AimsTo validate the perfusion, extent, depth, infection and sensation (PEDIS) classification system and to make the clinical practice easier, we created a score system and compared this system with two previously published common score systems.MethodsA retrospective cohort study was conducted on patients with diabetic foot ulcer (DFU) attending our hospital (n=364) from May 2007 to September 2013. Participants’ characteristics and all variables composing the PEDIS classification system were assessed.ResultsDuring a median follow-up of 25 months (range 6-82), ulcers healed in 217 of the 364 patients (59.6%), remained unhealed in 37 patients (10.2%), and were resolved by amputation in 62 patients (17.0%); 48 patients (13.2%) died. When measured using the PEDIS classification system, the outcome of DFU deteriorated with increasing severity of each subcategory. Additionally, longer ulcer history, worse perfusion of lower limb, a larger extent of the ulcer, a deeper wound, more severe infection, and loss of protective sensation were independent predictors of adverse outcome. More importantly, the new PEDIS score system showed good diagnostic accuracy, especially when compared with the SINBAD and Wagner score systems.ConclusionsThe PEDIS classification system, which encompasses relevant variables that contribute to the outcome of DFU and has excellent capacity for predicting the ulcer outcome, demonstrated acceptable accuracy. The PEDIS classification system might be useful in clinical practice and research both for the anticipation of health care costs and for comparing patient subgroups.

BackgroundChina’s rapid transition in healthcare service system has posed considerable challenges for the primary care system. Little is known regarding the capacity of township hospitals (THs) to deliver surgical care in rural China with over 600 million lives. We aimed to ascertain its current performance, barriers, and summary lessons for its re-building in central China.MethodsThis study was conducted in four counties from two provinces in central China. The New Rural Cooperative Medical System (NRCMS) claim data from two counties in Hubei province was analyzed to describe the current situation of surgical care provision. Based on previous studies, self-administered questionnaire was established to collect key indicators from 60 THs from 2011 to 2015, and social and economic statuses of the sampling townships were collected from the local statistical yearbook. Semi-structured interviews were conducted among seven key administrators in the THs that did not provide appendectomy care in 2015. Determinants of appendectomy care provision were examined using a negative binominal regression model.ResultsFirst, with the rapid increase in inpatient services provided by the THs, their proportion of surgical service provision has been nibbled by out-of-county facilities. Second, although DY achieved a stable performance, the total amount of appendectomy provided by the 60 THs decreased to 589 in 2015 from 1389 in 2011. Moreover, their proportion reduced to 26.77% in 2015 from 41.84% in 2012. Third, an increasing number of THs did not provide appendectomy in 2015, with the shortage of anesthesiologists and equipment as the most mentioned reasons (46.43%). Estimation results from the negative binomial model indicated that the annual average per capita disposable income and tightly integrated delivery networks (IDNs) negatively affected the amount of appendectomy provided by THs. By contrast, the probability of appendectomy provision by THs was increased by performance-related payment (PRP). Out-of-pocket (OOP) cost gap of appendectomy services between the two different levels of facilities, payment method, and the size of THs presented no observable improvement to the likelihood of appendectomy care in THs.ConclusionThe county-level health system did not effectively respond to the continuously increasing surgical care need. The surgical capacity of THs declined with the surgical patterns’ simplistic and quantity reduction. Deficits and critical challenges for surgical capacity building in central China were identified, including shortage of human resources and medical equipment and increasing income. Moreover, tight IDNs do not temporarily achieve capacity building. Therefore, the reimbursement rate should be further ranged, and physicians should be incentivized appropriately. The administrators, policy makers, and medical staff of THs should be aware of these findings owing to the potential benefits for the capacity building of the rural healthcare system.

BackgroundChina poverty reduction policy (PRP) addresses two important elements: the targeted poverty reduction (TPA) project since 2015 in line with social assistance policy as national policy; and reducing inequality in health services utilization by making provision of medical financial assistance (MFA). Therefore, this study aims to assess the effects of the PRP in health services utilization (both inpatient and outpatient services) among the central and western rural poor of China.MethodsThe study conducted household survey and applied propensity score matching (PSM) method to assess the effects of the PRP on health services utilization among the rural poor of Central and Western China. A sensitivity test was also performed on the PSM results to test their robustness.ResultsKey findings showed 17.6% of respondents were the beneficial of PRP. The average treatment effects on the treated (ATT) of the PRP on the inpatient visits within one year was found significantly positive (P = 0.026).ConclusionThere has been relationship between PRP with medical financial assistance and reduction of inequality in health services utilization by the poorer, in particular to accessing the inpatient services from the county or township hospitals of China. Policy makers should pay attention for making provision of improving responsiveness of supply, when subsidizing on the demand side.

The aim of this study was to describe the characteristics of diabetic foot ulcer (DFU) patients with anemia and assess the relationship between anemia and DFU outcome. A retrospective cohort study was conducted on patients with DFU who attended our hospital from May 2007 to September 2014. All of the variables in the DFU patients with and without anemia were compared. In this study, 353 subjects were included, anemia was present in 236 patients (66.9%). These patients were significantly male, more likely to be a smoker, had a lower level of serum albumin and worse kidney function, more likely to use at least 2 types of antibiotics and had a worse perfusion of the lower limb, a larger and deeper ulcer and a more severe infection. A multivariate analysis showed that male sex, lower serum albumin, and worse kidney function were independent predictors of anemia in DFU patients. Additionally, in multivariate models, anemia was one of the variables that was most significantly associated with adverse outcomes and with similar findings for secondary outcomes. Receiver operating characteristic analysis determined a hemoglobin cutoff of 12.3 g/dL (females) and 12.1 g/dL (males) to identify a high-risk population of DFU patients who would have adverse outcomes. So anemia is common in patients with DFU. Although typically mild or moderate, anemia has been associated with substantial morbidity and mortality in patients with DFU.

Purpose To investigate the differential clinical and computed tomography (CT) characteristics of pulmonary nonabsorbable inflammatory and malignant subsolid nodules (SSNs) with a solid component ≤5 mm. Patients and Methods We retrospectively analyzed 576 consecutive patients who underwent surgical resection and had SSNs with a solid component ≤5 mm on CT images. These patients were divided into inflammatory and malignant groups according to pathology. Their clinical and imaging data were analyzed and compared. Multiple logistic regression analysis was used to identify independent prognostic factors differentiating inflammatory from malignant SSNs. Furthermore, 146 consecutive patients were included as internal validation cohort to test the prediction efficiency of this model. Results Significant differences in 11 clinical characteristics and CT features were found between both groups ( P < 0.05). Presence of respiratory symptoms, distribution of middle/lower lobe, irregular shape, part-solid nodule (PSNs), CT value of ground-glass opacity (GGO) areas <−657 Hu, presence of abnormal intra-nodular vessel sign, and interlobular septal thickening were the most effective factors for diagnosing nonabsorbable inflammatory SSNs, with an AUC (95% CI), accuracy, sensitivity, and specificity of 0.843 (95% CI: 0.811–0.872), 89.76%, 72.86%, and 81.23%, respectively. The internal validation cohort obtained an AUC (95% CI), accuracy, sensitivity, and specificity of 0.830 (95% CI: 0.759–0.887), 83.56%, 73.91%, and 76.42%, respectively. Conclusion Nonabsorbable inflammatory and malignant SSNs with a solid component ≤5 mm exhibited different clinical and imaging characteristics.

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BackgroundBased on the “seed and soil” theory proposed by previous studies, we aimed to develop and validate a combined model of machine learning for predicting lymph node metastasis (LNM) in patients with peripheral lung adenocarcinoma (PLADC).MethodsRadiomics models were developed in a primary cohort of 390 patients (training cohort) with pathologically confirmed PLADC from January 2016 to August 2018. The patients were divided into the LNM (−) and LNM (+) groups. Thereafter, the patients were subdivided according to TNM stages N0, N1, N2, and N3. Radiomic features from unenhanced computed tomography (CT) were extracted. Radiomic signatures of the primary tumor (R1) and adjacent pleura (R2) were built as predictors of LNM. CT morphological features and clinical characteristics were compared between both groups. A combined model incorporating R1, R2, and CT morphological features, and clinical risk factors was developed by multivariate analysis. The combined model’s performance was assessed by receiver operating characteristic (ROC) curve. An internal validation cohort containing 166 consecutive patients from September 2018 to November 2019 was also assessed.ResultsThirty-one radiomic features of R1 and R2 were significant predictors of LNM (all P &lt; 0.05). Sex, smoking history, tumor size, density, air bronchogram, spiculation, lobulation, necrosis, pleural effusion, and pleural involvement also differed significantly between the groups (all P &lt; 0.05). R1, R2, tumor size, and spiculation in the combined model were independent risk factors for predicting LNM in patients with PLADC, with area under the ROC curves (AUCs) of 0.897 and 0.883 in the training and validation cohorts, respectively. The combined model identified N0, N1, N2, and N3, with AUCs ranging from 0.691–0.927 in the training cohort and 0.700–0.951 in the validation cohort, respectively, thereby indicating good performance.ConclusionCT phenotypes of the primary tumor and adjacent pleura were significantly associated with LNM. A combined model incorporating radiomic signatures, CT morphological features, and clinical risk factors can assess LNM of patients with PLADC accurately and non-invasively.

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