Aim We aimed to compare the neutrophil‐to‐lymphocyte ratio (NLR) in tubo‐ovarian abscess (TOA) patients who responded to medical treatment or who underwent surgical intervention due to medical treatment failure. Methods The files of the patients, hospitalized in our Obstetrics and Gynecology Department with TOA diagnosis between August 2015 and December 2017, were evaluated retrospectively. The conservative management group was comprised of 38 of the 81 patients (46.9%) who responded to sole medical treatment with the triple antibiotic regimen (gentamicin‐clindamycin‐ampicillin) and the surgical intervention group was comprised of 43 patients (53.1%) who did not respond to medical treatment and needed further surgery and/or interventional radiologic abscess drainage. Demographic and clinical data, imaging findings, and laboratory results including NLR were compared between two groups. Results There were statistically significant differences between the groups in terms of age, TOA diameter, white blood cell and neutrophil counts, and NLR levels (P < 0.05). The mean NLR was 7.4 ± 5.8 for the conservative management group and 10.3 ± 5.8 for the surgical intervention group (P = 0.004). The area under the curve (AUC) for NLR was 0.69 (threshold value was ≥6.97, 95% confidence interval, sensitivity 79.1%, specificity 57.9%). On multiple regression analysis, a significant correlation was identified between age, NLR and resistance to the medical treatment. Conclusion Neutrophil‐to‐lymphocyte ratio and age are significantly higher in patients with medical treatment failure and NLR could be used as a novel marker in addition to white blood cell in the prediction of medical treatment failure in TOA patients.

Reliable modeling of novel commutative cases of COVID-19 (CCC) is essential for determining hospitalization needs and providing the benchmark for health-related policies. The current study proposes multi-regional modeling of CCC cases for the first scenario using autoregressive integrated moving average (ARIMA) based on automatic routines (AUTOARIMA), ARIMA with maximum likelihood (ARIMAML), and ARIMA with generalized least squares method (ARIMAGLS) and ensembled (ARIMAML-ARIMAGLS). Subsequently, different deep learning (DL) models viz: long short-term memory (LSTM), random forest (RF), and ensemble learning (EML) were applied to the second scenario to predict the effect of forest knowledge (FK) during the COVID-19 pandemic. For this purpose, augmented Dickey–Fuller (ADF) and Phillips–Perron (PP) unit root tests, autocorrelation function (ACF), partial autocorrelation function (PACF), Schwarz information criterion (SIC), and residual diagnostics were considered in determining the best ARIMA model for cumulative COVID-19 cases (CCC) across multi-region countries. Seven different performance criteria were used to evaluate the accuracy of the models. The obtained results justified both types of ARIMA model, with ARIMAGLS and ensemble ARIMA demonstrating superiority to the other models. Among the DL models analyzed, LSTM-M1 emerged as the best and most reliable estimation model, with both RF and LSTM attaining more than 80% prediction accuracy. While the EML of the DL proved merit with 96% accuracy. The outcomes of the two scenarios indicate the superiority of ARIMA time series and DL models in further decision making for FK.

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BackgroundThere is a paucity of data on whether pre-operative walking and functional capacity has a direct association with post-operative gastrointestinal function in patients who have undergone surgery to treat gynecologic cancers.ObjectiveTo explore the relationship between pre-operative walking and post-operative recovery of bowel function.MethodsThis randomized trial was performed from January 1, 2018 to August 31, 2018. All patients had a diagnosis of endometrial or ovarian cancer and were scheduled for comprehensive staging. Group A served as the control group who did not walk regularly on the last night before surgery. Patients in group B walked for 30 min at an average speed of 3 km/h from 20.00 to 20.30 and 21.30. to 22.00 on the last night before surgery under the supervision of a nurse or doctor. The study was registered with clinicaltrials.gov (no: NCT03553121).ResultsA total of 85 patients were enrolled: 43 patients were assigned to the walking group and 42 to the control group. There were no significant differences in demographics between the groups. Median age was 57.3±8.5 in the control and 59.9±9.1 in the walking group. In addition, 28 patients had endometrial cancer and 14 had ovarian cancer in the control group. 33 patients and 10 patients in the walking group had endometrial and ovarian cancer, respectively. The mean time to first flatus was shorter in the walking group than in the control group (32.5±10.4 vs 40.6±16.9 hours, respectively; p=0.010). In addition, the time to first defecation was significantly shorter in the walking group (62.8±26.7 vs 91.4±51.8 hours; p=0.002). Patients who walked before surgery were less likely to have post-operative paralytic ileus (25.0% vs 60.7%; p=0.003). Walking before the operative period and laparoscopic surgery independently protected against the development of post-operative paralytic ileus.ConclusionWalking before surgery expedited time to bowel motility and ability to tolerate food. In addition, this method significantly decreased the risk of post-operative paralytic ileus.We consider that walking before surgery may be integrated into the pre-operative management of patients under going surgery for gynecologic cancers.Clinical trial registrationclinicaltrial.org record number: NCT03553121