Nomogram for predicting postoperative pulmonary complications in spinal tumor patients.

OBJECTIVES: Although several independent risk factors for postoperative pulmonary complications (PPCs) after spinal tumor surgery have been studied, a simple and valid predictive model for PPC occurrence after spinal tumor surgery has not been developed. PATIENTS AND METHODS: We collected data from patients who underwent elective spine surgery for a spinal tumor between 2013 and 2020 at a tertiary hospital in China. Data on patient characteristics, comorbidities, preoperative examinations, intraoperative variables, and clinical outcomes were collected. We used univariable and multivariable logistic regression models to assess predictors of PPCs and developed and validated a nomogram for PPCs. We evaluated the performance of the nomogram using the area under the receiver operating characteristic curve (ROC), calibration curves, the Brier Score, and the Hosmer-Lemeshow (H-L) goodness-of-fit test. For clinical use, decision curve analysis (DCA) was conducted to identify the model's performance as a tool for supporting decision-making. RESULTS: Among the participants, 61 (12.4%) individuals developed PPCs. Clinically significant variables associated with PPCs after spinal tumor surgery included BMI, tumor location, blood transfusion, and the amount of blood lost. The nomogram incorporating these factors showed a concordance index (C-index) of 0.755 (95% CI: 0.688-0.822). On internal validation, bootstrapping with 1000 resamples yielded a bias-corrected area under the receiver operating characteristic curve of 0.733, indicating the satisfactory performance of the nomogram in predicting PPCs. The calibration curve demonstrated accurate predictions of observed values. The decision curve analysis (DCA) indicated a positive net benefit for the nomogram across most predicted threshold probabilities. CONCLUSIONS: We have developed a new nomogram for predicting PPCs in patients who undergo spinal tumor surgery.

Beam wander of a partially coherent Airy beam in oceanic turbulence.

The beam wander of a partially coherent Airy beam in oceanic turbulence is investigated with the help of the extended Huygens-Fresnel integral formula. Analytical expression for the second-order moment and the beam wander of a partially coherent Airy beam propagating in oceanic turbulence is derived. From the numerical results based on the analytical formula, we find that increasing the dissipation rate of turbulent kinetic energy or decreasing the dissipation rate of mean-square temperature and relative strength of temperature and salinity fluctuations of oceanic turbulence tends to decrease the wander effect of a partially coherent Airy beam. Moreover, it is found that increasing the transverse scale factor and wavelength or decreasing the coherent length and exponential truncation factor of a partially coherent Airy beam decreases beam wander in oceanic turbulence. Our results will be useful in optical underwater communications and laser defense.

Mediators of the association between depression and migraine: a mendelian randomization study.

Background: An association between depression and migraine has been reported in observational studies; however, conventional observational studies are prone to bias. This study aims to investigate the causal relationship between depression and migraine and to quantify the mediating effects of known risk factors. Methods: We applied two-sample Mendelian randomization and utilized single nucleotide polymorphisms as genetic instruments for exposure (depression) and mediators (sleep traits). We utilized summary data on genome-wide association studies for depression, sleep-related traits mediators and migraine. For depression, genome-wide association studies (depression) were utilized as a test cohort for the primary analysis. Moreover, genome-wide association studies (major depressive disorder) were utilized to test the stability of the results for the validation cohort. IVW and MR-Egger regression were applied to test the heterogeneity, and Cochran's Q statistics were calculated to quantitatively evaluate the heterogeneity. MR-PRESSO analyses were utilized to examine and correct possible horizontal pleiotropy through removing outliers, and leave-one-out analyses were utilized to identify outlier SNPs. Results: Genetically predicted depression was associated with migraine (OR = 1.321, 95% CI: 1.184-1.473, p < 0.001). Furthermore, risk factors insomnia was associated with migraine risk (OR = 1.766, 95% CI: 1.120-2.784, p = 0.014). The mediator insomnia accounted for 19.5% of the total effect of depression on migraine. Conclusion: These results support a potential causal effect of depression on migraine, partly mediated by insomnia. Therefore, the enhancement of sleep quality and difficulty in falling asleep may reduce the migraine burden occasioned by depression.