A Point System for Predicting 10-Year Risk of Developing Type 2 Diabetes Mellitus in Japanese Men: Aichi Workers' Cohort Study

A comparison of the utility of the urine dipstick and urine protein-to-creatinine ratio for predicting microalbuminuria in patients with non-diabetic lifestyle-related diseases -a comparison with diabetes

BACKGROUND

The utility of dipstick proteinuria for predicting microalbuminuria in non-diabetic lifestyle-related diseases compared with the urine protein-to-creatinine ratio (uPCR) and the effect of dipstick proteinuria on the cut-off value (CO) and accuracy of uPCR are unclear.

METHODS

The subjects included Japanese patients ≥ 18 years old with lifestyle-related diseases who had an estimated glomerular filtration rate of ≥ 15 ml/min/1.73 m² and uPCR of < 0.5 g/gCr at initiation. Urine dipstick, uPCR and urine albumin-to-creatinine ratio (uACR) were measured three times per case. Microalbuminuria was defined as uACR of 30-299 mg/gCr for at least 2 of 3 measurements. Youden's Index was used as the optimal CO. Factors associated with microalbuminuria were analyzed using a logistic regression model.

RESULTS

In 313 non-diabetic cases (median 70.8 years old), 3 dipstick proteinuria measurements were independently useful for detecting microalbuminuria, and the CO was set when a trace finding was obtained at least 1 of 3 times (sensitivity 0.56, specificity 0.80, positive predictive value [PPV] 0.73, negative predictive value [NPV] 0.65). A single uPCR measurement was more useful than 3 dipstick measurements, and was useful for detecting microalbuminuria even in cases with three consecutive negative proteinuria findings, indicating that the CO of the second uPCR with G1-3a (n = 136) was 0.06 g/gCr (sensitivity 0.76, specificity 0.84. PPV 0.68, NPV 0.89), while that with G3-b4 (n = 59) was 0.10 g/gCr (sensitivity 0.56, specificity 0.91. PPV 0.83, NPV 0.71). The sum of 3 uPCRs was useful for detecting microalbuminuria in cases with G1-3a (sensitivity 0.67, specificity 0.94, PPV 0.82, NPV 0.86) and G3b-4 (sensitivity 0.78, specificity 0.94, PPV 0.91 NPV 0.83), with both COs being 0.23 g/gCr. These COs of microalbuminuria did not change when trace or more proteinuria was included, although the sensitivity increased. A high uPCR and low urine specific gravity or creatinine level were independent factors for uACR ≥ 30 mg/gCr in cases with negative proteinuria, although the uPCR was a major predictive factor of a uACR ≥ 30 mg/gCr.

CONCLUSIONS

The uPCR (preferably determined using early-morning urine), including in dipstick-negative proteinuria cases with non-diabetic lifestyle-related diseases, can aid in the early detection of microalbuminuria.

TRIAL REGISTRATION

Retrospectively registered.

Risk prediction models for incident type 2 diabetes in Chinese people with intermediate hyperglycemia: a systematic literature review and external validation study

Background

People with intermediate hyperglycemia (IH), including impaired fasting glucose and/or impaired glucose tolerance, are at higher risk of developing type 2 diabetes (T2D) than those with normoglycemia. We aimed to evaluate the performance of published T2D risk prediction models in Chinese people with IH to inform them about the choice of primary diabetes prevention measures.

Methods

A systematic literature search was conducted to identify Asian-derived T2D risk prediction models, which were eligible if they were built on a prospective cohort of Asian adults without diabetes at baseline and utilized routinely-available variables to predict future risk of T2D. These Asian-derived and five prespecified non-Asian derived T2D risk prediction models were divided into BASIC (clinical variables only) and EXTENDED (plus laboratory variables) versions, with validation performed on them in three prospective Chinese IH cohorts: ACE (n = 3241), Luzhou (n = 1333), and TCLSIH (n = 1702). Model performance was assessed in terms of discrimination (C-statistic) and calibration (Hosmer–Lemeshow test).

Results

Forty-four Asian and five non-Asian studies comprising 21 BASIC and 46 EXTENDED T2D risk prediction models for validation were identified. The majority were at high (n = 43, 87.8%) or unclear (n = 3, 6.1%) risk of bias, while only three studies (6.1%) were scored at low risk of bias. BASIC models showed poor-to-moderate discrimination with C-statistics 0.52–0.60, 0.50–0.59, and 0.50–0.64 in the ACE, Luzhou, and TCLSIH cohorts respectively. EXTENDED models showed poor-to-acceptable discrimination with C-statistics 0.54–0.73, 0.52–0.67, and 0.59–0.78 respectively. Fifteen BASIC and 40 EXTENDED models showed poor calibration (P < 0.05), overpredicting or underestimating the observed diabetes risk. Most recalibrated models showed improved calibration but modestly-to-severely overestimated diabetes risk in the three cohorts. The NAVIGATOR model showed the best discrimination in the three cohorts but had poor calibration (P < 0.05).

Conclusions

In Chinese people with IH, previously published BASIC models to predict T2D did not exhibit good discrimination or calibration. Several EXTENDED models performed better, but a robust Chinese T2D risk prediction tool in people with IH remains a major unmet need.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12933-022-01622-5.

Factors associated with spinal instability in low back lumbar diseases with leg pain: Analysis of sagittal translation and segmental angulation

BACKGROUND

Determining the association between radiographic spinal instability assessment and lower back lumbar diseases with lower limb symptoms can contribute to evidence-based assessment and treatment in clinical practice and rehabilitation. Therefore, radiological evidence of lumbar spine instability assessment, such as sagittal translation (ST) and segmental angulation (SA), is clinically important.

OBJECTIVE

To identify factors associated with the assessment of spinal instability in lumbar disc herniation with leg pain and discogenic low back pain using ST and SA.

METHODS

We examined 112 patients with lumbar disc herniation with leg pain and 116 with discogenic low back pain at our clinic from 2016 to 2021. Data on age, gender, sports activities, and occupation were collected from medical records. Additionally, ST and SA of L4 and L5 during maximum trunk flexion and extension were measured using radiography. Simple and multiple logistic regression analyses were used for statistical analysis.

RESULTS

Simple logistic regression analysis showed that ST and SA (odds ratio [OR]: 1.11; 95% confidence interval [CI]: 1.03-1.19) were associated with lumbar disc herniation. Multiple logistic regression analysis showed that only ST was associated with lumbar disc herniation (OR: 2.29; 95% CI: 1.78-3.00).

CONCLUSION

Multiple logistic regression analysis showed that ST was associated with lumbar disc herniation with leg pain and had a stronger association than SA.

High incidence of type 2 diabetes in a population with normal range body mass index and individual prediction nomogram in Vietnam

AIMS

The study aimed at determining 5-year incidence and prediction nomogram for new-onset type 2 diabetes (T2D) in a middle-aged population in Vietnam.

METHODS

A population-based prospective study was designed to collect socio-economic, anthropometric, lifestyle and clinical data. Five-year T2D incidence was estimated and adjusted for age and sex. Hazard ratio (HR) for T2D was investigated using discrete-time proportional hazards model. T2D prediction model entering the most significant risk factors was developed using the multivariable logistic-regression algorithm. The corresponding prediction nomogram was constructed and checked for discrimination, calibration and clinical usefulness.

RESULTS

The age- and sex-adjusted incidence was 21.0 cases (95% CI: 12.2-40.0) per 1000 person-years in people with mean BMI of 22.2 (95% CI: 21.9-22.7 kg/m² ). The HRs (95% CI) for T2D were 1.14 (1.05-1.23) per 10 mmHg systolic blood pressure, 1.05 (1.03-1.08) per 1 cm waist circumference, 1.40 (1.13-1.73) per 1 mmol/L fasting blood glucose, 1.77 (1.15-2.71) per sleeping time (<6 h/day vs 6-7 h/day) and 2.12 (1.25-3.61) per residence (urban vs rural). The prediction nomogram for new-onset T2D had a good discrimination (area under curve: 0.711, 95% CI: 0.666-0.755) and fit calibration (mean absolute error: 0.009). For the predicted probability thresholds between 0.03 and 0.36, the nomogram showed a positive net benefit, without increasing the number of false positives.

CONCLUSION

This study highlighted an alarmingly high incidence of T2D in a middle-aged population with a normal range BMI in Vietnam. The individual prediction nomogram with decision curve analysis for new-onset T2D would be valuable for early detection, intervention and treatment of the condition.

Prediction Models for Type 2 Diabetes Risk in the General Population: A Systematic Review of Observational Studies

OBJECTIVES

This study aimed to provide an overview of prediction models of undiagnosed type 2 diabetes mellitus (U-T2DM) or the incident T2DM (I-T2DM) using the transparent reporting of a multivariable prediction model for individual prognosis or diagnosis (TRIPOD) checklist and the prediction model risk of the bias assessment tool (PROBAST).

DATA SOURCES

Both PUBMED and EMBASE databases were searched to guarantee adequate and efficient coverage.

STUDY SELECTION

Articles published between December 2011 and October 2019 were considered.

DATA EXTRACTION

For each article, information on model development requirements, discrimination measures, calibration, overall performance, clinical usefulness, overfitting, and risk of bias (ROB) was reported.

RESULTS

The median (interquartile range; IQR) number of the 46 study populations for model development was 5711 (1971 - 27426) and 2457 (2060 - 6995) individuals for I-T2DM and U-T2DM, respectively. The most common reported predictors were age and body mass index, and only the Qrisk-2017 study included social factors (e.g., Townsend score). Univariable analysis was reported in 46% of the studies, and the variable selection procedure was not clear in 17.4% of them. Moreover, internal and external validation was reported in 43% the studies, while over 63% of them reported calibration. The median (IQR) of AUC for I-T2DM models was 0.78 (0.74 - 0.82); the corresponding value for studies derived before October 2011 was 0.80 (0.77 - 0.83). The highest discrimination index was reported for Qrisk-2017 with C-statistics of 0.89 for women and 0.87 for men. Low ROB for I-T2DM and U-T2DM was assessed at 18% and 41%, respectively.

CONCLUSIONS

Among prediction models, an intermediate to poor quality was reassessed in several aspects of model development and validation. Generally, despite its new risk factors or new methodological aspects, the newly developed model did not increase our capability in screening/predicting T2DM, mainly in the analysis part. It was due to the lack of external validation of the prediction models.

Sex differences in the association between fatty liver and type 2 diabetes incidence in non-obese Japanese: A retrospective cohort study

Aims/Introduction

Asians develop type 2 diabetes at a lower body mass index (BMI) compared with other races, which is partly because of Asian‐specific fat depots. Sex plays a role in fat deposition, regardless of race. This retrospective cohort study aimed to investigate the association among fatty liver, sex and type 2 diabetes in non‐obese Japanese.

Materials and Methods

The participants in this study (13,596 men and 6,037 women) were aged 30–64 years, and had undergone health checkups between 2013 and 2015, in Aichi, Japan. Baseline BMI was categorized as follows: <18.5, 18.5–19.9, 20–22.9, 23–24.9, 25–27.4 and ≥27.5 kg/m². Fatty liver was diagnosed by abdominal ultrasonography. The joint effect of BMI and fatty liver on the incidence of type 2 diabetes was assessed, stratified by sex.

Results

During follow up, 738 men and 138 women developed type 2 diabetes. Compared with the BMI of 20–22.9 kg/m² without fatty liver group, the BMI of 20–22.9 kg/m² with fatty liver was associated with a higher risk of type 2 diabetes in men, but not in women. Furthermore, men with a BMI of 23–24.9 and 25–27.4 kg/m² without fatty liver had no significant type 2 diabetes risk, whereas women with a BMI of 23–24.9 and 25–27.4 kg/m², regardless of fatty liver, had an increased risk.

Conclusions

These results suggest the association between fatty liver and type 2 diabetes in non‐obese Asians is different by sex; fatty liver increases diabetes risk among male, not female, non‐obese Asians.

Development of a clinical risk score for incident diabetes: A 10-year prospective cohort study

Aims/Introduction

We developed a self‐assessable Korean Diabetes Risk score using the data of the Korean Genome and Epidemiology Study.

Materials and Methods

A total of 8,740 participants without diabetes at baseline were followed up biannually over a period of 10 years. We included variables that were significantly different between participants who developed diabetes mellitus and those who did not in the development cohort at baseline. We assigned a maximum score of 100 to the selected variable in each gender group. Next, the 10‐year probability of incident diabetes was calculated and validated in the validation cohort. Finally, we compared the predictive power of Korean Diabetes Risk score with models including fasting plasma glucose or glycated hemoglobin and other cohort models of Atherosclerosis Risk in Communities and Korea National Health and Nutrition Examination Survey.

Results

During a median follow‐up period of 9.7 years, 22.7% of the participants progressed to diabetes. The Korean Diabetes Risk score included age, living location (urban or rural area), waist circumference, hypertension, family history of diabetes and smoking history. The developed risk score yielded acceptable discrimination for incident diabetes (area under the curve 0.657) and the predictive power was improved when the model included fasting plasma glucose (area under the curve 0.690) or glycated hemoglobin (area under the curve 0.746). In addition, our model predicted incident diabetes more accurately than previous Western or Korean models.

Conclusions

This newly developed self‐assessable diabetes risk score is easily applicable to predict the future risk of diabetes even without the necessity for laboratory tests. This score is useful for the Korean diabetes prevention program, because high‐risk individuals can be easily screened.

Systematic review with meta-analysis of the epidemiological evidence relating smoking to type 2 diabetes

BACKGROUND

Evidence relating tobacco smoking to type 2 diabetes has accumulated rapidly in the last few years, rendering earlier reviews considerably incomplete.

AIM

To review and meta-analyse evidence from prospective studies of the relationship between smoking and the onset of type 2 diabetes.

METHODS

Prospective studies were selected if the population was free of type 2 diabetes at baseline and evidence was available relating smoking to onset of the disease. Papers were identified from previous reviews, searches on Medline and Embase and reference lists. Data were extracted on a range of study characteristics and relative risks (RRs) were extracted comparing current, ever or former smokers with never smokers, and current smokers with non-current smokers, as well as by amount currently smoked and duration of quitting. Fixed- and random-effects estimates summarized RRs for each index of smoking overall and by various subdivisions of the data: Sex; continent; publication year; method of diagnosis; nature of the baseline population (inclusion/exclusion of pre-diabetes); number of adjustment factors; cohort size; number of type 2 diabetes cases; age; length of follow-up; definition of smoking; and whether or not various factors were adjusted for. Tests of heterogeneity and publication bias were also conducted.

RESULTS

The literature searches identified 157 relevant publications providing results from 145 studies. Fifty-three studies were conducted in Asia and 53 in Europe, with 32 in North America, and seven elsewhere. Twenty-four were in males, 10 in females and the rest in both sexes. Fifteen diagnosed type 2 diabetes from self-report by the individuals, 79 on medical records, and 51 on both. Studies varied widely in size of the cohort, number of cases, length of follow-up, and age. Overall, random-effects estimates of the RR were 1.33 [95% confidence interval (CI): 1.28-1.38] for current vs never smoking, 1.28 (95%CI: 1.24-1.32) for current vs non-smoking, 1.13 (95%CI: 1.11-1.16) for former vs never smoking, and 1.25 (95%CI: 1.21-1.28) for ever vs never smoking based on, respectively, 99, 156, 100 and 100 individual risk estimates. Risk estimates were generally elevated in each subdivision of the data by the various factors considered (exceptions being where numbers of estimates in the subsets were very low), though there was significant (P < 0.05) evidence of variation by level for some factors. Dose-response analysis showed a clear trend of increasing risk with increasing amount smoked by current smokers and of decreasing risk with increasing time quit. There was limited evidence of publication bias.

CONCLUSION

The analyses confirmed earlier reports of a modest dose-related association of current smoking and a weaker dose-related association of former smoking with type 2 diabetes risk.

Development of a Point System to Predict Discharge to Home for Acute Stroke Patients

BACKGROUND

While in an acute hospital setting, it is challenging for clinicians to make discharge decisions due to the multifactorial process and individual patient characteristics.

OBJECTIVE

To evaluate and develop a scoring system utilizing the Japan Rehabilitation Database (JRD) to identify acute stroke patients with a high possibility of discharge to home.

DESIGN

Retrospective observational cohort study.

SETTING

Thirty-seven acute hospitals in Japan.

PARTICIPANTS

A total of 10 270 patients admitted to the acute hospitals with stroke were identified. The inclusion criteria were (1) admission within 3 days of onset and (2) admission from home. Exclusion criteria were (1) incomplete data and (2) death in hospital. A total of 4216 patients were included in the study.

INTERVENTION

Not applicable.

MAIN OUTCOME MEASUREMENTS

Discharge destination from acute care hospital, that is, home versus other locations.

RESULTS

In the multivariate logistic regression, age, stroke type, Barthel Index on admission, modified Rankin scale on admission, the National Institutes of Health Stroke Scale on admission, and extent of paralysis were retained. When the cutoff point was 33, the scoring system showed a sensitivity of 80.4% and specificity of 80.3%. The area under curve (AUC) was 0.88. On evaluating the predictive performance, the model showed a sensitivity of 78.2% and a specificity of 78.5% with an AUC = 0.86.

CONCLUSIONS

We developed a point system to identify acute stroke patients with a high possibility of discharge to home using the JRD. This point system may provide useful information for clinicians to plan the discharge of acute stroke patients.

The Dose-Response Relationship between Alcohol Consumption and the Risk of Type 2 Diabetes among Asian Men: A Systematic Review and Meta-Analysis of Prospective Cohort Studies

The objective of this review was to provide a summary of the literature on the dose-response relationship between alcohol consumption and risk of type 2 diabetes (T2D) in Asian populations, particularly men. The present study was recorded in PROSPERO as CRD 42019121073. We searched the PubMed-Medline, Web of Science, and Cochrane Library for studies published in any language since the database inception to January 2019. Prospective cohort studies were included in the meta-analysis. Relative risks (RRs) and 95% confidence intervals (CIs) were calculated for random-effects models and dose-response meta-analyses. In total, 8 prospective cohort studies were included. High alcohol intake was significantly associated with increased risk of T2D (RR = 1.16, 95% CI: 1.04-1.29; Q statistic p = 0.326) compared to the lowest category of alcohol intake. Nonlinear association was observed between alcohol consumption and T2D risk in men (p = 0.003). Dose-wise, consuming ≤57 g/day of alcohol was not associated with the risk of T2D in this study; however, alcohol intake >57 g/day was associated with increased risk of T2D in men. Overall, the association between alcohol consumption and T2D among Asian men was J-shaped. Lifestyle recommendations for prevention of T2D should include advice on limiting alcohol intake. This trial is registered with Prospero registration: CRD 42019121073.