3.19-8.15)], compared with those with normoglycemia and SBP less than 120 mmHg. CONCLUSION: The association between SBP/DBP and heart failure risk weakened with worsening of glucose metabolism, suggesting strict BP control accompanied by excessively lowered DBP should be cautious in prevent heart failure in abnormal glycemic status. Particularly in diabetes, comprehensive management of risk factors other than BP may be essential to prevent heart failure. Further trials are needed to support these suggestions and apply them to clinical practice.

Network meta-analysis of glucose-lowering drug treatment regimens with the potential risk of hypoglycemia in patients with type 2 diabetes mellitus in terms of glycemic control and severe hypoglycemia.

Insulin and its secretagogues are essential for some patients with type 2 diabetes (T2D) to maintain good glycemic control (GC), but severe hypoglycemia (SH) is a concern. This network meta-analysis aimed to find optimal glucose-lowering drug treatment regimens in terms of GC and SH in T2D patients. MEDLINE and EMBASE were used to identify trials that compared two or more treatments including insulins and/or sulfonylurea or glinides and that examined both GC and SH. Treatment hierarchy was expressed as the surface under the cumulative ranking curve (SUCRA) probabilities. We identified 137 eligible trials comprising 42 treatments. The use of insulins and non-insulin glucose-lowering agents except for sulfonylurea or glinide had a higher SUCRA than insulins only for hemoglobin A1c (A1C) (p = 0.01) changes and achievement of A1C < 7.0% (p = 0.02) or A1C ≤ 6.5% (p = 0.002). The use of sulfonylurea or glinide and other non-insulin glucose-lowering agents resulted in a lower SUCRA for SH than insulins only when trials were analyzed for A1C change (p = 0.06) and achievement of A1C < 7.0% (p = 0.004) or A1C ≤ 6.5% (p = 0.004). Cluster analysis indicated that premixed insulin plus glucagon-like peptide-1 receptor agonist (Mix-ins + GLP1) belonged to the high-efficacy category for GC and glinide plus thiazolidinedione (glinide + TZD) belonged to the relatively high-efficacy category for GC among several high-safety categories regarding SH. In T2D patients, clinicians should consider appropriate combinations of non-insulin glucose-lowering agents (especially glinide + TZD) for reducing SH risk before switching to insulin therapies. If switching, they should be willing to add non-insulin glucose-lowering agents (especially, Mix-ins + GLP1) to insulins to further improve GC.

Relationship between changes in blood pressure from summer to winter and estimated 24-hour salt excretion using spot urine: the Niigata Wellness Study.

A convenient way to determine salt intake is salt excretion using spot urine (e-NaCl). We measured e-NaCl at health checkups and compared results with seasonal changes in blood pressure. Among 19,732 examinees who underwent health checkups from Aug. 2012 to Mar. 2013, age, body weight and e-NaCl were measured and compared to monthly mean systolic blood pressure (SBP). Excluded were those taking antihypertensive drugs and with creatinine levels higher than 2.0 mg/dL. Also examined was salt intake (i-NaCl) by an interview survey from Aug. to Dec. 2012. Correlations with SBP were R = 0.7718 for age, R = 0.5996 for body weight, R = 0.2498 for i-NaCl and R = 0.9335 for e-NaCl. e-NaCl decreased in summer. It was presumed that the reduced burden on the kidney of salt excretion due to sweating may be related to decreases in blood pressure in summer.

Fast walking and physical activity are independent contributors to improved physical function.

BACKGROUND AND OBJECTIVES: To clarify whether the presence or absence of fast walking and habitual physical activity are independently associated with the incidence of functional disability. METHODS: This historical cohort study was comprised of 9,652 (4,412 men, mean age 65 years) individuals aged 39-98 years without functional disability at baseline. Functional disability was determined based on the Japanese long-term care insurance system, which specified requirements for assistance in the activities of daily living. The impact of fast walking and habitual physical activity on the incidence of functional disability was analysed by Cox proportional hazards models. RESULTS: The follow-up period was a median of 3.7 years during which 165 patients were newly certified as having functional disability. In the multivariate analysis, baseline age in 5-year increments (hazard ratio 2.42 [95% confidence interval 2.18-2.69]), no habitual physical activity (1.56 [1.07-2.27]), and not fast walking (1.89 [1.32-2.69]) significantly increased the risk of functional disability after adjustment for covariates. The stratified analysis showed that compared with physical activity (+), the impact of physical activity (-) on the incidence of functional disability was observed in those aged ≥75 years regardless of fast walking (+). Fast walking (-) significantly increased the risk of disability compared with fast walking (+) in those aged <75 years regardless of a physical activity habit. CONCLUSION: In Japanese, slow walking speed and lack of a physical activity habit were shown to be independent risk factors for incident functional disability, with their impact differing according to age.

Impact of Medication Adherence and Glycemic Control on the Risk of Micro- and Macrovascular Diseases in Patients with Diabetes.

PURPOSE: Our purpose in the research was to clarify the impact of medication adherence to oral hypoglycemic agents during a 1-year period and subsequent glycemic control on the risk of micro- and macrovascular diseases. METHODS: Examined was a nationwide claims database on 13,256 individuals with diabetic eye disease without requiring prior treatment, 7,862 without prior initiation of dialysis, 15,556 without prior coronary artery disease, 16,243 without prior cerebrovascular disease, and 19,386 without prior heart failure from 2008 to 2016 in Japan. Medication adherence was evaluated by the proportion of days covered. Patients were considered to have poor adherence if the proportion of days covered was <80%. Multivariate Cox regression model identified risks of micro- and macrovascular diseases. RESULTS: In each group, mean age was 53 to 54 years, HbA1c was 7.1% to 7.2%, and median follow-up period was 4.6 to 5.1 years, and the percentage of poor adherence was approximately 30%. During the study period, 532 treatment-requiring diabetic eye disease, 75 dialysis, 389 coronary artery disease, 316 cerebrovascular disease, and 144 heart failure events occurred. Multivariate Cox regression model revealed that the hazard ratio (95% confidence interval) of dialysis in the poor adherence group was 2.04 (1.27-3.30) compared with the good adherence group. The hazard ratios in the poor adherence/poor glycemic control group were 3.34 (2.63-4.24) for treatment-requiring diabetic eye disease, 4.23 (2.17-8.26) for dialysis, 1.69 (1.23-2.31) for coronary artery disease, and 2.08 (1.25-3.48) for heart failure compared with the good adherence/good glycemic control group. CONCLUSIONS: Poor medication adherence was an independent risk factor for the initiation of dialysis, suggesting that clinicians must pay close attention to these patients.

Predictive ability of current machine learning algorithms for type 2 diabetes mellitus: A meta-analysis.

AIMS/INTRODUCTION: Recently, an increasing number of cohort studies have suggested using machine learning (ML) to predict type 2 diabetes mellitus. However, its predictive ability remains inconclusive. This meta-analysis evaluated the current ability of ML algorithms for predicting incident type 2 diabetes mellitus. MATERIALS AND METHODS: We systematically searched longitudinal studies published from 1 January 1950 to 17 May 2020 using MEDLINE and EMBASE. Included studies had to compare ML's classification with the actual incidence of type 2 diabetes mellitus, and present data on the number of true positives, false positives, true negatives and false negatives. The dataset for these four values was pooled with a hierarchical summary receiver operating characteristic and a bivariate random effects model. RESULTS: There were 12 eligible studies. The pooled sensitivity, specificity, positive likelihood ratio and negative likelihood ratio were 0.81 (95% confidence interval [CI] 0.67-0.90), 0.82 [95% CI 0.74-0.88], 4.55 [95% CI 3.07-6.75] and 0.23 [95% CI 0.13-0.42], respectively. The area under the summarized receiver operating characteristic curve was 0.88 (95% CI 0.85-0.91). CONCLUSIONS: Current ML algorithms have sufficient ability to help clinicians determine whether individuals will develop type 2 diabetes mellitus in the future. However, persons should be cautious before changing their attitude toward future diabetes risk after learning the result of the diabetes prediction test using ML algorithms.

Impact of prior cerebrovascular disease and glucose status on incident cerebrovascular disease in Japanese.

BACKGROUND: Although both a history of cerebrovascular disease (CVD) and glucose abnormality are risk factors for CVD, few large studies have examined their association with subsequent CVD in the same cohort. Thus, we compared the impact of prior CVD, glucose status, and their combinations on subsequent CVD using real-world data. METHODS: This is a retrospective cohort study including 363,627 men aged 18-72 years followed for ≥ 3 years between 2008 and 2016. Participants were classified as normoglycemia, borderline glycemia, or diabetes defined by fasting plasma glucose, HbA1c, and antidiabetic drug prescription. Prior and subsequent CVD (i.e. ischemic stroke, transient ischemic attack, and non-traumatic intracerebral hemorrhage) were identified according to claims using ICD-10 codes, medical procedures, and questionnaires. RESULTS: Participants' mean age was 46.1 ± 9.3, and median follow up was 5.2 (4.2, 6.7) years. Cox regression analysis showed that prior CVD + conferred excess risk for CVD regardless of glucose status (normoglycemia: hazard ratio (HR), 8.77; 95% CI 6.96-11.05; borderline glycemia: HR, 7.40, 95% CI 5.97-9.17; diabetes: HR, 5.73, 95% CI 4.52-7.25). Compared with normoglycemia, borderline glycemia did not influence risk of CVD, whereas diabetes affected subsequent CVD in those with CVD- (HR, 1.50, 95% CI 1.34-1.68). In CVD-/diabetes, age, current smoking, systolic blood pressure, high-density lipoprotein cholesterol, and HbA1c were associated with risk of CVD, but only systolic blood pressure was related to CVD risk in CVD + /diabetes. CONCLUSIONS: Prior CVD had a greater impact on the risk of CVD than glucose tolerance and glycemic control. In participants with diabetes and prior CVD, systolic blood pressure was a stronger risk factor than HbA1c. Individualized treatment strategies should consider glucose tolerance status and prior CVD.

A 52-week randomized controlled trial of ipragliflozin or sitagliptin in type 2 diabetes combined with metformin: The N-ISM study.

AIM: To compare the long-term efficacy of sodium-glucose co-transporter-2 inhibitors and dipeptidyl peptidase-4 inhibitors as second-line drugs after metformin for patients not at high risk of atherosclerotic cardiovascular disease (ASCVD). MATERIALS AND METHODS: In a 52-week randomized open-label trial, we compared ipragliflozin and sitagliptin in Japanese patients diagnosed with type 2 diabetes, without prior ASCVD and treated with metformin. The primary endpoint was a glycated haemoglobin (HbA1c) reduction of ≥0.5% (5.5 mmol/mol) without weight gain at 52 weeks. RESULTS: Of a total of 111 patients (mean age 59.2 years, mean body mass index [BMI] 26.6 kg/m2 , 61.3% men), 54 patients received ipragliflozin and 57 received sitagliptin. After 52 weeks, achievement of the primary endpoint was not significantly different (37.0% and 40.3%; P = 0.72). HbA1c reduction rate at 24 weeks was greater for sitagliptin (56.1%) than for ipragliflozin (31.5%; P = 0.01). From 24 to 52 weeks, the HbA1c reduction with sitagliptin was attenuated, with no significant difference in HbA1c reduction after 52 weeks between sitagliptin (54.4%) and ipragliflozin (38.9%; P = 0.10). Improvements in BMI, C-peptide and high-density lipoprotein cholesterol were greater with ipragliflozin than with sitagliptin. Adverse events occurred in 17 patients with ipragliflozin and in 10 patients with sitagliptin (P = 0.11). CONCLUSION: The HbA1c-lowering effect at 24 weeks was greater with sitagliptin than with ipragliflozin, but with no difference in efficacy related to HbA1c and body weight at 52 weeks. However, some ASCVD risk factors improved with ipragliflozin.

Severity of hypertension as a predictor of initiation of dialysis among study participants with and without diabetes mellitus.

To determine associations between severity of hypertension and risk of starting dialysis in the presence or absence of diabetes mellitus (DM). A nationwide database with claims data on 258 874 people with and without DM aged 19-72 years in Japan was used to elucidate the impact of severity of hypertension on starting dialysis. Initiation of dialysis was determined from claims using International Classification of Diseases-10 codes and medical procedures. Using multivariate Cox modeling, we investigated the severity of hypertension to predict the initiation of dialysis with and without DM. Hypertension was significantly associated with the initiation of dialysis regardless of DM. The incidence of starting dialysis in those with systolic blood pressure (SBP) ≤119 mm Hg and DM (DM+) was almost the same as in those with SBP ≥150 mm Hg and absence of DM (DM-). In comparison with SBP ≤119 mm Hg, SBP ≥150 mm Hg significantly increased the risk of the initiation of dialysis about 2.5 times regardless of DM+ or DM-. Compared with DM- and SBP ≤119 mm Hg, the HR for DM+ and SBP ≥150 mm Hg was 6.88 (95% CI 3.66 to 12.9). Although the risks of hypertension differed only slightly regardless of the presence or absence of DM, risks for starting dialysis with DM+ and SBP ≤119 mm Hg were equivalent to DM- and SBP ≥150 mm Hg, indicating more strict blood pressure interventions in DM+ are needed to avoid dialysis. Future studies are required to clarify the cut-off SBP level to avoid initiation of dialysis considering the risks of strict control of blood pressure.

Ability of Current Machine Learning Algorithms to Predict and Detect Hypoglycemia in Patients With Diabetes Mellitus: Meta-analysis.

BACKGROUND: Machine learning (ML) algorithms have been widely introduced to diabetes research including those for the identification of hypoglycemia. OBJECTIVE: The objective of this meta-analysis is to assess the current ability of ML algorithms to detect hypoglycemia (ie, alert to hypoglycemia coinciding with its symptoms) or predict hypoglycemia (ie, alert to hypoglycemia before its symptoms have occurred). METHODS: Electronic literature searches (from January 1, 1950, to September 14, 2020) were conducted using the Dialog platform that covers 96 databases of peer-reviewed literature. Included studies had to train the ML algorithm in order to build a model to detect or predict hypoglycemia and test its performance. The set of 2 × 2 data (ie, number of true positives, false positives, true negatives, and false negatives) was pooled with a hierarchical summary receiver operating characteristic model. RESULTS: A total of 33 studies (14 studies for detecting hypoglycemia and 19 studies for predicting hypoglycemia) were eligible. For detection of hypoglycemia, pooled estimates (95% CI) of sensitivity, specificity, positive likelihood ratio (PLR), and negative likelihood ratio (NLR) were 0.79 (0.75-0.83), 0.80 (0.64-0.91), 8.05 (4.79-13.51), and 0.18 (0.12-0.27), respectively. For prediction of hypoglycemia, pooled estimates (95% CI) were 0.80 (0.72-0.86) for sensitivity, 0.92 (0.87-0.96) for specificity, 10.42 (5.82-18.65) for PLR, and 0.22 (0.15-0.31) for NLR. CONCLUSIONS: Current ML algorithms have insufficient ability to detect ongoing hypoglycemia and considerate ability to predict impeding hypoglycemia in patients with diabetes mellitus using hypoglycemic drugs with regard to diagnostic tests in accordance with the Users' Guide to Medical Literature (PLR should be ≥5 and NLR should be ≤0.2 for moderate reliability). However, it should be emphasized that the clinical applicability of these ML algorithms should be evaluated according to patients' risk profiles such as for hypoglycemia and its associated complications (eg, arrhythmia, neuroglycopenia) as well as the average ability of the ML algorithms. Continued research is required to develop more accurate ML algorithms than those that currently exist and to enhance the feasibility of applying ML in clinical settings. TRIAL REGISTRATION: PROSPERO International Prospective Register of Systematic Reviews CRD42020163682; http://www.crd.york.ac.uk/PROSPERO/display_record.php?ID=CRD42020163682.

Physical Fitness and Dyslipidemia Among Japanese: A Cohort Study From the Niigata Wellness Study.

BACKGROUND: Grip strength reflects systemic muscle strength and mass and is reportedly associated with various metabolic variables. However, its prognostic association with dyslipidemia is unknown. We examined the association of grip strength and other physical fitness markers with the incidence of dyslipidemia among Japanese adults. METHODS: A total of 16,149 Japanese (6,208 women) individuals aged 20-92 years who underwent a physical fitness test between April 2001 and March 2002 were included in this cohort study. Grip strength, vertical jump, single-leg balance with eyes closed, forward bending, and whole-body reaction time were evaluated at baseline. Dyslipidemia was annually determined based on fasting serum lipid profiles and self-reported dyslipidemia from April 2001 to March 2008. RESULTS: During the follow-up period, 4,458 (44.9%) men and 2,461 (39.6%) women developed dyslipidemia. A higher relative grip strength (grip strength/body mass index) was associated with a lower incidence of dyslipidemia among both men and women (P for trend <0.001). Compared with those for the first septile, the hazards ratios and 95% confidence intervals (CIs) for the seventh septile were 0.56 (95% CI, 0.50-0.63) for men and 0.69 (95% CI, 0.58-0.81) for women. Moreover, relative vertical jump (vertical jump strength/body mass index) was also inversely associated with the incidence of dyslipidemia among both men and women (P for trend <0.001). There was no association between other physical fitness and dyslipidemia among both men and women. CONCLUSION: Relative grip strength and vertical jump may be useful risk markers of the incidence of dyslipidemia.

Diabetes mellitus and risk of new-onset and recurrent heart failure: a systematic review and meta-analysis.

Despite mounting evidence of the positive relationship between diabetes mellitus (DM) and heart failure (HF), the entire context of the magnitude of risk for HF in relation to DM remains insufficiently understood. The principal reason is because new-onset HF (HF occurring in participants without a history of HF) and recurrent HF (HF re-occurring in patients with a history of HF) are not discriminated. This meta-analysis aims to comprehensively and separately assess the risk of new-onset and recurrent HF depending on the presence or absence of DM. We systematically searched cohort studies that examined the relationship between DM and new-onset or recurrent HF using EMBASE and MEDLINE (from 1 Jan 1950 to 28 Jul 2019). The risk ratio (RR) for HF in individuals with DM compared with those without DM was pooled with a random-effects model. Seventy-four and 38 eligible studies presented data on RRs for new-onset and recurrent HF, respectively. For new-onset HF, the pooled RR [95% confidence interval (CI)] of 69 studies that examined HF as a whole [i.e. combining HF with preserved ejection fraction (HFpEF) and HF with reduced ejection fraction (HFrEF)] was 2.14 (1.96-2.34). The large between-study heterogeneity (I2 = 99.7%, P < 0.001) was significantly explained by mean age [pooled RR (95% CI) 2.60 (2.38-2.84) for mean age < 60 years vs. pooled RR (95% CI) 1.95 (1.79-2.13) for mean age ≥ 60 years] (P < 0.001). Pooled RRs (95% CI) of seven and eight studies, respectively, that separately examined HFpEF and HFrEF risk were 2.22 (2.02-2.43) for HFpEF and 2.73 (2.71-2.75) for HFrEF. The risk magnitudes between HFpEF and HFrEF were not significantly different in studies that examined both HFpEF and HFrEF risks (P = 0.86). For recurrent HF, pooled RR (95% CI) of the 38 studies was 1.39 (1.33-1.45). The large between-study heterogeneity (I2 = 80.1%, P < 0.001) was significantly explained by the proportion of men [pooled RR (95% CI) 1.53 (1.40-1.68) for < 65% men vs. 1.32 (1.25-1.39) for ≥65% men (P = 0.01)] or the large pooled RR for studies of only participants with HFpEF [pooled RR (95% CI), 1.73 (1.32-2.26) (P = 0.002)]. Results indicate that DM is a significant risk factor for both new-onset and recurrent HF. It is suggested that the risk magnitude is large for new-onset HF especially in young populations and for recurrent HF especially in women or individuals with HFpEF. DM is associated with future HFpEF and HFrEF to the same extent.

Physical Fitness Tests and Type 2 Diabetes Among Japanese: A Longitudinal Study From the Niigata Wellness Study.

BACKGROUND: Simple physical fitness test can be a useful potential predictor of type 2 diabetes (T2DM). We examined the association between performances on simple physical fitness tests and the incidence of T2DM. METHODS: This longitudinal study was conducted in 21,802 nondiabetic Japanese (6,649 women) aged 20 to 92 years, who underwent all physical fitness tests at baseline (April 2001 to March 2002). From April 2001 to March 2008, physical fitness tests, including grip strength, vertical jump, single-leg balance with eyes closed, forward bending, whole-body reaction time, and supine legs-up, were performed every year. Participants had physical fitness tests at least two times during the period. T2DM was also annually determined based on fasting blood glucose, glycated hemoglobin, and self-reported diabetes during the period. Discrete-time logit models were used to examine the influence of the serial level of each physical fitness test on the incidence of T2DM. RESULTS: During the entire study period, 972 participants developed diabetes. Lower relative grip strength (grip strength/body weight) and single-leg balance performance were associated with a higher incidence of T2DM. For relative grip strength, as compared with the fourth quartile group, the odds ratios for other groups ranged from 1.16 to 1.56 (P for trend < 0.001). For single-leg balance, the odds ratios ranged from 1.03 to 1.49 (P for trend < 0.001). CONCLUSION: The performance of a simple single-leg balance test as well as that of a grip strength test were negatively associated with the risk of T2DM among Japanese.

Patient perceptions of injection pain and anxiety: a comparison of NovoFine 32-gauge tip 6mm and Micro Fine Plus 31-gauge 5mm needles.

BACKGROUND: Injecting insulin may cause pain and anxiety and lead to suboptimal treatment of diabetes mellitus. The aim of this randomized, open-label, crossover study was to compare two types of needle design and diameter in patients with diabetes injecting insulin. METHODS: Patients with diabetes injecting insulin twice daily for at least 3 months were included. A NovoFine (Novo Nordisk, Bagsvërd, Denmark) 32-gauge tip 6mm tapered needle and a Micro Fine Plus (Nippon Becton Dickinson Co. Ltd., Tokyo, Japan) 31-gauge 5mm standard needle were compared. Patients were randomized to use one needle for 1 week, followed by the alternative needle for another week. Before and after each week patients completed a 14-item questionnaire assessing overall satisfaction and usability of the needles. Each item was scored on a visual analog scale from -100 (worst) to +100 (best). RESULTS: Thirty patients (24 men, six women) took part in this study: 24 with type 2 diabetes and six with latent autoimmune diabetes in adults. The mean +/- SD for age was 57.8 +/- 7.6 years, for body mass index was 23.0 +/- 3.1 kg/m(2), for duration of diabetes was 15.6 +/- 9.8 years, and for mean glycated hemoglobin was 7.1 +/- 1.1%. Patients were more satisfied with the use of NovoFine 32-gauge tip 6mm needles (P < 0.0001), found the needles less frightening (P < 0.05) and less painful (P < 0.01), and caused less frequent bleeding and bruising (P < 0.001) than Micro Fine Plus 31-gauge 5mm needles. CONCLUSIONS: These results suggest that the diameter and design of the needle play an important role in reducing injection pain and needle anxiety, which is particularly important for insulin initiation.

Comparison of patient's preference, pain perception, and usability between Micro Fine Plus 31-gauge needle and Microtapered NanoPass 33-gauge needle for insulin therapy.

BACKGROUND: How smoothly insulin is injected is one of the major concerns when patients commence insulin injection therapy. Improving its usability may be important in initiation therapy and adherence, resulting in clinical benefits to the patient. METHODS: In a single-center, open-label and randomized two-period crossover trial, the effect of the tapered needle of NanoPass (33 gauge, 5 mm) on usability in comparison with the standard needle of Micro Fine Plus (31 gauge, 5 mm) was examined using a questionnaire. Patients with insulin-dependent diabetes (n = 40, self-injecting insulin four times daily for more than 3 months) were randomized to use NanoPass or Micro Fine Plus needles for 1 week and then use the alternative for 1 week. Patients completed the questionnaire before and after each test week. Each evaluation was scored from -100 (worst) to +100 (best) by a visual analogue scale. A higher score indicated a more favorable outcome compared with the other needle. RESULTS: The NanoPass needle was significantly less painful to insert and caused less bruising than the Micro Fine Plus needle. However, there was no significant difference in the overall patient satisfaction score between the two needles. Meanwhile, the NanoPass needle, which had less resistance in insertion with a new lubricant coating method, had a significantly superior (P < 0.001) overall patient's satisfaction score, including less frightening use, less bleeding, and less dribbling of injected insulin in comparison with the former evaluation. CONCLUSIONS: For overall patient satisfaction in using an insulin needle, developing a thinner needle and improving other factors, such as lubricity coating the needle, are important.