Background
Hydrocephalus (HCP) is one of the most significant concerns in neurosurgical patients because it can cause increased intracranial pressure (ICP), resulting in mortality and morbidity. To date, machine learning (ML) has been helpful in predicting continuous outcomes. The primary objective of the present study was to identify the factors correlated with ICP, while the secondary objective was to compare the predictive performances among linear, non-linear, and ML regression models for ICP prediction.
Methods A total of 412 patients with various types of HCP who had undergone ventriculostomy was retrospectively included in the present study, and intraoperative ICP was recorded following ventricular catheter insertion. Several clinical factors and imaging parameters were analyzed for the relationship with ICP by linear correlation. The predictive performance of ICP was compared among linear, non-linear, and ML regression models.
Results Optic nerve sheath diameter (ONSD) had a moderately positive correlation with ICP (r=0.530, P<0.001), while several ventricular indexes were not statistically significant in correlation with ICP. For prediction of ICP, random forest (RF) and extreme gradient boosting (XGBoost) algorithms had low mean absolute error and root mean square error values and high R2 values compared to linear and non-linear regression when the predictive model included ONSD and ventricular indexes.
Conclusions The XGBoost and RF algorithms are advantageous for predicting preoperative ICP and establishing prognoses for HCP patients. Furthermore, ML-based prediction could be used as a non-invasive method.
Background We aimed to characterize patients hospitalized for coronavirus disease 2019 (COVID-19) and identify predictors of invasive mechanical ventilation (IMV). Methods: We performed a retrospective cohort study in patients with COVID-19 admitted to a private network in Sao Paulo, Brazil from March to October 2020. Patients were compared in three subgroups: non-intensive care unit (ICU) admission (group A), ICU admission without receiving IMV (group B) and IMV requirement (group C). We developed logistic regression algorithm to identify predictors of IMV. Results: We analyzed 1,650 patients, the median age was 53 years (42–65) and 986 patients (59.8%) were male. The median duration from symptom onset to hospital admission was 7 days (5–9) and the main comorbidities were hypertension (42.4%), diabetes (24.2%) and obesity (15.8%). We found differences among subgroups in laboratory values obtained at hospital admission. The predictors of IMV (odds ratio and 95% confidence interval [CI]) were male (1.81 [1.11– 2.94], P=0.018), age (1.03 [1.02–1.05], P<0.001), obesity (2.56 [1.57–4.15], P<0.001), duration from symptom onset to admission (0.91 [0.85–0.98], P=0.011), arterial oxygen saturation (0.95 [0.92– 0.99], P=0.012), C-reactive protein (1.005 [1.002–1.008], P<0.001), neutrophil-to-lymphocyte ratio (1.046 [1.005–1.089], P=0.029) and lactate dehydrogenase (1.005 [1.003–1.007], P<0.001). The area under the curve values were 0.860 (95% CI, 0.829–0.892) in the development cohort and 0.801 (95% CI, 0.733–0.870) in the validation cohort. Conclusions: Patients had distinct clinical and laboratory parameters early in hospital admission. Our prediction model may enable focused care in patients at high risk of IMV.
Background In septic shock patients with cirrhosis, impaired liver function might decrease lactate elimination and produce a higher lactate level. This study investigated differences in initial lactate, lactate clearance, and lactate utility between cirrhotic and non-cirrhotic septic shock patients.
Methods This is a retrospective cohort study conducted at a referral, university-affiliated medical center. We enrolled adults admitted during 2012–2018 who satisfied the septic shock diagnostic criteria of the Surviving Sepsis Campaign: 2012. Patients previously diagnosed with cirrhosis by an imaging modality were classified into the cirrhosis group. The initial lactate levels and levels 6 hours after resuscitation were measured and used to calculate lactate clearance. We compared initial lactate, lactate at 6 hours, and lactate clearance between the cirrhosis and non-cirrhosis groups. The primary outcome was in-hospital mortality.
Results Overall 777 patients were enrolled, of whom 91 had previously been diagnosed with cirrhosis. Initial lactate and lactate at 6 hours were both significantly higher in cirrhosis patients, but there was no difference between the groups in lactate clearance. A receiver operating characteristic curve analysis for predictors of in-hospital mortality revealed cut-off values for initial lactate, lactate at 6 hours, and lactate clearance of >4 mmol/L, >2 mmol/L, and <10%, respectively, among non-cirrhosis patients. Among patients with cirrhosis, the cut-off values predicting in-hospital mortality were >5 mmol/L, >5 mmol/L, and <20%, respectively. Neither lactate level nor lactate clearance was an independent risk factor for in-hospital mortality among cirrhotic and non-cirrhotic septic shock patients.
Conclusions The initial lactate level and lactate at 6 hours were significantly higher in cirrhosis patients than in non-cirrhosis patients.
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Urinary examination has formed part of patient assessment since the earliest days of medicine. Current definitions of oliguria are essentially arbitrary, but duration and intensity of oliguria have been associated with an increased risk of mortality, and this risk is not completely attributable to the development of concomitant acute kidney injury (AKI) as defined by changes in serum creatinine concentration. The increased risk of death associated with the development of AKI itself may be modified by directly or indirectly by progressive fluid accumulation, due to reduced elimination and increased fluid administration. None of the currently extant major illness severity scoring systems or outcome prediction models use modern definitions of AKI or oliguria, or any values representative of fluid volumes variables. Even if a direct relationship with mortality is not observed, then it is possible that fluid balance or fluid volume variables mediate the relationship between illness severity and mortality in the renal and respiratory physiological domains. Fluid administration and fluid balance may then be an important, easily modifiable therapeutic target for future investigation. These relationships require exploration in large datasets before being prospectively validated in groups of critically ill patients from differing jurisdictions to improve prognostication and mortality prediction.
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BACKGROUND To determine the prognostic value of the initial APACHE II score in the ED compared with the classic APACHE II score in the ICU and to check the usefulness of the MEDS score together for more rapid risk stratification of septic patients admitted to the ICU via the ED. METHODS We prospectively checked the initial APACHE II and MEDS scores of all the patients who had systemic inflammatory response syndrome in the ED and the classic APACHE II scores after admission to the ICU, as well 6 months later. We enrolled the only sepsis cases in the final diagnosis after reviewing the medical records. We evaluated the predictive abilities of the initial APACHE II and MEDS scores compared with the classic APACHE II score. RESULTS During 6 months, 58 patients diagnosed with sepsis were enrolled. Twenty-four (41.4%) patients died within 28 days of admission and 34 patients survived. The mortality group had a significantly higher mean classic APACHE II score (19 +/- 6.7 vs. 15 +/- 5.0, p < 0.01) and a higher mean MEDS score (16.67 +/- 2.70 vs. 8.91 +/- 3.11, p < 0.01) than the survivor group. The initial APACHE II score at the ED was not significantly different between the two groups.
ROC analysis showed the discriminative power of the MEDS score in predicting mortality was much better than the APACHE II score (areas under the curves of the APACHE II score in the ED and ICU, and the MEDS scores were 0.668, 0.807, and 0.967, respectively; p < 0.01). CONCLUSIONS The initial APACHE II score in the ED did not predict mortality better than the classic APACHE II score.
However, the MEDS score predicted the poor prognosis of septic patients more rapidly and accurately in the ED than the APACHE II model.
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