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Abstract BACKGROUND Surgical decompression for degenerative cervical myelopathy (DCM) is one of the mainstays of treatment, with generally positive outcomes. However, some patients who undergo surgery for DCM continue to show functional decline. OBJECTIVE To use machine learning (ML) algorithms to determine predictors of worsening functional status after surgical intervention for DCM. METHODS This is a retrospective analysis of prospectively collected data. A total of 757 patients enrolled in 2 prospective AO Spine clinical studies, who underwent surgical decompression for DCM, were analyzed. The modified Japanese Orthopedic Association (mJOA) score, a marker of functional status, was obtained before and 1 yr postsurgery. The primary outcome measure was the dichotomized change in mJOA at 1 yr according to whether it was negative (worse functional status) or non-negative. After applying an 80:20 training-testing split of the dataset, we trained, optimized, and tested multiple ML algorithms to evaluate algorithm performance and determine predictors of worse mJOA at 1 yr. RESULTS The highest-performing ML algorithm was a polynomial support vector machine. This model showed good calibration and discrimination on the testing data, with an area under the receiver operating characteristic curve of 0.834 (accuracy: 74.3%, sensitivity: 88.2%, specificity: 72.4%). Important predictors of functional decline at 1 yr included initial mJOA, male gender, duration of myelopathy, and the presence of comorbidities. CONCLUSION The reasons for worse mJOA are frequently multifactorial (eg, adjacent segment degeneration, tandem lumbar stenosis, ongoing neuroinflammatory processes in the cord). This study successfully used ML to predict worse functional status after surgery for DCM and to determine associated predictors. Graphical Abstract Graphical Abstract

Abstract BACKGROUND There is controversy over the optimal treatment strategy for patients with mild degenerative cervical myelopathy (DCM). OBJECTIVE To evaluate the degree of impairment in baseline quality of life as compared to population norms, as well as functional, disability, and quality of life outcomes following surgery in a prospective cohort of mild DCM patients undergoing surgical decompression. METHODS We identified patients with mild DCM (modified Japanese Orthopaedic Association [mJOA] 15 to 17) enrolled in the prospective, multicenter AOSpine CSM-NA or CSM-I trials. Baseline quality of life Short Form-36 version 2 (SF-36v2) was compared to population norms by the standardized mean difference (SMD). Outcomes, including functional status (mJOA, Nurick grade), disability (NDI [Neck Disability Index]), and quality of life (SF-36v2), were evaluated at baseline and 6 mo, 1 yr, and 2 yr after surgery. Postoperative complications within 30 d of surgery were monitored. RESULTS One hundred ninety-three patients met eligibility criteria. Mean age was 52.4 yr. There were 67 females (34.7%). Patients had significant impairment in all domains of the SF-36v2 compared to population norms, greatest for Social Functioning (SMD –2.33), Physical Functioning (SMD –2.31), and Mental Health (SMD –2.30). A significant improvement in mean score from baseline to 2-yr follow-up was observed for all major outcome measures, including mJOA (0.87, P < .01), Nurick grade (–1.13, P < .01), NDI (–12.97, P < .01), and SF-36v2 Physical Component Summary (PCS) (5.75, P < .01) and Mental Component Summary (MCS) (6.93, P < .01). The rate of complication was low. CONCLUSION Mild DCM is associated with significant impairment in quality of life. Surgery results in significant gains in functional status, level of disability, and quality of life.

Degenerative cervical myelopathy (DCM) is the leading cause of spinal cord dysfunction in adults worldwide. DCM encompasses various acquired (age-related) and congenital pathologies related to degeneration of the cervical spinal column, including hypertrophy and/or calcification of the ligaments, intervertebral discs and osseous tissues. These pathologies narrow the spinal canal, leading to chronic spinal cord compression and disability. Owing to the ageing population, rates of DCM are increasing. Expeditious diagnosis and treatment of DCM are needed to avoid permanent disability. Over the past 10 years, advances in basic science and in translational and clinical research have improved our understanding of the pathophysiology of DCM and helped delineate evidence-based practices for diagnosis and treatment. Surgical decompression is recommended for moderate and severe DCM; the best strategy for mild myelopathy remains unclear. Next-generation quantitative microstructural MRI and neurophysiological recordings promise to enable quantification of spinal cord tissue damage and help predict clinical outcomes. Here, we provide a comprehensive, evidence-based review of DCM, including its definition, epidemiology, pathophysiology, clinical presentation, diagnosis and differential diagnosis, and non-operative and operative management. With this Review, we aim to equip physicians across broad disciplines with the knowledge necessary to make a timely diagnosis of DCM, recognize the clinical features that influence management and identify when urgent surgical intervention is warranted.Degenerative cervical myelopathy is the leading cause of spinal cord dysfunction in adults worldwide. In this Review, the authors provide a comprehensive pathophysiological and clinical overview of the condition to equip physicians across broad disciplines with the knowledge needed for its diagnosis and management.

It is challenging to discriminate the early presentation of Degenerative Cervical Myelopathy (DCM) as well as sensitively and accurately distinguishing between mild, moderate, and severe levels of impairment. As gait dysfunction is one of the cardinal symptoms of DCM, we hypothesized that spatiotemporal gait parameters, including the enhanced gait variability index (eGVI), could be used to sensitively discriminate between different severities of DCM. A total of 153 patients recently diagnosed with DCM were recruited and stratified on the basis of DCM severity grades, as measured using the modified Japanese Orthopedic Association (mJOA) scale. Demographic information and neurological status were collected. Gait assessments were performed using an 8 m walkway. Spearman rank correlation was used to identify relationships between gait parameters and mJOA values as well as the mJOA lower extremity (LE) subscore. Kruskal–Wallis H test was performed to evaluate differences between severity groups, as defined by mJOA classification. A significant and relatively strong correlation was found between the mJOA score and eGVI, as well as between the LE subscore of the mJOA and eGVI. Significant differences in the eGVI (X2(2, N = 153) = 55.04, p < 0.0001, ε2 = 0.36) were found between all groups of DCM severity, with a significant increase in the eGVI as DCM progressed from mild to moderate. The eGVI was the most discriminative gait parameter, which facilitated objective differentiation between varying severities of DCM. Quantitative gait assessments show promise as an accurate and objective tool to diagnose and classify DCM, as well as to potentially evaluate the impact of therapeutic interventions.

Objective HELLP syndrome, a severe complication of preeclampsia, is associated with increased maternal and neonatal morbidity and mortality. This study aims to evaluate maternal and perinatal outcomes in preeclamptic women with and without HELLP syndrome in Indonesia. Methods A multicenter retrospective cohort study was conducted across 30 hospitals in Indonesia from January 2022 to December 2023. Data from 1,808 preeclamptic women were analyzed, with 219 (12.1%) classified as having HELLP syndrome. Maternal and perinatal outcomes were compared between the HELLP and non-HELLP groups. Results Women with HELLP syndrome had significantly higher risks of severe complications, including eclampsia ( p  < 0.001; aOR: 2.5 (1.5–4.18)), acute kidney injury ( p  < 0.01; aOR: 4.11 (2.07–8.15)), emergency hypertension ( p  = 0.048; aOR: 1.42 (1.01–2.01)), preterm birth < 37 weeks ( p  = 0.013; aOR: 1.54 (1.1–2.17)), and preterm birth < 34 weeks ( p  < 0.001; aOR: 1.8 (1.28–2.53)). HELLP syndrome increased the risk of Intra-uterine fetal death ( p  = 0.01; aOR: 2.18 (1.21–3.95)) and neonatal sepsis ( p  = 0.011; aOR: 2.32 (1.21–4.42)). Although the multivariate analysis did not yield any significant results, the HELLP syndrome group has a substantially higher prevalence of maternal death (3.7% vs 1%; p  = 0.005) and neonatal death (11.6% vs 6.4%; p  = 0.005). Conclusion HELLP syndrome significantly worsens maternal and neonatal outcomes in preeclampsia, reflecting a need for improved early detection of ‘high-risk’ preeclamptic women like sFlt1/PLGF ratio and perhaps other laboratory tests like haptoglobin and D-dimer’s. Many of these laboratory tests are currently not accessible in the Indonesian public health sector. Further research is needed to identify other markers that would assist in a more timely diagnosis of impending HELLP syndrome, particularly in early-onset preeclampsia patients managed conservatively.

Abstract BACKGROUND Patients with mild degenerative cervical myelopathy (DCM) represent a heterogeneous population, and indications for surgical decompression remain controversial. OBJECTIVE To dissociate patient phenotypes within the broader population of mild DCM associated with degree of impairment in baseline quality of life (QOL) and surgical outcomes. METHODS This was a post hoc analysis of patients with mild DCM (modified Japanese Orthopedic Association [mJOA] 15-17) enrolled in the AOSpine CSM-NA/CSM-I studies. A k-means clustering algorithm was applied to baseline QOL (Short Form-36 [SF-36]) scores to separate patients into 2 clusters. Baseline variables and surgical outcomes (change in SF-36 scores at 1 yr) were compared between clusters. A k-nearest neighbors (kNN) algorithm was used to evaluate the ability to classify patients into the 2 clusters by significant baseline clinical variables. RESULTS One hundred eighty-five patients were eligible. Two groups were generated by k-means clustering. Cluster 1 had a greater proportion of females (44% vs 28%, P = .029) and symptoms of neck pain (32% vs 11%, P = .001), gait difficulty (57% vs 40%, P = .025), or weakness (75% vs 59%, P = .041). Although baseline mJOA correlated with neither baseline QOL nor outcomes, cluster 1 was associated with significantly greater improvement in disability (P = .003) and QOL (P < .001) scores following surgery. A kNN algorithm could predict cluster classification with 71% accuracy by neck pain, motor symptoms, and gender alone. CONCLUSION We have dissociated a distinct patient phenotype of mild DCM, characterized by neck pain, motor symptoms, and female gender associated with greater impairment in QOL and greater response to surgery.

Background Tuberculosis is a leading cause of maternal and fetal mortality in women of reproductive age. Tuberculosis is frequently misdiagnosed and treated inadequately during pregnancy. Although the global case fatality rate of tuberculosis is decreasing annually, the trend of tuberculosis mortality in Indonesia remains relatively high. Most tuberculosis reports do not include pregnancy status because most countries do not routinely screen for tuberculosis in pregnant women and do not report pregnancy status in female cases. In Southeast Asia, there is currently insufficient data regarding the risk factors associated with maternal mortality due to tuberculosis. This study aimed to identify the risk factors associated with tuberculosis-related mortality during pregnancy. Methodology This retrospective study was conducted at Dr. Soetomo General Hospital, Surabaya. Data were collected from patients' medical records. The samples were all pulmonary tuberculosis cases in pregnancy (suspected, bacteriological, and radiologically confirmed cases) from 2014 to 2018. Data on maternal characteristics, underlying risk factors, and maternal outcomes in pregnant women with tuberculosis were collected from medical records. A total of 77 cases of pulmonary tuberculosis in pregnancy were obtained and analyzed using the chi-square test for differences between pregnant women with tuberculosis who survived and those who did not. Results In total, 77 cases of pulmonary tuberculosis out of 7,242 deliveries were found during the past five years (incidence per year was 1.07), of whom 20.8% (16/77) died. Eight patients died before the gestational age reached 28 weeks. Most of the non-surviving women were aged <35 years (93.8%; 15/16). More than 30% (5/16) of the patients had human immunodeficiency virus co-infection, and the highest risk factors were pneumonia and miliary tuberculosis. Miliary tuberculosis was significantly associated with maternal mortality in pulmonary tuberculosis (p = 0.004) with a relative risk of 3.43. Conclusions According to the findings of this study, miliary tuberculosis is a significant risk factor for maternal mortality during pregnancy.

Prognostic factors for clinical outcome after spinal cord (SC) injury (SCI) are limited but important in patient management and education. There is a lack of evidence regarding magnetic resonance imaging (MRI) and clinical outcomes in SCI patients. Therefore, we aimed to investigate whether baseline MRI features predicted the clinical course of the disease. This study is an ancillary to the prospective North American Clinical Trials Network (NACTN) registry. Patients were enrolled from 2005–2017. MRI within 72 h of injury and a minimum follow-up of one year were available for 459 patients. Patients with American Spinal Injury Association impairment scale (AIS) E were excluded. Patients were grouped into those with (n = 354) versus without (n = 105) SC signal change on MRI T2-weighted images. Logistic regression analysis adjusted for commonly known a priori confounders (age and baseline AIS). Main outcomes and measures: The primary outcome was any adverse event. Secondary outcomes were AIS at the baseline and final follow-up, length of hospital stay (LOS), and mortality. A regression model adjusted for age and baseline AIS. Patients with intrinsic SC signal change were younger (46.0 (interquartile range (IQR) 29.0 vs. 50.0 (IQR 20.5) years, p = 0.039). There were no significant differences in the other baseline variables, gender, body mass index, comorbidities, and injury location. There were more adverse events in patients with SC signal change (230 (65.0%) vs. 47 (44.8%), p < 0.001; odds ratio (OR) = 2.09 (95% confidence interval (CI) 1.31–3.35), p = 0.002). The most common adverse event was cardiopulmonary (186 (40.5%)). Patients were less likely to be in the AIS D category with SC signal change at baseline (OR = 0.45 (95% CI 0.28–0.72), p = 0.001) and in the AIS D or E category at the final follow-up (OR = 0.36 (95% CI 0.16–0.82), p = 0.015). The length of stay was longer in patients with SC signal change (13.0 (IQR 17.0) vs. 11.0 (IQR 14.0), p = 0.049). There was no difference between the groups in mortality (11 (3.2%) vs. 4 (3.9%)). MRI SC signal change may predict adverse events and overall LOS in the SCI population. If present, patients are more likely to have a worse baseline clinical presentation (i.e., AIS) and in- or outpatient clinical outcome after one year. Patients with SC signal change may benefit from earlier, more aggressive treatment strategies and need to be educated about an unfavorable prognosis.

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Phosphorus losses from agricultural land can cause accelerated eutrophication of surface water bodies. This study evaluated the use of soil test phosphorus (STP) levels to predict dissolved inorganic phosphorus (DIP) concentrations in runoff water from agricultural soils using laboratory rainfall simulation. The objectives of this study were to determine (i) to what extent STP concentrations can be used as a basis to predict P losses from Alberta soils and (ii) how extended rainfall simulation run times affected DIP losses. Soil samples collected from a total of 38 field sites, widely scattered throughout the southern half of Alberta, were subjected to rainfall simulation in the laboratory. The STP concentrations were determined using Miller-Axley, Norwest, Kelowna, Modified Kelowna Mehlich-III, and distilled water extraction methods. Each rainfall simulation event lasted for at least 90 min. Runoff samples were collected in time series for the duration of each simulation, during two distinct runoff intervals: (i) for the first 30 min of continuous runoff (T30) and (ii) for 40 min during runoff equilibrium (T(eq)). For all the STP extractants and both runoff intervals, the relationship with DIP-flow-weighted mean concentration (FWMC) was linear and highly significant with r2 values ranging from 0.74 to 0.96. However, the slopes of the resulting regression lines were, on average, 1.85 times greater for the T30 runoff interval over those computed for the T(eq) interval. Thus experimental methodology greatly influenced regression parameters, suggesting that more work was needed to verify these relationships under natural conditions. In addition, with many of the r2 values greater than 0.90 there would be little, if any, benefit derived by including soil properties in regression analysis.