Predicting short-term major postoperative complications in intestinal resection for Crohn’s disease:A machine learning-based study

BACKGROUND Due to the complexity and numerous comorbidities associated with Crohn’s disease(CD),the incidence of postoperative complications is high,significantly impacting the recovery and prognosis of patients.Consequently,additional stu-dies are required to precisely predict short-term major complications following intestinal resection(IR),aiding surgical decision-making and optimizing patient care.AIM To construct novel models based on machine learning(ML)to predict short-term major postoperative complications in patients with CD following IR.METHODS A retrospective analysis was performed on clinical data derived from a patient cohort that underwent IR for CD from January 2017 to December 2022.The study participants were randomly allocated to either a training cohort or a validation cohort.The logistic regression and random forest(RF)were applied to construct models in the training cohort,with model discrimination evaluated using the area under the curves(AUC).The validation cohort assessed the performance of the constructed models.RESULTS Out of the 259 patients encompassed in the study,5.0%encountered major postoperative complications(Clavien-Dindo≥III)within 30 d following IR for CD.The AUC for the logistic model was 0.916,significantly lower than the AUC of 0.965 for the RF model.The logistic model incorporated a preoperative CD activity index(CDAI)of≥220,a diminished preoperative serum albumin level,conversion to laparotomy surgery,and an extended operation time.A nomogram for the logistic model was plotted.Except for the surgical approach,the other three variables ranked among the top four important variables in the novel ML model.CONCLUSION Both the nomogram and RF exhibited good performance in predicting short-term major postoperative complic-ations in patients with CD,with the RF model showing more superiority.A preoperative CDAI of≥220,a di-minished preoperative serum albumin level,and an extended operation time might be the most crucial variables.The findings of this study can assist clinicians in identifying patients at a higher risk for complications and offering personalized perioperative management to enhance patient outcomes.

Can serious postoperative complications in patients with Crohn’s disease be predicted using machine learning?

The routine introduction of novel anti-inflammatory therapies into the mana-gement algorithms of patients with Crohn’s disease over the last 2 decades has not substantially changed the likelihood of ultimate surgery.Rather it has delayed the operative need and altered the presentation phenotype.The prospect of complic-ations continues to remain high in this modern era but depending upon the cohort assessed,it remains difficult to make strict comparisons between individual spe-cialist centres.Those patients who present rather late after their diagnosis with a septic complication like an intra-abdominal abscess and a penetrating/fistulizing pattern of disease are more likely to have a complicated course particularly if they have clinical features such as difficult percutaneous access to the collection or multilocularity both of which can make preoperative drainage unsuccessful.Eq-ually,those cases with extensive adhesions where an initial laparoscopic approach needs open conversion and where there is an extended operative time,unsur-prisingly will suffer more significant complications that impact their length of hospital stay.The need for a protective stoma also introduces its own derivative costs,utilizing a range of health resources as well as resulting in important alte-rations in quality of life outcomes.Having established the parameters of the pro-blem can the statistical analysis of the available data identify high-risk cases,promote the notion of centralization of specialist services or improve the allo-cation of disease-specific health expenditure?

Machine learning in predicting postoperative complications in Crohn’s disease

Crohn's disease(CD)is a chronic inflammatory bowel disease of unknown origin that can cause significant disability and morbidity with its progression.Due to the unique nature of CD,surgery is often necessary for many patients during their lifetime,and the incidence of postoperative complications is high,which can affect the prognosis of patients.Therefore,it is essential to identify and manage post-operative complications.Machine learning(ML)has become increasingly im-portant in the medical field,and ML-based models can be used to predict post-operative complications of intestinal resection for CD.Recently,a valuable article titled“Predicting short-term major postoperative complications in intestinal resection for Crohn's disease:A machine learning-based study”was published by Wang et al.We appreciate the authors'creative work,and we are willing to share our views and discuss them with the authors.

Influencing factors and preventive measures of infectious complications after intestinal resection for Crohn’s disease

The incidence of Crohn’s disease(CD)has increased in recent years,with most patients requiring intestinal resection.Complications after intestinal resection for CD can lead to poor prognosis and recurrence,among which infectious complic-ations are the most common.This study aimed to investigate the common risk factors,including medications,preoperative nutritional status,surgery-related factors,microorganisms,lesion location and type,and so forth,causing infectious complications after intestinal resection for CD,and to propose corresponding preventive measures.The findings provided guidance for identifying suscept-ibility factors and the early intervention and prevention of infectious complic-ations after intestinal resection for CD in clinical practice.

Machine learning as a tool predicting short-term postoperative complications in Crohn’s disease patients undergoing intestinal resection: What frontiers?

The recent study,“Predicting short-term major postoperative complications in intestinal resection for Crohn’s disease:A machine learning-based study”invest-igated the predictive efficacy of a machine learning model for major postoperative complications within 30 days of surgery in Crohn’s disease(CD)patients.Em-ploying a random forest analysis and Shapley Additive Explanations,the study prioritizes factors such as preoperative nutritional status,operative time,and CD activity index.Despite the retrospective design’s limitations,the model’s robu-stness,with area under the curve values surpassing 0.8,highlights its clinical potential.The findings align with literature supporting preoperative nutritional therapy in inflammatory bowel diseases,emphasizing the importance of compre-hensive assessment and optimization.While a significant advancement,further research is crucial for refining preoperative strategies in CD patients.

Histopathological Patterns and Early Postoperative Complications among Patients with Surgically Treated Thyroid Diseases at Bugando Medical Centre, Mwanza, Tanzania

Background: Thyroid diseases are among the leading endocrine disorders affecting a large proportion of people worldwide and show geographical variation in incidence and histopathological pattern related to age, sex, dietary and environmental factors. Histopathological patterns of surgically treated thyroid diseases play an important role in early diagnosis and management of these diseases. There is, however, limited published data regarding histopathological reports on thyroid disease in our local setting. This study aimed to determine the histopathological patterns and highlight early postoperative complications among patients with surgically treated thyroid diseases at Bugando Medical Centre (BMC). Methods: This was a longitudinal study involving all patients with surgically treated thyroid diseases seen at BMC over a period of 6 months from October 2019 to March 2020. Results: A total of 84 patients were studied. Females outnumbered males by a female to male ratio of 11:1. The median age of patients was 44 [IQR, 35 - 54] years old, the youngest was 14 years old and the oldest was 76 years old. Colloid goiter was the most common non-neoplastic lesion accounting for 34 (44.7%) patients. Among the neoplastic lesions, follicular adenoma was the most commonly encountered benign pathologies (n = 16;21.1%), while papillary carcinoma was the most commonly encountered malignancy (n = 4;50%). Following thyroidectomy, 12 (14.3%) patients developed early complications, of which hemorrhage sometimes requiring blood transfusion was the leading intra/postoperative complications accounting for 4 (33.3%) patients. Other complications include temporary recurrent laryngeal nerve palsy 2 (16.7%), surgical site infection 2 (16.7%) and tracheomalacia, bronchospasm, thyroid abscess and respiratory obstruction in 1 (8.3%) patient each, respectively. In this study, malignant thyroid lesion (p Conclusion: This study demonstrated that colloid goiter was the most common non-neoplastic lesion, and on the neoplastic category, follicular adenoma was the most common benign lesion, while papillary carcinoma was the most frequent malignant lesion.

Relationship between Kawasaki disease and abdominal pain

This editorial presents an analysis of an article recently published in the World Journal of Clinical Cases.Kawasaki disease(KD)is a well-known pediatric vasculitis characterized by fever,rash,conjunctivitis,oral mucosal changes,and swelling of the extremities.This editorial aims to delve into the intricate relationship between KD and abdominal pain,drawing insights from recent research findings to provide a comprehensive understanding and potential avenues for future investigation.

Application of artificial intelligence in the diagnosis and treatment of Kawasaki disease

This editorial provides commentary on an article titled"Potential and limitationsof ChatGPT and generative artificial intelligence(AI)in medical safety education"recently published in the World Journal of Clinical Cases.AI has enormous potentialfor various applications in the field of Kawasaki disease(KD).One is machinelearning(ML)to assist in the diagnosis of KD,and clinical prediction models havebeen constructed worldwide using ML;the second is using a gene signalcalculation toolbox to identify KD,which can be used to monitor key clinicalfeatures and laboratory parameters of disease severity;and the third is using deeplearning(DL)to assist in cardiac ultrasound detection.The performance of the DLalgorithm is similar to that of experienced cardiac experts in detecting coronaryartery lesions to promoting the diagnosis of KD.To effectively utilize AI in thediagnosis and treatment process of KD,it is crucial to improve the accuracy of AIdecision-making using more medical data,while addressing issues related topatient personal information protection and AI decision-making responsibility.AIprogress is expected to provide patients with accurate and effective medicalservices that will positively impact the diagnosis and treatment of KD in thefuture.

Rethinking Kawasaki disease diagnosis:Continuing the search for new biomarkers

Recent findings by Yamashita et al report a Kawasaki disease(KD)case with normal biomarker levels,challenging traditional diagnostic paradigms.This editorial explores the implications of such atypical KD presentations,emphasizing the need for novel biomarkers and revised diagnostic guidelines.The case underscores the limitations of current biomarkers,the importance of clinical judgment,and the necessity for comprehensive research to identify new diagnostic tools.Emerging technologies in proteomics and genomics offer potential avenues for discovering reliable biomarkers.Revisiting clinical guidelines to incorporate flexibility for atypical presentations is crucial.Ensuring timely and accurate KD diagnosis,even without elevated traditional biomarkers,prevents severe complications.Future advancements should focus on novel biomarkers to improve patient outcomes.

Application of Echocardiography Combined with Blood SAA, IL-6, PCT, and CRP Detection in the Diagnosis and Treatment of Kawasaki Disease in Children

Objective: To understand the application of echocardiography combined with blood SAA, IL-6, PCT, and CRP detection in the diagnosis and treatment of Kawasaki disease in children. Methods: 56 children with Kawasaki disease were selected as the study subjects as the treatment group, and 54 children with other diseases during the same period were selected as the control group. Echocardiography, blood SAA, IL-6, PCT and CRP were detected before and after treatment to observe the results of the two groups. A database was established to compare the changes of various indicators between the two groups, as well as the application value of each indicator in the clinical diagnosis and treatment of Kawasaki disease, and the pros and cons of the application of each indicator in the diagnosis and treatment of children with Kawasaki disease were analyzed, so as to provide a clearer early warning mechanism for the clinical diagnosis and treatment of children with Kawasaki disease. Results: There was no significant difference in the results of related imaging indexes in the control group before and after treatment (P > 0.05). There was no significant difference in the results of relevant imaging indicators in the treatment group before and after treatment (P > 0.05), except for LMCA (P < 0.05). The comparison of imaging related indicators before and after treatment between the two groups showed that except for no statistically significant difference in LMCA and RMCA before treatment (P > 0.05), all other indicators had statistical significance (P < 0.05). The results of relevant laboratory indexes in control group before and after treatment were statistically significant (P < 0.05). The results of relevant laboratory indexes before and after treatment in the treatment group were statistically significant (P < 0.05). The results of relevant laboratory indicators were compared between the two groups, except for the results of SAA, IL-6 and PCT before treatment, which were not statistically significant (P > 0.05), the differences in all other indicators were statistically significant (P Conclusion: The combination of echocardiography with blood SAA, IL-6, PCT, and CRP detection can establish the optimal evaluation plan for accurate and effective diagnosis, treatment, and prognosis of Kawasaki disease in children, providing more accurate and reliable diagnostic and treatment methods and laboratory data for clinical practice, and thus providing strong protection for children’s health.

Employing a random forest model to forecast the likelihood of coronary artery lesions in Kawasaki disease: a study centered on four biomarkers

Background:Kawasaki disease is an acute immune vasculitis,which is more common in children under 5 years old.Kawasaki disease mainly affects the cardiovascular system,especially the coronary arteries.Once coronary artery damage occurs,it can significantly impact the patient’s prognosis.Therefore,in some countries and regions,Kawasaki disease has become a common acquired heart disease.Methods:First,univariate analysis was conducted on each predictive factor.Then,Least Absolute Shrinkage and Selection Operator and random forest algorithms were used to screen all predictive factors,and the prediction model was evaluated using receiver operating characteristic curve,calibration curve,and Decision Curve Analysis.Results:This study,based on data from 228 Kawasaki disease patients,utilized a random forest model to identify four predictive factors:white blood cell count,creatine kinase isoenzyme MB,albumin,and neutrophil count.These factors were used to construct a prediction model,which achieved an area under the curve of 0.743.Conclusions:We developed a forest plot based on white blood cell count,creatine kinase isoenzyme MB,albumin,and neutrophil count to effectively predict the occurrence of coronary artery lesions in Kawasaki disease.

Hospital Discharge Plan in Family Caregivers of Children with Coronary Artery Aneurysm in Kawasaki Disease: A Review

Objective:The study reviews status,main time nodes and hospital discharge services for family caregivers of children with Kawasaki disease complicated by coronary artery aneurysm to provide references for the development of hospital discharge preparation services for medical personnel and patients.Background:CAL of Kawasaki disease is the main cause of acquired heart disease in children,but there is not enough research on the readiness for hospital discharge.Design:Systematic review of observational and interventional studies.

Correlation Analysis Between Changes of D-Dimer Level and Rheumatoid Arthritis Complicated with Interstitial Lung Disease

Objective:To explore the correlation between the change of D-dimer level and rheumatoid arthritis complicated with interstitial lung disease.Methods:From January 2022 to February 2024,20 rheumatoid arthritis patients complicated with interstitial lung disease(interstitial lung disease group),20 rheumatoid arthritis patients without interstitial lung disease(without interstitial lung disease group),and 20 healthy people(control group)in Xijing Hospital were selected for this study.The fasting venous blood of the three groups of subjects was collected and their D-dimer,C-reactive protein(CRP),rheumatoid factor(RF),and erythrocyte sedimentation rate(ESR)were detected.Subsequently,the correlation between each index and rheumatoid arthritis complicated with interstitial lung disease was analyzed.Results:The D-dimer level of the interstitial lung disease group was significantly higher than the other two groups(P<0.05).The D-dimer level of the group without interstitial lung disease was significantly higher than the control group(P<0.05).CRP levels in the interstitial lung disease group and the group without interstitial lung disease were significantly higher than those of the control group(P<0.05).The ESR and RF levels of the interstitial lung disease group were significantly higher than the other two groups(P<0.05).The levels of ESR and RF levels of the group without interstitial lung disease were significantly higher than the control group(P<0.05).Conclusion:D-dimer levels of rheumatoid arthritis patients are higher than those of healthy individuals,and those complicated with interstitial lung disease present even higher levels.This finding shows that there is a correlation between D-dimer levels and rheumatoid arthritis with interstitial lung disease,which may facilitate the evaluation and diagnosis of this disease.

Intestinal complications in patients with Crohn's disease in the Brazilian public healthcare system between 2011 and 2020

BACKGROUND This is a secondary database study using the Brazilian public healthcare system database.AIM To describe intestinal complications(ICs)of patients in the Brazilian public healthcare system with Crohn’s disease(CD)who initiated and either only received conventional therapy(CVT)or also initiated anti-tumor necrosis factor(anti-TNF)therapy between 2011 and 2020.METHODS This study included patients with CD[international classification of diseases–10th revision(ICD-10):K50.0,K50.1,or K50.8](age:≥18 years)with at least one claim of CVT(sulfasalazine,azathioprine,mesalazine,or methotrexate).IC was defined as a CD-related hospitalization,pre-defined procedure codes(from rectum or intestinal surgery groups),and/or associated disease(pre-defined ICD-10 codes),and overall(one or more type of ICs).RESULTS In the 16809 patients with CD that met the inclusion criteria,the mean follow-up duration was 4.44(2.37)years.In total,14697 claims of ICs were found from 4633 patients.Over the 1-and 5-year of follow-up,8.3%and 8.2%of the patients with CD,respectively,presented at least one IC,of which fistula(31%)and fistulotomy(48%)were the most commonly reported.The overall incidence rate(95%CI)of ICs was 6.8(6.5–7.04)per 100 patient years for patients using only-CVT,and 9.2(8.8–9.6)for patients with evidence of anti-TNF therapy.CONCLUSION The outcomes highlighted an important and constant rate of ICs over time in all the CD populations assessed,especially in patients exposed to anti-TNF therapy.This outcome revealed insights into the real-world treatment and complications relevant to patients with CD and highlights that this disease remains a concern that may require additional treatment strategies in the Brazilian public healthcare system.

How inflammation influences psychiatric disease

Recent studies highlight the strong correlation between infectious diseases and the development of neuropsychiatric disorders.In this editorial,we comment on the article“Anti-infective therapy durations predict psychological stress and laparoscopic surgery quality in pelvic abscess patients”by Zhang et al,published in the recent issue of the World Journal of Psychiatry 2023;13(11):903-911.Our discussion highlighted the potential consequences of anxiety,depression,and psychosis,which are all linked to bacterial,fungal,and viral infections,which are relevant to the impact of inflammation on the sequelae in mental health as those we are observing after the coronavirus disease 2019 pandemic.We focus specifically on the immune mechanisms triggered by inflammation,the primary contributor to psychiatric complications.Importantly,pathophysiological mechanisms such as organ damage,post-injury inflammation,and infectioninduced endocrine alterations,including hypocortisolism or autoantibody formation,significantly contribute to the development of chronic low-grade inflammation,promoting the emergence or development of psychiatric alterations in susceptible individuals.As inflammation can have long-term effects on patients,a multidisciplinary treatment plan can avoid complications and debilitating health issues,and it is crucial to recognize and address the mental health implications.

New anti-mesenteric delta-shaped stapled anastomosis: Technical report with short-term postoperative outcomes in patients with Crohn’s disease

BACKGROUND Medical treatment for Crohn’s disease(CD)has continuously improved,which has led to a decrease in surgical recurrence rates.Despite these advancements,25%of patients will undergo repeat intestinal surgery.Recurrence of CD com-monly occurs on the mesentery side of the anastomosis site.AIM To compare the new anti-mesenteric side-to-side delta-shaped stapled anasto-mosis(DSA)with the conventional stapled functional end-to-end anastomosis(CSA).METHODS This retrospective study included CD patients who underwent ileo-ileal or ileo-colic anastomosis between January 2020 and December 2023.The DSA technique employed a stapler to maintain the concept of anti-mesentery side-to-side ana-stomosis by performing a 90°vertical closure of the open window compared with the CSA technique.At the corner where the open window is closed,the DSA avoids forming a pouch and creates an anastomosis resembling a delta shape within the intestinal lumen.We compared demographics,preoperative condition,operative findings,and operative outcomes for the two techniques.RESULTS The study included 175 patients,including 92 in the DSA group and 83 in the CSA group.The two groups were similar in baseline characteristics,preoperative medical treatment,and operative findings except for the Montreal classification location.The 30-days postoperative complication rate was signi-ficantly lower in the DSA group compared with the CSA group(16.3%vs 32.5%,P=0.009).Ileus incidence was significantly lower in the DSA group than in the CSA group(4.3%vs 14.5%,P=0.033),and the hospital stay was shorter in the DSA group than in the CSA group(5.67±1.53 days vs 7.39±3.68 days,P=0.001).CONCLUSION The DSA technique was feasible and showed comparable postoperative outcomes with lower short-term complic-ations compared with the CSA technique.Further studies on CD recurrence and long-term complications are warranted.

Experience of humanistic nursing in hemodialysis nursing for patients with diabetic kidney disease

BACKGROUND Diabetic kidney disease(DKD)is a prevalent complication of diabetes that often requires hemodialysis for treatment.In the field of nursing,there is a growing recognition of the importance of humanistic care,which focuses on the holistic needs of patients,including their emotional,psychological,and social well-being.However,the application of humanistic nursing in the context of hemodialysis for DKD patients remains relatively unexplored.AIM To explore the experience of humanistic nursing in hemodialysis nursing for DKD patients.METHODS Ninety-six DKD patients treated with hemodialysis from March 2020 to June 2022 were included in the study and divided into the control cluster(48 cases)and the study cluster(48 cases)according to different nursing methods;the control cluster was given routine nursing and the study cluster was given humanized nursing.The variances of negative emotion mark,blood glucose,renal function,the incidence of complications,life mark and nursing satisfaction before and after nur-sing were contrasted between the two clusters.RESULTS No significant difference in negative emotion markers between the two clusters were observed before nursing(P>0.05),and the negative emotion markers of the two clusters decreased after nursing.The Hamilton Anxiety Rating Scale and Hamilton Depression Rating Scale markers were lower in the study cluster than the control cluster.The healing rate of patients in the study cluster was significantly higher than the control cluster(97.92%vs 85.42%,P<0.05).Blood glucose parameters were not significantly different between the groups prior to nursing(P>0.05).However,after nursing,blood urea nitrogen and serum creatinine(SCr)levels in the study cluster were lower than those in the control cluster(P<0.05).The incidence rate of complications was significantly lower in the study group compared to the control cluster(6.25%vs 20.83%,P<0.05).There was no significant difference in the life markers between the two clusters before nursing.While the life markers increased after nursing for both groups,the 36-item health scale markers in the study cluster were higher than those within the control cluster(P<0.05).Finally,the nursing satisfaction rate was 93.75% in the study cluster,compared to 75% in the control cluster(P<0.05).CONCLUSION In hemodialysis for DKD patients,the implementation of humanistic nursing achieved ideal results,effectively reducing patients’psychological negative emotion markers so that they can actively cooperate with the diagnosis and nursing,facilitate the control of blood glucose and the maintenance of residual renal function,reduce the occurrence of complications,and finally enhance the life quality and nursing satisfaction of patients.It is worthy of being widely popularized and applied.

Advancing perioperative optimization in Crohn's disease surgery with machine learning predictions

This editorial offers commentary on the article which aimed to forecast the likelihood of short-term major postoperative complications(Clavien-Dindo grade≥III),including anastomotic fistula,intra-abdominal sepsis,bleeding,and intestinal obstruction within 30 days,as well as prolonged hospital stays follow-ing ileocecal resection in patients with Crohn’s disease(CD).This prediction re-lied on a machine learning(ML)model trained on a cohort that integrated a no-mogram predictive model derived from logistic regression analysis and a random forest(RF)model.Both the nomogram and RF showed good performance,with the RF model demonstrating superior predictive ability.Key variables identified as potentially critical include a preoperative CD activity index≥220,low preope-rative serum albumin levels,and prolonged operation duration.Applying ML ap-proaches to predict surgical recurrence have the potential to enhance patient risk stratification and facilitate the development of preoperative optimization strate-gies,ultimately aiming to improve post-surgical outcomes.However,there is still room for improvement,particularly by the inclusion of additional relevant clinical parameters,consideration of medical therapies,and potentially integrating mole-cular biomarkers in future research efforts.

Liquid Subcutaneous Levodopa-Carbidopa ND0612 Effects on Motor Symptoms in Individuals with Parkinson’s Disease: A Systematic Review and Meta-Analysis

Objective: In the manuscript titled “Liquid subcutaneous Levodopa-Carbidopa ND0612 effects on motor symptoms in individuals with Parkinson’s Disease: A systematic review and meta-analysis”, the objective was to conduct a systematic review with meta-analysis to investigate the effects ND0612 24-hour dosing regimen has on motor symptoms in individuals with Parkinson’s Disease (PD). Introduction: ND0612 is a novel minimally invasive continuous subcutaneous delivery system of liquid Levodopa-Carbidopa being investigated for the treatment of PD in individuals experiencing motor symptoms. Methods: A systematic literature search was conducted in PubMed, Cochrane, and EBSCO databases to identify randomized controlled trials investigating the effects of ND0612 on motor symptoms in individuals with PD. Outcomes included the Unified Parkinson’s Disease Rating Scale (UPDRS) Part II and Part III scores. Methodological quality was assessed using the Cochrane Grading of Recommendations Assessment, Development, and Evaluation approach. Meta-analysis was performed using a random effects model with the DerSimonian and Laird method to estimate the effects of the ND0612 24-hour dosing regimen on UPDRS Part II and Part III scores. Results: Three studies were included in our review. There were statistically significant reductions in UPDRS Part II scores (mean difference (MD) −3.299;95% confidence interval (CI) −3.438, −3.159) and in UPDRS Part III scores (MD −12.695;95% CI −24.428, −0.962) in the ND0612 24-hour dosing regimen. Results were based on very low certainty of evidence. Conclusion: Based on very low certainty evidence, the ND0612 24-hour dosing regimen is effective at improving motor symptoms in individuals with PD. Our findings suggest that ND0612 is more effective at improving UPDRS Part II and Part III scores in individuals with PD than other pharmacological and non-pharmacological treatments, warranting further study.

Metabolic complications of psychotropic medications in psychiatric disorders:Emerging role of de novo lipogenesis and therapeutic consideration

Although significant advances have been made in understanding the pathophysiology of psychiatric disorders(PDs),therapeutic advances have not been very convincing.While psychotropic medications can reduce classical symptoms in patients with PDs,their long-term use has been reported to induce or exaggerate various pre-existing metabolic abnormalities including diabetes,obesity and non-alcoholic fatty liver disease(NAFLD).The mechanism(s)underlying these metabolic abnormalities is not clear;however,lipid/fatty acid accumulation due to enhanced de novo lipogenesis(DNL)has been shown to reduce membrane fluidity,increase oxidative stress and inflammation leading to the development of the aforementioned metabolic abnormalities.Intriguingly,emerging evidence suggest that DNL dysregulation and fatty acid accumulation could be the major mechanisms associated with the development of obesity,diabetes and NAFLD after long-term treatment with psychotropic medications in patients with PDs.In support of this,several adjunctive drugs comprising of anti-oxidants and antiinflammatory agents,that are used in treating PDs in combination with psychotropic medications,have been shown to reduce insulin resistance and development of NAFLD.In conclusion,the above evidence suggests that DNL could be a potential pathological factor associated with various metabolic abnormalities,and a new avenue for translational research and therapeutic drug designing in PDs.