In septic shock, coagulation factors FVII and FIX and Protein C had AUROCs 0.67–0.78. In severe sepsis, Antithrombin III, Protein C, C-reactive protein, Procalcitonin and Thrombopoietin had AUROCs 0.73–0.75. In sepsis, Tumor Necrosis Factor a, and Interleukins 1β and 10 had AUROCs 0.66–0.72. In patients admitted to the ICU with a suspected diagnosis of infection, coagulation factors and inhibitors, as well as cytokine and inflammatory marker levels, have substantial predictive value in distinct groups of septic patients.Although coagulation disorders and immune/inflammatory response have been associated with the final outcome of patients with sepsis, their link with thetemporaryclinical deterioration or improvement of patients is unknown. We aimed to investigate this link. We prospectively included consecutive patients admitted to the intensive care unit (ICU) with a suspected diagnosis of infection and evaluated within the first 24 h from admission. Blood levels of many cytokines and inflammatory and coagulation factors were measured and their predictive value was assessed by calculating the Area Under the Receiver Operating Characteristic (AUROC) curves. Patients ( Sepsis is one of the leading causes of death for patients in the Intensive Care Unit (ICU) and a major contributor to the growing financial burden of medical care worldwide ,2. As a In 2016, a new definition of sepsis was created (Sepsis-3), according to which sepsis is defined as an infection that causes organic dysfunction, with the abolition of the term SIRS when referring to sepsis and the term severe sepsis ,8,9. HowSeptic shock and multiorgan dysfunction are the most common causes of death in patients with sepsis ,4,5,6. SThe present study aimed to investigate whether the various disorders of the blood coagulation system and the immune and inflammatory response  can predict the temporary worsening or improvement of the clinical status of patients admitted to the ICU due to suspected infection. Therefore, we included patients admitted to the ICU and evaluated them on admission and then daily until their discharge from the ICU or death.This research study was conducted in the ICU of the General Hospital “Evangelismos”, Intensive Care Clinic of the Medical School of the National and Kapodistrian University of Athens. Over a period of one and a half years (1 January 2016–30 June 2017), were prospectively included all consecutive patients who were admitted to the ICU with a suspected diagnosis of infection, were evaluated within the first 24 h from admission and finally confirmed that: (a) had sepsis, severe sepsis or septic shock, or (b) had a disease associated with SIRS without infection. Additionalwere consecutively included patients who had undergone trauma or surgery without suspected infection and did not meet the SIRS criteria, but could potentially develop SIRS and sepsis. The latter group was studied as a control group. Were excluded patients: (a) under 16 years of age; (b) with chronic hepatic failure, chronic renal failure, known hematological disease with coagulation or platelet count disorders;(c) with malignancy under chemotherapy or malignancies associated with coagulation or platelet count disorders; (d) under anticoagulant or antiplatelet therapy; and (e) who had been transfused with units of fresh frozen plasma or concentrated coagulation agents or platelet units within the previous 48 h of admission to the ICU.Thestudywasapprovedbythehospitalinstitutionalreviewboards . Informed consent was waived.Blood levels of the following cytokines and inflammatory and coagulation factors were measured in the first 24 h after admission to the ICU: Procalcitonin (PCT), C-reactive protein (CRP), TPO, Interleukin 6 (IL-6), Tumor Necrosis Factor a (TNF-a), Interleukin 1β (IL-1b), Interleukin 10 (IL-10), Antithrombin III (ATIII), Protein C (PrC), D-dimmers (Dds), Fibrinogen (Fibrin), Plasminogen, and coagulation factors FV, FVII, FVIII, FIX, FvWillebrand (vWF), and FX.In the first 24 h after admission to the ICU, were also measured the arterial blood gases and usual laboratory parameters . Cultures of biological fluids were obtained in suitable transport media to isolate potential pathogenic microorganisms. Imaging was performed on admission (at least chest X-ray) and where specific diagnostic tests  were required to document a possible source of infection.All these clinical measures have scientific rationale based on the current mechanistic understanding of sepsis and were taken by the attending physicians according to the guidelines used in our ICU .All included patients were allocated in five groups, i.e., sepsis, severe sepsis, septic shock, SIRS without infection, and trauma or surgery without SIRS or infection. The classification of patients in one of these groups took place in the days following the admission of patients when the results of laboratory, bacteriological, and imaging tests were completed. This classification, as well as the clinical assessment of patients from ICU admission until their exit from the ICU or death, was performed by two experienced ICU physicians who did not participate in the study. These physicians assessed the stage of sepsis based on ACCP/SCCM criteria , the sevClinical improvement was defined as discharge from the ICU, a decrease of at least 1 point from baseline on a six-point ordinal scale, or both. The six-point scale consisted of the following categories: (1) not in the ICU; (2) in the ICU, without SIRS or infection; (3) in the ICU, with SIRS or sepsis; (4) in the ICU, with severe sepsis; (5) in the ICU, with septic shock; and (6) death. Clinical deterioration was defined as death, an increase of at least 1 point from baseline on the six-point ordinal scale, or both. The first change in the clinical status  of the patients was taken into account for the evaluation of the predictive value of the variables measured within the first 24 h from admission.Blood samples were obtained by collecting whole blood from a peripheral vein, on the one hand for the measurement of cytokines and inflammatory markers in sterile Wasserman tubes and collection of serum after whole blood coagulation for 45–60 min, and on the other hand for the measurement of factors of coagulation in tubes containing 3.8% sodium citrate as an anticoagulant for plasma collection. Both serum and plasma were taken up after centrifugation for 10 min at 3000 rpm. Serum and plasma were used immediately or kept frozen at −80 °C for subsequent analysis in 0.5 mL plastic tubes. All analyzes were performed without knowing either the patient’s name or the day of sample collection.The acute phase protein identified in our study was CRP measured by a nephelometric technique . PCT serum levels were measured using an immunoassay with a sandwich technique and a chemiluminescent detection system, according to the manufacturer’s protocol . TPO serum levels were measured using an enzyme-linked immunosorbent assay .The determination of cytokines TNF-a, IL-1b, IL-10, and IL-6 in the serum was done by the ELISA (enzyme-linked immunosorbent assay) method, using commercial diagnostic kits .The activity of ATIII, PrC and Plasminogen was measured in plasma by a chromogenic assay . The activity of coagulation factors FV, FVII, FVIII, FIX, vWF, and FX was determined by the method of micro-ELISA . The determination of Fibrinogen was done with a modification of the classic Clauss coagulation method . Dds were measured by an immuno-turbidimetric assay .p-value <0.05 were considered statistically significant. The evaluation of the predictive value of the various variables was done by creating ROC (Receiver Operating Characteristic) curves. Areas below the ROC curve  were considered poor when they were 0.6–0.7, sufficient 0.7–0.8, good 0.8–0.9, and excellent when they were ≥0.9 [The values of the various quantitative variables were expressed as median and range values due to the absence of a normal value distribution . Therefore, non-parametric tests were used for group comparisons. Differences between multiple groups were assessed by the Kruskall Wallis analysis of Variance by ranks, while comparisons between two groups were made by the Mann–Whitney U test. Differences in qualitative variables were assessed using the Yates corrected Chi-Square test. Differences with ere ≥0.9 . The sta2, and 3/102 patients (3%) had chronic lung disease, whereas 39/102 patients (38%) had at least two comorbidities.The demographic, clinical and usual laboratory data of patients upon admission to the ICU are presented in 2/FiO2 ratio and platelet count. Infections were microbiologically proven in 50 of the 59 patients with infection (85%), of which 43 (86%) were due to a Gram-negative germ, 3 (6%) to a Gram-positive germ and 4 (8%) were mixed infections.The study included prospectively 102 patients: 26 patients with trauma or surgery who did not meet at least two of the SIRS criteria, 17 patients with SIRS  and sufficient (AUROC 0.79) predictive value, respectively, while the rate of MODS was higher in patients who worsened compared to those who improved only in the group of patients with septic shock where its predictive value was excellent (AUROC 0.91).Despite many pre-clinical studies and clinical trials, there is no known treatment forsepsis. Based on the assessment of the various factors at admission, the present study aimed to unravel the most critical factors for the outcome of sepsis, and thus point to the type of intervention needed, or to the direction of scientific/clinical research to eventually improve the outcome.Our main findings were: (1) Among the coagulation system factors, only a few had a predictive value. In particular, FVII and FIX activities were lower in patients who deteriorated compared to those who improved only in the group of patients with septic shock with sufficient (AUROC 0.72) and poor (AUROC 0.67) predictive value, respectively. Among the other coagulation factors, only FVIIII activity was lower in patients who worsened than in those who improved in the trauma/surgery group albeit with poor predictive value (AUROC 0.63); (2) Among the coagulation inhibitors, both ATIII and PrC had significant predictive value. In particular, ATIII activity was lower in patients who deteriorated than in those who improved in the group of patients with severe sepsis with sufficient predictive value (AUROC 0.74). PrC activity also was lower in patients who deteriorated compared to those who improved in the groups of patients with severe sepsis and septic shock with sufficient predictive value ; (3) Cytokine levels had significant predictive value mainly in the group of patients with sepsis. Indeed, in this group, TNF-α, IL-1b and IL-10 levels were higher in patients who worsened than in those who improved with poor to sufficient predictive value ; (4) CRP, PCT, and TPO levels had significant predictive value only in the group of patients with severe sepsis. Indeed, in this group, the levels of all these proteins were higher in patients who worsened than in those who improved with sufficient predictive value (AUROCs 0.73–0.75); (5) Among the usual laboratory variables, only blood lactic acid had a significant predictive value restricted in the group of patients with septic shock. Indeed, lactate levels were higher in patients who deteriorated compared to those who improved in septic shock with good predictive value (AUROC 0.87); and (6) The various clinico-laboratory scores and measurements had a significant predictive value in almost all groups of septic patients. Specifically, APACHE, SOFA, and LIS were higher in patients who deteriorated compared to those who improved in all three groups of septic patients with sufficient to good prognostic value (AUROCs 0.72–0.84), PaOThe SOFA rating index is a simple but effective method to describe organ dysfunction in severely ill patients. It was originally designed to evaluate/describe and not to predict the survival expectancy of seriously ill patients . It inclIn our study, when patients entered the ICU, as expected, those with septic shock were more severely ill than patients in the other groups and had higher SOFA scores . SOFA scAPACHE II score is widely used in ICUs as a system for assessing the severity of patients, with high values associated with increased mortality . An earlIn our study, as expected, patients with septic shock were more severely ill than patients in the other groups, and had a higher APACHE II score . Additio2/FiO2 ratio and LIS could predict the need for mechanical respiratory support, but PaO2/FiO2 ratio was a better prognostic indicator for the length of stay in the ICU compared to the LIS [On ICU admission, both PaO the LIS . LIS has the LIS ,27.2/FiO2 ratio) except those in the severe sepsis group  overconsumption due to increased thrombin production, (b) degradation by plasma elastases, which are released by activated neutrophils, and (c) insufficient synthesis ,53,54,55In the present study, on ICU admission, ATIII had lower activity in patients with severe sepsis or septic shock than in the other three groups . ATIII aBesides its action as a coagulation inhibitor, PrC contributes to fibrinolysis, as follows: The conversion of plasminogen to plasmin is activated by tissue-type plasminogen activator (t-PA) and urokinase-like plasminogen activator (uPA). Endothelial cells are the main source of t-PA but t-PA can also be isolated in other tissues . The fibIn the present study, at the time of ICU admission, PrC had lower activity in patients with septic shock than in the other four groups . PrC actIt has been found that the activity of all coagulation factors is gradually reduced in severe sepsis and mainly in septic shock, mainly due to depletion of homeostatic mechanisms ,60.In our study, on ICU admission, significant differences in the activity of coagulation factors FVII, vWF, FX, and FV were observed between the groups . The actMany studies have been performed to evaluate interleukins as prognostic markers. In the study of Bozza et al. , IL-1b aIl-1b is not normally identified in the serum but is detected in the serum of patients with sepsis. McAllister et al.  detectedIL-10 was originally described as an inhibitor of cytokine production by activated macrophages. Gerard et al.  showed tIn the present study, IL-1b and IL-10 levels had significant predictive value only in the group of patients with sepsis. Indeed, IL-1b and IL-10 levels were higher in patients who deteriorated compared to those who improved only in the group of patients with sepsis  with sufTNF-a is a precursor of inflammation in a large number of inflammatory diseases, infectious and non-infectious . TNF-a cIn our study, TNF-a levels were higher in patients who deteriorated compared to those who improved only in the groups of patients with trauma/surgery and sepsis  with sufPCT in the blood of healthy individuals has values <0.1 ng/mL. In bacterial as well as fungal infections, PCT levels are found to be elevated to some degree, depending on the severity of the infection. Thus, in septic patients, PCT levels may increase 5.000–10.000-fold, while calcitonin levels remain within normal limits ,75. In S+ progenitor cells [TPO is a glycoprotein hormone that regulates the number of circulating platelets by stimulating the growth and maturation of megakaryocytes . It is aor cells . TPO is or cells . Moreoveor cells . These for cells  are consNevertheless, in the present study, the levels of CRP, PCT and TPO upon admission to the ICU were higher in patients who deteriorated compared to those who improved only in the group of patients with severe sepsis  with sufThis study has several strengths. First, we included all consecutive patients who were admitted to the ICU of a big referral Hospital with a suspected diagnosis of infection, thereby minimizing selection bias. Second, all data were prospectively collected and patients were evaluated on admission and then daily until their discharge from the ICU or death by two independent and experienced ICU physicians. Third, to the best of our knowledge, the present study is the first one assessing the predictive value, in the sense of patient temporary clinical deterioration or improvement, of the various factors and variables  measured on ICU admission, regardless from the final outcome. Indeed, many previous studies have examined the predictive value of most of these factors and variables in the sense of the final outcome, i.e., survival or death , thus making solid conclusions uncertain in these groups. Third, we did not measure coagulation factor FXIII activity which is a plasma transglutaminase responsible for final clot stabilitywith a strong role in inflammation and sepsis [We acknowledge some limitations. First, we included patients from only one Hospital, thereby potentially minimizing generalizability. Second, three of the groups of the study, i.e., SIRS without infection, sepsis, and severe sepsis, included a rather small number of patients (d sepsis .2/FiO2) had a significant predictive value in almost all groups of septic patients.In patients admitted to the ICU with a suspected diagnosis of infection, among the coagulation factors only FVII and FIX and the coagulation inhibitors, ATIII and PrC had substantial value in the sense of predicting temporary clinical improvement or deterioration in patients with severe sepsis or septic shock. Cytokine levels had a significant predictive value only in the group of patients with uncomplicated sepsis, while levels of CRP, PCT and TPO were predictive only in the group of patients with severe sepsis. Lactate had a significant predictive value only in the group of patients with septic shock, whereas the various clinico-laboratory scores and measurements (APACHE II, SOFA, LIS, and PaO


On psychiatric wards, aggressive behaviour displayed by patients is common and problematic. Understanding factors associated with the development of aggression offers possibilities for prevention and targeted interventions. This review discusses factors that contribute to the development of aggression on psychiatric wards.In Pubmed and Embase, a search was performed aimed at: prevalence data, ward characteristics, patient and staff factors that are associated with aggressive behaviour and from this search 146 studies were included.The prevalence of aggressive behaviour on psychiatric wards varied (8–76%). Explanatory factors of aggressive behaviour were subdivided into patient, staff and ward factors. Patient risk factors were diagnosis of psychotic disorder or bipolar disorder, substance abuse, a history of aggression, younger age. Staff risk factors included male gender, unqualified or temporary staff, job strain, dissatisfaction with the job or management, burn-out and quality of the interaction between patients and staff. Staff protective factors were a good functioning team, good leadership and being involved in treatment decisions. Significant ward risk factors were a higher bed occupancy, busy places on the ward, walking rounds, an unsafe environment, a restrictive environment, lack of structure in the day, smoking and lack of privacy.Despite a lack of prospective quantitative data, results did show that aggression arises from a combination of patient factors, staff factors and ward factors. Patient factors were studied most often, however, besides treatment, offering the least possibilities in prevention of aggression development. Future studies should focus more on the earlier stages of aggression such as agitation and on factors that are better suited for preventing aggression such as ward and staff factors. Management and clinicians could adapt staffing and ward in line with these results. Aggression is a serious problem on psychiatric wards and has large consequences for patients as well as staff working in mental healthcare: aggressive behaviour is an important reason to seclude or restrain a patient , but, acDevelopment and expression of aggression is generally explained as multifactorial: being environment-related , mental health care-system related , patient-related  and clinician-related  , 6. Prevcontinuum of severity, where agitation evolves into aggression and ultimately into violence. Violence differs from aggression by the severity and intentionality of the behaviour.The term aggression is ambiguous: multiple interpretations have been found, and it is often used interchangeably with agitation and violence. Agitation is defined in the DSM-5 as “a state of excessive psychomotor activity accompanied by increased tension and irritability” resulting in non-productive and repetitious behaviour” . GeneralThe vast amount of literature on aggression may reflect that the topic is important and of interest. Reviews on violence on the emergency ward , aggressOf the reviews that addressed all three factors, these either searched studies between 1983 and 2008 and this thus needs updating , 22, 23,This current review is the first with the aim to compile a complete overview of the available knowledge on patient, staff and ward factors that contribute to the development of aggression on a general psychiatric admission ward and underline this with statistic evidence where possible. With those insights more and improved preventative measures can be designed in the future.This systematic review was written in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines  followinStudies were included if their main objective was to examine the prevalence of aggression or to study factors associated with aggression on adult inpatient wards in a psychiatric hospital. Aggression is distributed on a continuum of severity ranging from agitation to aggression to violence. Therefore, the various stages of the continuum are incorporated. Inclusion criteria were: adult patients (age 18–65 years), inpatient in a psychiatric hospital, measurements of aggression, violence, agitation, assaults or incidents.Exclusion criteria were: aggression in case of delirium or dementia, forensic wards, the effect of aggression on mental health workers and health care costs, studies on aggression management, studies on rating scales for aggression prediction, papers on new legislation, publication year < 1999, conference abstracts and non-English language.Identified studies were conducted between January 1999 and December 2019, using the electronic databases Pubmed and Embase. The following search terms were used: ‘psychiatry’, ‘inpatients’, ‘aggression’, ‘violence’, and ‘agitation’ (see Eligibility assessment was performed independently by 2 reviewers (IW and MB), disagreements were resolved by consensus.Several checklists were available for quality assessment of the articles, the majority being observational research. However, we could not find an instrument that could be used for the articles in the present systematic review. Although Strobe  and NOS  are most-used and recommended, the NOS is outdated and has never been peer reviewed. Strobe is designed to assist authors in writing a paper on a cohort study, but was used as scoring quality because better assessment lists were lacking. As a quality assessment tool it is inefficient and it cannot be used to score case-control studies.For this reason, 2 existing methodological quality criteria lists (NOS and Strobe) were combined into a new list: the Observational Study Quality Evaluation (OSQE), which also includes all domains of the Risk Of Bias In Non-randomised Studies of Interventions (ROBINS-I), but with less details . AdvantaIn the present rating, the maximum number of stars is 15 , because 13 obligatory and 2 optional items (moderation and sample size) were included and no cut-off score was used. Quality assessment of the selected studies was performed by authors IW and EV and through meetings consensus was reached on the score of the papers. In case of not reaching mutual agreement, the papers were discussed with MB to obtain consensus.Data extracted were: number of included patients, demographic characteristics of included patients or staff , admission status (voluntary or involuntary or both), method of measuring aggression  as well as frequency, severity and type of aggression.The extracted factors contributing to the emergence of aggression were:Patient factors: gender, age, diagnosis, severity of psychopathology, history of aggression or violence, (history of) substance abuse, insight, homelessness.Ward factors: location, time, bed occupancy, atmosphere of the ward, restrictions and characteristics of the ward.Staff factors: mean age of nurses and medical staff, years of experience, gender, quality of the interaction with the patient and the level of staffing.Extracted data were imported in the database by IW and checked by MB.Descriptive statistics were applied such as averages and (weigthed) percentages. Due to heterogeneity of the data, a full meta-analysis was not considered feasible.The search yielded 4698 titles from PubMed and 698 titles from Embase. Cross-referencing from 20 reviews published earlier resulted in 816 papers on this topic . BeforehIn 71 studies, prevalence rates for inpatient aggression were reported. In this paragraph the results of studies that assessed the prevalence of aggressive incidents by patients on closed wards are presented. A division was made for studies assessing the prevalence of aggression experienced by staff (e.g. percentages of staff experiencing aggression in their career) and aggression incidents in groups of patients (e.g. a percentage of patients admitted that are involved in an incident).In 17 studies, prevalence of aggression towards nurses or other members of staff  was examined  28–44].–44.28–44The studies scored an average of 4.7  on the OSQE. OSQE scores including qualitative comments are available upon request. Of the included staff members, 62% was female. Prevalence of any sort of aggression ranged from 65%  tot 99% There were 53 patient cohort studies that reported on aggression prevalence in individual patients  46–95].–95.46–95Percentages of in-patients that were involved in aggression ranged from 7.5% up to 75.9%. The weighted mean percentage of patients that were involved in aggression is 23% (SD = 0.003).In the first 24 hours or first week, the highest percentages of aggression were measured , 79, 81.Of the 145 included studies, 82 presented data on patient factors associated with aggression. The factors addressed were diagnosis or severity of psychopathology, gender, age, history of violence, substance abuse, homelessness and illness insight. An additional 44 studies reported on other patient factors, which are mentioned at the end of this paragraph.Of the 68 studies on this item, the average OSQE score was 7  , 96–104,In one study aggressive patients were distracted by internal stimuli during an incident  in 60% oIn 12 papers diagnosis had no significant contribution to the development of aggression , 99, 101Assessment of symptom severity in relation to aggression development was addressed in 14 studies comparing PANSS or BPRS scores (as a measure for symptom severity) between aggressive and non-aggressive patient groups see  47, 48,, 106–110Higher scores on PANSS or BPRS appear to increase the risk for aggression, whereas a high score on the subscale for depression may be protective for aggression.Thirty-seven studies reported on gender as a potential factor related to aggression development , 108–117SD = 1.8; range 4–12) [In 35 included studies, age was examined in association with aggression with an average OSQE score of 7.7 (ge 4–12) –114, 118Age was not associated with the development of aggressive behaviour in 23 studies , 112–114In 25 studies, an association between the development of aggression and a history of violence was examined; the average score on the OSQE was 6.9 (SD = 1.9 range 3–11) , 121.Violence in a previous admission proved predictive for aggression in a subsequent admission  , 117. WiA history of aggression was found to have ORs between 1.45–7.25 for aggression during the admission , 88, 104Overall, a history of aggression seems to be a factor contributing to the development of aggression on the psychiatric ward.In 22 studies, a correlation between substance abuse and the occurrence of aggression was reported , 123. Th2 = 9.07; p < .005) [p < .01) [< .01) [Severely agitated patients were found to use substances more often compared to non-agitated patients: 7.1% vs 13.5% (χ < .005) . The ris < .005) . When thp < .01)  and it e [< .01) , OR = 5. [< .01) , OR = 2. [< .01) . For alc [< .01) .= .008) [Specifically patients with a bipolar disorder and a positive drug screen for cannabis had more episodes of agitation (p = .033) and more use of medication pro re nata (p = .008) .One study using a momentary assessment strategy found that physical aggression was associated with alcohol craving , cigarette craving  and symptoms of withdrawal  . Nurses Finally, 4 studies failed to show an association between substance abuse and aggression development , 114.Overall it can be concluded that current, or a history of substance or alcohol abuse is indeed a factor influencing the occurrence of aggression on the inpatient ward.2 = 32.44; p < .001 [< .01) [Five studies focussed on illness insight in relation to aggression development , 116. Nop < .001 . Violent [< .01) . No concPatient related factors that could not be classified in the aforementioned factors are briefly summarized in this paragraph. Aggressive patients may on average be admitted longer on wards ) , 91.2 = 9.07; p < .05) [< .001), have been in foster care as a child , have migrated from their country of origin , have divorced parents  or have a parent or sibling with psychiatric problems  [Aggressive patients more frequently used less antipsychotic medication on admission: 38.8% vs 76% (χp < .05) . In the p < .05) . Living p < .05) . Patientp < .05) . When pap < .05) . A firstp < .05) . Comparerovided) .2 = 4.38; p = .04 [2 = 324.412; p < .001 [Patients who were involuntarily admitted showed more aggression . Howevep < .001 , 74. A hp < .001 .One study found that patients with akathisia show more threatening behaviour  and more physical aggression  .Fifty-five studies reported on staff factors that may be associated with aggression at psychiatric wards, including the quality of interaction between staff and patients. The average OSQE-score was 4.9  , 127–151Fourteen studies reported data on the gender of the nurse in relation to aggression development, depicted in With limited evidence, it appears that male nurses were more often involved in aggressive incidents, which does not mean that they contribute to the occurrence of aggression because of their gender.Focussing on the age of staff members, younger nurses were more at risk to experience aggression against them  ; an age < .002) [In 13 studies, the years of professional experience or education level of nurses was studied as a potential factor associated with the occurrence of aggression on the ward –142, 146< .002)  or OR = < .002) , as well< .002)  and ARR < .002) ). The co< .002) , but not< .002) . Staff t< .002) , but thi< .001) and higher levels of temporary staff (F (df = 3) = 6.64; p < .001) [Inadequate numbers of staffing led to more aggression according to interviewed nurses , 130. In < .001) . Staff b < .001) .There were 24 studies included discussing the quality of interaction between nurses and patients in relation to aggression development , 152–158Studies that interviewed staff pointed to several factors explaining aggression development. Poor communication between staff and patients , 158 andNo provocation or trigger was found in the interaction in 37% , 157. FrOne study on the relation between aggressive incidents and perceived workload or stress experienced by staff, showed that job strain increased the risk for aggression , assessed in nurses with the Job Content Questionnaire . The risNurses who believed that aggression by patients is preventable, experienced lower rates of incidents in the past year: z = -2.02; p = .044 . Scores Nurses stated a lower risk of violence was present when they worked as a team and their personal knowledge was taken into account in the treatment decisions . Less ag37 studies were included discussing how ward factors influence the occurrence of aggression, with an average score on the OSQE of 5.7  , 159–1642 = 7.9; df = 1; p = .005) [< .0001 [< .001 [Patients as well as staff members reported overcrowding as a potential reason for aggression on the ward . The ave = .005) . The net[< .0001 . The lar[< .0001 . A 5% su [< .001 . One stu [< .001 . The eviWithin a shift in which a new patient was admitted on the ward the nurse was more likely to experience aggression  . Especia2 = 21.45; df1; p < .001).Seven studies reported on the location of incidents in a hospital , 151. MoAggressive incidents were reported in hallways (14%–67%), the day or activity room (13%–28%), patient bedroom (8.5%–21.9%), dining room (7%– 17%), staff office (6.1–19%) and in the courtyard of the unit 3.3% , 138.In 18 studies, the time of incidents was compared see  29, 72,, 161–163Patients reported that contributing factors to aggression were: unhygienic surroundings and not being heard when complaining about this, the quality and quantity of food, the unavailability of daily necessities, the lack of privacy and the realization that personal information was not handled confidential, noise levels on the ward, crowding or the place felt prison-like, a negative experience of seclusion, unfair limit-setting and poor communication about this, and a lack of structured activities .Staff members thought that problems with legislation and the way hospital management dealt with aggressive incidents contributed to the occurrence of aggression . BehavioFeeling unsafe in the ward led to angry outbursts and disruptive behaviour . Noise oWhen staff approached a patient with overpowering numbers, applied manual restraint or locked the doors of the ward for 1–3 hours, more aggressive incidents took place . In an oPatients stated that smoking habits led to aggression (e.g. because smokers and non-smokers shared rooms and established smoking restrictions) . A smokiDifferent restrictions and atmospheric factors on the ward seem to influence the occurrence of aggression on the inpatient ward, offering possibilities for change on the ward itself.The aim of this systematic review was to provide an overview of the scientific literature addressing the prevalence of, and factors associated with aggression on psychiatric wards. In accordance with previous studies, contributing factors are subdivided into patient, staff and ward-related factors , 165.agitation–aggression—violence resulting in a larger sample of studies which may reflect in the larger prevalence interval.Aggression is a serious issue in mental health care, where safety of both patients and staff needs to be protected. The weighted mean prevalence of aggressive events was 54%, with a wide prevalence range between studies (7.5% to 75.9%). This prevalence range deviates from a previous review, reporting a 3–44% range . An explOnly a small proportion of the admitted patients is responsible for the majority of the aggressive incidents: 0.5–33% of patients cause 42–66% of the incidents. The first three days of admission appear to be related with the highest prevalence rates, which is in accordance with an earlier review by Woods and colleagues (2007) . This fiThe prevalence of experiencing aggression among nurses in mental health care is 25%-80%. This is in line with an earlier review, which showed that the majority of staff in acute psychiatric units have been assaulted at some point in their career .Although the prevalence of aggression rates vary, they underline the scale and impact of the problem. Programs aimed at reducing aggression should focus their actions on the first days after admission and on helping staff to deal with aggression.In the current review identified patient factors that contribute to an increased risk of aggression development are: being diagnosed with a psychosis-spectrum disorder, a personality disorder or a bipolar disorder . At symptom level, paranoid delusions, impulsivity and hostility increase the risk for aggression development. These findings are a replication of previously published reviews on patient factors associated with aggression , 168–170A diagnosis of major depression or higher scores on feeling down or gloomy at symptom level decreased the risk of aggression. An earlier review by Dack (2013) found this decrease in risk for aggression for depression, bipolar disorder, adjustment disorder and substance abuse . In the A minority of the studies (n = 13) included here confirmed male gender as a factor influencing the occurrence of aggression, but most studies found no relation n = 22). Previous reviews concluded the same , 166, bu. PreviouThe review by Dack and colleagues (2013) concluded that younger age is a risk factor for aggression , which wIn spite of the use of different assessment methods, all studies indicated that a history of aggression (broadly defined) predicted renewed occurrence of aggression. This is in line with earlier reviews where a history of aggression was significantly associated with aggression in the current admission , 172.Substance abuse may be a factor contributing to aggression, since a majority of studies (18 out of 22) concluded some attributing effect. This is in line with the reviews written in the past , 25, 166Although homelessness and insight have been mentioned as a risk factor in a review by Witt in 2018 , only foIn the review by Dack and colleagues (2013), involuntary admission was found to be a contributing factor , which wClinical variables such as more severe symptoms and unresponsiveness to treatment have shown to be better predictors of aggression than demographic variables  and thesStaff on psychiatric wards are not only victim to aggression, but also contribute to the occurrence of aggression since aggression is interpersonal. Aggression development in patients is positively related to male gender of staff, job strain, job dissatisfaction, overwork, dissatisfaction with leadership, tiredness, lack of good introduction of the nurse, poor collaboration between nurses, more temporary staff, and more anxiety in nurses. This is a replication of the findings in earlier reviews, but none of them integrated these factors in one review –23, 172.Some form of interaction between patient and staff precipitates aggression in 40% of the incidents , 176. ThFuture studies should address explicitely patient-staff interaction and factors as job strain, job dissatisfaction and overwork that influence this interaction. These factors are crucial for a safe atmosphere on wards and essential for management in guiding ward staff appropriately.The ward in itself may also contribute to more aggression development, which was also concluded by Welsh in their review on environmental factors  regardinNumerous other factors have been examined, such as the perceived (absence of) privacy for patients, personal space and freedom to move around, restrictions placed upon patients, inconsistent following of the rules, feeling unsafe, noise on the ward and the feeling of physical confinement. All these are mentioned in earlier reviews , 10, 23.The locked doors of a closed ward may be perceived by the patient as being controlled, although it may also provide a secure feeling. For staff it reduces the need for close observation and protects the ward from the outside , 178. PrThe model of High Intensive Care (HIC) has been adopted in many psychiatric institutions in Europe. The HIC model focusses on creating an optimal healing environment, with as much autonomy and privacy as possible. Preventing unnecessary escalation is persued through a welcoming atmosphere, frequent contact between patients and nurses that focus on the strengths of a patient, frequent contact with ambulatory carers, multidisciplinary staff, minimum use of coercive measures, and in case of agitated behaviour or aggression the possibility of one-on-one nursing . The resThe heterogeneity of the studies in this systematic review is large because of differences in quality of methodology and a range of definitions of aggression in the included studies. The variability of the concept aggression in the literature is large with the majority of articles not providing a clear definition or comment on which definition was used. Mostly, agitation, aggression and violence are recognized as stages of aggression and used interchangeably, with indistinct and unclear underlying concepts and demarcations. However, also incidents or assaults are studied without a clear definition. Comparison of outcome for the different stages of agitation-aggression-violence was not feasible because of these poorly described definitions. That is why in the present review all these different definitions and concepts were taken together. It would be advisable that studies define the level of aggression on the continuum of agitation-aggression-violence.A range for the search was chosen for 1999–2019, which makes this review a complete overview of the literature of 20 years. Papers written before 1999 were described in older studies and reviews and were most likely of poor methodological quality  and hospital care was organized very differently . These sVariations in hospital settings are difficult to compare  if descrPrevalence rates are difficult to compare between articles, as they employ a variety of definitions for aggression and differ in methodology: incidents per patient, incidents per week or per month, incidents per occupied bed, incidents per week, per unit, per admission, or per hospital. A consensus and clear description of methodology in every study is required for an objective comparing of the data, however missing . In the A wide variety of assessment instruments are used in the literature to measure aggression, for example the Staff Observation Aggression Scale (SOAS), Overt Aggression Scale (sometimes in modified version), Clinical Global Impression scale (CGI), Positive and Negative Symptom Scale-Excited Component (PANSS-EC), and the Social Dysfunction and Aggression Scale (SDAS). Moreover, studies applied a vast amount of questionnaires lacking information on validity and reliability, obtaining quantitative data with multiple interview techniques or self-designed questionnaires, which are not explained in detail. Quantitative questionnaires on aggression are most often answered by staff and are therefor an interpretation of the staff, which might differ from a patients point of view, introducing a potential bias. To overcome this matter, these studies were described separately in the present review.Inclusion and exclusion criteria are not always well described. Male patients with a psychotic disorder are overrepresented in the studies, IQ of the patient was never a measured factor. Without severity scores of symptoms, missing in the majority of studies, the severity of the psychopathology remains unclear. Presumably, a large bias has been introduced here and aggression prevalences may be even higher as well as different factors may play a more important role, since the most ill patients are very unlikely to sign informed consent due to suspiciousness, but may show the most aggressive behaviour. With keeping this limitation in mind, results are still applicable to the less ill inpatients.The quality of papers was divers with scores on the OSQE ranging from 1 to 12 points, reflecting papers with very poor quality to very good quality. This shows that there is a great range in methodological quality of included papers. For the patient factors, the majority of papers had a higher OSQE score of 7 or higher (58%), for the staff and ward factors the majority of papers was of poor quality with a score of 6 and lower (77% and 68% respectively). Despite the wide variety in methodological quality, the large range in quality did hardly reflect differences in outcome. In other words: both articles with very poor quality (reflected by an OSQE score of 2 for example) and articles with very good quality (reflected by an OSQE score of 12 for example) presented similar results. Thus, for most results, the discussion of methodological quality to discriminate between conflicting results was not necessary.Another limitation constitutes the lack of controlled prospective studies (being only 13%). Furthermore, longitudinal or natural cohort studies that follow-up patients during their stay on the ward and take patient, ward, and staff factors into account, are missing . The preMost studies failed to control for important descriptive factors in their analyses  which may have confounded the interpretation of the results (expressed through odds ratios).Notwithstanding these shortcomings, the presented results provide a clear perspective on the magnitude of the issue of aggression in mental health care institutions and support the model of the three main factors  in contributing to the risk of aggression.Future research requires a prospective design, with clear descriptions of patient factors, including IQ. An IQ between 50–84 is a risk factor for the use of coercive measures , but hasAggression is a major issue among psychiatric inpatient units, with both nurses and fellow patients being victimized. Aggression is best defined as part of a continuum of agitation–aggression–violence. Development of aggression is explained by a combination of factors embodied in patients, staff and the ward. The majority of studies focus primarily on the contribution of patient factors in developing aggression, neglecting ward and staff factors that may be more promising targets for interventions to reduce or prevent aggression development on the inpatient psychiatric ward. Future research should focus on prospective naturalistic studies to gain more insight into the dynamics of aggression development in psychiatric wards, specifically the ward and staff factors. This may help identify more precise prevention and intervention strategies.S1 Checklist(DOC)Click here for additional data file.S1 File(DOCX)Click here for additional data file.S2 File(DOCX)Click here for additional data file.S1 Table(DOCX)Click here for additional data file.S2 Table(DOCX)Click here for additional data file.S1 Dataset(XLSX)Click here for additional data file.


Obesity, older age, and male sex are recognized risk factors for sleep apnea. However, it is unclear whether the severity of hypoxic burden, an essential feature of sleep apnea, is associated with the risk of sleep apnea worsening. Thus, we investigated our hypothesis that the worsening of sleep apnea is expedited in individuals with more severe desaturations.2) signals of 805 Sleep Heart Health Study participants with mild sleep apnea [5 ≤ oxygen desaturation index (ODI) < 15] were analyzed at baseline and after a mean follow-up time of 5.2 years. Linear regression analysis, adjusted for relevant covariates, was utilized to study the association between baseline SpO2-derived parameters and change in sleep apnea severity, determined by a change in ODI. SpO2-derived parameters, consisting of ODI, desaturation severity (DesSev), desaturation duration (DesDur), average desaturation area (avg. DesArea), and average desaturation duration (avg. DesDur), were standardized to enable comparisons between the parameters.The blood oxygen saturation (SpOp = 0.001), avg. DesArea , DesDur , and DesSev  were significantly associated with sleep apnea worsening, whereas ODI was not . In sex-stratified analysis, avg. DesDur , avg. DesArea , and DesDur  were significantly associated with sleep apnea worsening in men.In the group consisting of both men and women, avg. DesDur (β = 1.594, Longer and deeper desaturations are more likely to expose a patient to the worsening of sleep apnea. This information could be useful in the planning of follow-up monitoring or lifestyle counseling in the early stage of the disease. The apnea–hypopnea index (AHI) is the most widely used parameter in sleep apnea diagnostics and is derived from polysomnography (PSG)  . Howeverhy (PSG) . The oxycreening . The ODIcreening . Furthernetworks . TherefoMale sex, obesity, and older age are known risk factors for sleep apnea . In addi2-derived parameters  is a multicenter cohort study implemented by the National Heart, Lung, and Blood Institute to determine the consequences of sleep-disordered breathing, such as cardiovascular diseases (CVD). The SHHS dataset is available through the National Sleep Research Resource . Partici2 with a 1-Hz sampling frequency. Mercury gauge sensors were used to record the body position during sleep. Total sleep time was determined based on 30-s epochs in which the sleep stage was scored as non-rapid eye movement sleep  or rapid eye movement sleep (REM).In-home PSGs were performed with Compumedics P-series portable monitors  . The finEach PSG recording was supplemented with a sleep habits questionnaire, medical history, medication usage, blood pressure, and anthropometric measurements. NC was measured just below the laryngeal prominence. The existence of hypertension was defined if the systolic blood pressure was ≥140 mmHg, diastolic blood pressure was ≥90 mmHg, or medication for hypertension was in use. At the medical history interview, history of CVD, consisting of myocardial infarction, heart failure, stroke, coronary angioplasty, and coronary artery bypass graft, was inquired. In addition, the existence of diabetes was defined based on self-reported diabetes status and usage of insulin or oral hypoglycemic agents.2 signal; (2) minimum event duration of 3 s; (3) maximum plateau duration of 45 s; and (4) values lower than 50% were considered as artifacts . The maximum plateau duration denotes the maximum period within the desaturation event during which the SpO2 signal values do not change. If this period is exceeded, the end point of the desaturation is determined to be the starting point of the plateau. It was observed that the software started automatic event scorings systematically one data point too early, and thus, this was corrected in the parameter calculations. To validate the accuracy of the automatic scorings, 30 SpO2 signals were randomly selected from the available SHHS dataset of 8,444 recordings and scored manually. Correlations and Bland–Altman plot agreements between manual and automatic scorings of the desaturation events were calculated. In addition to the ODI, novel SpO2 signal-based parameters consisting of desaturation severity (DesSev), desaturation duration (DesDur), average desaturation duration (avg. DesDur), and average desaturation area (avg. DesArea) were calculated  at baseline, from which 27 were excluded due to the missing covariate data. Therefore, 805 (441 men and 364 women) participants were included for further analyses . The resU test and Chi-squared test for continuous and categorical variables, respectively. Linear regression was used to investigate the association between the baseline desaturation parameters and the progression of mild sleep apnea with and without covariate adjustment. Change in the ODI between the PSG recordings was used as a continuous dependent variable. Baseline BMI, change in BMI during the follow-up, age, NC/H, the existence of hypertension, diabetes, and CVD, percentage of time slept in the supine position, percentage of time slept in REM, change in the time slept in REM between the PSGs, and follow-up time were used as covariates in the adjusted models. Desaturation parameters at baseline were standardized to enable comparisons between parameters. Thus, regression coefficients  correspond to the expedited increase in ODI between the PSG recordings that were associated with a one standard deviation (SD) change in the desaturation parameter values at baseline. In addition, we investigated whether the desaturation parameter values at baseline differed between the participants whose sleep apnea severity remained in the healthy-to-mild state  and the participants whose disease worsened to moderate (15 ≤ ODI < 30) or severe (ODI ≥ 30) sleep apnea during the follow-up. Finally, to address the possibility of selection bias, we investigated whether there were differences in the baseline parameter values between the participants with mild sleep apnea who underwent only baseline PSG and those with both PSGs. Analyses were conducted in MATLAB®, . To address the multiple comparisons, due to five investigated desaturation parameters, a Bonferroni-corrected p-value threshold of <0.01 was used to indicate statistical significance, whereas p-values < 0.05 were considered as nominal evidence.The statistical significance of the differences in the demographic and desaturation parameters between the baseline and follow-up were evaluated within men and women using the Wilcoxon signed-rank test, and between men and women with the Mann–Whitney p < 0.001), whereas avg. DesArea decreased  (p = 0.002), DesSev (p = 0.002), and DesDur (p < 0.001) was greater in men than in women.During the follow-up, the ODI, DesSev, and DesDur values increased for both sexes (r women) . The incp < 0.05) associated with sleep apnea worsening in the unadjusted models. In the covariate-adjusted models for the group consisting of both sexes, avg. DesArea (p = 0.001) and avg. DesDur (p = 0.004) were significantly associated with sleep apnea worsening by fulfilling the Bonferroni-corrected threshold, while DesSev (p = 0.040) and DesDur (p = 0.028) reached the limit of nominal significance. Moreover, in men, avg. DesDur was associated with sleep apnea worsening at the Bonferroni-corrected threshold (p = 0.003), while avg. DesArea (p = 0.024) and DesDur (p = 0.033) reached nominal association. Overall, in men and in the group consisting of both sexes, a one SD unit increase in avg. DesDur resulted in the greatest expedited increase in ODI during the follow-up , followed by avg. DesArea.Linear regression analyses revealed that the baseline ODI was not associated with the worsening of mild sleep apnea either in the unadjusted or in the adjusted model . Howeverp < 0.001 for men, p = 0.008 for women), DesSev , and DesDur  at baseline compared to the participants who remained in the healthy-to-mild state  and women  whose mild sleep apnea worsened to severe sleep apnea during the follow-up. In addition, avg. DesArea (p < 0.001) and avg. DesDur (p = 0.021) were significantly higher at baseline in women whose disease worsened to moderate sleep apnea. The only statistically significant difference between the participants who worsened to moderate sleep apnea and those who worsened to severe sleep apnea was observed in ODI (p = 0.039) in the group consisting of both sexes.Men and women whose mild sleep apnea worsened to moderate sleep apnea during the follow-up had significantly higher ODI , the median differences in the parameter values were minimal , and agrIn this study, we investigated whether the desaturation parameters at baseline were associated with the worsening of mild sleep apnea. We provide novel evidence showing that especially avg. DesDur and avg. DesAreas are associated with the expedited worsening of sleep apnea. Notably, the baseline ODI values did not appear to be associated with the worsening of mild sleep apnea. These findings suggest that a detailed analysis of the oxygen desaturation signal that considers the morphology of the desaturation events is relevant in the risk assessment of sleep apnea progression. More importantly, this study focused on patients with mild sleep apnea as these patients are not systematically treated especially when symptomless. Therefore, our results implicate that mild sleep apnea patients with deeper and longer desaturation events might benefit from regular follow-up monitoring.n = 805 vs. n = 50), and we had a longer follow-up period (5.2 vs. 3 years). In addition, their study population consisted of patients who were suffering from more severe sleep apnea at baseline (ODI mean ± SD = 20.8 ± 13.4), whereas we focused only on patients with mild sleep apnea. Nevertheless, the present results are consistent with other previously reported findings (n = 32) of patients with more severe sleep apnea (mean AHI = 52.2 at baseline).Previously, findings  with a svice versa. Therefore, it seems that it is highly dependent on the severity of sleep apnea whether baseline ODI or AHI values can be used in the risk assessment of sleep apnea progression; thus, the generalization of our findings should be done with caution.Moreover, it has been shown that AHI does not change over time (mean follow-up period of 5.1 years) in severe sleep apnea patients, and the ones whose AHI increased have initially mild or moderate disease . It was We observed that mild sleep apnea patients with longer and deeper desaturations experience an expedited worsening of the disease. However, in the sex-stratified analyses, significant findings were observed in men when the ODI 4% criterion was used, whereas the associations were stronger in women with the ODI 3% criterion . In addi2 signal. For example, the minimum or the maximum durations of the desaturation events are not specified in the rules of the American Academy of Sleep Medicine (AASM), unlike in the case of hypopneas and apneas  and severity (novel parameters) of the events and, therefore, the determined parameter values. Furthermore, we decided to use the 4% criterion for our primary analysis as, without associating desaturation events to the respiratory events, the 3% criterion was assumed to be too sensitive.The present study has limitations. First, the desaturations were autoscored using a commercial software without further manual adjustment by specialists. However, the correlations and agreements between the subset of manual and automatic scorings were excellent and the median differences minimal . Therefod apneas . FurtherApnea–hypopnea index was not used for the severity categorization in this study because the scoring criteria have changed since the apneas and hypopneas were originally scored in the late 1990s and early 2000s. The biggest difference is in the channels used for hypopnea scoring. At the time the recordings were conducted, hypopneas could have been scored based on signals from the thermistor, respiratory belts around the thorax or abdominal region, or some combination of them . The cur2 is not a direct measure of breathing, the ODI cannot be used as a direct measure of the frequency of respiratory events. In addition, the ODI cannot distinguish between obstructive and central respiratory events. Furthermore, no standardized criteria exist to score desaturations, as discussed above. The ODI can also potentially underestimate the AHI, as hypopneas can be scored with an association to desaturation or arousal . In addition, treating a large number of mild sleep apnea patients would be costly while not providing significant benefits for many of the patients, thus being a waste of resources. Therefore, using novel SpOtimation , allowinThe present results indicate that, in the risk assessment of mild sleep apnea worsening, the severity of the desaturation events is more useful than the exact number of the events. Based on the present findings, sleep apnea can be understood as a progressive disease, and many of the mild patients develop more severe disease in 5 years.https://sleepdata.org/datasets/shhs/. Access to the full Sleep Heart Health Study data was granted by the National Sleep Research Resource as a part of Mazzotti’s proposal (agreement #2731).Publicly available datasets were analyzed in this study. This data can be found here: National Sleep Research Resource: https://sleepdata.org/datasets/shhs/pages/full-description.md): Boston University, Case Western Reserve University, Johns Hopkins University, Missouri Breaks Research, Inc. New York University Medical Center, University of Arizona, University of California at Davis, University of Minnesota – Clinical and, Translational Science Institute, University of Washington.Each patient/participant provided written informed consent and the study protocol was reviewed and approved by the institutional review boards of each participating site of the Sleep Heart Health Study (SHHS). Participating institutions in the Sleep Heart Health Study are (TK contributed to the study design, data analysis, and interpretation, and wrote the manuscript. SM contributed to the study design and writing of the manuscript. SN contributed to the writing of the manuscript and data analysis. DM contributed to data interpretation and writing of the manuscript. JT and TL contributed to the study design, data interpretation, and writing of the manuscript. All authors contributed to the article and approved the submitted version.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Despite the increasing trend of Postabortion Care (PAC) needs and provision, the evidence related to its cost is lacking. This study aims to review the costs of Postabortion Care (PAC) per patient at a national level.A systematic review of literature related to PAC cost published in 1994 – October 2020 was performed. Electronic databases such as PubMed, Medline, The Cochrane Library, CINAHL, and PsycINFO were used to search the literature. Following the title and abstract screening, reporting quality was appraised using the Consolidates Health Economic Evaluation (CHEERS) checklist. PAC costs were extrapolated into US dollars ($US) and international dollars ($I), both in 2019.Twelve studies met the inclusion criteria. All studies reported direct medical cost per patient in accessing PAC, but only three of them included indirect medical cost. All studies reported either average or range of cost. In terms of range, the highest direct cost of PAC with MVA  services can be found in Colombia, between $US50.58–212.47, while the lowest is in Malawi ($US15.2–139.19). The highest direct cost of PAC with D&C (Dilatation and Curettage), services is in El Salvador ($US65.22–240.75), while the lowest is in Bangladesh ($US15.71–103.85). Among two studies providing average indirect cost data, Uganda with $US105.04 has the highest average indirect medical cost, while Rwanda with $US51.44 has the lowest.Our review shows variability in the cost of PAC across countries. This study depicts a clearer picture of how costly it is for women to access PAC services, although it is still seemingly underestimated. When a study compared the use of UE (Uterine Evacuation) method between MVA and D&C, it is confirmed that MVA treatments tend to have lower costs and potentially reduce a significant cost. Therefore, by looking at both clinical and economic perspectives, improving and strengthening the quality and accessibility of PAC with MVA is a priority.The online version contains supplementary material available at 10.1186/s12913-022-07765-1. Despite a 35 percent decline over a seven-year period, maternal deaths are still considered high in 2017, with an estimated 295,000 deaths worldwide . BetweenUnder restrictive legal settings, many women with an unwanted pregnancy tend to seek unsafe abortions and they will potentially experience severe health complications as a result . To manaProviding PAC treatment is a financial challenge for a government, especially because the severity of complications experienced by women varies. To illustrate, in Sub-Saharan Africa, Vlassoff et al.  indicateThe aim of this study was to explore the variation of cost of accessing PAC per patient at a national level across countries. We conducted a systematic review and extrapolated the cost into the international dollar for comparing purposes, where appropriate. Further, a comparison of costs can be used as a reference for the government in setting rules regarding the PAC method to be used nationally and strengthening and providing high-quality PAC services.The review was guided by The PRISMA statement  and the We developed the search term for health-system-cost related from Gordon and Rowell  and for In this paper, we focus on the costs incurred by health facilities, namely direct medical costs and indirect medical costs. Direct medical costs consist of labor costs and supplies costs while indirect medical costs consist of overhead costs and capital costs.Fully reported direct medical costs, personnel costs, supplies costs, indirect medical costs, overhead costs, and capital costs.Only reported direct medical costs and indirect medical costsOnly reported personnel costs, supplies costs, overhead costs, and capital costsResearch quality appraisal was guided by CHEERS statement – a specific instrument or guidelines developed for studies reporting economic outcomes as they tend to require additional economic data such as resource use, costs, and effectiveness results . Hence, Twelve studies were located in Eastern Africa  and international dollars ($I), both in 2019, to improve the comparability and transferability of results across studies. An international dollar is a hypothetical unit of currency used for comparisons between countries, and at a given point in time, it has the equivalent purchasing power parity of the US dollar in the United States .The cost extrapolation process starts with adjusting costs in US dollars ($US) in the year of the study for inflation using the US GDP deflator to obtain the PAC cost in US dollars ($US) in 2019. Afterward, costs are converted into the country’s local currency unit from each study in 2019 using the official exchange rate, then divided by the PPP of each study country to obtain the PAC cost in international dollars ($I) in 2019. This PPP is used to equalize purchasing power between countries by eliminating differences in price levels , which mBased on the first search, we found 275 potentially relevant papers throughout the sources. After review based on titles as well as excluded duplication, a total of 58 distinct articles were selected for initial screening based on titles and abstracts Fig. . From thA total of 10 full-text articles were retrieved to assess for more detailed evaluation, including examining their quality and clarity in terms of reporting using the CHEERS statement. From this process, three studies were excluded because one study was based on a household perspective and other chosen studies superseded the remaining two studies. We then manually searched potential articles from the reference lists of the seven articles and found five studies to include. Table Table In terms of approaches, costing analysis can be divided into two types, a “top-down” and a “bottom-up”. When a study uses the first approach, it scrutinizes large administrative datasets and derives PAC-related cost for estimating its overall cost per patient , 16. Whesavings, an excel-based tool to estimate per-case PAC costs [Most of the studies used the PACCM as their tools. The PACCM is a bottom-up ‘ingredients’ approach that relies on expert opinion for estimating the health-system-cost component . A studyAC costs , 23.Table Table Additionally, two studies report the labor cost and supplies/drugs cost of UE using MVA & D&C, these are Bangladesh and El Salvador. For the use of MVA, the labor cost in Bangladesh ranges from $US7.15 to $US8.48 while for the use of D&C, it ranges from $US5.94 to $US13.46. For the supplies/drugs cost, the use of MVA in Bangladesh also costs less ($US7.22–20.53) compared to D&C ($US13.33—90.38). Similar to Bangladesh, the use of D&C in El Salvador generally requires more labor hours, longer stays in the hospital, and more supplies/drugs; consequently, it will raise labor costs and supplies/drugs costs.Unlike the direct medical cost, the studies that reported the indirect cost of providing PAC did not distinguish between the use of UE method, as shown in Table Table Looking from a complications’ point of view, in terms of the average amount of direct cost, Rwanda has the highest direct medical cost for incomplete abortion ($US60.83), shock ($US103.14) compared to other countries. In Senegal, the highest average cost is a result of shock ($US39.53), while its lowest is incomplete abortion ($US15.77). Lastly, in Uganda, the complication that costs the most, on average, is perforation ($US125.61), and the least is shock ($US44.48).Out of the twelve papers that were included in this review, we found no study examining the indirect cost of PAC, which limits our knowledge in estimating the actual cost of PAC. Our review provides insights into the service delivery costs of providing PAC per patient at a national level across countries, particularly developing countries. As shown, the cost is varied and dependent on many factors, such as data availability, number of severe cases, period of data collection, and costing method. For example, almost half of the chosen studies used the PACCM tool, which was developed by the Guttmacher Institute and is argued as a low-cost approach yet provides a robust estimation for policy analysis , 19. AllUsing US dollar ($US) in 2019, the most expensive MVA case in this study is found in Colombia ($212.47), whereas the most expensive D&C case is in El Salvador ($240.75). MVA cases cost the least in Malawi ($US15.71), and D&C cases cost the least in Bangladesh ($US15.71). As illustrated in Malawi, where the cheapest PAC treatment is $US15.71 and the most expensive is $139.19, averaging the cost of PAC treatment remains difficult. Further, when comparing the cost, it first needs to be adjusted to account for the severity of the case.In addition, to extrapolate the cost into the US dollar ($US) in 2019, this review also converted all costs into international dollars ($I). Where appropriate, this would allow us to compare the patient’s purchasing power in affording postabortion care in their respective countries to other countries. It is suggested that the use of the international dollar should be interpreted carefully as converting to the international dollar could result in differences that are plausibly caused by high rates of inflation in some countries relative to the USA . For exaSome of the studies explored the cost of WHO-recommended UE methods, like MVA in more detail. Not only the cost is relatively lower than D&C, but MVA also has been clinically proven to be as effective and safer than sharp curettage for treating incomplete abortion and inducing first-trimester abortion . As prevA study in Malawi made a simulation if all women seeking first-trimester induced abortion chose MVA, the result would be an estimated 20% cost reduction . A studyThis systematic review has some limitations for consideration and discussion. First, the review only included English-language articles, which may lead to a lesser search result. Second, the differences in the operational definitions in the selected studies can potentially affect the findings of this review. In some studies , 20, comOur review shows variability in providing PAC across countries. This study depicts a clearer picture of how costly it is for women to access PAC service, although it is still seemingly underestimated. Our findings also reconfirm MVA as a method of choice for PAC. In addition to the medical safety and women-centered approach of the method, it is also shown that MVA is less costly compared to D&C. With a projected increasing demand of PAC globally, shifting UE methods to MVA will not solely benefit women but in turn, will lead to a reduced burden of cost associated with PAC across levels. Hence, shifting UE methods to MVA should be initiated and promoted. Among others, it should be started with updated policies and clinical guidelines related to it, health workers capacity buildings, and supplies at the facilities level. The government, medical professionals, and health facilities’ roles are critical in this effort.Additional file 1.


Dietary intervention is crucial for the prevention and control of diabetes. China has the largest diabetic population in the world, yet no one dietary strategy matches the eating habits of the Chinese people. To explore an effective and acceptable dietary pattern, this study uses oat and buckwheat compound (OBC) as a staple food substitute and explored its effects on diabetic Sprague–Dawley rats. The model of diabetic rats was established by combining high-calorie feed and streptozotocin (STZ) injection. The dietary intervention for the seven groups, including a normal control group, a model control group, a metformin control group, a wheat flour control group, and three OBC groups with different doses, started from the beginning of the experiment and lasted for 11 weeks, two consecutive injections of STZ in small doses were operated at the 6th week. General states, glucose metabolism, and lipid metabolism indexes were measured. Antioxidant and inflammatory indexes and pathologic changes of kidney and liver tissues were tested. Changes in kidney and ileum ultramicrostructure were detected. What's more, ileal epithelial tight junction proteins and gut microbiota were analyzed. Significant decreases in fasting blood glucose (FBG), glucose tolerance, serum insulin, and insulin resistance were observed in rats intervened with OBC, and these rats also showed a higher level of superoxide dismutase (SOD) together with improved lipid metabolism, attenuated inflammation, and liver and kidney injuries. In addition, in OBC groups, the intestinal barrier was improved, and the disturbance of gut microbiota was reduced. These results suggest that OBC has health-promoting effects for diabetic rats, and since oat and buckwheat are traditionally consumed grains in China, OBC could be a potential and easy-to-accept staple food substitute for the dietary pattern for Chinese. Diabetes is a serious chronic metabolic disease with complications in many parts of the body and can increase the overall risk of dying prematurely. Around 463 million people are estimated to be suffering from diabetes in 2019, which is expected to rise to 700 million (10.9%) by 2,045  as a staple food substitute and explored its effects on diabetes by researching the physiology and gut microbiota of diabetic rats. This work will provide a valuable reference for promoting the exploration of dietary patterns that are suitable for the prevention and treatment of diabetes in China.Oat and buckwheat compound is a mixture made from buckwheat and oat mixed in the ratio 2.2 to 1. The ratio of buckwheat to oat was selected by our previous experiments. Both oat (Bayou 1) and buckwheat (Dasanleng) were purchased from DongFangLiang Life Technology Ltd. . The nutrients of oat and buckwheat used in the experiment are shown in Streptozotocin (99.8% purity) was purchased from Sigma Chemical Co. . Glucose (99.8% purity) was purchased from Beijing Jinhua Taiya Chemical Reagent Co., Ltd. . Metformin hydrochloride extended-release tablets were purchased from Sino-American Shanghai Squibb Pharmaceuticals Ltd. . Citric acid (99.9% purity) and sodium citrate (99.9% purity) used in the streptozotocin injection solution were purchased from Beijing Tong Guang fine chemicals company.Basic feed was processed by Beijing Biotech HD Biotechnology Co., Ltd. , according to the national standard (GB 14924.3-2010). High-calorie feed was processed by Beijing Biotech HD Biotechnology Co., Ltd.  according to the evaluation method of auxiliary hypoglycemic function of health food . Feed for OBC groups and wheat flour control (WFC) group were made by replacing the cornstarch in high-calorie feed with different proportions of OBC or wheat flour . At the same time, maltodextrin, 10 in each group, had been adjusted to ensure that the feed quality of each group was equal, while calories of feeds for each group were in agreement (the differences were <0.07%). The feed ingredients of each group are shown in Male Sprague–Dawley rats (200 ± 10 g) were provided by the Department of Laboratory Animal Science, Peking University  and bred in a specific pathogen free (SPF) room there, production certificate No.: SCXK (Beijing) 2016-0010, use license No.: SYXK (Beijing) 2016-0041. Two rats were housed per cage, with the temperature of the SPF room controlled at 25°C ± 1°C, relative air humidity controlled at 50–60%, and 12-h light/dark cycles. Due to the polyuria caused by diabetes, the cage bedding was changed daily after injecting STZ. All animal procedures meet the Regulation on the Administration of Laboratory Animals and were approved by the Ethics Committee of Peking University (ethics No.: LA2018189).Healthy adult male SD rats were fed adaptively for 1 week before the experiment. After 45 days fed by each group's corresponding feed, rats to be modeled received two intraperitoneal injections of low-dose STZ (30 mg/kg body weight) at an interval of 1 week. Three days after the second injection, rats were fasted for 5 h to measure their tail vein blood glucose. Rats with a blood glucose of 10–25 mmol/L were used as diabetic rats for our study.n = 10), the model control group , the , the metformin positive control group , and three OBC treatment groups including a low dose group , a medium dose group , and a high dose group . As a reference hypoglycemic drug, metformin was used to intervene rats in the MPC group by gavage after the injection of STZ. The initial dose of metformin was 50 mg/kg body weight, and it increased by 50 mg/kg body weight every 2 weeks until the maximum dose at 200 mg/kg body weight. All rats in other groups received distilled water every day at the same time with a bodyweight volume of 10 ml/kg until the end of the experiment. The general state of rats includes haircoat state, mental state, body weight, water, and food intake were recorded daily. Six rats were randomly selected in each group and fed individually in the metabolic cage for 24 h to collect and record the urine volume of the rats. Each metabolic cage has a funnel and measuring cylinder for urine collection. The schematic diagram of the study protocol is shown in Based on their baseline serum glucose, 72 rats were randomly divided into seven groups, the normal control group  was calculated by the following formula:Homeostasis model assessment of insulin resistance (HOMA-IR) was calculated by the following formula:The main organs  of rats were removed and weighed at the end of the experiment to calculate the organ coefficients and for further testing including hematoxylin–eosin (HE) staining and ultramicrostructure observation. The level of serum insulin was detected by using an XH-6080 γ radioimmunocounter . The level of SOD and malonaldehyde (MDA) were detected by using a 721-G Visible spectrophotometer . The level of FBG and all other biochemical indicators include glycated serum protein, tumor necrosis factor-α (TNF-α), interleukin-6 (IL-6), aspartate aminotransferase (AST), and alanine aminotransferase (ALT) were detected by using an AU480 automatic biochemistry analyzer . The pathologic changes of kidney and liver tissues were detected by HE staining. Kidney ultramicrostructure was observed with a transmission electron microscope. Western blotting was used to detect ileal tight junction proteins. Cecal feces sample microbiota analysis was divided into the following sections: sample collection, DNA extraction and amplification, 16S rDNA sequencing, and taxonomic classification.p < 0.05 was considered statistically significant.Data accorded with normal distribution and homogeneity of variance were expressed as means ± SD, compared by one-way analysis of variance (ANOVA), otherwise, expressed as medians and quartiles, and compared by Kruskal–Wallis H test. SPSS 22.0  was applied for statistical analysis. The value With withered yellow fur and less well-formed feces, the diabetic rats showed a much poorer haircoat quality and a symptom of diarrhea, compared with normal rats. Besides, rats with STZ-induced diabetes also shared reduced general activity. As shown in As shown in The fasting blood glucose of all rats showed a normal level (6.3 ± 0.91 mmol/L), and no significant differences were seen among these groups before modeling. After the diabetic model was established, different from the normal group, the FBG level statistically increased over time in the diabetic rats since the 7th week . By the To analyze the effect of OBC on glucose tolerance in diabetic rats, we conducted the OGTT in the third, 7th, and 11th weeks. As shown in As shown in As shown in The serum SOD level was significantly lower in MC and WFC groups as compared with normal rats; meanwhile, diabetic rats in OBC groups showed a markedly higher SOD level than rats in the MC group , showingAs shown in Serum ALT and AST levels can reflect the degree of liver cell injury. The ALT data, which does not conform to the normal distribution, is represented by a boxplot and analyzed by Kruskal-Wallis H tests, showing that compared with rats in the NC group, serum ALT in diabetic rats increased significantly, and the ALT levels of rats in OBC groups were significantly lower than rats in the MC, WFC, and MPC groups . The serAll diabetic rats showed a classic symptom of polyuria, as shown in As shown in Compared with normal rats, the expression of Claudin-1, ZO-1, and Occludin was weakened significantly in diabetic rats in the MC group . All theAccording to the sequence similarity (>97%), high-quality sequences were classified into multiple operational taxonomic units (OTUs) using QIIME to facilitate analysis. The number of OTUs detected in the cecal stool samples of rats in the seven test groups  were 507, 542, 562, 505, 516, 524, 522, respectively, whereas the number of unique OTUs was 6, 4, 12, 1, 2, 6, 6, respectively. There were 331 OTUs shared by seven groups.p = 0.26) and Chao1 index (p = 0.49), but there was a significant difference in the Simpson index (p = 0.02). MC group had higher evenness indexes [0.97 ] than the NC group [0.96 ], whereas each intervention group had a lower evenness index than MC group, WFC: 0.95 , MPC: 0.91 , OBC-L: 0.95 , OBC-M: 0.93 , OBC-H: 0.91 . Indicators of alpha diversity were reported as the median ± IQR.The observed species can reflect the actual number of OTUs observed. Chao1 is an estimator of phylotype richness, and the Simpson index of diversity reflects both the richness and community evenness. In this study, there was no significant difference found in the observed species .In addition, ANOSIM demonstrated the differences in the gut microbiota among these groups. The intergroup differences among these groups were greater than the intragroup differences . Thus, there was no clear dose-response relationship between OBC intervention and improvement of diabetes. This may be due to the complexity of ingredients in OBC and intervention pathways for diabetes. In addition, the limited sample size and grouping dose level in this work may also preclude the discovery of the dose-response relationship. Follow-up studies can explore a clearer dose-effect relationship by increasing the sample size and reducing the dosage gradient.Several studies , 20–24 iThere is growing evidence that gut microbiota is closely associated with metabolic diseases including type 2 diabetes –28. SpecReasons for OBC impacting gut microbiota may be related to its components. Higher Parasutterella abundance was observed in the OBC-L group. Though there is insufficient knowledge on the relationship between specific strains and dietary components, evidence has shown that complex carbohydrates may be involved. Yuan et al.  found thThe underlying mechanisms of gut microbiota impacted by OBC regulating host metabolism may include favorable changes in bacterial composition and/or activity, improvement of intestinal barrier function , productIn addition, this study shows that OBC can reduce inflammation, moderate liver damage, and improve the intestinal barrier, whereas metformin, which is a commonly used drug for diabetes treatment, cannot. It is noteworthy that there was no difference in food taken, this suggesting the palatability of OBC. Besides, compared with medication, people are also more receptive to OBC, common foods in daily life, and thus OBC is a more suitable potential food for diabetes prevention and long-term intervention.Although this work could provide new insights to explore the diet intervention on diabetes, it has several limitations. First, in our work there was only one compounding ratio of buckwheat and oat, and more compounding ratios may enhance the experimental evidence. Second, although this work shows that the consumption of OBC is closely related to the improvement of diabetes and gut microbiota ameliorating, further research, such as fecal bacteria transplantation, is needed to decipher the causal relationship involving bacterial disequilibrium and diabetes and to explore key bacteria which may play an important role in the intervention. Third, follow-up studies are needed to support the improvement of OBC on glucose tolerance in diabetes, and to explore the recommended dose of OBC for the specific dietary pattern.The results revealed that as a staple food substitute, OBC could exert promoting effects on diabetic rats. By improving antioxidant capacity, reducing inflammation, and improving the imbalance of intestinal microbiota, the glucose and lipid metabolism and insulin resistance of diabetic rats have been improved. Meanwhile, by improving a variety of tissues and organs in the diabetic state, OBC may have the potential to prevent diabetic complications. OBC can be used as a potential staple food substitute in dietary patterns that are suitable for the Chinese.The original contributions presented in the study are included in the article/The animal study was reviewed and approved by Ethics Committee of Peking University.SL and JW: conceptualization and methodology. SL: formal analysis and writing original draft preparation. SL, CH, XL, XY, HM, and XZ: investigation. YX: resources. SL and XY: data curation. MX and JW: writing review and editing. YL and JW: supervision. JW: project administration and funding acquisition. All authors contributed to the article and approved the submitted version.This research was funded by the Ministry of Science and Technology of the People's Republic of China, Grant Number 2017YFD0401202.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


Background: Coronary heart disease (CHD) is the major cause of mortality in the world with a significant impact on the younger population. The aim of this study was to identify prematurity among patients with coronary artery bypass graft surgery (CABG) based on the clustering of CHD risk factors.Methods: Patients were recruited from an existing cohort of candidates for CABG surgery named Tehran Heart Center Coronary Outcome Measurement (THC-COM). A latent class analysis (LCA) model was formed using 11 potential risk factors as binary variables: cigarette smoking, obesity, diabetes, family history of CHD, alcohol use, opium addiction, hypertension, history of stroke, history of myocardial infarction (MI), peripheral vascular disease (PVD), and hyperlipidemia (HLP). We analyzed our data to figure out how the patients are going to be clustered based on their risk factors.Results: For 566 patients who were studied, the mean age (SD) and BMI of patients were 59.1 (8.9) and 27.3 (4.1), respectively. The LCA model fit with two latent classes was statistically significant . The mean (SD) age of patients for Class I and Class II was 55.66 (8.55) and 60.87 (8.66), respectively. Class I (premature) was characterized by a high probability of smoking, alcohol consumption, opium addiction, and a history of MI (P < 0.05), and class II by a high probability of obesity, diabetes, and hypertension.Conclusion: Latent class analysis calculated two groups of severe CHD with distinct risk markers. The younger group, which is characterized by smoking, addiction, and the history of MI, can be regarded as representative of premature CHD. Of the There is no consensus on the definition, risk factors, and age limits for premature CHD in the clinical setting. The Task Force of the European Society of Cardiology (ESC), European Atherosclerosis Society (EAS), and European Society of Hypertension (ESH) have recommended screening for coronary risk factors to the close relatives of patients with premature CHD. They have been defined premature CHD as having CHDs for men <55 years and women <65 years . Some haLatent class analysis (LCA) is a commonly used empirical approach for identifying subpopulations by shared item response patterns. It is also a commonly used data reduction tool for analyzing multivariate categorical data . A finitParticipants in this cross-sectional study were candidates for CABG surgery recruited for Tehran Heart Center Coronary Outcome Measurement (THC-COM) study. Baseline data were collected as part of the large study started in May 2006 . The samData collection was conducted through interviews, physical examinations, and paramedical evaluation. Patients were asked about demographic characteristics, including gender, age, family history of CHD [a first-degree relative with CHD was defined as positive family history ], cigaret-test, and categorical variables were analyzed using a chi-square test between male patients and female patients. An LCA model was built using 11 known and proposed risk factors for CHD as binary variables: cigarette smoking, obesity, diabetes, family history of CHD, alcohol consumption, opium addiction, hypertension, PVD, HLP, history of stroke, and MI. The included risk factors were added to the statistical model based on premature systematic review studies  is used. Then, AIC and BIC can be calculated for model selection. The smaller the value of AIC and BIC, the more fit the model. The fit model contains the optimum number of latent classes. Then, we can nominate these classes based on their characteristics . The probability of membership was 33.8 and 66.2% for Class (I) and Class (II), respectively. Latent Class I was characterized by a high probability of smoking, a history of MI, alcohol consumption, and opium addiction (P < 0.05). Latent class II was characterized by a high probability of obesity, type 2 diabetes, and hypertension (P < 0.05). Family history, stroke, PVD, and HLP were not significantly different between the two classes. The models with 2, 3, 4, and 5 latent classes are shown in Latent class membership and response probabilities for each indicator are summarized in G2 = 731.7, df = 379, p < 0.0001 for men and G2 = 162.5, df = 112, p < 0.0001 for women). Larger conditional probabilities are in boldface to highlight the overall pattern. While latent class I was characterized by a high probability of smoking, alcohol consumption, opium addiction, and a history of MI in men, it was characterized by a history of MI among women.Latent class membership and response probabilities for each indicator for men and women are presented in P < 0.001). Patients in class I were about 5 years younger than patients in class II. Therefore, we named class I “premature” and class II “non-premature.” The rate of membership in class I for men and women was 44.3 and 2.7%, respectively. Also, the mean age (SD) of people who were categorized in class I was 55.58 (8.57) for men and 60 (6.55) for women. Only three women were categorized as class I or premature.The mean (SD) age for classes I and II was 55.66 (8.55) and 60.87 (8.66), respectively. There were significant differences in the age of the two groups of patients  and lipoprotein-associated risk  could explain premature CAD among South Asians . StudiesTo have a better knowledge of premature CHD risk factors, simultaneous classification of patients according to their conditions appears to be an important contributor.Our findings have important implications for clinical practice and in particular, underline the importance of screening in lower age populations who have risk markers for premature CHD to adopt prevention strategies in primary and secondary care settings. This may be of benefit in the larger group of patients compared to those looking for a family history of CHD.We used LCA for distinguishing the pattern of risk factor distribution among our patients, and it worked well. A model of two groups fitted best and was in accordance with two age groups with the significantly different incidence of risk factors. However, there are some points to be addressed. The prevalence rates of smoking, alcohol consumption, and opium addiction were lower among women compared to those among men in our study. Latent class analysis categorized only three women in class I (premature CHD). A larger sample size is probably needed before we can judge the predictors and cutoff point for the age of premature CHD in women. Given the low rate of smoking, alcohol consumption, and opium addiction among women in studies , it is pThe average age of 55 years for men and 60 years for women that we found in our study is related to the Iranian patients with severe CHD who were candidates for CABG, and it cannot be applied for the diagnosis of premature CHD in other groups of patients. Moreover, we did not ask the patients about the time they were diagnosed as patients with CHD even though it is not practical to document the exact time the CHD has begun. However, coronary artery involvement was severe among all participants of this study and they were candidates for CABG, which means they were at the same level regarding the progress of CHD. Additionally, the cross-sectional design of this study restricts causal interpretation of the association between unhealthy behaviors in the development of CHD. The current study was the dataset of the THC-COM study, and it was not possible for authors to include other variables such as the duration of the study.In this study, we employed LCA to identify clusters of patients with regard to their risk markers and recognize different categories of CHD. The best model fitted two classes that we named premature and non-premature CHD. The latent class I (premature CHD) was characterized by smoking, alcohol consumption, opium addiction, and the history of MI, while class II was characterized by known major risk factors like obesity, diabetes, and hypertension. There was a difference between men and women regarding CHD risk markers.The original contributions presented in the study are included in the article/The studies involving human participants were reviewed and approved by Tehran University of Medical Sciences. The patients/participants provided their written informed consent to participate in this study. The study was approved by the Ethics Committee of Tehran University of Medical Sciences and Tabriz University of Medical Sciences (NO. IR.TBZMED.REC.1400.748). All participants gave written informed consent. The data and material is available.LJ collected the data and wrote the first draft. MN was the main investigator who contributed to designing and helping in recruitment. MA helped in the interpretation of results and manuscript drafting. PS conducted study analysis. All the authors read and approved the manuscript.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.