Easy Cases Research Articles

A PROSPECTIVE STUDY OF THE INCIDENCE OF CONVERSION OF LAPAROSCOPIC CHOLECYSTECTOMY TO OPEN CHOLECYSTECTOMY IN 100 PATIENTS

Background: Laparoscopic cholecystectomy is the gold standard treatment for symptomatic gallstones. Conversion to an open procedure is necessary in 5–10% of patients. The aim of work: The present study was to illustrate theincidence of conversion of laparoscopic cholecystectomy to open cholecystectomy & to validate the efficacy of “CLOC” (Conversion from Laparoscopic to open cholecystectomy) risk scoring system on the patients included in the study.Patients and methods: The present observational prospective study was conducted in EL-Demerdash Teaching Hospital (January 2019- January 2020). The study included (100) symptomatic cholelithiasis patients. Patients were divided into two groups, firstly those who completed laparoscopic cholecystectomy and secondly those who were converted into open cholecystectomy. Preoperative variables included patient demographics, indications for surgery, ASA grade, admission type, ultrasound findings and preoperative endoscopic retrograde cholangiopancreatography (ERCP). Validation of the “CLOC” scoring system was applied to all patients. Operative data were gathered prospectively, and the difficulty of theprocedure was graded using the Nassar scale (grades 1–4). Results: (24%) of patients recorded difficult total score; opensurgery was conducted in (5%). There was statistically significant relation between CLOC risk scoring level and age (p 7 and conversions in the’ low risk >6 easy’ group below. (p=0.042); highly statistically significant increase of mean in difficult group compared to essay group (p < 0.001). Thedifficult group complications rate was higher than the easy group (75% versus 10.5%); gallbladder rupture was mostly reported in (37.5% and 2.6%) of difficult group and easy group cases, respectively. Receiver operating characteristics (ROC) curve sensitivity was 92%; specificity was 98.7%. Age, gender, indication, ASA, gallbladder wall and Pre-Operative ERCP have a significant effect on the difficulty. Conclusion: The present study could conclude that parametersas older age, male gender, cholecystitis, ASA, thick wall GB, preoperative ERCP are predictors for difficult LC. Meanwhile these factors are predictors for conversion to open cholecystectomy. CLOC” risk score may be the most helpful tool in stratifying risks.

Artificial intelligence-assisted analysis of endoscopic retrograde cholangiopancreatography image for identifying ampulla and difficulty of selective cannulation

The advancement of artificial intelligence (AI) has facilitated its application in medical fields. However, there has been little research for AI-assisted endoscopy, despite the clinical significance of the efficiency and safety of cannulation in the endoscopic retrograde cholangiopancreatography (ERCP). In this study, we aim to assist endoscopists performing ERCP through automatic detection of the ampulla and the identification of cannulation difficulty. We developed a novel AI-assisted system based on convolutional neural networks that predict the location of the ampulla and the difficulty of cannulation to the ampulla. ERCP data of 531 and 451 patients were utilized in the evaluation of our model for each task. Our model detected the ampulla with mean intersection-over-union 64.1%, precision 76.2%, recall 78.4%, and centroid distance 0.021. In classifying the cannulation difficulty, it achieved the recall of 71.9% for the class of easy cases and that of 61.1% for that of difficult cases. Remarkably, our model accurately detected AOV with varying morphological shape, size, and texture on par with the level of a human expert and showed promising results for recognizing cannulation difficulty. It demonstrated its potential to improve the quality of ERCP by assisting endoscopists.

An accelerated first-order method with complexity analysis for solving cubic regularization subproblems

We propose a first-order method to solve the cubic regularization subproblem (CRS) based on a novel reformulation. The reformulation is a constrained convex optimization problem whose feasible region admits an easily computable projection. Our reformulation requires computing the minimum eigenvalue of the Hessian. To avoid the expensive computation of the exact minimum eigenvalue, we develop a surrogate problem to the reformulation where the exact minimum eigenvalue is replaced with an approximate one. We then apply first-order methods such as the Nesterov’s accelerated projected gradient method (APG) and projected Barzilai-Borwein method to solve the surrogate problem. As our main theoretical contribution, we show that when an $$\epsilon$$ -approximate minimum eigenvalue is computed by the Lanczos method and the surrogate problem is approximately solved by APG, our approach returns an $$\epsilon$$ -approximate solution to CRS in $${\tilde{O}}(\epsilon ^{-1/2})$$ matrix-vector multiplications (where $${\tilde{O}}(\cdot )$$ hides the logarithmic factors). Numerical experiments show that our methods are comparable to and outperform the Krylov subspace method in the easy and hard cases, respectively. We further implement our methods as subproblem solvers of adaptive cubic regularization methods, and numerical results show that our algorithms are comparable to the state-of-the-art algorithms.

A NECESSIDADE DA JUSTIFICAÇÃO POR DEDUÇÃO NA CONSTRUÇÃO DA RATIO DECIDENDI DE CASOS FÁCEIS A PARTIR DA TEORIA DE NEIL MACCORMICK: UMA ANÁLISE DO RESP 1.745.333/RS

O objetivo deste artigo é analisar o Recurso Especial n. 1.745.333/RS a partir da argumentação justificada exclusivamente pela dedução. Neil MacCormick propõe uma teoria integradora para argumentar por justificação as decisões jurídicas, nesse sentido, ele apresenta um método para casos fáceis e difíceis. A partir do método defendido por ele para justificar casos fáceis é que o presente artigo se fundamenta. Desse modo, para construir este artigo é utilizado o método hipotético-dedutivo, por meio de análise bibliográfica e documental, assim, possui abordagem qualitativa, do tipo básica e exploratória. Inicialmente, são expostos os pressupostos teóricos dessa abordagem, como o silogismo aristotélico. Depois, apresenta-se a justificação por dedução proposta por Neil MacCormick, para então analisar o referido acórdão. Ao final são apresentados os pressupostos e limites dessa teoria. A partir dessa análise, foi possível chegar à conclusão de que a justificação por dedução é possível, mas única e exclusivamente nos casos fáceis, o que confirma a teoria de MacCormick.

How Many Cases Are Easy?

Abstract Because judges are expected to decide cases through the impartial application of existing law, they are often reluctant to admit that they must make law in hard cases. Many judges claim that such hard cases are rare, constituting roughly 10 percent of cases. In stark contrast, economic models of the selection of disputes for litigation predict that easy cases will settle, so that only hard cases would remain in trial and appellate courts. Empirical indicators, such as dissent rates or voting differences between Democratic and Republican appointees, have yielded muddled conclusions about the proportion of easy and hard cases in appellate courts. In fact, none of these crude statistics relate directly to the proportion of easy cases. This article develops a new approach for empirically analyzing the proportion of easy cases. Although the easiness and hardness of cases are subjective, it is possible to estimate feasible combinations of the proportion of hard cases and clear errors. This approach relies only on the basic premise that reasonable judges should not disagree in easy cases. The article then illustrates this approach using two datasets of appeals. An analysis of asylum appeals in the 9th Circuit finds widespread disagreement, implying high proportions of hard cases, clear errors, or both. By contrast, voting data from labor and environmental cases in the D.C. Circuit is consistent with the claim that 90 percent of cases are easy and 1 percent of decisions are clear errors.

Phantom Bethe roots in the integrable open spin- 12 XXZ chain

We investigate special solutions to the Bethe Ansatz equations (BAE) for open integrable $XXZ$ Heisenberg spin chains containing phantom (infinite) Bethe roots. The phantom Bethe roots do not contribute to the energy of the Bethe state, so the energy is determined exclusively by the remaining regular excitations. We rederive the phantom Bethe roots criterion and focus on BAE solutions for mixtures of phantom roots and regular (finite) Bethe roots. We prove that in the presence of phantom Bethe roots, all eigenstates are split between two invariant subspaces, spanned by chiral shock states. Bethe eigenstates are described by two complementary sets of Bethe Ansatz equations for regular roots, one for each invariant subspace. The respective "semi-phantom" Bethe vectors are states of chiral nature, with chirality properties getting less pronounced when more regular Bethe roots are added. For the easy plane case "semi-phantom" Bethe states carry nonzero magnetic current, and are characterized by quasi-periodic modulation of the magnetization profile, the most prominent example being the spin helix states (SHS). We illustrate our results investigating "semi-phantom" Bethe states generated by one regular Bethe root (the other Bethe roots being phantom), with simple structure of the invariant subspace, in all details. We obtain the explicit expressions for Bethe vectors, and calculate the simplest correlation functions, including the spin-current for all the states in the single particle multiplet.

A Multistage Passive Islanding Detection Method for Synchronous-Based Distributed Generation

A multistage approach to passive islanding detection is proposed that utilizes a decision tree (DT) like classification algorithm. The novelty of the proposed method is centered on the way in which features are passed to subsequent stages of the DT. Feature sets extracted using different sized time windows are passed to successive stages of the tree. This provides two important advantages: 1) cases that can be easily determined as either islanding or nonislanding events are flagged as soon as possible without waiting for the full feature set to become available; 2) because the algorithm allows for the use of different sized time windows, features are analyzed in time-scales that fit their natural patterns of temporal evolution. In this article, the proposed classifier is trained and tested using a database of feature vectors, obtained using PSCAD, which were designed to reflect a variety of commonly encountered events on an IEEE 34-bus distribution system. One of the key requirements for the proposed algorithm was that easy cases should be flagged as soon as possible; this property was confirmed by the observation that most events ( <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\approx$</tex-math></inline-formula> 79%) were detected within 10–20 ms, while at the same time retaining a very high detection rate overall cases ( <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$&gt;\!99$</tex-math></inline-formula> %).

Laser-induced breakdown spectroscopy as a straightforward bioimaging tool for plant biologists; the case study for assessment of photon-upconversion nanoparticles in Brassica oleracea L. plant

The main purpose of this work is to thoroughly describe the implementation protocol of laser-induced breakdown spectroscopy (LIBS) method in the plant analysis. Numerous feasibility studies and recent progress in instrumentation and trends in chemical analysis make LIBS an established method in plant bioimaging. In this work, we present an easy and straightforward phytotoxicity case study with a focus on LIBS method. We intend to demonstrate in detail how to manipulate with plants after exposures and how to prepare them for analyses. Moreover, we aim to achieve 2D maps of spatial element distribution with a good resolution without any loss of sensitivity. The benefits of rapid, low-cost bioimaging are highlighted.In this study, cabbage (Brassica oleracea L.) was treated with an aqueous dispersion of photon-upconversion nanoparticles (NaYF4 doped with Yb3+ and Tm3+ coated with carboxylated silica shell) in a hydroponic short-term toxicity test. After a 72-hour plant exposure, several macroscopic toxicity end-points were monitored. The translocation of Y, Yb, and Tm across the whole plant was set by employing LIBS with a lateral resolution 100 µm. The LIBS maps of rare-earth elements in B.oleracea plant grown with 50 μg/mL nanoparticle-treated and ion-treated exposures showed the root as the main storage, while the transfer via stem into leaves was minimal. On the contrary, the LIBS maps of plants exposed to the 500 μg/mL nanoparticle-treated and ion-treated uncover slightly different trends, nanoparticles as well as ions were transferred through the stem into leaves. However, the main storage organ was a root as well.

3D Object Detection Using Frustums and Attention Modules for Images and Point Clouds

Three-dimensional (3D) object detection is essential in autonomous driving. Three-dimensional (3D) Lidar sensor can capture three-dimensional objects, such as vehicles, cycles, pedestrians, and other objects on the road. Although Lidar can generate point clouds in 3D space, it still lacks the fine resolution of 2D information. Therefore, Lidar and camera fusion has gradually become a practical method for 3D object detection. Previous strategies focused on the extraction of voxel points and the fusion of feature maps. However, the biggest challenge is in extracting enough edge information to detect small objects. To solve this problem, we found that attention modules are beneficial in detecting small objects. In this work, we developed Frustum ConvNet and attention modules for the fusion of images from a camera and point clouds from a Lidar. Multilayer Perceptron (MLP) and tanh activation functions were used in the attention modules. Furthermore, the attention modules were designed on PointNet to perform multilayer edge detection for 3D object detection. Compared with a previous well-known method, Frustum ConvNet, our method achieved competitive results, with an improvement of 0.27%, 0.43%, and 0.36% in Average Precision (AP) for 3D object detection in easy, moderate, and hard cases, respectively, and an improvement of 0.21%, 0.27%, and 0.01% in AP for Bird’s Eye View (BEV) object detection in easy, moderate, and hard cases, respectively, on the KITTI detection benchmarks. Our method also obtained the best results in four cases in AP on the indoor SUN-RGBD dataset for 3D object detection.

Proof Discontinuities and Civil Settlements

Abstract This Article explores settlement incentives under three different burden of proof rules. The conventional burden of proof is a discontinuous step-function, jumping from no damages to full damages at the 0.5 jury confidence level. Continuous burdens of proof, by contrast, would permit sanctions to steadily increase as juror confidence rises from 0 to 1, with no discontinuity. Linear burdens, which have received extensive attention in prior literature, escalate sanctions steadily across the whole range of confidence levels, while the logistic burden takes a nonlinear form. Using a data simulation approach guided by the empirical realities of American civil litigation, I consider the incentives that each of these rules creates for parties contemplating settlement, using a model in which parties make divergent forecasts of their expected outcomes at trial due to optimism bias. Based on this analysis, I conclude that a linear burden would likely raise our settlement rate by a modest amount, except in very large cases and in “easy” cases, in which an unbiased person would predict that a trial factfinder would have a level of confidence in liability quite close to either zero or one. I also compare the expected error rate of the settlements that each rule produces, and find that the linear rule modestly lowers the expected error rate of settlement overall, although this benefit does not hold for easy cases or those with very high damages. Lastly, I conduct a similar analysis for the logistic burden, finding that it induces a similar quality and quantity of settlements as we currently achieve using conventional burdens.

Pushing the Online Boolean Matrix-vector Multiplication conjecture off-line and identifying its easy cases

Henzinger et al. posed the so-called Online Boolean Matrix-vector Multiplication (OMv) conjecture and showed that it implies tight hardness results for several basic dynamic or partially dynamic problems [STOC'15]. We first show that the OMv conjecture is implied by a simple off-line conjecture that we call the MvP conjecture. We then show that if the definition of the OMv conjecture is generalized to allow individual (i.e., it might be different for different matrices) polynomial-time preprocessing of the input matrix, then we obtain another conjecture (called the OMvP conjecture) that is in fact equivalent to our MvP conjecture. On the other hand, we demonstrate that the OMv conjecture does not hold in restricted cases where the rows of the matrix or the input vectors are clustered, and develop new efficient randomized algorithms for such cases. Finally, we present applications of our algorithms to answering graph queries.

The Convergence of the Generalized Lanczos Trust-Region Method for the Trust-Region Subproblem

Solving the trust-region subproblem (TRS) plays a key role in numerical optimization and many other applications. The generalized Lanczos trust-region (GLTR) method is a well-known Lanczos type approach for solving a large-scale TRS. The method projects the original large-scale TRS onto a sequence of lower dimensional Krylov subspaces, whose orthonormal bases are generated by the symmetric Lanczos process, and computes approximate solutions from the underlying subspaces. There have been some a priori bounds available for the errors of the approximate solutions and approximate objective values obtained by the GLTR method, but no a priori bound exists on the errors of the approximate Lagrangian multipliers and the residual norms of approximate solutions obtained by the GLTR method. In this paper, a general convergence theory of the GLTR method is established for the TRS in the easy case, showing that the a priori bounds for these four quantities are closely interrelated and the one for the computable residual norm is of crucial importance in both theory and practice as it can predict the sizes of other three uncomputable errors reliably. Numerical experiments demonstrate that our bounds are realistic and predict the convergence rates of the four quantities accurately.

Sędzia w poszukiwaniu absurdów prawnych

In some cases judges have to deal with legal absurdities, which have an adverse impact on the legal system and on the situation of parties to legal transactions. There are judges who fail to notice legal absurdities or just wave them aside, for instance, driven by a formalistic creed of application of law, but there are also judges who know how to discover and skillfully remove them. The aim of this paper is an attempt to establish what set of circumstances (factors) may influence judges’ ability to discover legal absurdities in the cases they decide. An analysis of selected judgements leads to several important conclusions concerning the issue of judges discovering legal absurdities. (1) Judges use different methods to track down legal absurdities, although some similarities between them are noticeable; (2) The search for legal absurdities is done in the context of a judge’s discretionary power. (3) Judges discover legal absurdities in both in easy and hard cases. (4) In order to track down a legal absurdity it may be necessary to assess not only the legal text, but also an act of application of law. (5) Judges consider all facts of a given case, including its unique circumstances, to discover a legal absurdity. (6) Tracking down legal absurdities is strictly and directly connected with knowledge of different kinds of legal absurdities.

Reproducibility of 2016 ASE/EACVI algorithm for estimation of LV filling pattern: Not perfect but enough

Transthoracic echocardiography (TTE) is currently the gold standard in the routine evaluation of Left Ventricular Filling Pressure (LVFP) in patients with dyspnea and/or heart failure, which is guided by the 2016 American Society of Echocardiography (ASE) and European Association of Cardiovascular Imaging (EACVI) guidelines. Although, at least of 5 to 6 different parameters were necessary to conclude, each of them with their own intra- and interobserver variability. The present report examined the reproducibility of each parameter of the algorithm and its influence on the final decision of the clinician. We selected 12 adults admitted for dyspnea with a complete TTE. Each exam was analysed by two readers (one junior and one senior) in 5 French cardiologic tertiary centres. The methodology was always the same and replicated blinded. We focused on the reproducibility of the dichotomial choice for each value because of it's the only information needed for using the algorithm. As demonstrated in Fig. 1 , only E/A ratio and LVEF status (preserved or not) had a substantial – but not perfect – agreement, LAVi had the poorest reproducibility. The final decision on left ventricular filling pressure pattern had a moderate agreement. Of note, the conclusion was identical for 5 patients for all readers. For the others, there was some discrepancy between readers, which was similar for seniors and juniors. Main discordance exists in considering mitral calcifications significant or not and for value which are around the cut-off. Without considering performance, this multicentric French study puts forward limits of actual algorithm recommended for left ventricular filling pressure pattern assessment. Agreement is excellent in caricatural (easy) cases (LV pressure clearly normal or clearly elevated), but a great discordance exists in grey zone. Improvement in the algorithm and in method for LVFP determination would be proposed.

ASAP: assemble species by automatic partitioning.

Here, we describe Assemble Species by Automatic Partitioning (ASAP), a new method to build species partitions from single locus sequence alignments (i.e., barcode data sets). ASAP is efficient enough to split data sets as large 104 sequences into putative species in several minutes. Although grounded in evolutionary theory, ASAP is the implementation of a hierarchical clustering algorithm that only uses pairwise genetic distances, avoiding the computational burden of phylogenetic reconstruction. Importantly, ASAP proposes species partitions ranked by a new scoring system that uses no biological prior insight of intraspecific diversity. ASAP is a stand-alone program that can be used either through a graphical web-interface or that can be downloaded and compiled for local usage. We have assessed its power along with three others programs (ABGD, PTP and GMYC) on 10 real COI barcode data sets representing various degrees of challenge (from small and easy cases to large and complicated data sets). We also used Monte-Carlo simulations of a multispecies coalescent framework to assess the strengths and weaknesses of ASAP and the other programs. Through these analyses, we demonstrate that ASAP has the potential to become a major tool for taxonomists as it proposes rapidly in a full graphical exploratory interface relevant species hypothesis as a first step of the integrative taxonomy process.

Being Familiar with What One Wants

AbstractSelf‐ascriptions of desire seem to differ in their epistemic security. There are easy cases in which a sincere self‐ascription immediately counts as knowledgeable, and there are hard cases in which it is an open question whether an agent actually knows that they have the desire that they take themselves to have. In this paper, I suggest an explanation according to which whether a self‐ascription of desire is easy or hard depends on whether one is familiar with the content of the self‐ascribed desire.

Rational guidewire use in the coronary chronic total occlusion interventions

BackgroundProcedures for coronary chronic total occlusion (CTO) are still a clinical challenge with relatively lower success rates. Recent advances in the biotechnology and introduction of CTO-dedicated guidewires have increased the procedural success rate of CTO interventions. Herein, we aimed to reveal the clinical and angiographic predictors of the crossability of the initial guidewire choice and rational guidewire usage in CTO interventions. A total of 177 patients with an indication for a coronary CTO procedure were included in this study. The use of 1–3 guidewires and crossing of the CTO lesion with the initial guidewire choice was defined as rational guidewire usage. The CTO lesions were classified according to the Japanese chronic total occlusion registry (J-CTO) and EuroCTO scores for evaluating the difficulty of the procedures. Then, a statistical analysis was performed to assess the initial guidewire choice, crossability, and contributors to rational guidewire usage.ResultsThe mean J-CTO score was 1.42 ± 1.16, and the mean EuroCTO score was 1.44 ± 1.18. The success rate of the procedures was 90.4%. The initial guidewire choice crossed the lesion in 44.1% of the cases, in which 1–3 guidewires were used (82.1%). The crossability of the polymeric and moderate stiff tip guidewires was higher (82.1% and 64.1%, respectively), and the Pilot series was the most successful brand (36.2%). Logistic regression analysis confirmed that J-CTO score, procedural technique, guidewire type, and stiffness of the tip were the major predictors of rational guidewire usage.ConclusionOur analysis showed that the use of polymeric and moderate stiff tip guidewires, particularly the Pilot brand, were associated with rational guidewire usage in easy and intermediate difficulty CTO cases.

Machine Learning to Improve the Prioritization and Effectiveness of Pre-Treatment Physics Chart Checks

Quality assurance (QA) is an integral part of planning for every patient prior to administering radiation therapy. The nationally regulated approach to QA involves performing multiple chart checks and often requires a high cognitive burden and significant amount of time. The purpose of this study is to explore the use of machine learning to classify the potential difficulty of physics pre-treatment chart check QA for a given radiation plan. Herein, we demonstrate a model that classifies radiation treatment plans as easy, medium, or hard with reference to QA time involved and cognitive burden. Pre-treatment data was collected for 1343 cases encompassing all cancer sites that were planned between August 2018 and October 2019. The outcome variable, a degree of difficulty on a scale of 1-10 was collected as a subjective rating by physicists who performed the pre-treatment chart checks. Scores of 1-3 were labeled as easy, 4-6 as intermediate, and 7-10 as difficult. A clinician and physicist then identified potential features, based on clinical relevance, contribution to plan complexity, and QA metrics. 1074 patient plans were used as a training set and the remaining 269 were set aside as a test set, an 80/20 split. The training data was used to train a k-nearest neighbor (KNN) classifier (k = 2) and a neural network (hidden layers = 3). Forward feature elimination was then utilized to incorporate only variables of importance prior to training decision tree (max depth = 10), random forest, and Adaboost (max depth = 0) classifiers. These five algorithms were incorporated into a majority voting classifier. Both training and test sets were equivalent in their proportion of difficult (11%), intermediate (41%), and easy (47%) cases. Accuracy on the test set was calculated for each classifier and was found to be 96% for the Adaboost and random forest classifiers, 94% for the neural network, 90% for the decision tree, and 84% for the KNN. The majority voting classifier achieved an accuracy of 95% overall, with 94% accuracy on difficult cases, 95% on medium cases, and 95% on easy cases. Precision, recall, and F-score were also calculated for each classifier and for the majority vote (see Table). We present a majority voting classifier that uses clinical, plan complexity, and QA features in order to predict the difficulty of radiation treatment plans. This will be used in our department to guide the physicist in prioritizing their activities in an effort to reduce cognitive workload and improve the effectiveness of pre-treatment chart checks. Future directions include validating this model at our community practices and addressing limitations such as class imbalance and missing data.Abstract 110; TableAdaboostDecision TreeKNNNeural NetworkRandom ForestMajority (hard vote)Accuracy96%90%84%94%96%95%Precision (PPV)96%93%86%95%97%96%Recall (Sensitivity)96%88%82%93%96%95%F-score96%90%84%94%96%95% Open table in a new tab

An easy and cheap surgical pocket case for draining blood when performing scalp surgery

Skin cancers are increasing in their incidence worldwide. The scalp is a frequent site for cutaneous carcinoma, both basal cell and squamous cell. Scalp carcinomas usually bring difficulties in surgical management owing to the high bleeding risk and the uncomfortable position for the surgeon. In particular, during the surgical excision such lesions tend to bleed because of the high vascular support of the scalp, and this can negatively affect surgical management.

Does difficulty assessment of laparoscopic cholecystectomy using currently available preoperative scores need revision

Introduction Risk factors used for preoperative anticipation of a difficult laparoscopic cholecystectomy should be identified to prevent complications beforehand. The aim of this study was to evaluate factors predicting difficulty and the possibility of conversion to open cholecystectomy before surgery. Patients and methods Patients diagnosed with symptomatic cholelithiasis and scheduled for elective laparoscopic cholecystectomy were enrolled in the study. Patient’s age and sex, previous hospital admissions, BMI, previous abdominal scar, a palpable gall bladder, gall bladder wall thickness, the presence of pericholecystic fluid collection, and impacted stone are considered risk factors that were used to calculate preoperative scores. Surgical procedure was categorized intraoperative as easy, difficult, or very difficult on the basis of duration of surgery or conversion to open cholecystectomy. Results There was no significant difference between intraoperative difficulty regarding age, sex, BMI, and the presence of either abdominal scar or impacted stone. The absence of previous history of hospitalization and the presence of nonpalpable gall bladder were significantly associated with intraoperative categorization as easy cases (P=0.002). Discussion and conclusion The evaluated scoring system requires meticulous revision for the factors included. Insensitive factors could be removed without negative effect on the outcome. Focus should be directed toward significant items regarding sonography findings. It could be applied as a useful tool to predict easy cases but needs adjustment for the factors considered in case of predicting difficult and very difficult cases. The experience of the surgeon is an important factor in assessing difficulty intraoperative.