Is early pregnancy hemoglobin A1c useful to predict gestational diabetes mellitus diagnosed during mid pregnancy?

To verify whether hemoglobin A1c (HbA1c) levels in early pregnancy can predict the diagnosis of gestational diabetes mellitus (GDM) in mid-pregnancy. This was a retrospective cohort study of 2008 pregnant women who delivered singletons at the Yokohama City university Medical Center. Concomitant or history of diabetes mellitus and overt diabetes in pregnancy were excluded. Pregnant women at high risk for GDM underwent a one-step 75-g oral glucose tolerance test (OGTT) during mid-pregnancy. For other pregnant women, GDM was diagnosed by a two-step 75-g oral glucose tolerance test (OGTT) when the 50-g glucose challenge test result in mid-pregnancy was ≥140 mg/dL. The thresholds for 75-g OGTT followed those of the International Association of Diabetes and Pregnancy Study Group (IADPSG) criteria (92-180-153 mg/dL). The relationship between HbA1c level measured at <20 weeks of gestation and GDM diagnosis at mid pregnancy was assessed using a receiver operating characteristic curve (ROC); area under the curve (AUC) and optimal cutoff value of HbA1c, predictive of GDM were calculated. The median HbA1c level at <20 weeks of gestation was 5.3%, and 8.5% of women were diagnosed with GDM. In the ROC curve of the GDM diagnosis rate by HbA1c level, AUC was 0.706, and the optimal cutoff value was 5.4%, with a sensitivity of 0.6176, specificity of 0.6834, positive predictive value of 15.4%, and negative predictive value of 95.1%. Although HbA1c at less than 20 weeks of gestation is acceptable discrimination as a diagnostic tool of GDM in mid-pregnancy, it is not clinically useful to predict GDM in mid-pregnancy.

Nakanishi S ，Aoki S ，Iwama N ，Yasuhi I ，Sugiyama T ，Miyakoshi K ... -  《-》

Comparison of Two Modern Survival Prediction Tools, SORG-MLA and METSSS, in Patients With Symptomatic Long-bone Metastases Who Underwent Local Treatment With Surgery Followed by Radiotherapy and With Radiotherapy Alone.

Survival estimation for patients with symptomatic skeletal metastases ideally should be made before a type of local treatment has already been determined. Currently available survival prediction tools, however, were generated using data from patients treated either operatively or with local radiation alone, raising concerns about whether they would generalize well to all patients presenting for assessment. The Skeletal Oncology Research Group machine-learning algorithm (SORG-MLA), trained with institution-based data of surgically treated patients, and the Metastases location, Elderly, Tumor primary, Sex, Sickness/comorbidity, and Site of radiotherapy model (METSSS), trained with registry-based data of patients treated with radiotherapy alone, are two of the most recently developed survival prediction models, but they have not been tested on patients whose local treatment strategy is not yet decided. (1) Which of these two survival prediction models performed better in a mixed cohort made up both of patients who received local treatment with surgery followed by radiotherapy and who had radiation alone for symptomatic bone metastases? (2) Which model performed better among patients whose local treatment consisted of only palliative radiotherapy? (3) Are laboratory values used by SORG-MLA, which are not included in METSSS, independently associated with survival after controlling for predictions made by METSSS? Between 2010 and 2018, we provided local treatment for 2113 adult patients with skeletal metastases in the extremities at an urban tertiary referral academic medical center using one of two strategies: (1) surgery followed by postoperative radiotherapy or (2) palliative radiotherapy alone. Every patient's survivorship status was ascertained either by their medical records or the national death registry from the Taiwanese National Health Insurance Administration. After applying a priori designated exclusion criteria, 91% (1920) were analyzed here. Among them, 48% (920) of the patients were female, and the median (IQR) age was 62 years (53 to 70 years). Lung was the most common primary tumor site (41% [782]), and 59% (1128) of patients had other skeletal metastases in addition to the treated lesion(s). In general, the indications for surgery were the presence of a complete pathologic fracture or an impending pathologic fracture, defined as having a Mirels score of ≥ 9, in patients with an American Society of Anesthesiologists (ASA) classification of less than or equal to IV and who were considered fit for surgery. The indications for radiotherapy were relief of pain, local tumor control, prevention of skeletal-related events, and any combination of the above. In all, 84% (1610) of the patients received palliative radiotherapy alone as local treatment for the target lesion(s), and 16% (310) underwent surgery followed by postoperative radiotherapy. Neither METSSS nor SORG-MLA was used at the point of care to aid clinical decision-making during the treatment period. Survival was retrospectively estimated by these two models to test their potential for providing survival probabilities. We first compared SORG to METSSS in the entire population. Then, we repeated the comparison in patients who received local treatment with palliative radiation alone. We assessed model performance by area under the receiver operating characteristic curve (AUROC), calibration analysis, Brier score, and decision curve analysis (DCA). The AUROC measures discrimination, which is the ability to distinguish patients with the event of interest (such as death at a particular time point) from those without. AUROC typically ranges from 0.5 to 1.0, with 0.5 indicating random guessing and 1.0 a perfect prediction, and in general, an AUROC of ≥ 0.7 indicates adequate discrimination for clinical use. Calibration refers to the agreement between the predicted outcomes (in this case, survival probabilities) and the actual outcomes, with a perfect calibration curve having an intercept of 0 and a slope of 1. A positive intercept indicates that the actual survival is generally underestimated by the prediction model, and a negative intercept suggests the opposite (overestimation). When comparing models, an intercept closer to 0 typically indicates better calibration. Calibration can also be summarized as log(O:E), the logarithm scale of the ratio of observed (O) to expected (E) survivors. A log(O:E) > 0 signals an underestimation (the observed survival is greater than the predicted survival); and a log(O:E) < 0 indicates the opposite (the observed survival is lower than the predicted survival). A model with a log(O:E) closer to 0 is generally considered better calibrated. The Brier score is the mean squared difference between the model predictions and the observed outcomes, and it ranges from 0 (best prediction) to 1 (worst prediction). The Brier score captures both discrimination and calibration, and it is considered a measure of overall model performance. In Brier score analysis, the "null model" assigns a predicted probability equal to the prevalence of the outcome and represents a model that adds no new information. A prediction model should achieve a Brier score at least lower than the null-model Brier score to be considered as useful. The DCA was developed as a method to determine whether using a model to inform treatment decisions would do more good than harm. It plots the net benefit of making decisions based on the model's predictions across all possible risk thresholds (or cost-to-benefit ratios) in relation to the two default strategies of treating all or no patients. The care provider can decide on an acceptable risk threshold for the proposed treatment in an individual and assess the corresponding net benefit to determine whether consulting with the model is superior to adopting the default strategies. Finally, we examined whether laboratory data, which were not included in the METSSS model, would have been independently associated with survival after controlling for the METSSS model's predictions by using the multivariable logistic and Cox proportional hazards regression analyses. Between the two models, only SORG-MLA achieved adequate discrimination (an AUROC of > 0.7) in the entire cohort (of patients treated operatively or with radiation alone) and in the subgroup of patients treated with palliative radiotherapy alone. SORG-MLA outperformed METSSS by a wide margin on discrimination, calibration, and Brier score analyses in not only the entire cohort but also the subgroup of patients whose local treatment consisted of radiotherapy alone. In both the entire cohort and the subgroup, DCA demonstrated that SORG-MLA provided more net benefit compared with the two default strategies (of treating all or no patients) and compared with METSSS when risk thresholds ranged from 0.2 to 0.9 at both 90 days and 1 year, indicating that using SORG-MLA as a decision-making aid was beneficial when a patient's individualized risk threshold for opting for treatment was 0.2 to 0.9. Higher albumin, lower alkaline phosphatase, lower calcium, higher hemoglobin, lower international normalized ratio, higher lymphocytes, lower neutrophils, lower neutrophil-to-lymphocyte ratio, lower platelet-to-lymphocyte ratio, higher sodium, and lower white blood cells were independently associated with better 1-year and overall survival after adjusting for the predictions made by METSSS. Based on these discoveries, clinicians might choose to consult SORG-MLA instead of METSSS for survival estimation in patients with long-bone metastases presenting for evaluation of local treatment. Basing a treatment decision on the predictions of SORG-MLA could be beneficial when a patient's individualized risk threshold for opting to undergo a particular treatment strategy ranged from 0.2 to 0.9. Future studies might investigate relevant laboratory items when constructing or refining a survival estimation model because these data demonstrated prognostic value independent of the predictions of the METSSS model, and future studies might also seek to keep these models up to date using data from diverse, contemporary patients undergoing both modern operative and nonoperative treatments. Level III, diagnostic study.

Lee CC ，Chen CW ，Yen HK ，Lin YP ，Lai CY ，Wang JL ，Groot OQ ，Janssen SJ ，Schwab JH ，Hsu FM ，Lin WH ... -  《-》

Glycated albumin levels in the third trimester of women with gestational diabetes mellitus are associated with adverse pregnancy-related outcomes.

Glycated albumin (GA) levels have been considered as a promising biomarker for estimating glycemic control during pregnancy, but the relationship between GA levels and the incidence of adverse pregnancy outcomes in women with gestational diabetes mellitus (GDM) remains unclear. Our study aimed to investigate the relationship between GA levels during the third trimester and 13 different adverse pregnancy-related outcomes among women with GDM in China. We retrospectively extracted clinical data from the medical records of 819 pregnant women with GDM who underwent prenatal examinations and child delivery at the Affiliated Hospital of Qingdao University between January 2022 and October 2022. The cohort was divided into GA-high (GA-H) and GA-low (GA-L) groups based on the median GA level of 10.6%. Then, the incidence rates of 13 specific adverse pregnancy outcomes were compared between the two groups. Furthermore, we estimated the mean GA levels in pregnant GDM women with or without specific adverse outcomes. Multivariate logistic regression analysis was performed to assess whether the GA levels (high or low) were independent risk factors for specific adverse outcomes in pregnant women with GDM. Receiver operating characteristic (ROC) curve analysis was performed to assess the predictive value of GA levels for the adverse pregnant outcomes in women with GDM. E-value for sensitivity analysis was performed to assess the robustness of the findings to unmeasured confoundings. We included 819 pregnant women with GDM, whose average age was 33.09 ± 4.47 years, average pre-pregnancy BMI was 23.51 ± 3.67 kg/m2, and the average gestational week in which GDM diagnosed was 24.80 ± 1.79 weeks. The analysis showed that 80.71% (661/819) pregnant women with GDM were associated with adverse pregnancy-related outcomes. Pregnant women in the GA-L group showed higher incidence of the premature rupture of membranes (PROM), whereas those in the GA-H group showed higher incidence of neonatal hypoglycemia. The GA levels showed acceptable clinical performance for predicting neonatal hypoglycemia with an area under the ROC curve (AUC) value of 0.700 (P = 0.010), sensitivity of 71.4%, and specificity of 70.2%. The optimal cut off value for GA was 11.55%. This study demonstrated that GA levels were significantly associated with specific adverse pregnancy outcomes, especially PROM and neonatal hypoglycemia. Furthermore, GA levels in the third trimester showed acceptable clinical performance for predicting neonatal hypoglycemia among pregnant women with GDM. In the future, the potential role of GA as a predictor of adverse pregnancy outcomes need to be further confirmed and explored in GDM women.

Pan Y ，Gu R ，Li Q ，Wang J ，Zhang Y ，Zhao L ，Wu Y ，Wei L ... -  《BMC Pregnancy and Childbirth》

Multiple positive points during the 75 g oral glucose tolerance test are good predictors for early insulin therapy in gestational diabetes mellitus diagnosed before 24 gestational weeks.

This study evaluated the risk factors for insulin therapy before 24 gestational weeks (early insulin therapy) in pregnant women with gestational diabetes diagnosed before 24 gestational weeks (E-GDM). This study included 530 singleton mothers with E-GDM who underwent a 75 g oral glucose tolerance test (OGTT) in the first trimester at Keio University Hospital between January 2013 and December 2021. E-GDM can be classified according to its management into only diet therapy until delivery (Diet E-GDM), insulin therapy started before 24 gestational weeks (EarlyIns E-GDM), and insulin therapy started after 24 gestational weeks (LateIns E-GDM). We analyzed the risk factors for EarlyIns E-GDM. Patients with EarlyIns E-GDM had a significantly higher maternal age at delivery, pre-pregnancy BMI, first trimester hemoglobin A1c, 1 h plasma glucose levels (1 h-PG), and 2 h-PG, as well as a more pronounced initial increase and subsequent decrease, compared with those in the Diet E-GDM group. However, the Apgar scores at both 1 and 5 min were significantly lower in patients with EarlyIns E-GDM than in those with Diet E-GDM. The number of abnormal values in the OGTT showed the largest area under the receiver operating characteristic curve (AUC) for predicting EarlyIns E-GDM (0.83, 95% confidence interval [CI]: 0.79-0.86), followed by the 1 h-PG value (AUC: 0.81, 95% CI: 0.77-0.85). The initial increase showed the third largest AUC (0.78, 95% CI: 0.74-0.82). Although further research is needed, our data suggest the importance of early insulin therapy in cases of E-GDM with multiple abnormal OGTT values, especially with high 1 h-PG levels and initial increase.

Kasuga Y ，Takahashi M ，Kajikawa K ，Akita K ，Tamai J ，Fukuma Y ，Tanaka Y ，Hasegawa K ，Otani T ，Ikenoue S ，Tanaka M ... -  《-》

Development and validation of prediction models for fetal growth restriction and birthweight: an individual participant data meta-analysis.

Allotey J ，Archer L ，Coomar D ，Snell KI ，Smuk M ，Oakey L ，Haqnawaz S ，Betrán AP ，Chappell LC ，Ganzevoort W ，Gordijn S ，Khalil A ，Mol BW ，Morris RK ，Myers J ，Papageorghiou AT ，Thilaganathan B ，Da Silva Costa F ，Facchinetti F ，Coomarasamy A ，Ohkuchi A ，Eskild A ，Arenas Ramírez J ，Galindo A ，Herraiz I ，Prefumo F ，Saito S ，Sletner L ，Cecatti JG ，Gabbay-Benziv R ，Goffinet F ，Baschat AA ，Souza RT ，Mone F ，Farrar D ，Heinonen S ，Salvesen KÅ ，Smits LJ ，Bhattacharya S ，Nagata C ，Takeda S ，van Gelder MM ，Anggraini D ，Yeo S ，West J ，Zamora J ，Mistry H ，Riley RD ，Thangaratinam S ... -  《-》